GPU devices are currently seen as one of the trending topics for parallelcomputing. Commonly, GPU applications are developed with programming tools based on compiled languages, like C/C++ and Fortran. this paper pres...
详细信息
ISBN:
(纸本)9781665469586
GPU devices are currently seen as one of the trending topics for parallelcomputing. Commonly, GPU applications are developed with programming tools based on compiled languages, like C/C++ and Fortran. this paper presents a performance and programming effort analysis employing the Python high-level language to implement the NAS parallel Benchmark kernels targeting GPUs. We used Numba environment to enable CUDA support in Python, a tool that allows us to implement a GPU application with pure Python code. Our experimental results showed that Python applications reached a performance similar to C++ programs employing CUDA and better than C++ using OpenACC for most NPB kernels. Furthermore, Python codes required less operations related to the GPU framework than CUDA, mainly because Python needs a lower number of statements to manage memory allocations and data transfers. However, our Python versions demanded more operations than OpenACC implementations.
Accurate prediction of gene regulation rules is important for understanding complex life processes. Existing computational algorithms designed for bulk transcriptome datasets typically require a large number of time p...
详细信息
ISBN:
(纸本)9781450396868
Accurate prediction of gene regulation rules is important for understanding complex life processes. Existing computational algorithms designed for bulk transcriptome datasets typically require a large number of time points to infer gene regulatory networks (GRNs), are suitable for a small number of genes, and cannot efficiently detect potential regulatory relationships. We propose an approach based on a deep learning framework to reconstruct GRNs from bulk transcriptome datasets, assuming that the expression levels of transcription factors involved in gene regulation are strong predictors of the expression of their target genes. the algorithm uses multilayer perceptrons to infer the regulatory relationship between multiple transcription factors and a gene, and uses genetic algorithms to search for the best regulatory gene combination. the results show that our approach is more accurate than other methods for reconstructing gene regulatory networks on real-world and simulated bulk transcriptome gene expression datasets.
As modern industrial chains grow increasingly complex and time-sensitive, traditional transportation planning methods face efficiency bottlenecks. To address this, we propose a parallelization method based on Sparse M...
详细信息
the development of distributed information systems essentially relies on the complex application of Web services technologies, cloud, 9;green9;, GRID, multi-agent and many others. In many of these technologies, ...
详细信息
Electric vehicles (EVs) are thriving to alleviate environmental issues. Conventional two-stage onboard charger (OBC) in EV only contains one large-power DC/DC converter to connect the whole battery pack to the inverte...
详细信息
ISBN:
(纸本)9781665486682
Electric vehicles (EVs) are thriving to alleviate environmental issues. Conventional two-stage onboard charger (OBC) in EV only contains one large-power DC/DC converter to connect the whole battery pack to the inverter. It requires dozens of battery cells to connect in parallel and then in series for charging. parallel connection causes circulating current among batteries, increasing the loss and safety risk and decreasing the battery life. Aimed at diminishing the circulating current by reducing parallel connections of battery cells, a distributed OBC architecture is proposed in this paper. It contains a bi-directional inverter and numerous paralleled bi-directional low-power DC/DC converters. the batteries are divided into multiple clusters with less paralleled cells to interface withthose DC/DC converters, respectively. Furthermore, a novel virtual synchronous machine (VSM) control is proposed for the distributed OBC, enabling the OBC to provide inertia and frequency regulation to the grid and to serve as an emergency power supply in island mode. Compared to the conventional OBC, the distributed OBC under the proposed VSM control achieves higher fault tolerance, better power allocation, less circulating current among batteries, and less current impact on the batteries. those priorities are finally verified by simulation results.
Digital phenotyping applications use sensor data from personal digital devices (e.g., smartphones, smart bands) to quantify moment-to-moment human phenotype at the individual in-situ level. Ensuring the quality and di...
