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On November 30th, 2022, OpenAI released the large language model ChatGPT, an extension of GPT-3. The AI chatbot provides real-time communication in response to users’ requests. The quality of ChatGPT’s natural speaking answers marks a major shift in how we will use AI-generated information in our day-to-day lives. For a software engineering student, the use cases for ChatGPT are manifold: assessment preparation, translation, and creation of specified source code, to name a few. It can even handle more complex aspects of scientific writing, such as summarizing literature and paraphrasing text. Hence, this position paper addresses the need for discussion of potential approaches for integrating ChatGPT into higher education. Therefore, we focus on articles that address the effects of ChatGPT on higher education in the areas of software engineering and scientific writing. As ChatGPT was only recently released, there have been no peer-reviewed articles on the subject. Thus, we performed a structured grey literature review using Google Scholar to identify preprints of primary studies. In total, five out of 55 preprints are used for our analysis. Furthermore, we held informal discussions and talks with other lecturers and researchers and took into account the authors’ test results from using ChatGPT. We present five challenges and three opportunities for the higher education context that emerge from the release of ChatGPT. The main contribution of this paper is a proposal for how to integrate ChatGPT into higher education in four main areas.
The research project "Herbar Digital" was started in 2007 with the aim to digitize 3.5 million dried plants on paper sheets belonging to the Botanic Museum Berlin in Germany. Frequently the collector of the plant is unknown, so a procedure had to be developed in order to determine the writer of the handwriting on the sheet. In the present work the static character was transformed into a dynamic form. This was done with the model of an inert ball which was rolled along the written character. During this off-line writer recognition, different mathematical procedures were used such as the reproduction of the write line of individual characters by Legendre polynomials. When only one character was used, a recognition rate of about 40% was obtained. By combining multiple characters, the recognition rate rose considerably and reached 98.7% with 13 characters and 93 writers (chosen randomly from the international IAM-database [3]). A global statistical approach using the whole handwritten text resulted in a similar recognition rate. By combining local and global methods, a recognition rate of 99.5% was achieved.
The methods developed in the research project "Herbar Digital" are to help plant taxonomists to master the great amount of material of about 3.5 million dried plants on paper sheets belonging to the Botanic Museum Berlin in Germany. Frequently the collector of the plant is unknown. So a procedure had to be developed in order to determine the writer of the handwriting on the sheet. In the present work the static character is transformed into a dynamic form. This is done with the model of an inert ball which is rolled through the written character. During this off-line writer recognition, different mathematical procedures are used such as the reproduction of the write line of individual characters by Legendre polynomials. When only one character is used, a recognition rate of about 40% is obtained. By combining multiple characters, the recognition rate rises considerably and reaches 98.7% with 13 characters and 93 writers (chosen randomly from the international IAM-database [3]). Another approach tries to identify the writer by handwritten words. The word is cut out and transformed into a 6-dimensional time series and compared e.g. by means of DTW-methods. A global statistical approach using the whole handwritten sentences results in a similar recognition rate of more than 98%. By combining the methods, a recognition rate of 99.5% is achieved.
Wikidata and Wikibase as complementary research data management services for cultural heritage data
(2022)
The NFDI (German National Research Data Infrastructure) consortia are associations of various institutions within a specific research field, which work together to develop common data infrastructures, guidelines, best practices and tools that conform to the principles of FAIR data. Within the NFDI, a common question is: What is the potential of Wikidata to be used as an application for science and research? In this paper, we address this question by tracing current research usecases and applications for Wikidata, its relation to standalone Wikibase instances, and how the two can function as complementary services to meet a range of research needs. This paper builds on lessons learned through the development of open data projects and software services within the Open Science Lab at TIB, Hannover, in the context of NFDI4Culture – the consortium including participants across the broad spectrum of the digital libraries, archives, and museums field, and the digital humanities.
The NOA project collects and stores images from open access publications and makes them findable and reusable. During the project a focus group workshop was held to determine whether the development is addressing researchers’ needs. This took place before the second half of the project so that the results could be considered for further development since addressing users’ needs is a big part of the project. The focus was to find out what content and functionality they expect from image repositories.
In a first step, participants were asked to fill out a survey about their images use. Secondly, they tested different use cases on the live system. The first finding is that users have a need for finding scholarly images but it is not a routine task and they often do not know any image repositories. This is another reason for repositories to become more open and reach users by integrating with other content providers. The second finding is that users paid attention to image licenses but struggled to find and interpret them while also being unsure how to cite images. In general, there is a high demand for reusing scholarly images but the existing infrastructure has room to improve.
For anomaly-based intrusion detection in computer networks, data cubes can be used for building a model of the normal behavior of each cell. During inference an anomaly score is calculated based on the deviation of cell metrics from the corresponding normality model. A visualization approach is shown that combines different types of diagrams and charts with linked user interaction for filtering of data.
Visual effects and elements in video games and interactive virtual environments can be applied to transfer (or delegate) non-visual perceptions (e.g. proprioception, presence, pain) to players and users, thus increasing perceptual diversity via the visual modality. Such elements or efects are referred to as visual delegates (VDs). Current fndings on the experiences that VDs can elicit relate to specifc VDs, not to VDs in general. Deductive and comprehensive VD evaluation frameworks are lacking. We analyzed VDs in video games to generalize VDs in terms of their visual properties. We conducted a systematic paper analysis to explore player and user experiences observed in association with specifc VDs in user studies. We conducted semi-structured interviews with expert players to determine their preferences and the impact of VD properties. The resulting VD framework (VD-frame) contributes to a more strategic approach to identifying the impact of VDs on player and user experiences.
Scientific papers from all disciplines contain many abbreviations and acronyms. In many cases these acronyms are ambiguous. We present a method to choose the contextual correct definition of an acronym that does not require training for each acronym and thus can be applied to a large number of different acronyms with only few instances. We constructed a set of 19,954 examples of 4,365 ambiguous acronyms from image captions in scientific papers along with their contextually correct definition from different domains. We learn word embeddings for all words in the corpus and compare the averaged context vector of the words in the expansion of an acronym with the weighted average vector of the words in the context of the acronym. We show that this method clearly outperforms (classical) cosine similarity. Furthermore, we show that word embeddings learned from a 1 billion word corpus of scientific exts outperform word embeddings learned from much larger general corpora.
In huge warehouses or stockrooms, it is often very difficult to find a certain item, because it has been misplaced and is therefore not at its assumed position. This position paper presents an approach on how to coordinate mobile RFID agents using a blackboard architecture based on Complex Event Processing.
In the area of manufacturing and process automation in industrial applications, technical energy management systems are mainly used to measure, collect, store, analyze and display energy data. In addition, PLC programs on the control level are required to obtain the energy data from the field level. If the measured data is available in a PLC as a raw value, it still has to be processed by the PLC, so that it can be passed on to the higher layers in a suitable format, e.g. via OPC UA. In plants with heterogeneous field device installations, a high engineering effort is required for the creation of corresponding PLC programs. This paper describes a concept for a code generator that can be used to reduce this engineering effort.
With the use of an energy management system in an industrial company according to ISO 50001, a step-by-step increase in energy efficiency can be achieved. The realization of energy monitoring and load management functions requires programs on edge devices or PLCs to acquire the data, adapt the data type or scale the values of the energy information. In addition, the energy information must be mapped to communication interfaces (e.g. based on OPC UA) in order to convey this energy information to the energy management application. The development of these energy management programs is associated with a high engineering effort, because the field devices from the heterogeneous field level do not provide the energy information in standardized semantics. To mitigate this engineering effort, a universal energy data information model (UEIM) is developed and presented in this paper.
To avoid the shortcomings of traditional monolithic applications, the Microservices Architecture (MSA) style plays an increasingly important role in providing business services. This is true even for the more conventional insurance industry with its highly heterogeneous application landscape and sophisticated cross-domain business processes. Therefore, the question arises of how workflows can be implemented to grant the required flexibility and agility and, on the other hand, to exploit the potential of the MSA style. In this article, we present two different approaches – orchestration and choreography. Using an application scenario from the insurance domain, both concepts are discussed. We introduce a pattern that outlines the mapping of a workflow to a choreography.
In this paper the workflow of the project 'Untersuchungs-, Simulations- und Evaluationstool für Urbane Logistik` (USEfUL) is presented. Aiming to create a web-based decision support tool for urban logistics, the project needed to integrate multiple steps into a single workflow, which in turn needed to be executed multiple times. While a service-oriented system could not be created, the principles of service orientation was utilized to increase workflow efficiency and flexibility, allowing the workflow to be easily adapted to new concepts or research areas.
