Informatik

Permanent URI for this collection

https://oa.tib.eu/renate/handle/123456789/4453

Browse

Now showing 1 - 20 of 215

168-195 GHz Power Amplifier with Output Power Larger Than 18 dBm in BiCMOS Technology
(New York, NY : IEEE, 2020) Ali, Abdul; Yun, Jongwon; Giannini, Franco; Ng, Herman Jalli; Kissinger, Dietmar; Colantonio, Paolo
This paper presents a 4-way combined G-band power amplifier (PA) fabricated with a 130-nm SiGe BiCMOS process. First, a single-ended PA based on the cascode topology (CT) is designed at 185 GHz, which consists of three stages to get an overall gain and an output power higher than 27 dB and 13 dBm, respectively. Then, a 4-way combiner/splitter was designed using low-loss transmission lines at 130-210 GHz. Finally, the combiner was loaded with four single-ended PAs to complete the design of a 4-way combined PA. The chip of the fabricated PA occupies an area of 1.35mm2. The realized PA shows a saturated output power of 18.1 dBm with a peak gain of 25.9 dB and power-added efficiency (PAE) of 3.5% at 185 GHz. A maximum output power of 18.7 dBm with PAE of 4.4% is achieved at 170 GHz. The 3-dB and 6-dB bandwidth of the PA are 27 and 42 GHz, respectively. In addition, the PA delivers a saturated output power higher than 18 dBm in the frequency range 140-186 GHz. To the best of our knowledge, the power reported in this paper is the highest for G-band SiGe BiCMOS PAs. © 2013 IEEE.
3-Step flow focusing enables multidirectional imaging of bioparticles for imaging flow cytometry
(Cambridge : RSC, 2020) Kleiber, Andreas; Ramoji, Anuradha; Mayer, Günter; Neugebauer, Ute; Popp, Jürgen; Henkel, Thomas
Multidirectional imaging flow cytometry (mIFC) extends conventional imaging flow cytometry (IFC) for the image-based measurement of 3D-geometrical features of particles. The innovative core is a flow rotation unit in which a vertical sample lamella is incrementally rotated by 90 degrees into a horizontal lamella. The required multidirectional views are generated by guiding all particles at a controllable shear flow position of the parabolic velocity profile of the capillary slit detection chamber. All particles pass the detection chamber in a two-dimensional sheet under controlled rotation while each particle is imaged multiple times. This generates new options for automated particle analysis. In an experimental application, we used our system for the accurate classification of 15 species of pollen based on 3D-morphological information. We demonstrate how the combination of multi directional imaging with advanced machine learning algorithms can improve the accuracy of automated bio-particle classification. As an additional benefit, we significantly decrease the number of false positives in the classification of foreign particles,i.e.those elements which do not belong to one of the trained classes by the 3D-extension of the classification algorithm. © The Royal Society of Chemistry 2020.
5G transport network requirements for the next generation fronthaul interface
(Heidelberg : Springer, 2017) Bartelt, J.; Vucic, N.; Camps-Mur, D.; Garcia-Villegas, E.; Demirkol, I.; Fehske, A.; Grieger, M.; Tzanakaki, A.; Gutiérrez, J.; Grass, E.; Lyberopoulos, G.; Fettweis, G.
To meet the requirements of 5G mobile networks, several radio access technologies, such as millimeter wave communications and massive MIMO, are being proposed. In addition, cloud radio access network (C-RAN) architectures are considered instrumental to fully exploit the capabilities of future 5G RANs. However, RAN centralization imposes stringent requirements on the transport network, which today are addressed with purpose-specific and expensive fronthaul links. As the demands on future access networks rise, so will the challenges in the fronthaul and backhaul segments. It is hence of fundamental importance to consider the design of transport networks alongside the definition of future access technologies to avoid the transport becoming a bottleneck. Therefore, we analyze in this work the impact that future RAN technologies will have on the transport network and on the design of the next generation fronthaul interface. To understand the especially important impact of varying user traffic, we utilize measurements from a real-world 4G network and, taking target 5G performance figures into account, extrapolate its statistics to a 5G scenario. With this, we derive both per-cell and aggregated data rate requirements for 5G transport networks. In addition, we show that the effect of statistical multiplexing is an important factor to reduce transport network capacity requirements and costs. Based on our investigations, we provide guidelines for the development of the 5G transport network architecture.
