004 Datenverarbeitung; Informatik
Filtern
Volltext vorhanden
- ja (37) (entfernen)
Erscheinungsjahr
- 2023 (37) (entfernen)
Dokumenttyp
Sprache
- Englisch (37)
Schlagworte
- Deep learning (3)
- P4 (3)
- 5G (2)
- SDN (2)
- connected mobility applications (2)
- multipath scheduling (2)
- network calculus (2)
- 3D Reconstruction (1)
- 3D-Rekonstruktion (1)
- 4D-GIS (1)
- 5G core network (1)
- 6G (1)
- ATSSSS (1)
- Accessibility (1)
- Add-on-Miss (1)
- BPM (1)
- BPMN (1)
- Benutzererlebnis (1)
- Benutzerforschung (1)
- Bildverarbeitung (1)
- CHI Conference (1)
- Computer Vision (1)
- Containerization (1)
- Deep Learning (1)
- Dijkstra’s algorithm (1)
- Domänenspezifische Sprache (1)
- Dreidimensionale Rekonstruktion (1)
- Edge-MEC-Cloud (1)
- Emotion inference (1)
- Emotionserkennung (1)
- Emotionsinterpretation (1)
- FIFO caching strategies (1)
- Gefühl (1)
- Human-centered computing / Access (1)
- Human-centered computing / Human computer interaction (HCI) / Interaction paradigms / Mixed / augmented reality (1)
- Human-centered computing / Human computer interaction (HCI) / Interaction paradigms / Virtual reality (1)
- Human-centered computing / Human computer interaction (HCI) / Interactiondevices (1)
- Human-centered computing / Human computerinteraction (HCI) / Interaction techniques (1)
- IT security (1)
- Internet of Things (1)
- IoT (1)
- IoT-driven processes (1)
- JCAS (1)
- Kathará (1)
- Klima (1)
- Kryoelektronenmikroskopie (1)
- LFU (1)
- LRU (1)
- Linux (1)
- MP-DCCP (1)
- Machine Learning (1)
- Maschinelles Lernen (1)
- Maschinelles Sehen (1)
- Medical Image Analysis (1)
- Metaverse (1)
- Methode (1)
- Modell (1)
- Mycoplasma pneumoniae (1)
- Network Emulator (1)
- Neuronales Netz (1)
- Object Detection (1)
- P4-INT (1)
- PROLOG <Programmiersprache> (1)
- Punktwolke (1)
- Selbstkalibrierung (1)
- Self-calibration (1)
- Sensing-aaS (1)
- Structure-from-Motion (1)
- TTL validation of data consistency (1)
- Tomografie (1)
- Underwater Mapping (1)
- Underwater Scanning (1)
- Visualized Kathará (1)
- WhatsApp (1)
- Wissenschaftliche Beobachtung (1)
- anthropomorphism (1)
- availability (1)
- background knowledge (1)
- baseline detection (1)
- bit (1)
- camera orientation (1)
- climate (1)
- cognitive impairment (1)
- communication models (1)
- communication networks (1)
- computer performance evaluation (1)
- content-based image retrieval (1)
- cosmology (1)
- cryo-EM (1)
- cryo-ET (1)
- data warehouse (1)
- deep learning (1)
- definite clause grammars (1)
- delay constrained (1)
- dementia (1)
- disjoint multi-paths (1)
- eHealth (1)
- electronic health records (1)
- emergent time (1)
- emulation (1)
- energy efficiency (1)
- extended reality (1)
- feature matching (1)
- federated learning (1)
- fog computing (1)
- fully convolutional neural networks (1)
- global IPX network (1)
- group-based communication (1)
- hardware-in-the-loop simulation (1)
- hardware-in-the-loop streaming system (1)
- historical document analysis (1)
- historical images (1)
- hit ratio analysis and simulation (1)
- hospital data (1)
- human–computer interaction (1)
- informal education (1)
- information extraction (1)
- intelligent voice assistant (1)
- key-insight extraction (1)
- knowledge representation (1)
- layout recognition (1)
- least cost (1)
- logic programming (1)
- long-term analysis (1)
- media analysis (1)
- medical records (1)
- membrane protein (1)
- misconceptions (1)
- mobile instant messaging (1)
- mobile messaging application (1)
- model output statistics (1)
- multipath (1)
- multipath packet scheduling (1)
- multiscale encoder (1)
- mycoplasma (1)
- neural networks (1)
- non-terrestrial networks (1)
- ontology (1)
- orchestration (1)
- packet reception method (1)
- particle picking (1)
- performance (1)
- performance monitoring (1)
- phase space (1)
- phase transition (1)
- pneumoniae (1)
- private chat groups (1)
- qubit (1)
- radiology (1)
- ransomware (1)
- satellite communication (1)
- scalability (1)
- scalability evaluation (1)
- sentinel (1)
- service-curve estimation (1)
- shortest path routing (1)
- signaling traffic (1)
- smart speaker (1)
- social interaction (1)
- social relationship (1)
- social role (1)
- state management (1)
- statistics and numerical data (1)
- surface model (1)
- sustainability (1)
- table extraction (1)
- table understanding (1)
- text line detection (1)
- timestamping method (1)
- tomography (1)
- visual proteomics (1)
Institut
Sonstige beteiligte Institutionen
EU-Projektnummer / Contract (GA) number
- 101069547 (1)