Agile methods require constant optimization of one’s approach and leading to the adaptation of agile practices. These practices are also adapted when introducing them to companies and their software development teams due to organizational constraints. As a consequence of the widespread use of agile methods, we notice a high variety of their elements:
Practices, roles, and artifacts. This multitude of agile practices, artifacts, and roles results in an unsystematic mixture. It leads to several questions: When is a practice a practice, and when is it a method or technique? This paper presents the tree of agile elements, a taxonomy of agile methods, based on the literature and guidelines of widely used agile methods. We describe a taxonomy of agile methods using terms and concepts of software engineering, in particular software process models. We aim to enable agile elements to be delimited, which should help companies, agile teams, and the research community gain a basic understanding of the interrelationships and dependencies of individual components of agile methods.
Microservices build a deeply distributed system. Although this offers significant flexibility for development teams and helps to find solutions for scalability or security questions, it also intensifies the drawbacks of a distributed system. This article offers a decision framework, which helps to increase the resiliency of microservices. A metamodel is used to represent services, resiliency patterns, and quality attributes. Furthermore, the general idea for a suggestion procedure is outlined.
The negative effects of traffic, such as air quality problems and road congestion, put a strain on the infrastructure of cities and high-populated areas. A potential measure to reduce these negative effects are grocery home deliveries (e-grocery), which can bundle driving activities and, hence, result in decreased traffic and related emission outputs. Several studies have investigated the potential impact of e-grocery on traffic in various last-mile contexts. However, no holistic view on the sustainability of e-grocery across the entire supply chain has yet been proposed. Therefore, this paper presents an agent-based simulation to assess the impact of the e-grocery supply chain compared to the stationary one in terms of mileage and different emission outputs. The simulation shows that a high e-grocery utilization rate can aid in decreasing total driving distances by up to 255 % relative to the optimal value as well as CO 2 emissions by up to 50 %.
Microservices are meanwhile an established software engineering vehicle, which more and more companies are examining and adopting for their development work. Naturally, reference architectures based on microservices come into mind as a valuable thing to utilize. Initial results for such architectures are published in generic and in domain-specific form. Missing to the best of our knowledge however, is a domain-specific reference architecture based on microservices, which takes into account specifics of the insurance industry domain. Jointly with partners from the German insurance industry, we take initial steps to fill this gap in the present article. Thus, we aim towards a microservices-based reference software architecture for (at least German) insurance companies. As the main results of this article we thus provide an initial such reference architecture together with a deeper look into two important parts of it.
In this poster we present the ongoing development of an integrated free and open source toolchain for semantic annotation of digitised cultural heritage. The toolchain development involves the specification of a common data model that aims to increase interoperability across diverse datasets and to enable new collaborative research approaches.
Complexes like iron (II)-triazoles exhibit spin crossover behavior at ambient temperature and are often considered for possible application. In previous studies, we implemented complexes of this type into polymer nanofibers and first polymer-based optical waveguide sensor systems. In our current study, we synthesized complexes of this type, implemented them into polymers and obtained composites through drop casting and doctor blading. We present that a certain combination of polymer and complex can lead to composites with high potential for optical devices. For this purpose, we used two different complexes [Fe(atrz)3](2 ns)2 and [Fe(atrz)3]Cl1.5(BF4)0.5 with different polymers for each composite. We show through transmission measurements and UV/VIS spectroscopy that the optical properties of these composite materials can reversibly change due to the spin crossover effect.
Research information, i.e., data about research projects, organisations, researchers or research outputs such as publications or patents, is spread across the web, usually residing in institutional and personal web pages or in semi-open databases and information systems. While there exists a wealth of unstructured information, structured data is limited and often exposed following proprietary or less-established schemas and interfaces. Therefore, a holistic and consistent view on research information across organisational and national boundaries is not feasible. On the other hand, web crawling and information extraction techniques have matured throughout the last decade, allowing for automated approaches of harvesting, extracting and consolidating research information into a more coherent knowledge graph. In this work, we give an overview of the current state of the art in research information sharing on the web and present initial ideas towards a more holistic approach for boot-strapping research information from available web sources.
Even for the more traditional insurance industry, the Microservices Architecture (MSA) style plays an increasingly important role in provisioning insurance services. However, insurance businesses must operate legacy applications, enterprise software, and service-based applications in parallel for a more extended transition period. The ultimate goal of our ongoing research is to design a microservice reference architecture in cooperation with our industry partners from the insurance domain that provides an approach for the integration of applications from different architecture paradigms. In Germany, individual insurance services are classified as part of the critical infrastructure. Therefore, German insurance companies must comply with the Federal Office for Information Security requirements, which the Federal Supervisory Authority enforces. Additionally, insurance companies must comply with relevant laws, regulations, and standards as part of the business’s compliance requirements. Note: Since Germany is seen as relatively ’tough’ with respect to privacy and security demands, fullfilling those demands might well be suitable (if not even ’over-achieving’) for insurances in other countries as well. The question raises thus, of how insurance services can be secured in an application landscape shaped by the MSA style to comply with the architectural and security requirements depicted above. This article highlights the specific regulations, laws, and standards the insurance industry must comply with. We present initial architectural patterns to address authentication and authorization in an MSA tailored to the requirements of our insurance industry partners.
Context: Companies adapt agile methods, practices or artifacts for their use in practice since more than two decades. This adaptions result in a wide variety of described agile practices. For instance, the Agile Alliance lists 75 different practices in its Agile Glossary. This situation may lead to misunderstandings, as agile practices with similar names can be interpreted and used differently.
Objective: This paper synthesize an integrated list of agile practices, both from primary and secondary sources.
Method: We performed a tertiary study to identify existing overviews and lists of agile practices in the literature. We identified 876 studies, of which 37 were included.
Results: The results of our paper show that certain agile practices are listed and used more often in existing studies. Our integrated list of agile practices comprises 38 entries structured in five categories. Conclusion: The high number of agile practices and thus, the wide variety increased steadily over the past decades due to the adaption of agile methods. Based on our findings, we present a comprehensive overview of agile practices. The research community benefits from our integrated list of agile practices as a potential basis for future research. Also, practitioners benefit from our findings, as the structured overview of agile practices provides the opportunity to select or adapt practices for their specific needs.
In 2020, the world changed due to the Covid 19 pandemic. Containment measures to reduce the spread of the virus were planned and implemented by many countries and companies. Worldwide, companies sent their employees to work from home. This change has led to significant challenges in teams that were co-located before the pandemic. Agile software development teams were affected by this switch, as agile methods focus on communication and collaboration. Research results have already been published on the challenges of switching to remote work and the effects on agile software development teams. This article presents a systematic literature review. We identified 12 relevant papers for our studies and analyzed them on detail. The results provide an overview how agile software development teams reacted to the switch to remote work, e.g., which agile practices they adapted. We also gained insights on the changes of the performance of agile software development teams and social effects on agile software development teams during the pandemic.
Companies worldwide have enabled their employees to work remotely as a consequence of the Covid 19 pandemic. Software development is a human-centered discipline and thrives on teamwork. Agile methods are focusing on several social aspects of software development. Software development teams in Germany were mainly co-located before the pandemic. This paper aims to validate the findings of existing studies by expanding on an existing multiple-case study. Therefore, we collected data by conducting semi-structured interviews, observing agile practices, and viewing project documents in three cases. Based on the results, we can confirm the following findings: 1) The teams rapidly adapted the agile practices and roles, 2) communication is more objective within the teams, 3) decreased social exchange between team members, 4) the expectation of a combined approach of remote and onsite work after the pandemic, 5) stable or increased (perceived) performance and 6) stable or increased well-being of team members.
The reuse of scientific raw data is a key demand of Open Science. In the project NOA we foster reuse of scientific images by collecting and uploading them to Wikimedia Commons. In this paper we present a text-based annotation method that proposes Wikipedia categories for open access images. The assigned categories can be used for image retrieval or to upload images to Wikimedia Commons. The annotation basically consists of two phases: extracting salient keywords and mapping these keywords to categories. The results are evaluated on a small record of open access images that were manually annotated.
To learn a subject, the acquisition of the associated technical language is important.