About Migration Flows and Sentiment Analysis on Twitter Data: Building the Bridge Between Technical and Legal approaches to data protection
(Paris : European Language Resources Association (ELRA), 2022) Gottschalk, Thilo; Pichierri, Francesca; Rigault, Mickaël; Arranz, Victoria; Siegert, Ingo
Sentiment analysis has always been an important driver of political decisions and campaigns across all fields. Novel technologies allow automatizing analysis of sentiments on a big scale and hence provide allegedly more accurate outcomes. With user numbers in the billions and their increasingly important role in societal discussions, social media platforms become a glaring data source for these types of analysis. Due to its public availability, the relative ease of access and the sheer amount of available data, the Twitter API has become a particularly important source to researchers and data analysts alike. Despite the evident value of these data sources, the analysis of such data comes with legal, ethical and societal risks that should be taken into consideration when analysing data from Twitter. This paper describes these risks along the technical processing pipeline and proposes related mitigation measures.
Advances in Semantics and Explainability for NLP: Joint Proceedings of the 2nd International Workshop on Deep Learning meets Ontologies and Natural Language Processing (DeepOntoNLP 2021) & 6th International Workshop on Explainable Sentiment Mining and Emotion Detection (X-SENTIMENT 2021), co-located with the 18th Extended Semantic Web Conference (ESWC 2021)
(Aachen : RWTH Aachen, 2021) Ben Abbès, Sarra; Hantach, Rim; Calvez, Philippe; Buscaldi, Davide; Dessì, Danilo; Dragoni, Mauro; Reforgiato Recupero, Diego; Sack, Harald
[no abstract available]
An AI-based open recommender system for personalized labor market driven education
(Amsterdam [u.a.] : Elsevier Science, 2022) Tavakoli, Mohammadreza; Faraji, Abdolali; Vrolijk, Jarno; Molavi, Mohammadreza; Mol, Stefan T.; Kismihók, Gábor
Attaining those skills that match labor market demand is getting increasingly complicated, not in the last place in engineering education, as prerequisite knowledge, skills, and abilities are evolving dynamically through an uncontrollable and seemingly unpredictable process. Anticipating and addressing such dynamism is a fundamental challenge to twenty-first century education. The burgeoning availability of data, not only on the demand side but also on the supply side (in the form of open educational resources) coupled with smart technologies, may provide a fertile ground for addressing this challenge. In this paper, we propose a novel, Artificial Intelligence (AI) driven approach to the development of an open, personalized, and labor market oriented learning recommender system, called eDoer. We discuss the complete system development cycle starting with a systematic user requirements gathering, and followed by system design, implementation, and validation. Our recommender prototype (1) derives the skill requirements for particular occupations through an analysis of online job vacancy announcements
Analogue pattern recognition with stochastic switching binary CMOS-integrated memristive devices
([London] : Macmillan Publishers Limited, part of Springer Nature, 2020) Zahari, Finn; Pérez, Eduardo; Mahadevaiah, Mamathamba Kalishettyhalli; Kohlstedt, Hermann; Wenger, Christian; Ziegler, Martin
Biological neural networks outperform current computer technology in terms of power consumption and computing speed while performing associative tasks, such as pattern recognition. The analogue and massive parallel in-memory computing in biology differs strongly from conventional transistor electronics that rely on the von Neumann architecture. Therefore, novel bio-inspired computing architectures have been attracting a lot of attention in the field of neuromorphic computing. Here, memristive devices, which serve as non-volatile resistive memory, are employed to emulate the plastic behaviour of biological synapses. In particular, CMOS integrated resistive random access memory (RRAM) devices are promising candidates to extend conventional CMOS technology to neuromorphic systems. However, dealing with the inherent stochasticity of resistive switching can be challenging for network performance. In this work, the probabilistic switching is exploited to emulate stochastic plasticity with fully CMOS integrated binary RRAM devices. Two different RRAM technologies with different device variabilities are investigated in detail, and their potential applications in stochastic artificial neural networks (StochANNs) capable of solving MNIST pattern recognition tasks is examined. A mixed-signal implementation with hardware synapses and software neurons combined with numerical simulations shows that the proposed concept of stochastic computing is able to process analogue data with binary memory cells. © 2020, The Author(s).
