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Semantic Modelling of Multivariate Time-Series Data in Cognitive IoT 9

Semantic Modelling of Multivariate Time-Series Data in Cogni...

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9th international conference on Advanced Computing and Communication Systems, ICACCS 2023

作者： Jha, Vidyapati Tripathi, Priyanka NIT Raipur Department of Computer Application India

ISBN: (纸本)9798350397376

With the use of sensors and intelligent devices to assist interactions with the physical environment, we observe a significant rise in the amount of sensory input, which is continual, volatile, sometimes actual, and diverse in structure. the Internet of things (IoT) encapsulates this phenomenon. In addition, when IoT integrates cognition into system design, it is called Cognitive IoT (CIoT). CIoT requires techniques to autonomously extract semantic patterns from plain sensory data for efficient service delivery. Only a little scientific attention has been paid to automatically identifying semantic patterns from a massive time-series data set. this research presents a scaffold for real-time automatic semantic pattern extraction in the Cognitive Internet of things. It utilizes the Symbolic Aggregate Approximation (SAX) technique for sensory data with a multivariate time series. Further, the output of SAX is used to create a symbol table with their frequency. this frequency table is transformed into its corresponding probabilistic value. Finally, this value is used to generate the semantic pattern, which can be further processed using a rule-based method to create a machine-interpretable pattern. Experimental evaluation of this research study reveals that the proposed method can extract semantic patterns from heterogeneous multivariate sensory data. © 2023 IEEE.

关键词： Internet of things

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A Case Study for Exploring the Impact of Optimized K - Means Algorithm on the Energy Efficiency of Multicore Systems 25

A Case Study for Exploring the Impact of Optimized K - Means...

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25th IEEE international conferences on High Performance Computing and Communications, 9th international conference on Data Science and Systems, 21st IEEE international conference on Smart City and 9th IEEE international conference on Dependability in Sensor, Cloud and Big Data Systems and Applications, HPCC/DSS/SmartCity/DependSys 2023

作者： Hajiamini, Shervin Blanchard, Jeffrey D. Lin, Davin Shirazi, Behrooz Vanderbilt University Department of Computer Science Nashville United States Grinnell College Department of Mathematics and Statistics Grinnell United States Grinnell College Department of Computer Science Grinnell United States School of Eecs Washington State University Pullman United States

ISBN: (纸本)9798350330014

Cluster-based manycore system is a practical design for manufacturing the multicore systems. In this design, cores are divided into multiple clusters, where cores within a cluster share the same VoltagelFrequency (V/F) level. Each of clusters may have distinct V/F level compared to the others. Because all cores of a cluster share the same V/F level, it is critical that the size of a cluster would not be much bigger or smaller compared to the other clusters. this is because the uneven distribution of cores among clusters negatively impacts the energy efficiency: speeding up underloaded clusters wastes energy and slowing down overloaded clusters delays runtime. In this paper, we present a case study to optimize the functionality of the K - Means algorithm for improving the performance of a multi -core system. Among the existing clustering algorithms, we chose K-Means because of its simple design and broad use in various disciplines. the standard K - Means clusters cores with similar workloads that differ in computation from one phase to another. However, clusters formed by K-Means vary in size, putting too many cores inside some clusters while leaving others with very few cores. To address the balance of clusters, we use an existing variation of K - Means (constrained K-Means) that defines a lower bound for the number of cores in each of clusters. Constraining the size of each cluster of the multicore system creates the balanced clusters, where the sizes of clusters are almost identical. To measure the energy efficiency of the applied clustering, this paper suggests a Dynamic Voltage and Frequency Scaling (DVFS) methodology that adjusts the V/F levels of clusters at each phase of an application. For several multi-threaded applications, results show that at the best case the constrained K - Means improves the Energy-Delay Product (EDP) up to 40% compared to the standard version. the results also show that on average across all applications the constrained K-Means impro

关键词： Energy efficiency

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throughput Improvement for Buffer-aided UAV Relaying Communications With Jamming

Throughput Improvement for Buffer-Aided UAV Relaying Communi...

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international conference on computer and Communications (ICCC)

作者： Dongju Cao Guoqing Qu Yali Zhu Yang Li School of Information and Electronic Jiangsu Vocational College of Business Nantong China

Due to the high mobility of unmanned aerial vehicles (UAVs) and the broadcast nature of wireless communication channels, UAV systems are more vulnerable to malicious jamming attacks. this paper investigates a UAV assisted relaying communication system where a buffer-aided UAV acts as an aerial mobile relay to aid the information transmission between ground terminal nodes in the presence of malicious jamming. For the maximum end-to-end throughput, this paper formulates the optimization problem of joint communication scheduling, transmit power allocation and UAV trajectory planning under the buffer constraints. However, the non-convexity of the optimization problem will lead it to be intractable to obtain an optimal solution at an acceptable complexity, hence an efficient iterative algorithm is proposed to achieve an approximate suboptimal solution of the original problem. Numerical results not only demonstrate the convergence of the proposed iterative algorithm, but also indicate that the proposed joint design can considerably enhance the system throughput.