Despite this widely accepted importance of learning the technical language, hardly any studies are published that describe the characteristics of most technical languages that students are supposed to learn. This might largely be due to the absence of specialized text corpora to study such languages at lexical, syntactical and textual level. In the present paper we describe a corpus of German physics text that can be used to study the language used in physics. A large and a small variant are compiled. The small version of the corpus consists of 5.3 Million words and is available on request.
Cloud computing has become well established in private and public sector projects over the past few years, opening ever new opportunities for research and development, but also for education. One of these opportunities presents itself in the form of dynamically deployable, virtual lab environments, granting educational institutions increased flexibility with the allocation of their computing resources. These fully sandboxed labs provide students with their own, internal network and full access to all machines within, granting them the flexibility necessary to gather hands-on experience with building heterogeneous microservice architectures. The eduDScloud provides a private cloud infrastructure to which labs like the microservice lab outlined in this paper can be flexibly deployed at a moment’s notice.
This paper deals with new job profiles in libraries, mainly systems librarians (German: Systembibliothekare), IT librarians (German: IT-Bibliothekare) and data librarians (German: Datenbibliothekare). It investigates the vacancies and requirements of these positions in the German-speaking countries by analyzing one hundred and fifty published job advertisements of OpenBiblioJobs between 2012-2016. In addition, the distribution of positions, institutional bearers, different job titles as well as time limits, scope of work and remuneration of the positions are evaluated. The analysis of the remuneration in the public sector in Germany also provides information on demands for a bachelor's or master's degree.
The average annual increase in job vacancies between 2012 and 2016 is 14.19%, confirming the need and necessity of these professional library profiles.
The higher remuneration of the positions in data management, in comparison to the systems librarian, proves the prerequisite of the master's degree and thus indicates a desideratum due to missing or few master's degree courses. Accordingly, the range of bachelor's degree courses (or IT-oriented major areas of study with optional compulsory modules in existing bachelor's degree courses) for systems and IT librarians must be further expanded. An alternative could also be modular education programs for librarians and information scientists with professional experience, as it is already the case for music librarians.
In the present paper we sketch an automated procedure to compare different versions of a contract. The contract texts used for this purpose are structurally differently composed PDF files that are converted into structured XML files by identifying and classifying text boxes. A classifier trained on manually annotated contracts achieves an accuracy of 87% on this task. We align contract versions and classify aligned text fragments into different similarity classes that enhance the manual comparison of changes in document versions. The main challenges are to deal with OCR errors and different layout of identical or similar texts. We demonstrate the procedure using some freely available contracts from the City of Hamburg written in German. The methods, however, are language agnostic and can be applied to other contracts as well.
We present an approach towards a data acquisition system for digital twins that uses a 5G net- work for data transmission and localization. The current hardware setup, which utilizes stereo vision and LiDAR for 3D mapping, is explained together with two recorded point cloud data sets. Furthermore, a resulting digital twin comprised of voxelized point cloud data is shown. Ideas for future applications and challenges regarding the system are discussed and an outlook on further development is given.
Compounds that exhibit the spin crossover effect are known to show a change of spin states through external stimuli. This reversible switching of spin states is accompanied by a change of the properties of the compound. Complexes, like iron (II)-triazole complexes, that exhibit this behavior at ambient temperature are often discussed for potential applications. In previous studies we synthesized iron (II)-triazole complexes and implemented them into electrospun nanofibers. We used Mössbauer spectroscopy in first studies to prove a successful implementation with maintaining spin crossover properties. Further studies from us showed that it is possible to use different electrospinning methods to either do a implementation or a deposition of the synthesized solid SCO material into or onto the polymer nanofibers. We now used a solvent in which both, the used iron (II)-triazole complex [Fe(atrz)3](2 ns)2 and three different polymers (Polyacrylonitrile, Polymethylmethacrylate and Polyvinylpyrrolidone), are soluble. This shall lead to a higher homogeneous distribution of the complex along the nanofibers. Mössbauer spectroscopy and other measurements are therefore in use to show a successful implementation without any significant changes to the complex.
In recent years, multiple efforts for reducing energy usage have been proposed. Especially buildings offer high potentials for energy savings. In this paper, we present a novel approach for intelligent energy control that combines a simple infrastructure using low cost sensors with the reasoning capabilities of Complex Event Processing. The key issues of the approach are a sophisticated semantic domain model and a multi-staged event processing architecture leading to an intelligent, situation-aware energy management system.
We present a simple method to find topics in user reviews that accompany ratings for products or services. Standard topic analysis will perform sub-optimal on such data since the word distributions in the documents are not only determined by the topics but by the sentiment as well. We reduce the influence of the sentiment on the topic selection by adding two explicit topics, representing positive and negative sentiment. We evaluate the proposed method on a set of over 15,000 hospital reviews. We show that the proposed method, Latent Semantic Analysis with explicit word features, finds topics with a much smaller bias for sentiments than other similar methods.
Fall events and their severe consequences represent not only a threatening problem for the affected individual, but also cause a significant burden for health care systems. Our research work aims to elucidate some of the prospects and problems of current sensor-based fall risk assessment approaches. Selected results of a questionnaire-based survey given to experts during topical workshops at international conferences are presented. The majority of domain experts confirmed that fall risk assessment could potentially be valuable for the community and that prediction is deemed possible, though limited. We conclude with a discussion of practical issues concerning adequate outcome parameters for clinical studies and data sharing within the research community. All participants agreed that sensor-based fall risk assessment is a promising and valuable approach, but that more prospective clinical studies with clearly defined outcome measures are necessary.
Operators of production plants are increasingly emphasizing secure communication, including real-time communication, such as PROFINET, within their control systems. This trend is further advanced by standards like IEC 62443, which demand the protection of realtime communication in the field. PROFIBUS and PROFINET International (PI) is working on the specification of the security extensions for PROFINET (“PROFINET Security”), which shall fulfill the requirements of secure communication in the field.
This paper discusses the matter in three parts. First, the roles and responsibilities of the plant owner, the system integrator, and the component provider regarding security, and the basics of the IEC 62443 will be described. Second, a conceptual overview of PROFINET Security, as well as a status update about the PI specification work will be given. Third, the article will describe how PROFINET Security can contribute to the defense-in-depth approach, and what the expected operating environment is. We will evaluate how PROFINET Security contributes to fulfilling the IEC 62443-4-2 standard for automation components.
Two of the authors are members of the PI Working Group CB/PG10 Security.
Self-directed learning is an essential basis for lifelong learning and requires constantly changing, target groupspecific and personalized prerequisites in order to motivate people to deal with modern learning content, not to overburden them and yet to adequately convey complex contexts. Current challenges in dealing with digital resources such as information overload, reduction of complexity and focus, motivation to learn, self-control or psychological wellbeing are taken up in the conception of learning settings within our QpLuS IM project for the study program Information Management and Information Management extra-occupational (IM) at the University of Applied Sciences and Arts Hannover. We present an interactive video on the functionality of search engines as a practical example of a medially high-quality and focused self-learning format that has been methodically produced in line with our agile, media-didactic process and stage model of complexity levels.
Requirements for an energy data information model for a communication-independent device description
(2021)
With the help of an energy management system according to ISO 50001, industrial companies obtain the opportunities to reduce energy consumption and to increase plant efficiencies. In such a system, the communication of energy data has an important function. With the help of so-called energy profiles (e.g. PROFIenergy), energy data can be communicated between the field level and the higher levels via proven communication protocols (e.g. PROFINET). Due to the fact that in most cases several industrial protocols are used in an automation system, the problem is how to transfer energy data from one protocol to another with as less effort as possible. An energy data information model could overcome this problem and describe energy data in a uniform and semantically unambiguous way. Requirements for a unified energy data information model are presented in this paper.
In order to ensure validity in legal texts like contracts and case law, lawyers rely on standardised formulations that are written carefully but also represent a kind of code with a meaning and function known to all legal experts. Using directed (acyclic) graphs to represent standardized text fragments, we are able to capture variations concerning time specifications, slight rephrasings, names, places and also OCR errors. We show how we can find such text fragments by sentence clustering, pattern detection and clustering patterns. To test the proposed methods, we use two corpora of German contracts and court decisions, specially compiled for this purpose. However, the entire process for representing standardised text fragments is language-agnostic. We analyze and compare both corpora and give an quantitative and qualitative analysis of the text fragments found and present a number of examples from both corpora.
