检索结果-内蒙古大学图书馆

2024 IEEE International Conference on Big Data, BigData 2024

作者： Malysiak-Mrozek, Bozena Pawlowicz, Paulina Sunderam, Vaidy Hung, Che-Lun Kwiecien, Andrzej Mrozek, Dariusz Silesian University of Technology Department of Distributed Systems and Informatic Devices Gliwice Poland Silesian University of Technology Department of Applied Informatics Gliwice Poland Emory University Department of Computer Science AtlantaGA United States National Yang Ming Chiao Tung University Institute of Biomedical Informatics Taipei City Taiwan

ISBN: (纸本)9798350362480

Proteins are complex biological information granules that play a crucial role in various cellular processes within living organisms. Processing 3D protein structures, which are the most informative from the biological point of view, is both intricate and time-consuming. In particular, performing 3D protein structure searches against large protein datasets involves identifying similarities and conducting structural alignments across numerous molecules (granules). This task demands advanced methods for matching identical and similar regions within protein structures and substantial computational resources to handle large collections of macromolecular data efficiently. In this paper, we present our parallel implementation of scalable 3D structural alignment on the Apache Spark big data platform. We describe a customized approach that leverages Spark data transformations within the data processing pipeline for the alignment process. Our experimental results demonstrate that this solution, tightly integrated with the Spark processing model, is both efficient and scalable, even with the increasing volume of protein structure data. © 2024 IEEE.

关键词： Information granules

来源：评论

学校读者我要写书评

暂无评论

Neural NILM Learning Paradigms: From Centralised to Decentralised Learning 5

Neural NILM Learning Paradigms: From Centralised to Decentra...

引用

5th International Conference on Signal Processing and Information Security, ICSPIS 2022

作者： Bousbiat, Hafsa Klemenjak, Christoph Himeur, Yassine Elmenreich, Wilfried Amira, Abbes Mansoor, Wathiq Atalla, Shadi University of Klagenfurt Institute of Networked and Embedded Systems Klagenfurt Austria University of Dubai College of Engineering and IT Dubai United Arab Emirates University of Sharjah Department of Computer Science United Arab Emirates

ISBN: (纸本)9781665492652

Non-intrusive Load Monitoring (NILM) is becoming a paramount in both industrial and residential sectors to achieve efficient energy consumption. Thus, research on this matter flourished in recent years, where deep neural networks gained the highest interest from the research community, commonly referred to as neural NILM. As a predominant practice, neural NILM models follow a centralised based learning scheme where the energy data is assumed to be available in a central node for training. However, this practice and the enormous amount of data required by these algorithms raise privacy and security concerns from the consumer's side since energy data can reveal in-home activities and occupancy records if intercepted. Federated Learning (FL), also referred to as collaborative learning, is seen as viable solution to address these issues. Nonetheless, its application in neural NILM is still in its infancy and many challenges are yet to be addressed. The current paper presents an overview of neural NILM models following both a centralised and a federated learning paradigm. Furthermore, it identifies the main challenges with regard to both learning paradigms along with potential future research directions for more robust, secure and privacy-preserving models in the neural NILM industry. © 2022 IEEE.

关键词： Deep neural networks

来源：评论

学校读者我要写书评

暂无评论

Let me quickly share it - Time Pressure when Sharing on Social Media 24

Let me quickly share it - Time Pressure when Sharing on Soci...

引用

23rd International Conference on Mobile and Ubiquitous Multimedia, MUM 2024

作者： Panskus, Rebecca Tanni, Tangila Islam Ponticello, Alexander Meissner, Echo Solihin, Yan Krombholz, Katharina Marky, Karola Ruhr University Bochum Bochum Germany Department of Computer Science University of Central Florida Orlando United States CISPA Helmholtz Center for Information Security Saarland University Germany Saarbrücken Germany Institute of Distributed Systems Ulm University Ulm Germany CISPA Helmholtz Center for Information Security Saarbrücken Germany

ISBN: (纸本)9798400712838

Photo sharing has become an integral part of social media;many new platforms even prompt their users to share photos under time pressure. Yet, sharing photos can also affect the privacy of individuals in a negative way. In this paper, we investigate the factor of time pressure when sharing on social media in relation to target audiences and photo content. For this, we conducted an online study (N=195) where we simulated time-pressured sharing scenarios with photos containing different sorts of content, including private information and unfamiliar bystanders. Among our results, we show that time pressure can impact sharing decisions even though this is not consciously considered by users. Additionally, we confirm the influence of non-privacy-related influence factors like trust towards the target audience, photo aesthetics, and connection with others. Based on our results, we discuss design implications for photo-sharing prompts to better protect private information and bystanders in social media photos. © 2024 Copyright held by the owner/author(s).