Analysis of Knowledge Tracing performance on synthesised student data
(Hannover : Technische Informationsbibliothek, 2024) Pagonis, Panagiotis; Hartung, Kai; Wu, Di; Georges, Munir; Gröttrup, Sören
Knowledge Tracing (KT) aims to predict the future performance of students by tracking the development of their knowledge states. Despite all the recent progress made in this field, the application of KT models in education systems is still restricted from the data perspectives: 1) limited access to real life data due to data protection concerns, 2) lack of diversity in public datasets, 3) noises in benchmark datasets such as duplicate records. To resolve these problems, we simulated student data with three statistical strategies based on public datasets and tested their performance on two KT baselines. While we observe only minor performance improvement with additional synthetic data, our work shows that using only synthetic data for training can lead to similar performance as real data.
Analysis of Single Event Transient Effects in Standard Delay Cells Based on Decoupling Capacitors
(Singapore [u.a.] : World Scientific, 2022) Andjelkovic, Marko; Marjanovic, Milos; Drasko, Bojan; Calligaro, Cristiano; Schrape, Oliver; Gatti, Umberto; Kuentzer, Felipe A.; Ilic, Stefan; Ristic, Goran; Krstic, Milos
Single Event Transients (SETs), i.e., voltage glitches induced in combinational logic as a result of the passage of energetic particles, represent an increasingly critical reliability threat for modern complementary metal oxide semiconductor (CMOS) integrated circuits (ICs) employed in space missions. In rad-hard ICs implemented with standard digital cells, special design techniques should be applied to reduce the Soft Error Rate (SER) due to SETs. To this end, it is essential to consider the SET robustness of individual standard cells. Among the wide range of logic cells available in standard cell libraries, the standard delay cells (SDCs) implemented with the skew-sized inverters are exceptionally vulnerable to SETs. Namely, the SET pulses induced in these cells may be hundreds of picoseconds longer than those in other standard cells. In this work, an alternative design of a SDC based on two inverters and two decoupling capacitors is introduced. Electrical simulations have shown that the propagation delay and SET robustness of the proposed delay cell are strongly influenced by the transistor sizes and supply voltage, while the impact of temperature is moderate. The proposed design is more tolerant to SETs than the SDCs with skew-sized inverters, and occupies less area compared to the hardening configurations based on partial and complete duplication. Due to the low transistor count (only six transistors), the proposed delay cell could also be used as a SET filter.
Analysis, simulation and prediction of multivariate random fields with package randomfields
(Los Angeles, Calif. : UCLA, Dept. of Statistics, 2015) Schlather, Martin; Malinowski, Alexander; Menck, Peter J.; Oesting, Marco; Strokorb, Kirstin
Modeling of and inference on multivariate data that have been measured in space, such as temperature and pressure, are challenging tasks in environmental sciences, physics and materials science. We give an overview over and some background on modeling with crosscovariance models. The R package RandomFields supports the simulation, the parameter estimation and the prediction in particular for the linear model of coregionalization, the multivariate Matérn models, the delay model, and a spectrum of physically motivated vector valued models. An example on weather data is considered, illustrating the use of RandomFields for parameter estimation and prediction.