Social patterns and roles can develop when users talk to intelligent voice assistants (IVAs) daily. The current study investigates whether users assign different roles to devices and how this affects their usage behavior, user experience, and social perceptions. Since social roles take time to establish, we equipped 106 participants with Alexa or Google assistants and some smart home devices and observed their interactions for nine months. We analyzed diverse subjective (questionnaire) and objective data (interaction data). By combining social science and data science analyses, we identified two distinct clusters—users who assigned a friendship role to IVAs over time and users who did not. Interestingly, these clusters exhibited significant differences in their usage behavior, user experience, and social perceptions of the devices. For example, participants who assigned a role to IVAs attributed more friendship to them used them more frequently, reported more enjoyment during interactions, and perceived more empathy for IVAs. In addition, these users had distinct personal requirements, for example, they reported more loneliness. This study provides valuable insights into the role-specific effects and consequences of voice assistants. Recent developments in conversational language models such as ChatGPT suggest that the findings of this study could make an important contribution to the design of dialogic human–AI interactions.
In this paper, we work to understand the global IPX network from the perspective of an MVNO. In order to do this, we provide a brief description of the global architecture of mobile carriers. We provide initial results with respect to mapping the vast and complex interconnection network enabling global roaming from the point of view of a single MVNO. Finally, we provide preliminary results regarding the quality of service observed under global roaming conditions.
Climate models are the tool of choice for scientists researching climate change. Like all models they suffer from errors, particularly systematic and location-specific representation errors. One way to reduce these errors is model output statistics (MOS) where the model output is fitted to observational data with machine learning. In this work, we assess the use of convolutional Deep Learning climate MOS approaches and present the ConvMOS architecture which is specifically designed based on the observation that there are systematic and location-specific errors in the precipitation estimates of climate models. We apply ConvMOS models to the simulated precipitation of the regional climate model REMO, showing that a combination of per-location model parameters for reducing location-specific errors and global model parameters for reducing systematic errors is indeed beneficial for MOS performance. We find that ConvMOS models can reduce errors considerably and perform significantly better than three commonly used MOS approaches and plain ResNet and U-Net models in most cases. Our results show that non-linear MOS models underestimate the number of extreme precipitation events, which we alleviate by training models specialized towards extreme precipitation events with the imbalanced regression method DenseLoss. While we consider climate MOS, we argue that aspects of ConvMOS may also be beneficial in other domains with geospatial data, such as air pollution modeling or weather forecasts.
The holy grail of structural biology is to study a protein in situ, and this goal has been fast approaching since the resolution revolution and the achievement of atomic resolution. A cell's interior is not a dilute environment, and proteins have evolved to fold and function as needed in that environment; as such, an investigation of a cellular component should ideally include the full complexity of the cellular environment. Imaging whole cells in three dimensions using electron cryotomography is the best method to accomplish this goal, but it comes with a limitation on sample thickness and produces noisy data unamenable to direct analysis. This thesis establishes a novel workflow to systematically analyse whole-cell electron cryotomography data in three dimensions and to find and identify instances of protein complexes in the data to set up a determination of their structure and identity for success. Mycoplasma pneumoniae is a very small parasitic bacterium with fewer than 700 protein-coding genes, is thin enough and small enough to be imaged in large quantities by electron cryotomography, and can grow directly on the grids used for imaging, making it ideal for exploratory studies in structural proteomics. As part of the workflow, a methodology for training deep-learning-based particle-picking models is established.
As a proof of principle, a dataset of whole-cell Mycoplasma pneumoniae tomograms is used with this workflow to characterize a novel membrane-associated complex observed in the data. Ultimately, 25431 such particles are picked from 353 tomograms and refined to a density map with a resolution of 11 Å. Making good use of orthogonal datasets to filter search space and verify results, structures were predicted for candidate proteins and checked for suitable fit in the density map. In the end, with this approach, nine proteins were found to be part of the complex, which appears to be associated with chaperone activity and interact with translocon machinery.
Visual proteomics refers to the ultimate potential of in situ electron cryotomography: the comprehensive interpretation of tomograms. The workflow presented here is demonstrated to help in reaching that potential.