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A review on Machine Learning based IDS approaches in Wireless sensor networks 9

A review on Machine Learning based IDS approaches in Wireles...

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9th international conference on Advanced Computing and Communication Systems, ICACCS 2023

作者： Madhu Midhan, T. Devika, Kalepalli Rajakumar, R. Manikandan, R. Dinesh, K. Sreedevi, M. Madanapalle Institute of Technology & Science Department of Computer Science and Technology Madanapalle India

ISBN: (纸本)9798350397376

In wireless sensor networks (WSNs), sensors are scattered in a particular region to record and evaluate the physical data from the environment. they are widely utilised in various applications, including healthcare, event detection, agriculture, and disaster management. However, the challenges in WSNs include high bandwidth demand, energy consumption, route design, quality of service (QoS) provisioning, unusual activities, etc. However, numerous ways are being considered to solve the aforementioned difficulties. Detecting abnormal network movements is one of the most difficult challenges. An intrusion detection system (IDS) is a productive way to detect infiltration effectively. However, the growth of contemporary technologies necessitates using an effective IDS strategy. As a result, many academicians focus on reducing and eliminating anomalous network security vulnerabilities. According to the findings, machine learning techniques are more critical in addressing these issues. the accuracy of several machine learning algorithms for detecting intrusion in WSNs is investigated in this work. Furthermore, this paper examines the various datasets, performance measurements, and future directions. © 2023 IEEE.

关键词： Wireless sensor networks

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Indian Sign Language Generation from Live Audio or Text for Tamil 9

Indian Sign Language Generation from Live Audio or Text for ...

引用

9th international conference on Advanced Computing and Communication Systems, ICACCS 2023

作者： Reddy, Bandi Rupendra Rup, Daka Chandra Rohith, Mathi Belwal, Meena Amrita School of Computing Department of Computer Science and Engineering Amrita Vishwa Vidyapeetham Bengaluru India

ISBN: (纸本)9798350397376

Communication is the key behind the whole human evolution, and there would be nothing possible if the stream for communicating our thoughts to one another were cut off. Language is a significant factor when it comes to conveying one's ideas, thoughts, and information to other people. Sign language is used to communicate hard-of-hearing people's opinions. Every country has different sign languages. In this paper, we have used ISL (Indian Sign Language). To ease communication between ordinary people and deaf/dumb people, we propose the design and implementation of a model that translates a live voice, audio recordings, or text of a native Indian regional language (Tamil) to text and then further matches it to sign language animations from the video animation dataset. the speech is converted to text using two deep learning models LSTM(Long Short Term Memory), Bi-LSTM, and Google API. then the text is transformed into a sign using ISL (Indian Sign Language) dataset. the proposed models achieved 45%, 65%, and 95% accuracy for LSTM, Bi-LSTM, and Google API, respectively. © 2023 IEEE.

关键词： Long short-term memory

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design of Online Teaching Resources Management System Based on Distributed Database 9th

Design of Online Teaching Resources Management System Based ...

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9th EAI international conference on e-Learning, e-Education, and Online Training, eLEOT 2023

作者： Wu, Lini Gao, Jie Department of Building Management Chongqing College of Architecture and Technology Chongqing400030 China

ISBN: (纸本)9783031514708

With the rapid development of information technology and the Internet, online teaching has become increasingly popular. However, the management of online teaching resources has become a pressing issue. In this paper, we propose the design of an online teaching resources management system based on a Distributed database, aiming to address this challenge effectively. the system includes several key components and functionalities. Firstly, it reconstructs the time series Phase space of online teaching resources, allowing for the calculation of initial information weights in a timely manner. this helps create a comprehensive time series of online teaching resources stored in the Distributed database. To optimize the transmission efficiency of teaching resources within the Distributed database, the system extracts the main features of online teaching resources and determines attribute weighing coefficients. this improvement ensures efficient resource transmission. Additionally, the system integrates user management, online teaching resource management, and system management modules, creating a functional and comprehensive online teaching resource management system. the system has been tested, demonstrating that it successfully meets user needs, especially after optimizing the transmission efficiency of teaching resources in the Distributed database. © ICST Institute for computer Sciences, Social Informatics and Telecommunications Engineering 2024.

关键词： Time series

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Politicising Animal-computer Interaction: an Approach to Political Engagement with Animal-Centred design An Approach to Political Engagement with Animal-Centred design 9

Politicising Animal-Computer Interaction: an Approach to Pol...

