Refine
Year of publication
Document Type
- Conference Proceeding (162) (remove)
Has Fulltext
- yes (162)
Is part of the Bibliography
- no (162)
Keywords
- Digitalisierung (9)
- Energiemanagement (8)
- Mikroservice (8)
- Angewandte Botanik (7)
- Gepresste Pflanzen (7)
- Herbar Digital (7)
- Herbarium (7)
- Serviceorientierte Architektur (7)
- Virtualisierung (7)
- Agile Softwareentwicklung (6)
Die Weltwirtschaftskrise des Jahres 1929 beendete ein „goldenes Zeitalter“. Sie veränderte nachhaltig die internationale Völkergemeinschaft, unter anderem in Bezug auf den Welthandel, die Finanzströme und die Arbeitslosigkeit. Die Auswirkungen unserer heutigen Krise scheinen vergleichbar, die Ausgangslage, Ursachen und Verantwortung sind jedoch grundverschieden.<br /> Kein Lehrbuch und keine Vorlesung haben uns auf diese Krisenform vorbereitet. Auch liegen keine wirtschaftspolitischen Erfahrungen vor, die als Grundlage zur Bewältigung einer Krise in dieser Dimension dienen könnten. Aber wir können– obgleich die Krise andauert – schon heute beobachten, dass die Konsequenzen anders ausfallen und zu langfristigen, einschneidenden Veränderungen führen.<br /> Mit unserer Fachveranstaltung bieten wir Erklärungsansätze und diskutieren über Verantwortung und Konsequenzen. Drei Beiträge führen aus unterschiedlichen Perspektiven in das Thema ein.
„Grappa“ ist eine Middleware, die auf die Anbindung verschiedener Autobewerter an verschiedene E-Learning-Frontends respektive Lernmanagementsysteme (LMS) spezialisiert ist. Ein Prototyp befindet sich seit mehreren Semestern an der Hochschule Hannover mit dem LMS „moodle“ und dem Backend „aSQLg“ im Einsatz und wird regelmäßig evaluiert. Dieser Beitrag stellt den aktuellen Entwicklungsstand von Grappa nach diversen Neu- und Weiterentwicklungen vor. Nach einem Bericht über zuletzt gesammelte Erfahrungen mit der genannten Kombination von Systemen stellen wir wesentliche Neuerungen der moodle-Plugins, welche der Steuerung von Grappa aus moodle heraus dienen, vor. Anschließend stellen wir eine Erweiterung der bisherigen Architektur in Form eines neuentwickelten Grappa-php-Clients zur effizienteren Anbindung von LMS vor. Weiterhin berichten wir über die Anbindung eines weiteren Autobewerters „Graja“ für Programmieraufgaben in Java. Der Bericht zeigt, dass bereits wichtige Schritte für eine einheitliche Darstellung automatisierter Programmbewertung in LMS mit unterschiedlichen Autobewertern für die Studierenden absolviert sind. Die praktischen Erfahrungen zeigen aber auch, dass sowohl bei jeder der Systemkomponenten individuell, wie auch in deren Zusammenspiel via Grappa noch weitere Entwicklungsarbeiten erforderlich sind, um die Akzeptanz und Nutzung bei Studierenden sowie Lehrenden weiter zu steigern.
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.
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.
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.
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.
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.
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.
The Logical Observation Identifiers, Names and Codes (LOINC) is a common terminology used for standardizing laboratory terms. Within the consortium of the HiGHmed project, LOINC is one of the central terminologies used for health data sharing across all university sites. Therefore, linking the LOINC codes to the site-specific tests and measures is one crucial step to reach this goal. In this work we report our ongoing efforts in implementing LOINC to our laboratory information system and research infrastructure, as well as our challenges and the lessons learned. 407 local terms could be mapped to 376 LOINC codes of which 209 are already available to routine laboratory data. In our experience, mapping of local terms to LOINC is a widely manual and time consuming process for reasons of language and expert knowledge of local laboratory procedures.
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.
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.
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.