关键词： Social Media

来源：评论

学校读者我要写书评

暂无评论

Hybrid PTX Analysis for GPU accelerated CNN inferencing aiding computer Architecture Design

Hybrid PTX Analysis for GPU accelerated CNN inferencing aidi...

引用

Forum on Specification, Verification and Design Languages, FDL

作者： Christopher A. Metz Christina Plump Bernhard J. Berger Rolf Drechsler Institute of Computer Science University of Bremen Bremen Germany Cyber-Physical Systems DFKI GmbH Bremen Germany Institute of Embedded Systems Hamburg University of Technology Hamburg Germany

General-Purpose Computation on Graphics Processing Units (GPGPUs) are becoming crucial in accelerating computing capacity. Due to the massive parallelism capabilities of GPUs, they can achieve impressive speedups of up to 32 times compared to common CPUs. However, writing highly parallel code and utilizing a GPU is challenging for programmers. Developers are facing new challenges since GPUs handle threads and parallelism differently from CPUs. Academia and industry proposed several profilers to support developers in terms of code optimization. These profilers often require an actual device (e.g., GPU) and take a long time for the profiling process. We propose HyPA, a hybrid Parallel Thread Execution (PTX) Analyzer that inspects PTX code statically and dynamically. HyPA implements a partly functional emulator that executes instructions that rely on runtime dependencies to count the number of executed PTX instructions and divergent branches. HyPa executes compiled kernels—the programs that run on GPUs—generated by the CUDA compiler and supports the full PTX 7.7 specification. Our functional emulator allows significantly faster analysis of PTX code compared to standard profilers. In our evaluation, we quantify this increase in performance through benchmark runs. HyPA achieved speedups of up to 536% compared to the nvprof profiler. Moreover, our approach can gather performance metrics beyond static analysis (e.g., branch efficiency) by a faster execution time than by profiling the application on an actual device. Finally, we provide an open-source implementation of HyPA to help developers and system designers in further research and development.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Destination Scheduling for Secure Pinhole-Based Power-Line Communication

IEEE Open Journal of the Communications Society

引用

IEEE Open Journal of the Communications Society 2023年 4卷 2245-2260页

作者： Kundu, Chinmoy Dubey, Ankit Tonello, Andrea M. Nallanathan, Arumugam Flanagan, Mark F. University College Dublin School of Electrical and Electronic Engineering Dublin 4D04 V1W8 Ireland Indian Institute of Technology Jammu Department of Ee Jammu181221 India Institute of Networked and Embedded Systems University of Klagenfurt Klagenfurt9020 Austria Queen Mary University of London School of Electronic Engineering and Computer Science LondonE1 4NS United Kingdom

We propose an optimal destination scheduling scheme to improve the physical layer security (PLS) of a power-line communication (PLC) based Internet-of-Things system in the presence of an eavesdropper. We consider a pinhole (PH) architecture for a multi-node PLC network to capture the keyhole effect in PLC. The transmitter-to-PH link is shared between the destinations and an eavesdropper which correlates all end-to-end links. The individual channel gains are assumed to follow independent log-normal statistics. Furthermore, the additive impulsive noise at each node is modeled by an independent Bernoulli-Gaussian process. Exact computable expressions for the average secrecy capacity (ASC) and the probability of intercept (POI) performance over many different networks are derived. Approximate closed-form expressions for the asymptotic ASC and POI are also provided. We find that the asymptotic ASC saturates to a constant level as transmit power increases. We observe that the PH has an adverse effect on the ASC. Although the shared link affects the ASC, it has no effect on the POI. We show that by artificially controlling the impulsive to background noise power ratio and its arrival rate at the receivers, the secrecy performance can be improved. © 2020 IEEE.

关键词： Impulse noise

来源：评论

学校读者我要写书评

暂无评论

Optimal Deep Dense Convolutional Neural Network Based Classification Model for COVID-19 Disease

引用

computers, Materials & Continua 2022年第1期70卷 2031-2047页

作者： A.Sheryl Oliver P.Suresh A.Mohanarathinam Seifedine Kadry Orawit Thinnukool Department of Computer Science and Engineering St.Joseph’s College of Engineering600119ChennaiIndia Department of Computer Science and Engineering KPR Institute of Engineering and TechnologyCoimbatore641407India Faculty of Engineering Karpagam Academy of Higher EducationCoimbatore641021India Faculty of Applied Computing and Technology Noroff University CollegeKristiansand4608Norway Research Group of Embedded Systems and Mobile Application in Health Science College of ArtsMedia and TechnologyChiang Mai UniversityChiang Mai50200Thailand