State Management at line rate is crucial for critical applications in next-generation networks. P4 is a language used in software-defined networking to program the data plane. The data plane can profit in many circumstances when it is allowed to manage its state without any detour over a controller. This work is based on a previous study by investigating the potential and performance of add-on-miss insertions of state by the data plane. The state keeping capabilities of P4 are limited regarding the amount of data and the update frequency. We follow the tentative specification of an upcoming portable-NIC-architecture and implement these changes into the software P4 target T4P4S. We show that insertions are possible with only a slight overhead compared to lookups and evaluate the influence of the rate of insertions on their latency.
Group-based communication is a highly popular communication paradigm, which is especially prominent in mobile instant messaging (MIM) applications, such as WhatsApp. Chat groups in MIM applications facilitate the sharing of various types of messages (e.g., text, voice, image, video) among a large number of participants. As each message has to be transmitted to every other member of the group, which multiplies the traffic, this has a massive impact on the underlying communication networks. However, most chat groups are private and network operators cannot obtain deep insights into MIM communication via network measurements due to end-to-end encryption. Thus, the generation of traffic is not well understood, given that it depends on sizes of communication groups, speed of communication, and exchanged message types. In this work, we provide a huge data set of 5,956 private WhatsApp chat histories, which contains over 76 million messages from more than 117,000 users. We describe and model the properties of chat groups and users, and the communication within these chat groups, which gives unprecedented insights into private MIM communication. In addition, we conduct exemplary measurements for the most popular message types, which empower the provided models to estimate the traffic over time in a chat group.
The introduction of new types of frequency spectrum in 6G technology facilitates the convergence of conventional mobile communications and radar functions. Thus, the mobile network itself becomes a versatile sensor system. This enables mobile network operators to offer a sensing service in addition to conventional data and telephony services. The potential benefits are expected to accrue to various stakeholders, including individuals, the environment, and society in general. The paper discusses technological development, possible integration, and use cases, as well as future development areas.
The Fifth Generation (5G) communication technology, its infrastructure and architecture, though already deployed in campus and small scale networks, is still undergoing continuous changes and research. Especially, in the light of future large scale deployments and industrial use cases, a detailed analysis of the performance and utilization with regard to latency and service times constraints is crucial. To this end, a fine granular investigation of the Network Function (NF) based core system and the duration for all the tasks performed by these services is necessary. This work presents the first steps towards analyzing the signaling traffic in 5G core networks, and introduces a tool to automatically extract sequence diagrams and service times for NF tasks from traffic traces.
The landscape of today’s programming languages is manifold. With the diversity of applications, the difficulty of adequately addressing and specifying the used programs increases. This often leads to newly designed and implemented domain-specific languages. They enable domain experts to express knowledge in their preferred format, resulting in more readable and concise programs. Due to its flexible and declarative syntax without reserved keywords, the logic programming language Prolog is particularly suitable for defining and embedding domain-specific languages.
This thesis addresses the questions and challenges that arise when integrating domain-specific languages into Prolog. We compare the two approaches to define them either externally or internally, and provide assisting tools for each. The grammar of a formal language is usually defined in the extended Backus–Naur form. In this work, we handle this formalism as a domain-specific language in Prolog, and define term expansions that allow to translate it into equivalent definite clause grammars. We present the package library(dcg4pt) for SWI-Prolog, which enriches them by an additional argument to automatically process the term’s corresponding parse tree. To simplify the work with definite clause grammars, we visualise their application by a web-based tracer.
The external integration of domain-specific languages requires the programmer to keep the grammar, parser, and interpreter in sync. In many cases, domain-specific languages can instead be directly embedded into Prolog by providing appropriate operator definitions. In addition, we propose syntactic extensions for Prolog to expand its expressiveness, for instance to state logic formulas with their connectives verbatim. This allows to use all tools that were originally written for Prolog, for instance code linters and editors with syntax highlighting. We present the package library(plammar), a standard-compliant parser for Prolog source code, written in Prolog. It is able to automatically infer from example sentences the required operator definitions with their classes and precedences as well as the required Prolog language extensions. As a result, we can automatically answer the question: Is it possible to model these example sentences as valid Prolog clauses, and how?
We discuss and apply the two approaches to internal and external integrations for several domain-specific languages, namely the extended Backus–Naur form, GraphQL, XPath, and a controlled natural language to represent expert rules in if-then form. The created toolchain with library(dcg4pt) and library(plammar) yields new application opportunities for static Prolog source code analysis, which we also present.
The emerging serverless computing may meet Edge Cloud in a beneficial manner as the two offer flexibility and dynamicity in optimizing finite hardware resources. However, the lack of proper study of a joint platform leaves a gap in literature about consumption and performance of such integration. To this end, this paper identifies the key questions and proposes a methodology to answer them.