Regional knowledge map is a tool recently demanded by some actors in an institutional level to help regional policy and innovation in a territory. Besides, knowledge maps facilitate the interaction between the actors of a territory and the collective learning. This paper reports the work in progress of a research project which objective is to define a methodology to efficiently design territorial knowledge maps, by extracting information of big volumes of data contained in diverse sources of information related to a region. Knowledge maps facilitate management of the intellectual capital in organisations. This paper investigates the value to apply this tool to a territorial region to manage the structures, infrastructures and the resources to enable regional innovation and regional development. Their design involves the identification of information sources that are required to find which knowledge is located in a territory, which actors are involved in innovation, and which is the context to develop this innovation (structures, infrastructures, resources and social capital). This paper summarizes the theoretical background and framework for the design of a methodology for the construction of knowledge maps, and gives an overview of the main challenges for the design of regional knowledge maps.
During the transition from conventional towards purely electrical, sustainable mobility, transitional technologies play a major part in the task of increasing adaption rates and decreasing range anxiety. Developing new concepts to meet this challenge requires adaptive test benches, which can easily be modified e.g. when progressing from one stage of development to the next, but also meet certain sustainability demands themselves.
The system architecture presented in this paper is built around a service-oriented software layer, connecting a modular hardware layer for direct access to sensors and actuators to an extensible set of client tools. Providing flexibility, serviceability and ease of use, while maintaining a high level of reusability for its constituent components and providing features to reduce the required overall run time of the test benches, it can effectively decrease the CO2 emissions of the test bench while increasing its sustainability and efficiency.
PROFINET Security: A Look on Selected Concepts for Secure Communication in the Automation Domain
(2023)
We provide a brief overview of the cryptographic security extensions for PROFINET, as defined and specified by PROFIBUS & PROFINET International (PI). These come in three hierarchically defined Security Classes, called Security Class 1, 2 and 3. Security Class 1 provides basic security improvements with moderate implementation impact on PROFINET components. Security Classes 2 and 3, in contrast, introduce an integrated cryptographic protection of PROFINET communication. We first highlight and discuss the security features that the PROFINET specification offers for future PROFINET products. Then, as our main focus, we take a closer look at some of the technical challenges that were faced during the conceptualization and design of Security Class 2 and 3 features. In particular, we elaborate on how secure application relations between PROFINET components are established and how a disruption-free availability of a secure communication channel is guaranteed despite the need to refresh cryptographic keys regularly. The authors are members of the PI Working Group CB/PG10 Security.
Aim/Purpose: We explore impressions and experiences of Information Systems graduates during their first years of employment in the IT field. The results help to understand work satisfaction, career ambition, and motivation of junior employees. This way, the attractiveness of working in the field of IS can be increased and the shortage of junior employees reduced.
Background: Currently IT professions are characterized by terms such as “shortage of professionals” and “shortage of junior employees”. To attract more people to work in IT detailed knowledge about experiences of junior employees is necessary.
Methodology: Data from a large survey of 193 graduates of the degree program “Information Systems” at University of Applied Sciences and Arts Hannover (Germany) show characteristics of their professional life like work satisfaction, motivation, career ambition, satisfaction with opportunities, development and career advancement, satisfaction with work-life balance. It is also asked whether men and women gain the same experiences when entering the job market and have the same perceptions.
Findings: The participants were highly satisfied with their work, but limitations or restrictions due to gender are noteworthy.
Recommendations for Practitioners: The results provide information on how human resource policies can make IT professions more attractive and thus convince graduates to seek jobs in the field. For instance, improving the balance between work and various areas of private life seems promising. Also, restrictions with respect to the work climate and improving communication along several dimensions need to be considered.
Future Research: More detailed research on ambition and achievement is necessary to understand gender differences.
Research into new forms of care for complex chronic diseases requires substantial efforts in the collection, storage, and analysis of medical data. Additionally, providing practical support for those who coordinate the actual care management process within a diversified network of regional service providers is also necessary. For instance, for stroke units, rehabilitation partners, ambulatory actors, as well as health insurance funds. In this paper, we propose the concept of comprehensive and practical receiver-oriented encryption (ROE) as a guiding principle for such data-intensive, research-oriented case management systems, and
illustrate our concept with the example of the IT infrastructure of the project STROKE OWL.
Legal documents often have a complex layout with many different headings, headers and footers, side notes, etc. For the further processing, it is important to extract these individual components correctly from a legally binding document, for example a signed PDF. A common approach to do so is to classify each (text) region of a page using its geometric and textual features. This approach works well, when the training and test data have a similar structure and when the documents of a collection to be analyzed have a rather uniform layout. We show that the use of global page properties can improve the accuracy of text element classification: we first classify each page into one of three layout types. After that, we can train a classifier for each of the three page types and thereby improve the accuracy on a manually annotated collection of 70 legal documents consisting of 20,938 text elements. When we split by page type, we achieve an improvement from 0.95 to 0.98 for single-column pages with left marginalia and from 0.95 to 0.96 for double-column pages. We developed our own feature-based method for page layout detection, which we benchmark against a standard implementation of a CNN image classifier. The approach presented here is based on corpus of freely available German contracts and general terms and conditions.
Both the corpus and all manual annotations are made freely available. The method is language agnostic.
This paper presents the fundamental investigation on crack propagation rate (CPR) and Stress Intensity Factor (SIF) for a typical fatigue and welded specimens which are Compact Tension (CT) and Single Edge Notch Tension (SENT) as well as Butt and longitudinal T-joint. The material data of austenitic stainless steel SS316L was used to observe crack propagation rate with different initial crack length and different tensile load was used for the fracture mechanics investigation. The geometry of the specimens was modelled by using open source software CASCA while Franc 2D was used for post processing based on Paris Erdogan Law with different crack increment steps. The analysis of crack propagation using fracture mechanics technique requires an accurate calculation of the stress intensity factor SIF and comparison of the critical strength of the material (KIC) was used to determine the critical crack length of the specimens. it can be concluded that open source finite element method software can be used for predicting of fatigue life on simplified geometry.
Concreteness of words has been studied extensively in psycholinguistic literature. A number of datasets have been created with average values for perceived concreteness of words. We show that we can train a regression model on these data, using word embeddings and morphological features, that can predict these concreteness values with high accuracy. We evaluate the model on 7 publicly available datasets. Only for a few small subsets of these datasets prediction of concreteness values are found in the literature. Our results clearly outperform the reported results for these datasets.
Image captions in scientific papers usually are complementary to the images. Consequently, the captions contain many terms that do not refer to concepts visible in the image. We conjecture that it is possible to distinguish between these two types of terms in an image caption by analysing the text only. To examine this, we evaluated different features. The dataset we used to compute tf.idf values, word embeddings and concreteness values contains over 700 000 scientific papers with over 4,6 million images. The evaluation was done with a manually annotated subset of 329 images. Additionally, we trained a support vector machine to predict whether a term is a likely visible or not. We show that concreteness of terms is a very important feature to identify terms in captions and context that refer to concepts visible in images.
Concreteness of words has been measured and used in psycholinguistics already for decades. Recently, it is also used in retrieval and NLP tasks. For English a number of well known datasets has been established with average values for perceived concreteness.
We give an overview of available datasets for German, their correlation and evaluate prediction algorithms for concreteness of German words. We show that these algorithms achieve similar results as for English datasets. Moreover, we show for all datasets there are no significant differences between a prediction model based on a regression model using word embeddings as features and a prediction algorithm based on word similarity according to the same embeddings.
Agility is considered the silver bullet for survival in the VUCA world. However, many organisations are afraid of endangering their ISO 9001 certificate when introducing agile processes. A joint research project of the University of Applied Sciences and Arts Hannover and the DGQ has set itself the goal of providing more security in this area. The findings were based on interviews with managers and team members from various organisations of different sizes and industries working in an agile manner as well as on common audit practices and a literature analysis. The outcome presents a clear distinction of agility from flexibility as well as useful guidelines for the integration of agile processes in QM systems - for QM practitioners and auditors alike.
The increasing variety of combinations of different building technology components offers a high potential for energy and cost savings in today's buildings. However, in most cases, this potential is not yet fully exploited due to the lack of intelligent supervisory control systems that are required to manage the complexity of the resulting overall systems. In this article, we present the implementation of a mixed-integer nonlinear model predictive control approach as a smart realtime building energy management system. The presented methodology is based on a forward-looking optimization of the overall energy costs. It takes into account energy demand forecasts and varying electricity market prices. We achieve real-time capability of the controller by applying a decomposition approach, which approximates the optimal solution of the underlying mixed-integer optimal control problem by convexification and rounding of the relaxed solution. The quality of the suboptimal solution is evaluated by comparison with the globally optimal solution obtained by the dynamic programming method. Based on a real-world scenario, we demonstrate that utilization of the real-time capable mixedinteger nonlinear model predictive control approach in a building control system leads to savings of 16% in the total operating costs and 13% in primary energy compared to the state-of-the-art control strategy without any loss of comfort for the residents.