Analyzing social media for measuring public attitudes toward controversies and their driving factors: a case study of migration
(Wien : Springer, 2022) Chen, Yiyi; Sack, Harald; Alam, Mehwish
Among other ways of expressing opinions on media such as blogs, and forums, social media (such as Twitter) has become one of the most widely used channels by populations for expressing their opinions. With an increasing interest in the topic of migration in Europe, it is important to process and analyze these opinions. To this end, this study aims at measuring the public attitudes toward migration in terms of sentiments and hate speech from a large number of tweets crawled on the decisive topic of migration. This study introduces a knowledge base (KB) of anonymized migration-related annotated tweets termed as MigrationsKB (MGKB). The tweets from 2013 to July 2021 in the European countries that are hosts of immigrants are collected, pre-processed, and filtered using advanced topic modeling techniques. BERT-based entity linking and sentiment analysis, complemented by attention-based hate speech detection, are performed to annotate the curated tweets. Moreover, external databases are used to identify the potential social and economic factors causing negative public attitudes toward migration. The analysis aligns with the hypothesis that the countries with more migrants have fewer negative and hateful tweets. To further promote research in the interdisciplinary fields of social sciences and computer science, the outcomes are integrated into MGKB, which significantly extends the existing ontology to consider the public attitudes toward migrations and economic indicators. This study further discusses the use-cases and exploitation of MGKB. Finally, MGKB is made publicly available, fully supporting the FAIR principles.
Anthropomorphized artificial intelligence, attachment, and consumer behavior
(Dordrecht [u.a.] : Springer, 2021) Hermann, Erik
The increasing humanization and emotional intelligence of AI applications have the potential to induce consumers’ attachment to AI and to transform human-to-AI interactions into human-to-human-like interactions. In turn, consumer behavior as well as consumers’ individual and social lives can be affected in various ways. Following this reasoning, I illustrate the implications and research opportunities related to consumers’ (potential) attachment to humanized AI applications along the stages of the consumption process.
Applications of nanogenerators for biomedical engineering and healthcare systems
(Weinheim : Wiley, 2021) Wang, Wanli; Pang, Jinbo; Su, Jie; Li, Fujiang; Li, Qiang; Wang, Xiaoxiong; Wang, Jingang; Ibarlucea, Bergoi; Liu, Xiaoyan; Li, Yufen; Zhou, Weijia; Wang, Kai; Han, Qingfang; Liu, Lei; Zang, Ruohan; Rümmeli, Mark H.; Li, Yang; Liu, Hong; Hu, Han; Cuniberti, Gianaurelio
The dream of human beings for long living has stimulated the rapid development of biomedical and healthcare equipment. However, conventional biomedical and healthcare devices have shortcomings such as short service life, large equipment size, and high potential safety hazards. Indeed, the power supply for conventional implantable device remains predominantly batteries. The emerging nanogenerators, which harvest micro/nanomechanical energy and thermal energy from human beings and convert into electrical energy, provide an ideal solution for self‐powering of biomedical devices. The combination of nanogenerators and biomedicine has been accelerating the development of self‐powered biomedical equipment. This article first introduces the operating principle of nanogenerators and then reviews the progress of nanogenerators in biomedical applications, including power supply, smart sensing, and effective treatment. Besides, the microbial disinfection and biodegradation performances of nanogenerators have been updated. Next, the protection devices have been discussed such as face mask with air filtering function together with real‐time monitoring of human health from the respiration and heat emission. Besides, the nanogenerator devices have been categorized by the types of mechanical energy from human beings, such as the body movement, tissue and organ activities, energy from chemical reactions, and gravitational potential energy. Eventually, the challenges and future opportunities in the applications of nanogenerators are delivered in the conclusive remarks. The combination of nanogenerator and biomedicine have been accelerating the development of self‐powered biomedical devices, which show a bright future in biomedicine and healthcare such as smart sensing, and therapy.