引用

9th international conference on Animal-computer Interaction (ACI)

作者： Mancini, Clara Hirsch-Matsioulas, Orit Metcalfe, Daniel Open Univ Milton Keynes Bucks England Univ Haifa Haifa Israel Technion Israel Inst Technol Haifa Israel

ISBN: (纸本)9781450398305

While ACI researchers aspire to design animal-centred technology, they must operate within socio-economic systems that are not necessarily animal-centred. this creates a tension between researchers' endeavour to address the immediate needs of animals in specific situations through technological interventions, on the one hand, and these interventions' wider implications and consequences for the situation and life of various animal stakeholders beyond specific ACI projects, on the other hand. In this paper, we focus on the political nature of ACI, drawing from literature on political interaction design, which argues that designers should work towards social justice. Drawing from political philosophies, we then explore how extending the notion of social justice to animals might help define a political notion of animal centredness in ACI. Finally, through the lens of this notion of animal centredness, we consider the relevance of previously proposed strategies for political interaction design and propose an approach that could support ACI researchers' political engagement in animal-centred design.

关键词： Animal-Centred design Political design Animal Justice Animal Centredness Political Engagement

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A design Ranking Method for Many-Objective Evolutionary Optimization 20th

A Design Ranking Method for Many-Objective Evolutionary Opti...

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20th international conference on computer-aided Architectural design Futures, CAAD Futures 2023

作者： Wang, Likai Tung, Do Phuong Bui Janssen, Patrick Xi’an Jiaotong – Liverpool University Suzhou China National University of Singapore 21 Lower Kent Ridge Road Singapore Singapore Packhunt Amsterdam Netherlands

ISBN: (纸本)9783031371882

this study presents a design ranking method for evolutionary optimization that is aimed to address design optimization problems with many performance-related evaluation metrics. the application of the method consists of three strategies. First, all evaluation scores are expressed as percentages that indicate the proportion of the design achieving acceptable performance. Second, related evaluation scores are grouped, and for each group, a combined score is calculated using a weighted product approach. third, design populations are evolved using the Pareto optimization of the combined evaluation scores. the combination of the three steps helps designers to define and organize the design evaluation metrics and can also produce optimization results revealing meaningful information. A case study is presented to demonstrate the efficacy of the proposed design ranking method. the relevance of the proposed method to performance-based evolutionary optimization research is also discussed. © 2023, the Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Pareto principle

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Enhancing Chinese Event Causality Identification with Supervised Contrastive Learning 9

Enhancing Chinese Event Causality Identification with Superv...

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9th IEEE international conference on Cloud Computing and Intelligence Systems, CCIS 2023

作者： Yin, Maoxin Chen, Yuheng Qian, Huixun Liu, Haifeng Zhou, Junsheng Nanjing Normal University Department of Computer and Electronic Information Nanjing210023 China

ISBN: (纸本)9798350304428

Event causality identification is a significant task in natural language processing, aiming to discern causal relationships between pairs of events within a given text. Identifying causal relationships is helpful to sort out the causes and effects of events. It is of great significance to the development of logical reasoning, building event relationship diagrams, and question answering systems. Existing research predominantly relies on pre-trained models to encode events and obtain vector ***, these representations obtained in such a manner are anisotropic and fail to adequately convey the semantic information of events. To alleviate this problem, we propose a supervised contrastive learning-based event causality identification model. We construct positive and negative example pairs to improve the generalization ability and robustness of the model. We also design a supervised contrastive loss function to jointly train with the cross-entropy loss function to identify the causal relationships between events. the experimental results show that our supervised contrastive learning-based model achieves superior accuracy in identifying causal relationships between events, with an F1 score of 90.48% and an accuracy of 93.14%. © 2023 IEEE.

关键词： Semantics

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2021 ICCAD CAD Contest Problem C: GPU Accelerated Logic Rewriting 40

2021 ICCAD CAD Contest Problem C: GPU Accelerated Logic Rewr...

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40th IEEE/ACM international conference on computer aided design (ICCAD)

作者： Pasandi, Ghasem Pratty, Sreedhar Brown, David Zhang, Yanqing Ren, Haoxing Khailany, Brucek NVIDIA Corp Santa Clara CA 95051 USA NVIDIA Corp Austin TX USA

ISBN: (纸本)9781665445078

Logic rewriting is an important optimization function that can improve Quality of Results (QoR) in modern VLSI circuits. this optimization function usually has a greedy approach and involves steps such as graph traversal, cut computation and ranking, and functional matching. For logic rewriting to be effective in improving the QoR, there should be many local rewriting iterations which can be very slow for industrial level benchmark circuits. One effective solution to speed up the logic rewriting operation is to upload its time consuming steps to graphics Processing Units (GPUs) to benefit from massively parallel computations that is available there. In this regard, the present contest problem studies the possibility of using GPUs in accelerating a classical logic rewriting function. State-of-the-art large-scale open-source benchmark circuits as well as industrial-level designs will be used to test the GPU accelerated logic rewriting function.

关键词： design automation graphics processing units Life estimation Logic gates Benchmark testing Very large scale integration Optimization

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