This paper presents a novel approach for modelling the energy consumption of the coupled parallel moulding sand mixers of a foundry as an optimal control problem. The minimization of energy consumption is optimized by scheduling the mixing processes in a linear integer programming scheme. The sand flow through the foundry’s sand preparation is characterized by a physical model. This model considers the sand demand of the moulding machine as disturbance, the stored sand masses in the mixer hoppers and machine hoppers, respectively. The novel approach of handling dwell-times for dosing, mixing and transport processes using dead-time systems and constraint pushing allows the application of a linear model. The formulation of the optimal control problem aims at real-time application as model predictive control at the production plant. Initial application results indicate an improvement in energy consumption of approximately 8%.
Industrial Control Systems (ICS) succumb to an ever evolving variety of threats. Additionally, threats are increasing in number and get more complex. This requires a holistic and up-to-date security concept for ICS as a whole. Usually security concepts are applied and updated based on regularly performed ICS security assessments. Such ICS security assessments require high effort and extensive knowledge about ICS and its security. This is often a problem for small and mediumsized enterprises (SME), which do not have sufficient respective sufficiently skilled human resources. This paper defines in a first step requirements on the knowledge needed to perform an ICS security assessment and the life cycle of this knowledge. Afterwards the ICS security knowledge and its life cycle are developed and discussed considering the requirements and related work.
In parcel delivery, the “last mile” from the parcel hub to the customer is costly, especially for time-sensitive delivery tasks that have to be completed within hours after arrival. Recently, crowdshipping has attracted increased attention as a new alternative to traditional delivery modes. In crowdshipping, private citizens (“the crowd”) perform short detours in their daily lives to contribute to parcel delivery in exchange for small incentives. However, achieving desirable crowd behavior is challenging as the crowd is highly dynamic and consists of autonomous, self-interested individuals. Leveraging crowdshipping for time-sensitive deliveries remains an open challenge. In this paper, we present an agent-based approach to on-time parcel delivery with crowds. Our system performs data stream processing on the couriers’ smartphone sensor data to predict delivery delays. Whenever a delay is predicted, the system attempts to forge an agreement for transferring the parcel from the current deliverer to a more promising courier nearby. Our experiments show that through accurate delay predictions and purposeful task transfers many delays can be prevented that would occur without our approach.
In this paper we investigate how concreteness and abstractness are represented in word embedding spaces. We use data for English and German, and show that concreteness and abstractness can be determined independently and turn out to be completely opposite directions in the embedding space. Various methods can be used to determine the direction of concreteness, always resulting in roughly the same vector. Though concreteness is a central aspect of the meaning of words and can be detected clearly in embedding spaces, it seems not as easy to subtract or add concreteness to words to obtain other words or word senses like e.g. can be done with a semantic property like gender.
The dependency of word similarity in vector space models on the frequency of words has been noted in a few studies, but has received very little attention. We study the influence of word frequency in a set of 10 000 randomly selected word pairs for a number of different combinations of feature weighting schemes and similarity measures. We find that the similarity of word pairs for all methods, except for the one using singular value decomposition to reduce the dimensionality of the feature space, is determined to a large extent by the frequency of the words. In a binary classification task of pairs of synonyms and unrelated words we find that for all similarity measures the results can be improved when we correct for the frequency bias.
Portable-micro-Combined-Heat-and-Power-units are a gateway technology bridging conventional vehicles and Battery Electric Vehicles (BEV). Being a new technology, new software has to be created that can be easily adapted to changing requirements. We propose and evaluate three different architectures based on three architectural paradigms. Using a scenario-based evaluation, we conclude that a Service-Oriented Architecture (SOA) using microservices provides a higher quality solution than a layered or Event-Driven Complex-Event-Processing (ED-CEP) approach. Future work will include implementation and simulation-driven evaluation.
NOA is a search engine for scientific images from open access publications based on full text indexing of all text referring to the images and filtering for disciplines and image type. Images will be annotated with Wikipedia categories for better discoverability and for uploading to WikiCommons. Currently we have indexed approximately 2,7 Million images from over 710 000 scientific papers from all fields of science.
Hadoop is a Java-based open source programming framework, which supports the processing and storage of large volumes of data sets in a distributed computing environment. On the other hand, an overwhelming majority of organizations are moving their big data processing and storing to the cloud to take advantage of cost reduction – the cloud eliminates the need for investing heavily in infrastructures, which may or may not be used by organizations. This paper shows how organizations can alleviate some of the obstacles faced when trying to make Hadoop run in the cloud.
We present a novel long short-term memory (LSTM) approach for time-series prediction of the sand demand which arises from preparing the sand moulds for the iron casting process of a foundry. With our approach, we contribute to qualify LSTM and its combination with feedback-corrected optimal scheduling for industrial processes.
The sand is produced in an energy intensive mixing process which is controlled by optimal scheduling. The optimal scheduling is solved for a fixed prediction horizon. One major influencing factor is the sand demand, which is highly disturbed, for example due to production interruptions. The causes of production interruptions are in general physically unknown. We assume that information about the future behavior of the sand demand is included in current and past process data. Therefore, we choose LSTM networks for predicting the time-series of the sand demand.
The sand demand prediction is performed by our multi model approach. This approach outperforms the currently used naive estimation, even when predicting far into the future. Our LSTM based prediction approach can forecast the sand demand with a conformity up to 38 % and a mean value accuracy of approximately 99%. Simulating the optimal scheduling with sand demand prediction leads to an improvement in energy savings of approximately 1.1% compared to the naive estimation. The application of our novel approach at the real production plant of a foundry proves the simulation results and verifies the capability of our approach.
In distributional semantics words are represented by aggregated context features. The similarity of words can be computed by comparing their feature vectors. Thus, we can predict whether two words are synonymous or similar with respect to some other semantic relation. We will show on six different datasets of pairs of similar and non-similar words that a supervised learning algorithm on feature vectors representing pairs of words outperforms cosine similarity between vectors representing single words. We compared different methods to construct a feature vector representing a pair of words. We show that simple methods like pairwise addition or multiplication give better results than a recently proposed method that combines different types of features. The semantic relation we consider is relatedness of terms in thesauri for intellectual document classification. Thus our findings can directly be applied for the maintenance and extension of such thesauri. To the best of our knowledge this relation was not considered before in the field of distributional semantics.
Against the background of climate change and finite fossil resources, bio-based plastics have been in the focus of research for the last decade and were identified as a promising alternative to fossil-based plastics. Now, with an evolving bio-based plastic market and application range, the environmental advantages of bio-based plastic have come to the fore and identified as crucial by different stakeholders. While the majority of assessments for bio-based plastics are carried out based on attributional life cycle assessment, there have been only few consequential studies done in this area. Also, the application of eco-design strategies has not been in the focus for the bio-based products due to the prevailing misconceptions of renewable materials (as feedstock for bio-based plastics) considered in itself as an ‘eco-design strategy’. In this paper, we discuss the life cycle assessment as well as eco-design strategies of a bio-based product taking attributional as well as consequential approaches into account.
Microservices is an architectural style for complex application systems, promising some crucial benefits, e.g. better maintainability, flexible scalability, and fault tolerance. For this reason microservices has attracted attention in the software development departments of different industry sectors, such as ecommerce and streaming services. On the other hand, businesses have to face great challenges, which hamper the adoption of the architectural style. For instance, data are often persisted redundantly to provide fault tolerance. But the synchronization of those data for the sake of consistency is a major challenge. Our paper presents a case study from the insurance industry which focusses consistency issues when migrating a monolithic core application towards microservices. Based on the Domain Driven Design (DDD) methodology, we derive bounded contexts and a set of microservices assigned to these contexts. We discuss four different approaches to ensure consistency and propose a best practice to identify the most appropriate approach for a given scenario. Design and implementation details and compliance issues are presented as well.
This paper presents a cascaded methodology for enhancing the path accuracy of industrial robots by using advanced control schemes. It includes kinematic calibration as well as dynamic modeling and identification. This is followed by a centralized model-based compensation of robot dynamics. The implemented feed-forward torque control shows the expected improvements of control accuracy. However, external measurements show the influence of joint elasticities as systematic path errors. To further increase the accuracy an iterative learning controller (ILC) based on external camera measurements is designed. The implementation yields to significant improvements of path accuracy. By means of a kind of automated ”Teach-In”, an overall effective concept for the automated calibration and optimization of the accuracy of industrial robots in high-dynamic path-applications is realized.