An Approach to Evaluate User Interfaces in a Scholarly Knowledge Communication Domain
(Cham : Springer, 2023) Obrezkov, Denis; Oelen, Allard; Auer, Sören; Abdelnour-Nocera, José L.; Marta Lárusdóttir; Petrie, Helen; Piccinno, Antonio; Winckler, Marco
The amount of research articles produced every day is overwhelming: scholarly knowledge is getting harder to communicate and easier to get lost. A possible solution is to represent the information in knowledge graphs: structures representing knowledge in networks of entities, their semantic types, and relationships between them. But this solution has its own drawback: given its very specific task, it requires new methods for designing and evaluating user interfaces. In this paper, we propose an approach for user interface evaluation in the knowledge communication domain. We base our methodology on the well-established Cognitive Walkthough approach but employ a different set of questions, tailoring the method towards domain-specific needs. We demonstrate our approach on a scholarly knowledge graph implementation called Open Research Knowledge Graph (ORKG).
Artificial intelligence in marketing: friend or foe of sustainable consumption?
(London : Springer, 2021) Hermann, Erik
[No abstract available]
Automated tangential-flow diafiltration device
(Amsterdam : Elsevier, 2021) Lüken, Arne; Bruckhaus, Maike; Kosfeld, Udo; Emondts, Meike; Wessling, Matthias
Tangential flow filtration (TFF) is a chemical unit operation used to purify and concentrate liquid suspensions of colloids, proteins, or cells. The solution flows tangentially across a membrane, such that a selective part of the fluid permeates the membrane while the filtrated matter is retained, increasing its concentration. TFF is a mild mechanical purification method that does not interact chemically with the filtrate. It is applied in sensitive separation tasks in protein chemistry, microbiology, or immunology. It is a fast alternative for dialysis applications, also applicable in the field of colloid purification. However, the costs of automated lab-scale devices (30,000 €) and the consumable membrane modules (100–600 €) make TFF currently hardly accessible for lab-scale polymer researchers. Therefore, we built a low-cost TFF system (2400 €) partly automated by an Arduino microcontroller and optimized for diafiltration buffer exchange and concentration processes in soft matter colloid research. We use medical hemodialysis membrane modules that only cost a share (20–50 €) of alternative TFF modules, and we demonstrate the functionality of the system for an exemplary colloidal microgel purification process.
B!SON: A Tool for Open Access Journal Recommendation
(Heidelberg : Springer, 2022) Entrup, Elias; Eppelin, Anita; Ewerth, Ralph; Hartwig, Josephine; Tullney, Marco; Wohlgemuth, Michael; Hoppe, Anett; Nugent, Ronan
Finding a suitable open access journal to publish scientific work is a complex task: Researchers have to navigate a constantly growing number of journals, institutional agreements with publishers, funders’ conditions and the risk of Predatory Publishers. To help with these challenges, we introduce a web-based journal recommendation system called B!SON. It is developed based on a systematic requirements analysis, built on open data, gives publisher-independent recommendations and works across domains. It suggests open access journals based on title, abstract and references provided by the user. The recommendation quality has been evaluated using a large test set of 10,000 articles. Development by two German scientific libraries ensures the longevity of the project.