Early diagnosis and detection are important tasks in controlling the spread of COVID-19.A number of Deep Learning techniques has been established by researchers to detect the presence of COVID-19 using CT scan images and ***,these methods suffer from biased results and inaccurate detection of the ***,the current research article developed Oppositional-based Chimp Optimization Algorithm and Deep Dense Convolutional Neural Network(OCOA-DDCNN)for COVID-19 prediction using CT images in IoT *** proposed methodology works on the basis of two stages such as pre-processing and ***,CT scan images generated from prospective COVID-19 are collected from open-source system using IoT *** collected images are then preprocessed using Gaussian *** filter can be utilized in the removal of unwanted noise from the collected CT scan ***,the preprocessed images are sent to prediction *** this phase,Deep Dense Convolutional Neural Network(DDCNN)is applied upon the pre-processed *** proposed classifier is optimally designed with the consideration of Oppositional-basedChimp Optimization Algorithm(OCOA).This algorithm is utilized in the selection of optimal parameters for the proposed ***,the proposed technique is used in the prediction of COVID-19 and classify the results as either COVID-19 or *** projected method was implemented in MATLAB and the performances were evaluated through statistical *** proposed method was contrasted with conventional techniques such as Convolutional Neural Network-Firefly Algorithm(CNN-FA),Emperor Penguin Optimization(CNN-EPO)*** results established the supremacy of the proposed model.

关键词： Deep learning deep dense convolutional neural network covid-19 CT images chimp optimization algorithm

来源：评论

学校读者我要写书评

暂无评论

A Novel Evaluation Strategy to Artificial Neural Network Model Based on Bionics

引用

Journal of Bionic Engineering 2022年第1期19卷 224-239页

作者： Sen Tian Jin Zhang Xuanyu Shu Lingyu Chen Xin Niu You Wang School of Mathematics and Statistics Hunan Normal UniversityChangsha410081China College of Information Science and Engineering Hunan Normal UniversityChangsha410081China School of Computer and Communication Engineering Changsha University of Science and TechnologyChangsha410114China Key Laboratory of Industrial Control Technology Zhejiang UniversityHangzhou310058China Science and Technology on Parallel and Distributed Laboratory College of ComputerNational University of Defense TechnologyChangsha410199China Key Laboratory of Industrial Control Technology Institute of Cyber Systems and ControlZhejiang UniversityHangzhou310027China

With the continuous deepening of Artificial Neural Network(ANN)research,ANN model structure and function are improving towards diversification and ***,the model is more evaluated from the pros and cons of the problem-solving results and the lack of evaluation from the biomimetic aspect of imitating neural networks is not inclusive ***,a new ANN models evaluation strategy is proposed from the perspective of bionics in response to this problem in the ***,four classical neural network models are illustrated:Back Propagation(BP)network,Deep Belief Network(DBN),LeNet5 network,and olfactory bionic model(KIII model),and the neuron transmission mode and equation,network structure,and weight updating principle of the models are analyzed *** analysis results show that the KIII model comes closer to the actual biological nervous system compared with other models,and the LeNet5 network simulates the nervous system in ***,evaluation indexes of ANN are constructed from the perspective of bionics in this paper:small-world,synchronous,and chaotic ***,the network model is quantitatively analyzed by evaluation indexes from the perspective of *** experimental results show that the DBN network,LeNet5 network,and BP network have synchronous *** the DBN network and LeNet5 network have certain chaotic characteristics,but there is still a certain distance between the three classical neural networks and actual biological neural *** KIII model has certain small-world characteristics in structure,and its network also exhibits synchronization characteristics and chaotic *** with the DBN network,LeNet5 network,and the BP network,the KIII model is closer to the real biological neural network.

关键词： Artificial neural network(ANN) Back Propagation(BP)network Deep Belief Network(DBN) LeNet5 network Olfactory bionic model(KIII model) Small world Chaos Synchronous

来源：评论

学校读者我要写书评

暂无评论

EarSonar: An Acoustic Signal-Based Middle-Ear Effusion Detection Using Earphones

EarSonar: An Acoustic Signal-Based Middle-Ear Effusion Detec...