The impact of vertical and horizontal integration in the context of Industry 4.0 requires new concepts for the security of industrial Ethernet protocols. The defense in depth concept, basing on the combination of several measures, especially separation and segmentation, needs to be complimented by integrated protection measures for industrial real-time protocols. To cover this challenge, existing protocols need to be equipped with additional functionality to ensure the integrity and availability of the network communication, even in environments, where possible attackers can be present. In order to show a possible way to upgrade an existing protocol, this paper describes a security concept for the industrial Ethernet protocol PROFINET.
Autonomous mobile six-legged robots are able to demonstrate the potential of intelligent control systems based on recurrent neural networks. The robots evaluate only two forward and two backward looking infrared sensor signals. Fast converging genetic training algorithms are applied to train the robots to move straight in six directions. The robots performed successfully within an obstacle environment and there could be observed a never trained useful interaction between each of the single robots. The paper describes the robot systems and presents the test results. Video clips are downloadable under www.inform.fh-hannover.de/download/lechner.php. Held on IFAC International Conference on Intelligent Control Systems and Signal Processing (ICONS 2003, April 2003, Portugal).
After kidney transplantation graft rejection must be prevented. Therefore, a multitude of parameters of the patient is observed pre- and postoperatively. To support this process, the Screen Reject research project is developing a data warehouse optimized for kidney rejection diagnostics. In the course of this project it was discovered that important information are only available in form of free texts instead of structured data and can therefore not be processed by standard ETL tools, which is necessary to establish a digital expert system for rejection diagnostics. Due to this reason, data integration has been improved by a combination of methods from natural language processing and methods from image processing. Based on state-of-the-art data warehousing technologies (Microsoft SSIS), a generic data integration tool has been developed. The tool was evaluated by extracting Banff-classification from 218 pathology reports and extracting HLA mismatches from about 1700 PDF files, both written in german language.
Autonomous and integrated passenger and freight transport (APFIT) is a promising approach to tackle both, traffic and last-mile-related issues such as environmental emissions, social and spatial conflicts or operational inefficiencies. By conducting an agent-based simulation, we shed light on this widely unexplored research topic and provide first indications regarding influential target figures of such a system in the rural area of Sarstedt, Germany. Our results show that larger fleets entail inefficiencies due to suboptimal utilization of monetary and material resources and increase traffic volume while higher amounts of unused vehicles may exacerbate spatial conflicts. Nevertheless, to fit the given demand within our study area, a comparatively large fleet of about 25 vehicles is necessary to provide reliable service, assuming maximum passenger waiting times of six minutes to the expense of higher standby times, rebalancing effort, and higher costs for vehicle acquisition and maintenance.
Complex Event Processing (CEP) has been established as a well-suited software technology for processing high-frequent data streams. However, intelligent stream based systems must integrate stream data with semantical background knowledge. In this work, we investigate different approaches on integrating stream data and semantic domain knowledge. In particular, we discuss from a software engineering per- spective two different architectures: an approach adding an ontology access mechanism to a common Continuous Query Language (CQL) is compared with C-SPARQL, a streaming extension of the RDF query language SPARQL.
Integrating distributional and lexical information for semantic classification of words using MRMF
(2016)
Semantic classification of words using distributional features is usually based on the semantic similarity of words. We show on two different datasets that a trained classifier using the distributional features directly gives better results. We use Support Vector Machines (SVM) and Multirelational Matrix Factorization (MRMF) to train classifiers. Both give similar results. However, MRMF, that was not used for semantic classification with distributional features before, can easily be extended with more matrices containing more information from different sources on the same problem. We demonstrate the effectiveness of the novel approach by including information from WordNet. Thus we show, that MRMF provides an interesting approach for building semantic classifiers that (1) gives better results than unsupervised approaches based on vector similarity, (2) gives similar results as other supervised methods and (3) can naturally be extended with other sources of information in order to improve the results.
Nowadays, smartphones and sensor devices can provide a variety of information about a user’s current situation. So far, many recommender systems neglect this kind of information and thus cannot provide situationspecific recommendations. Situation-aware recommender systems adapt to changes in the user’s environment and therefore are able to offer recommendations that are more appropriate for the current situation. In this paper, we present a software architecture that enables situation awareness for arbitrary recommendation techniques. The proposed system considers both (semi-)static user profiles and volatile situational knowledge to obtain meaningful recommendations. Furthermore, the implementation of the architecture in a museum of natural history is presented, which uses Complex Event Processing to achieve situation awareness.
This paper describes the approach of the Hochschule Hannover to the SemEval 2013 Task Evaluating Phrasal Semantics. In order to compare a single word with a two word phrase we compute various distributional similarities, among which a new similarity measure, based on Jensen-Shannon Divergence with a correction for frequency effects. The classification is done by a support vector machine that uses all similarities as features. The approach turned out to be the most successful one in the task.
Social skills are essential for a successful understanding of agile methods in software development. Several studies highlight the opportunities and advantages of integrating real-world projects and problems while collaborating with companies into higher education using agile methods. This integration comes with several opportunities and advantages for both the students and the company. The students are able to interact with real-world software development teams, analyze and understand their challenges and identify possible measures to tackle them. However, the integration of real-world problems and companies is complex and may come with a high effort in terms of coordination and preparation of the course. The challenges related to the interaction and communication with students are increased by virtual distance teaching during the Covid-19 pandemic as direct contact with students is missing. Also, we do not know how problem-based learning in virtual distance teaching is valued by the students. This paper presents our adapted eduScrum approach and learning outcome of integrating experiments with real-world software development teams from two companies into a Master of Science course organized in virtual distance teaching. The evaluation shows that students value analyzing real-world problems using agile methods. They highlight the interaction with real-world software development teams. Also, the students appreciate the organization of the course using an iterative approach with eduScrum. Based on our findings, we present four recommendations for the integration of agile methods and real world problems into higher education in virtual distance teaching settings. The results of our paper contribute to the practitioner and researcher/lecturer community, as we provide valuable insights how to fill the gap between practice and higher education in virtual distance settings.
Context: Agile software development (ASD) sets social aspects like communication and collaboration in focus. Thus, one may assume that the specific work organization of companies impacts the work of ASD teams. A major change in work organization is the switch to a 4-day work week, which some companies investigated in experiments. Also, recent studies show that ASD teams are affected by the switch to remote work since the Covid 19 pandemic outbreak in 2020.
Objective: Our study presents empirical findings on the effects on ASD teams operating remote in a 4-day work week organization. Method: We performed a qualitative single case study and conducted seven semi-structured interviews, observed 14 agile practices and screened eight project documents and protocols of agile practices.
Results: We found, that the teams adapted the agile method in use due to the change to a 4-day work week environment and the switch to remote work. The productivity of the two ASD teams did not decrease. Although the stress level of the ASD team member increased due to the 4-day work week, we found that the job satisfaction of the individual ASD team members is affected positively. Finally, we point to affects on social facets of the ASD teams.
Conclusion: The research community benefits from our results as the current state of research dealing with the effects of a 4-day work week on ASD teams is limited. Also, our findings provide several practical implications for ASD teams working remote in a 4-day work week.
Complications may occur after a liver transplantation, therefore proper monitoring and care in the post-operation phase plays a very important role. Sometimes, monitoring and care for patients from abroad is difficult due to a variety of reasons, e.g., different care facilities. The objective of our research for this paper is to design, implement and evaluate a home monitoring and decision support infrastructure for international children who underwent liver transplant operation. A point-of-care device and the PedsQL questionnaire were used in patients’ home environment for measuring the blood parameters and assessing quality of life. By using a tablet PC and a specially developed software, the measured results were able to be transmitted to the health care providers via internet. So far, the developed infrastructure has been evaluated with four international patients/families transferring 38 records of blood test. The evaluation showed that the home monitoring and decision support infrastructure is technically feasible and is able to give timely alarm in case of abnormal situation as well as may increase parent’s feeling of safety for their children.