In vielen Fällen muss vor dem Kleben eine Klebflächenbehandlung durchgeführt werden, da Klebverbindungen mit unvorbehandelten Teilen häufig zu geringe Klebfestigkeiten und/oder eine unzureichende Alterungsbeständigkeit aufweisen. Zur Klebflächenbehandlung stehen unterschiedliche Verfahren zur Verfügung. Wenn mit mehreren Behandlungen klebtechnisch einwandfreie Verbindungen hergestellt werden können, gilt es, das Verfahren zu ermitteln, welches am besten in den Fertigungsfluss integriert werden kann und die geringsten Kosten verursacht. Dabei muss auch die Arbeitssicherheit und der Umweltschutz mit beachtet werden. Zur Beurteilung der Verfahren werden Bewertungskriterien gegeben. Die Verfahren werden abschließend kurz charakterisiert.
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.
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.
l. Einleitung/Ausgangssituation - Auswirkungen unabgestimmter Prozesse - Prozeßnahe Werkstattsteuerungen 2. Defizite, Prozeßanforderungen - Daten-Anforderungsprofil - Datenvolumen-Trichtermodell - Argumente für Leitstand-Einsatz 3. Integrierter Leitstandeinsatz - Top-Down-Ansatz - Integrierte Regelkreise - Hierarchisches Planungs- und Steuerungskonzept 4. Abgrenzung zwischen Leitstand-, PPS und BDE-Funktionen - Ressourcen-Verfügbarkeitsanforderungen - Leitstand-Funktionsumfang - Integrierter Logistik-Sollablauf 5. Kennzeichen der 2ten Leitstandgeneration - Wissensbasierter LS-Einsatz - Event-Steuerungen 6. Anforderungsgerechte Leitstandeinführung - CIM-house-Modell - Mitarbeiter-Anforderungen
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).
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.
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.
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.
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.
INHALT: l. Einleitung und Standortbestimmung 2. Japanische Wertvorstellungen 3. Inhalte der Lean Production 4. Fertigungssegmentierung 5. Informationsmanagement mit CIM- und Logistik-Komponenten 6. Logistikgerechte Strukturen der Lean Production 7. Realisierung der Lean Production 8. Zusammenfassung
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.
An der Fachhochschule Hannover wurde Mitte 2007 das Projekt "Herbar-Digital" gestartet. In dem Forschungsprojekt "Herbar-Digital" sollen aus 3,5 Millionen Papierbögen (Herbarbelege) des Botanischen Museums Berlin möglichst alle Objekte erkannt werden und separat verarbeitbar sein. Bei den Objekten handelt es sich um Barcodes, Tüten, Stempel, Farbtabellen, Elemente aus dem Pflanzenbereich sowie Hand- und Druckschriften. Es soll unter Zuhilfenahme des ADA-BOOST-Algorithmus vom Verfasser eine Objekterkennung realisiert werden, die folgende Eigenschaften aufweist: Position der zu erkennenden Objekte im Bild variabel, auch dreidimensionale - und konturschwache Objekte müssen erkannt werden, gleiche Objekte unterschiedlicher Form müssen erkennbar sein, das System muss lernfähig sein.
Das Forschungsprojekt „Herbar Digital” startete 2007 mit dem Ziel der Digitalisierung des Bestands von mehr als 3,5 Millionen getrockneter Pflanzen bzw. Pflanzenteile auf Papierbögen (Herbarbelege) des Botanischen Museums Berlin. Die Aufgabe des Autors ist die Analyse der hochaufgelösten Bilder mit 10400 Zeilen und 7500 Spalten. Die Herbarbelege können außerdem unterschiedliche Objekte enthalten wie Umschläge mit zusätzlichen Pflanzenteilen, gedruckte oder handgeschriebene Etiketten, Farbtabellen, Maßstäbe, Stempel, Barcodes, farbige „Typus-Etiketten“ und handschriftliche Anmerkungen direkt auf dem Beleg. Die schriftlichen Anmerkungen, insbesondere in Handschrift, sind von besonderem Interesse. Kommerzielle OCR-Software kann oftmals Schrift in komplexen Umgebungen nicht lokalisieren, wie sie häufig auf den Herbarbelegen vorliegt, auf denen Schrift zwischen Blättern, Wurzeln und anderen Objekten angeordnet ist. Im folgenden wird eine Methode vorgestellt, die es ermöglicht, Schriftpassagen im Bild automatisch zu finden.
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.