详细信息
ISBN:
(纸本)9783031345852;9783031345869
Digital phenotyping applications use sensor data from personal digital devices (e.g., smartphones, smart bands) to quantify moment-to-moment human phenotype at the individual in-situ level. Ensuring the quality and distribution of the data used is essential requirement in the domain of these applications. Context Quality (QoC) refers to the Information Quality (QoI) used and the Quality of Service (QoS) level of information distribution. QoI is measured by parameters that define how reliable the information is. On the other hand, QoS is provided by specifying the quality of service for distributing context data. Some aspects can degrade the QoC of the application, such as information from sensors being imprecise, wireless communication technologies used in the acquisition and distribution of information, scalability problems can cause information delay, and intermittent connection due to user mobility can result in data loss. therefore, this study conceives a process for incorporating QoC requirements and a Domain-Specific Language (DSL) to specify these requirements in digital phenotyping applications. A case study was carried out where the scenario of an application for monitoring workers' health was considered. It was possible to prove the expressiveness and simplicity of the proposed language when using it to define the instances of the application classes responsible for the acquisition and distribution of context information.
the proceedings contain 34 papers. the special focus in this conference is on Mining Humanistic Data. the topics include: Boosting Data Monetisation with DATAMITE;Boosting Digitalization Across European Regions: ...
ISBN:
(纸本)9783031632266
the proceedings contain 34 papers. the special focus in this conference is on Mining Humanistic Data. the topics include: Boosting Data Monetisation with DATAMITE;Boosting Digitalization Across European Regions: the AMBITIOUS Approach;Data Monetization Opportunities and Challenges: the European Landscape by DATAMITE;Innovative Digital Forensic and Investigation Tools for Law Enforcement: the EMPOWER & TRACY Approach;market Analysis of a Data Platform in the European Data Ecosystem;OCTAPUS: Empowering Next Generation Central Offices with Cross-Layer Network Intelligence Towards a Reconfigurable Data Plane;On 6G-Enabled SDN-Based Mobile Network User Plane with DRL-Based Traffic Engineering;on the Efficient Architecture for 6G System;Promoting Deployment of Innovative Use Cases in Market Verticals for the Support of 6G Evolution: the 6G-PAth Context;scalable Data Profiling for Quality Analytics Extraction;seamless Integration of Efficient 6G Wireless technologies for Communication and Sensing Enabling Ecosystems;testing Plan Description and Field Measurements for Real-Time Wide Area Monitoring of Interconnected Power Systems in the Smart5Grid Project;comparative Analysis of Time Series and Machine Learning Models for Air Quality Prediction Utilizing IoT Data;Efficient Energy Disaggregation Using DBSCAN: A Novel Approach for Enhanced Energy Management;integrating Machine Learning and Biological Context for Single-Cell Gene Regulatory Network Inference;museum Education: Integration of Cultural Heritage and Educational Metadata Schemas;net Zero Strategies: Empowering Climate Change Solutions through Advanced Analytics and Time Series;New Perspectives in e-Learning: EEG-Based Modelling of Human Cognition Individual Differences;optimizing Vehicle-to-Vehicle Energy Sharing with Predictive Modeling;predicting Song Popularity through Machine Learning and Sentiment Analysis on Social Networks;transformer-Based Anomaly Detection in Energy Consumption Data;Advancing Agricultural
Both revolutionary technologies of Fog computing (FC) and Blockchain (BC) serve as enablers for enhanced, people-centric trusted applications, and they do meet in the provision of higher standards and expectations. In...
详细信息
ISBN:
(纸本)9783031061561;9783031061554
Both revolutionary technologies of Fog computing (FC) and Blockchain (BC) serve as enablers for enhanced, people-centric trusted applications, and they do meet in the provision of higher standards and expectations. In this paper, we address the reliability of fog-enhanced BC systems by analyzing the forking phenomenon under different conditions, and provide a reliable distributed Ledger (DL) consistency assessment. We use the FoBSim tool that is specifically designed to mimic and emulate realistic FC-BC integration, in which we deploy the Proof-of-Work (PoW) consensus algorithm and analyze the forking probability under fluctuating conditions. Based on our results, we propose an inconsistency formula, which can quantitatively describe how consistent the DL in a BC system can be. Finally, we show how to deploy this formula in a decision making model for indicating optimal deployment features of a BC network in a Fog-enhanced system.
Withthe development of the Internet, the information stored on the network in text form is exploding. the large accumulation of dynamic information hinders its effective human use. As an information retrieval tool on...
详细信息
Healthcare technology is the practical application and synthesis of various knowledge for enhancing, preserving, and supporting human health. the improvement of engineering applications to healthcare technologies, whi...
详细信息
暂无评论