The technical, environmental and economic potential of hemp fines as a natural filler in bioplastics to produce biocomposites is the subject of this study – giving a holistic overview. Hemp fines are an agricultural by-product of the hemp fibres and shives production. Shives and fibres are for example used in the paper, animal bedding or composite area. About 15 to 20 wt.-% per kg hemp straw results in hemp fines after processing. In 2010 about 11,439 metric tons of hemp fines were produced in Europe. Hemp fines are an inhomogeneous material which includes hemp dust, shives and fibre. For these examinations the hemp fines are sieved in a further step with a tumbler sieving machine to obtain more specified fractions. The untreated hemp fines (ex work) as well as the sieved fractions are combined with a polylactide polymer (PLA) using a co-rotating twin screw extruder to produce biocomposites with different hemp fine content. By using an injection moulding machine standard test bars are produced to conduct several material tests. The Young’s modulus is increased and the impact strength reduced by hemp fines. With a content of above 15 wt.-% hemp fines are also improving the environmental (global warming potential) and economic performance in comparison to pure PLA.
In the context of modern mobility, topics such as smart-cities, Car2Car-Communication, extensive vehicle sensor-data, e-mobility and charging point management systems have to be considered. These topics of modern mobility often have in common that they are characterized by complex and extensive data situations. Vehicle position data, sensor data or vehicle communication data must be preprocessed, aggregated and analyzed. In many cases, the data is interdependent. For example, the vehicle position data of electric vehicles and surrounding charging points have a dependence on one another and characterize a competition situation between the vehicles. In the case of Car2Car-Communication, the positions of the vehicles must also be viewed in relation to each other. The data are dependent on each other and will influence the ability to establish a communication. This dependency can provoke very complex and large data situations, which can no longer be treated efficiently. With this work, a model is presented in order to be able to map such typical data situations with a strong dependency of the data among each other. Microservices can help reduce complexity.
Techno-economic analysis that allocate costs to the energy flows of energy systems are helpful to understand the formation of costs within processes and to increase the cost efficiency. For the economic evaluation, the usefulness or quality of the energy is of great importance. In exergy-based methods, this is considered by allocating costs to the exergy instead of energy. As exergy represents the ability of performing work, it is often named the useful part of energy. In contrast, the anergy, the part of energy, which cannot perform work, is often assumed to be not useful.
However, heat flows as used e.g. in domestic heating are always a mixture of a relative small portion of exergy and a big portion of anergy. Although of lower quality, the anergy is obviously useful for these applications. The question is, whether it makes sense to differentiate between exergy and anergy and take both properties into account for the economic evaluation.
To answer this question, a new methodical concept based on the definition of an anergy-exergy cost ratio is compared to the commonly applied approaches of considering either energy or exergy as the basis for economic evaluation. These three different approaches for the economic analysis of thermal energy systems are applied to an exemplary heating system with thermal storages. It is shown that the results of the techno-economic analysis can be improved by giving anergy an economic value and that the proposed anergy-cost ratio allows a flexible adaptation of the evaluation depending on the economic constraints of a system.
Flatness-based feedforward control is an approach for combining fast motion with low oscillations for nonlinear or flexible drive systems. Its desired trajectories must be continuously differentiable to the degree of the system order. Designing such trajectories, that also reach the dynamic system limits, poses a challenge. Common solutions, like Gevrey functions, usually require lengthy offline calculations. To achieve a quicker and simpler industrial-suited solution, this paper presents a new online trajectory generation scheme. The algorithm utilizes higher order s-curve trajectories created by a cyclic filtering process using moving average filters. An experimental validation proves the capability as well as industrial applicability of the presented approach for flexible structures like stacker cranes.
Our research project, "Rationalizing the virtualization of botanical document material and their usage by process optimization and automation (Herbar-Digital)" started on July 1, 2007 and will last until 2012. Its long-term aim is the digitization of the more than 3,5 million specimens in the Berlin Herbarium. The University of Applied Sciences and Arts in Hannover collaborates with the department of Biodiversity Informatics at the BGBM (Botanic Garden and Botanical Museum Berlin-Dahlem) headed by Walter Berendsohn. The part of Herbar-Digital here presented deals with the analysis of the generated high resolution images (10,400 lines x 7,500 pixel).
This paper presents a possibility to extend the formalism of linear indexed grammars. The extension is based on the use of tuples of pushdowns instead of one pushdown to store indices during a derivation. If a restriction on the accessibility of the pushdowns is used, it can be shown that the resulting formalisms give rise to a hierarchy of languages that is equivalent with a hierarchy defined by Weir. For this equivalence, that was already known for a slightly different formalism, this paper gives a new proof. Since all languages of Weir's hierarchy are known to be mildly context sensitive, the proposed extensions of LIGs become comparable with extensions of tree adjoining grammars and head grammars.
Nowadays, REST is the most dominant architectural style of choice at least for newly created web services. So called RESTfulness is thus really a catchword for web application, which aim to expose parts of their functionality as RESTful web services. But are those web services RESTful indeed? This paper examines the RESTfulness of ten popular RESTful APIs (including Twitter and PayPal). For this examination, the paper defines REST, its characteristics as well as its pros and cons. Furthermore, Richardson's Maturity Model is shown and utilized to analyse those selected APIs regarding their RESTfulness. As an example, a simple, RESTful web service is provided as well.
Our work is motivated primarily by the lack of standardization in the area of Event Processing Network (EPN) models. We identify general requirements for such models. These requirements encompass the possibility to describe events in the real world, to establish temporal and causal relationships among the events, to aggregate the events, to organize the events into a hierarchy, to categorize the events into simple or complex, to create an EPN model in an easy and simple way and to use that model ad hoc. As the major contribution, this paper applies the identified requirements to the RuleCore model.
Editorial for the 17th European Networked Knowledge Organization Systems Workshop (NKOS 2017)
(2017)
Knowledge Organization Systems (KOS), in the form of classification systems, thesauri, lexical databases, ontologies, and taxonomies, play a crucial role in digital information management and applications generally. Carrying semantics in a well-controlled and documented way, Knowledge Organization Systems serve a variety of important functions: tools for representation and indexing of information and documents, knowledge-based support to information searchers, semantic road maps to domains and disciplines, communication tool by providing conceptual framework, and conceptual basis for knowledge based systems, e.g. automated classification systems. New networked KOS (NKOS) services and applications are emerging, and we have reached a stage where many KOS standards exist and the integration of linked services is no longer just a future scenario. This editorial describes the workshop outline and overview of presented papers at the 17th European Networked Knowledge Organization Systems Workshop (NKOS 2017) which was held during the TPDL 2017 Conference in Thessaloniki, Greece.
Editorial for the 15th European Networked Knowledge Organization Systems Workshop (NKOS 2016)
(2016)
Knowledge Organization Systems (KOS), in the form of classification systems, thesauri, lexical databases, ontologies, and taxonomies, play a crucial role in digital information management and applications generally. Carrying semantics in a well-controlled and documented way, Knowledge Organisation Systems serve a variety of important functions: tools for representation and indexing of information and documents, knowledge-based support to information searchers, semantic road maps to domains and disciplines, communication tool by providing conceptual framework, and conceptual basis for knowledge based systems, e.g. automated classification systems. New networked KOS (NKOS) services and applications are emerging, and we have reached a stage where many KOS standards exist and the integration of linked services is no longer just a future scenario. This editorial describes the workshop outline and overview of presented papers at the 15th European Networked Knowledge Organization Systems Workshop (NKOS 2016) in Hannover, Germany.
Discovery and efficient reuse of technology pictures using Wikimedia infrastructures. A proposal
(2016)
Multimedia objects, especially images and figures, are essential for the visualization and interpretation of research findings. The distribution and reuse of these scientific objects is significantly improved under open access conditions, for instance in Wikipedia articles, in research literature, as well as in education and knowledge dissemination, where licensing of images often represents a serious barrier.
Whereas scientific publications are retrievable through library portals or other online search services due to standardized indices there is no targeted retrieval and access to the accompanying images and figures yet. Consequently there is a great demand to develop standardized indexing methods for these multimedia open access objects in order to improve the accessibility to this material.
With our proposal, we hope to serve a broad audience which looks up a scientific or technical term in a web search portal first. Until now, this audience has little chance to find an openly accessible and reusable image narrowly matching their search term on first try - frustratingly so, even if there is in fact such an image included in some open access article.
Building a well-founded understanding of the concepts, tasks and limitations of IT in all areas of society is an essential prerequisite for future developments in business and research. This applies in particular to the healthcare sector and medical research, which are affected by the noticeable advances in digitization. In the transfer project “Zukunftslabor Gesundheit” (ZLG), a teaching framework was developed to support the development of further education online courses in order to teach heterogeneous groups of learners independent of location and prior knowledge. The study at hand describes the development and components of the framework.