Der Bachelor-Studiengang Mediendesigninformatik der Hochschule Hannover ist ein Informatikstudiengang mit dem speziellen Anwendungsgebiet Mediendesign. In Abgrenzung von Studiengängen der Medieninformatik liegt der Anwendungsfokus auf der kreativen Gestaltung etwa von 3D-Modellierungen, Animationen und Computerspielen. Absolvent*innen des Studiengangs sollen an der Schnittstelle zwischen Informatik und Mediendesign agieren können, zum Beispiel bei der Erstellung von Benutzungsschnittstellen und VR/AR-Anwendungen. Der Artikel stellt das Curriculum des interdisziplinären Studiengangs vor und reflektiert nach dem Abschluss der ersten beiden Studierendenkohorten die Erfahrungen, indem die ursprünglichen Ziele den Zahlen der Hochschulstatistik und den Ergebnissen zweier Studierendenbefragungen gegenübergestellt werden.
An der Bibliothek der Fachhochschule Hannover (FHH) ergab sich durch den Umzug eines Fachbereiches und die Auslagerung der entsprechenden Bestände die Chance, die defizitäre Situation bezüglich studentischer Arbeitsplätze zu verbessern. Das bisherige offene Konzept mit einem Nebeneinander von Medienaufstellung, Einzel- sowie Gruppenarbeitsplätzen hatte zu erheblichen Störungen der durchaus noch vorhandenen still lesenden Bibliotheksnutzern geführt. Die Zahl der Arbeitsplätze zu erhöhen und gleichzeitig die Arbeitsbedingungen hinsichtlich Akustik und Klimatisierung zu verbessern war deshalb vorrangiges Ziel eines studentischen Projektes des Studiengangs Innenarchitektur der FHH. Als Ergebnis entstand ein einheitliches Gesamtkonzept mit einer strikten Trennung der Funktionsbereiche und eine Vielzahl unterschiedlicher Einzelmaßnahmen (Nutzbare Atrien, Bibliothekslounge, Lernkabinen etc.). Nach der Entscheidung der Hochschulleitung, die Umbaumaßnahmen aus Studienbeiträgen zu finanzieren,wurde in Kooperation von Hochschule (Bibliotheksleitung, Liegenschaftsdezernat), Staatlichem Baumanagement, einem beauftragten freien Architekturbüro sowie einem Akustiker mit Planung und schrittweiser Realisierung der Umbaumaßnahmen begonnen. Im Vortrag werden das Konzept, der Planungsprozess sowie inzwischen (Stand: 5/2008) geplante und realisierte Baumaßnahmen anhand zahlreicher Illustrationen erläutert.
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.
Da mit wachsender Verwendung von Kunststoffen für konstruktive Anwendungen deren Klebbarkeit immer größere Bedeutung erhält und Vorbehandlungen mit umweltbelastenden Verfahren nur mit Vorbehalt eigesetzt werden können, dürften umweltfreundliche Verbehandlungen, wie die Vorbehandlung im Niederdruckplasma, im Folgenden kurz NDP-Vorbehandlung genannt, eine steigende Bedeutung erlangen. Die Umweltfreundlichkeit des Verfahrens ist darin begründet, dass keine verbrauchten Beizbäder anfallen, die mit hohem Aufwand beseitigt werden müssen, und dass der Prozess in einem geschlossenem System abläuft und somit ein unkontrolliertes Entweichen von Schadstoffen nicht möglich ist. Bei der Ndp-Behandlung gegebenenfalls entstehende Schadstoffe fallen nur in sehr geringem Umfang an und können leicht abgefangen und nachbehandelt werden. Da die verwendeten Gase nicht giftig sind, geht von ihnen keine Gefährdung aus.
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.
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.
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.
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.
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.
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.
The German Corona Consensus (GECCO) established a uniform dataset in FHIR format for exchanging and sharing interoperable COVID-19 patient specific data between health information systems (HIS) for universities. For sharing the COVID-19 information with other locations that use openEHR, the data are to be converted in FHIR format. In this paper, we introduce our solution through a web-tool named “openEHR-to-FHIR” that converts compositions from an openEHR repository and stores in their respective GECCO FHIR profiles. The tool provides a REST web service for ad hoc conversion of openEHR compositions to FHIR profiles.
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%.
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.
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.
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.
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 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.
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.
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.
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.