Search results for "computer.software_genre"
showing 10 items of 3858 documents
Domain-Specific OWL Ontology Visualization with OWLGrEd
2015
The OWLGrEd ontology editor allows graphical visualization and authoring of OWL 2.0 ontologies using a compact yet intuitive presentation that combines UML class diagram notation with textual Manchester syntax for expressions. We present an extension mechanism for OWLGrEd that allows adding custom information areas, rules and visual effects to the ontology presentation thus enabling domain specific OWL ontology visualizations. The usage of OWLGrEd and its extensions is demonstrated on ontology engineering examples involving custom annotation visualizations, advanced UML class dia-gram constructs and integrity constraints in semantic database schema design.
CoCoDat: a database system for organizing and selecting quantitative data on single neurons and neuronal microcircuitry.
2004
We present a novel database system for organizing and selecting quantitative experimental data on single neurons and neuronal microcircuitry that has proven useful for reference-keeping, experimental planning and computational modelling. Building on our previous experience with large neuroscientific databases, the system takes into account the diversity and method-dependence of single cell and microcircuitry data and provides tools for entering and retrieving published data without a priori interpretation or summarizing. Data representation is based on the framework suggested by biophysical theory and enables flexible combinations of data on membrane conductances, ionic and synaptic current…
Analysis and Visualization of Product Memory Layout in IP-XACT
2017
Modern ASIC and FPGA based embedded products use model based design, in which both hardware and software are developed in parallel. Previously HW was completed first and the information handed over to SW team, typically in the form of register tables. The information was even manually copied to SW code, making any changes error-prone and laborious. IP-XACT is the most feasible standard to model HW also for the SW needs. The HW design connectivity and overall memory layout may change due to component instantiations, configurations and conditional operation states, which makes it difficult to create register tables even for documentation. Current register design tools fall short in serving th…
A methodology to assess the intrinsic discriminative ability of a distance function and its interplay with clustering algorithms for microarray data …
2013
Abstract Background Clustering is one of the most well known activities in scientific investigation and the object of research in many disciplines, ranging from statistics to computer science. Following Handl et al., it can be summarized as a three step process: (1) choice of a distance function; (2) choice of a clustering algorithm; (3) choice of a validation method. Although such a purist approach to clustering is hardly seen in many areas of science, genomic data require that level of attention, if inferences made from cluster analysis have to be of some relevance to biomedical research. Results A procedure is proposed for the assessment of the discriminative ability of a distance functi…
Evaluation of the Measuring Active Drag system usability: An important step for its integration into training sessions
2010
This paper is the first stage of an iterative process aiming at the (re)design of a training device for swimming. The purpose of this study was to evaluate the usability of the Measuring Active Drag (MAD) system, a technical device for biomechanical evaluation and performance analysis. To do so, this study examines real activity of elite swimmers using this system. It was conducted within an activity-centred approach: the course-of-action technological research programme. Three international male swimmers volunteered to participate in the study. Two types of data were collected: (a) video recordings, and (b) verbalisations during post-protocol interviews. The data were processed in two step…
Indexing a sequence for mapping reads with a single mismatch
2014
Mapping reads against a genome sequence is an interesting and useful problem in computational molecular biology and bioinformatics. In this paper, we focus on the problem of indexing a sequence for mapping reads with a single mismatch. We first focus on a simpler problem where the length of the pattern is given beforehand during the data structure construction. This version of the problem is interesting in its own right in the context of the next generation sequencing. In the sequel, we show how to solve the more general problem. In both cases, our algorithm can construct an efficient data structure in time and space and can answer subsequent queries in time. Here, n is the length of the s…
Automated Uncertainty Quantification Through Information Fusion in Manufacturing Processes
2017
International audience; Evaluation of key performance indicators (KPIs) such as energy consumption is essential for decision-making during the design and operation of smart manufacturing systems. The measurements of KPIs are strongly affected by several uncertainty sources such as input material uncertainty, the inherent variability in the manufacturing process, model uncertainty, and the uncertainty in the sensor measurements of operational data. A comprehensive understanding of the uncertainty sources and their effect on the KPIs is required to make the manufacturing processes more efficient. Towards this objective, this paper proposed an automated methodology to generate a hierarchical B…
Knowledge-based verification of concatenative programming patterns inspired by natural language for resource-constrained embedded devices
2020
We propose a methodology to verify applications developed following programming patterns inspired by natural language that interact with physical environments and run on resource-constrained interconnected devices. Natural language patterns allow for the reduction of intermediate abstraction layers to map physical domain concepts into executable code avoiding the recourse to ontologies, which would need to be shared, kept up to date, and synchronized across a set of devices. Moreover, the computational paradigm we use for effective distributed execution of symbolic code on resource-constrained devices encourages the adoption of such patterns. The methodology is supported by a rule-based sys…
Evaluation of Ensemble Machine Learning Methods in Mobile Threat Detection
2017
The rapid growing trend of mobile devices continues to soar causing massive increase in cyber security threats. Most pervasive threats include ransom-ware, banking malware, premium SMS fraud. The solitary hackers use tailored techniques to avoid detection by the traditional antivirus. The emerging need is to detect these threats by any flow-based network solution. Therefore, we propose and evaluate a network based model which uses ensemble Machine Learning (ML) methods in order to identify the mobile threats, by analyzing the network flows of the malware communication. The ensemble ML methods not only protect over-fitting of the model but also cope with the issues related to the changing be…
Assessment of Deep Learning Methodology for Self-Organizing 5G Networks
2019
In this paper, we present an auto-encoder-based machine learning framework for self organizing networks (SON). Traditional machine learning approaches, for example, K Nearest Neighbor, lack the ability to be precisely predictive. Therefore, they can not be extended for sequential data in the true sense because they require a batch of data to be trained on. In this work, we explore artificial neural network-based approaches like the autoencoders (AE) and propose a framework. The proposed framework provides an advantage over traditional machine learning approaches in terms of accuracy and the capability to be extended with other methods. The paper provides an assessment of the application of …