For the analysis of contract texts, validated model texts, such as model clauses, can be used to identify used contract clauses. This paper investigates how the similarity between titles of model clauses and headings extracted from contracts can be computed, and which similarity measure is most suitable for this. For the calculation of the similarities between title pairs we tested various variants of string similarity and token based similarity. We also compare two additional semantic similarity measures based on word embeddings using pre-trained embeddings and word embeddings trained on contract texts. The identification of the model clause title can be used as a starting point for the mapping of clauses found in contracts to verified clauses.
Since textual user generated content from social media platforms contains valuable information for decision support and especially corporate credit risk analysis, automated approaches for text classification such as the application of sentiment dictionaries and machine learning algorithms have received great attention in recent user generated content based research endeavors. While machine learning algorithms require individual training data sets for varying sources, sentiment dictionaries can be applied to texts immediately, whereby domain specific dictionaries attain better results than domain independent word lists. We evaluate by means of a literature review how sentiment dictionaries can be constructed for specific domains and languages. Then, we construct nine versions of German sentiment dictionaries relying on a process model which we developed based on the literature review. We apply the dictionaries to a manually classified German language data set from Twitter in which hints for financial (in)stability of companies have been proven. Based on their classification accuracy, we rank the dictionaries and verify their ranking by utilizing Mc Nemar’s test for significance. Our results indicate, that the significantly best dictionary is based on the German language dictionary SentiWortschatz and an extension approach by use of the lexical-semantic database GermaNet. It achieves a classification accuracy of 59,19 % in the underlying three-case-scenario, in which the Tweets are labelled as negative, neutral or positive. A random classification would attain an accuracy of 33,3 % in the same scenario and hence, automated coding by use of the sentiment dictionaries can lead to a reduction of manual efforts. Our process model can be adopted by other researchers when constructing sentiment dictionaries for various domains and languages. Furthermore, our established dictionaries can be used by practitioners especially in the domain of corporate credit risk analysis for automated text classification which has been conducted manually to a great extent up to today.
In microservice architectures, data is often hold redundantly to create an overall resilient system. Although the synchronization of this data proposes a significant challenge, not much research has been done on this topic yet. This paper shows four general approaches for assuring consistency among services and demonstrates how to identify the best solution for a given architecture. For this, a microservice architecture, which implements the functionality of a mainframe-based legacy system from the insurance industry, serves as an example.
With an increasing complexity and scale, sufficient evaluation of Information Systems (IS) becomes a challenging and difficult task. Simulation modeling has proven as suitable and efficient methodology for evaluating IS and IS artifacts, presupposed it meets certain quality demands. However, existing research on simulation modeling quality solely focuses on quality in terms of accuracy and credibility, disregarding the role of additional quality aspects. Therefore, this paper proposes two design artifacts in order to ensure a holistic quality view on simulation quality. First, associated literature is reviewed in order to extract relevant quality factors in the context of simulation modeling, which can be used to evaluate the overall quality of a simulated solution before, during or after a given project. Secondly, the deduced quality factors are integrated in a quality assessment framework to provide structural guidance on the quality assessment procedure for simulation. In line with a Design Science Research (DSR) approach, we demonstrate the eligibility of both design artifacts by means of prototyping as well as an example case. Moreover, the assessment framework is evaluated and iteratively adjusted with the help of expert feedback.
In this paper we describe the selection of a modern build automation tool for an industry research partner of ours, namely an insurance company. Build automation has become increasingly important over the years. Today, build automation became one of the central concepts in topics such as cloud native development based on microservices and DevOps. Since more and more products for build automation have entered the market and existing tools have changed their functional scope, there is nowadays a large number of tools on the market that differ greatly in their functional scope. Based on requirements from our partner company, a build server analysis was conducted. This paper presents our analysis requirements, a detailed look at one of the examined tools and a summarizes our comparison of all three tools from our final comparison round.
With regard to climate change, increasing energy efficiency is still a significant issue in the industry. In order to acquire energy data at the field level, so-called energy profiles can be used. They are advantageous as they are integrated into existing industrial ethernet standards (e.g. PROFINET). Commonly used energy profiles such as PROFIenergy and sercos Energy have been established in industrial use. However, as the Industrial Internet of Things (IIoT) continues to develop, the question arises whether the established energy profiles are sufficient to fullfil the requirements of the upcoming IIoT communication technologies. To answer this question the paper compares and discusses the common energy profiles with the current and future challenges of energy data communication. Furthermore, this analysis examines the need for further research in this field.
A new FOSS (free and open source software) toolchain and associated workflow is being developed in the context of NFDI4Culture, a German consortium of research- and cultural heritage institutions working towards a shared infrastructure for research data that meets the needs of 21st century data creators, maintainers and end users across the broad spectrum of the digital libraries and archives field, and the digital humanities. This short paper and demo present how the integrated toolchain connects: 1) OpenRefine - for data reconciliation and batch upload; 2) Wikibase - for linked open data (LOD) storage; and 3) Kompakkt - for rendering and annotating 3D models. The presentation is aimed at librarians, digital curators and data managers interested in learning how to manage research datasets containing 3D media, and how to make them available within an open data environment with 3D-rendering and collaborative annotation features.
The CogALex-V Shared Task provides two datasets that consists of pairs of words along with a classification of their semantic relation. The dataset for the first task distinguishes only between related and unrelated, while the second data set distinguishes several types of semantic relations. A number of recent papers propose to construct a feature vector that represents a pair of words by applying a pairwise simple operation to all elements of the feature vector. Subsequently, the pairs can be classified by training any classification algorithm on these vectors. In the present paper we apply this method to the provided datasets. We see that the results are not better than from the given simple baseline. We conclude that the results of the investigated method are strongly depended on the type of data to which it is applied.
Cloud Computing: Serverless
(2021)
A serverless architecture is a new approach to offering services over the Internet. It combines BaaS (Backend-as-a-service) and FaaS (Function-as-a-service). With the serverless architecture no own or rented infrastructures are needed anymore. In addition, the company does not have to worry about scaling any longer, as this happens automatically and immediately. Furthermore, there is no need any longer for maintenance work on the servers, as this is completely taken over by the provider. Administrators are also no longer needed for the same reason. Finally, many ready-made functions are offered, with which the development effort can be reduced. As a result, the serverless architecture is very well suited to many application scenarios, and it can save considerable costs (server costs, maintenance costs, personnel costs, electricity costs, etc.). The company only must subdivide the source code of the application and upload it to the provider’s server. The rest is done by the provider.
The amount of papers published yearly increases since decades. Libraries need to make these resources accessible and available with classification being an important aspect and part of this process. This paper analyzes prerequisites and possibilities of automatic classification of medical literature. We explain the selection, preprocessing and analysis of data consisting of catalogue datasets from the library of the Hanover Medical School, Lower Saxony, Germany. In the present study, 19,348 documents, represented by notations of library classification systems such as e.g. the Dewey Decimal Classification (DDC), were classified into 514 different classes from the National Library of Medicine (NLM) classification system. The algorithm used was k-nearest-neighbours (kNN). A correct classification rate of 55.7% could be achieved. To the best of our knowledge, this is not only the first research conducted towards the use of the NLM classification in automatic classification but also the first approach that exclusively considers already assigned notations from other
classification systems for this purpose.
Regional Innovation Systems describe the relations between actors, structures and infrastructures in a region in order to stimulate innovation and regional development. For these systems the collection and organization of information is crucial. In the present paper we investigate the possibilities to extract information from websites of companies. First we describe regional innovation systems and the information types that are necessary to create them. Then we discuss the possibilities of text mining and keyword extraction techniques to extract this information from company websites. Finally, we describe a small scale experiment in which keywords related to economic sectors and commodities are extracted from the websites of over 200 companies. This experiment shows what the main challenges are for information extraction from websites for regional innovation systems.
BYOD Bring Your Own Device
(2013)
Using modern devices like smartphones and tablets offers a wide variety of advantages; this has made them very popular as consumer devices in private life. Using them in the workplace is also popular. However, who wants to carry around and handle two devices; one for personal use, and one for work-related tasks? That is why “dual use”, using one single device for private and business applications, may represent a proper solution. The result is “Bring Your Own Device,” or BYOD, which describes the circumstance in which users make their own personal devices available for company use. For companies, this brings some opportunities and risks. We describe and discuss organizational issues, technical approaches, and solutions.