引用

International Conference on distributed Computing systems

作者： Jingyang Hu Hongbo Jiang Daibo Liu Zhu Xiao Hangcheng Cao Yue Qi Schahram Dustdar Jiangchuan Liu College of Computer Science and Electronic Engineering Hunan University OPPO Research Institute Computer Science heading the Research Division of Distributed Systems Vienna University of Technology School of Computing Science Simon Fraser University

Middle ear effusion is a common symptom of otitis media, the reactive physical manifestation of otitis media (OM) in children's middle ear. However, diagnosing MEE for little children at home is troublesome due to their difficulty cooperating and the caregiver's lack of medical knowledge. To this end, we propose EarSonar, a novel acoustic-based MEE diagnostic system. The principle behind EarSonar is that the acoustic absorption effect exists in ear scenarios, and the volume of middle ear fluid can markedly affect the absorbed spectrum energy. By automatically eliminating the impact of potential interference factors and identifying the representative frequency range with the typical reaction of acoustic absorption, EarSonar captures fine-grained signal features on absorbed spectrum energy and models the intrinsic relationship between acoustic absorption and the volume of the filler fluid in the eardrum. On that basis, EarSonar extracts the features of the MEE signal segment and uses k-means clustering to classify middle ear effusion status. We conducted a test on 112 adolescents aged 4–6. We divided the degree of middle ear effusion into three grades. The final average detection accuracy rate exceeds 92%, which is 8 % higher than the previous method. We have implemented a proof-of-concept prototype of EarSonar by building upon earphones embedded with a microphone and speaker. Experimental results demonstrate a feasible and effective way to turn earphones into potential home-use MEE screening tools.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Assessing mowing intensity:A new index incorporating frequency,type of machinery,and technique

引用

Grassland Research 2024年第3期3卷 264-274页

作者： Margarita Hartlieb Sebastian Raubitzek Johanna L.Berger Michael Staab Juliane Vogt Manfred Ayasse Andreas Ostrowski Wolfgang Weisser Nico Blüthgen Ecological Networks Department of BiologyTechnical University of DarmstadtDarmstadtGermany SBA-Research ViennaAustria Natura 2000-Station Unstrut-Hainich/Eichsfeld Wildtierland Hainich gGmbHHörselberg-HainichGermany Institute of Evolutionary Ecology and Conservation Genomics Ulm UniversityUlmGermany Heinz Nixdorf Chair for Distributed Information Systems Faculty of Mathematics and Computer ScienceFriedrich Schiller UniversityJenaGermany Department of Life Science Systems School of Life SciencesTechnical University of MunichTerrestrial Ecology Research GroupFreisingGermany

Background:Only a few decades ago,colorful,small-scale,heterogeneous,and species-rich hay meadows or extensive pastures were common,but have often been replaced by species-poor,uniform,large-scale multicut *** advancements and improved efficiency in grassland management have come at the cost of ***:In Germany,150 grassland plots have been investigated since *** these extensive data,we propose a new compound index for estimating the site-specific mowing intensity in order to facilitate assessment of the impact of mowing intensity on biodiversity and ecosystem *** index integrates the various qualitative components of mowing machine type,mowing height and use of a conditioner,with the annual number of ***:The newly proposed index achieves a much finer gradation of mowing intensity compared to the previous quantification based on the number of cuts ***,a decrease in plant and arthropod species was observed at higher mowing ***:The proposed mowing intensity index offers enhanced precision in calculations and can easily be integrated into assessments of land-use intensity in ***,it could serve as a basis for providing subsidies to farmers,who adopt low-impact mowing practices.

关键词： applications conditioner mower mowing height number of cuts species richness

来源：评论

学校读者我要写书评

暂无评论

Scalable and low-cost remote lab platforms: Teaching industrial robotics using open-source tools and understanding its social implications

arXiv

引用

arXiv 2024年

作者： Kumar, Amit Jose, Jaison Jain, Archit Kulkarni, Siddharth Arya, Kavi Centre for Systems and Control Indian Institute of Technology Bombay Mumbai India Embedded Real-Time Systems / e-Yantra Lab. Indian Institute of Technology Bombay Mumbai India Computer Science and Engineering Department Indian Institute of Technology Bombay Mumbai India

With recent advancements in industrial robots, educating students in new technologies and preparing them for the future is imperative. However, access to industrial robots for teaching poses challenges, such as the high cost of acquiring these robots, the safety of the operator and the robot, and complicated training material. This paper proposes two low-cost platforms built using open-source tools like Robot Operating System (ROS) and its latest version ROS 2 to help students learn and test algorithms on remotely connected industrial robots. Universal Robotics (UR5) arm and a custom mobile rover were deployed in different life-size testbeds, a greenhouse, and a warehouse to create an Autonomous Agricultural Harvester System (AAHS) and an Autonomous Warehouse Management System (AWMS). These platforms were deployed for a period of 7 months and were tested for their efficacy with 1,433 and 1,312 students, respectively. The hardware used in AAHS and AWMS was controlled remotely for 160 and 355 hours, respectively, by students over a period of 3 months. © 2024, CC BY.

关键词： Costs

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：