Blood platelet enrichment in mass-producible surface acoustic wave (SAW) driven microfluidic chips
(Cambridge : RSC, 2019) Richard, Cynthia; Fakhfouri, Armaghan; Colditz, Melanie; Striggow, Friedrich; Kronstein-Wiedemann, Romy; Tonn, Torsten; Medina-Sánchez, Mariana; Schmidt, Oliver G.; Gemming, Thomas; Winkler, Andreas
The ability to separate specific biological components from cell suspensions is indispensable for liquid biopsies, and for personalized diagnostics and therapy. This paper describes an advanced surface acoustic wave (SAW) based device designed for the enrichment of platelets (PLTs) from a dispersion of PLTs and red blood cells (RBCs) at whole blood concentrations, opening new possibilities for diverse applications involving cell manipulation with high throughput. The device is made of patterned SU-8 photoresist that is lithographically defined on the wafer scale with a new proposed methodology. The blood cells are initially focused and subsequently separated by an acoustic radiation force (ARF) applied through standing SAWs (SSAWs). By means of flow cytometric analysis, the PLT concentration factor was found to be 7.7, and it was proven that the PLTs maintain their initial state. A substantially higher cell throughput and considerably lower applied powers than comparable devices from literature were achieved. In addition, fully coupled 3D numerical simulations based on SAW wave field measurements were carried out to anticipate the coupling of the wave field into the fluid, and to obtain the resulting pressure field. A comparison to the acoustically simpler case of PDMS channel walls is given. The simulated results show an ideal match to the experimental observations and offer the first insights into the acoustic behavior of SU-8 as channel wall material. The proposed device is compatible with current (Lab-on-a-Chip) microfabrication techniques allowing for mass-scale, reproducible chip manufacturing which is crucial to push the technology from lab-based to real-world applications. © The Royal Society of Chemistry.
BLOOM: BLoom filter based oblivious outsourced matchings
(2017) Ziegeldorf, Jan Henrik; Pennekamp, Jan; Hellmanns, David; Schwinger, Felix; Kunze, Ike; Henze, Martin; Hiller, Jens; Matzutt, Roman; Wehrle, Klaus
Whole genome sequencing has become fast, accurate, and cheap, paving the way towards the large-scale collection and processing of human genome data. Unfortunately, this dawning genome era does not only promise tremendous advances in biomedical research but also causes unprecedented privacy risks for the many. Handling storage and processing of large genome datasets through cloud services greatly aggravates these concerns. Current research efforts thus investigate the use of strong cryptographic methods and protocols to implement privacy-preserving genomic computations.
Bridging the Gap Between (AI-) Services and Their Application in Research and Clinical Settings Through Interoperability: the OMI-Protocol
(Hannover : Technische Informationsbibliothek, 2024-02) Sigle, Stefan; Werner, Patrick; Schweizer, Simon; Caldeira, Liliana; Hosch, René; Dyrba, Martin; Fegeler, Christian; Sigle, Stefan; Werner, Patrick; Schweizer, Simon; Caldeira, Liliana; Hosch, René; Dyrba, Martin; Fegeler, Christian; Grönke, Ana; Seletkov, Dmitrii; Kotter, Elmar; Nensa, Felix; Wehrle, Julius; Kaufmes, Kevin; Scherer, Lucas; Nolden, Marco; Boeker, Martin; Schmidt, Marvin; Pelka, Obioma; Braren, Rickmer; Stump, Shura-Roman; Graetz, Teresa; Pogarell, Tobias; Susetzky, Tobias; Wieland, Tobias; Parmar, Vicky; Wang, Yuanbin
Artificial Intelligence (AI) in research and clinical contexts is transforming the areas of medical and life sciences permanently. Aspects like findability, accessibility, interoperability, and reusability are often neglected for AI-based inference services. The Open Medical Inference (OMI) protocol aims to support remote inference by addressing the aforementioned aspects. Key component of the proposed protocol is an interoperable registry for remote inference services, which addresses the issue of findability for algorithms. It is complemented by information on how to invoke services remotely. Together, these components lay the basis for the implementation of distributed inference services beyond organizational borders. The OMI protocol considers prior work for aspects like data representation and transmission standards wherever possible. Based on Business Process Modeling of prototypical use cases for the service registry and common inference processes, a generic information model for remote services was inferred. Based on this model, FHIR resources were identified to represent AI-based services. The OMI protocol is first introduced using AI-services in radiology but is designed to be generalizable to other application domains as well. It provides an accessible, open specification as blueprint for the introduction and implementation of remote inference services.

Browse

Browsing Informatik by Title

Results Per Page

Sort Options