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1st International Conference on Computing, sciences and Communications, ICCSC 2024

作者： Venkatesan, C. Thamaraimanalan, T. Mohammed Ibrahim, M. Vinoly, G. Ramkumar, M. Saranya, K. HKBK College of Engineering Department of Electronics and Communication Engineering Karnataka Bengaluru India Sri Eshwar College of Engineering Department of Electronics and Communication Engineering Tamilnadu Coimbatore India Sona College of Technology Department of Computer Science and Engineering Tamilnadu Salem India Tamilnadu Thiruchengode India Knowledge Institute of Technology Department of Computer Science and Business Systems Tamilnadu Salem India

ISBN: (数字)9798350353648

ISBN: (纸本)9798350353648

In Internet of Things (IoT) networks, long-range (LoRa) technology is well-known for its wide communication range, but using it with mobile devices presents unique difficulties. Frequently occurring channel attenuation, which causes packet loss, increased energy consumption, and longer transmission times, is one of these difficulties. An improved Adaptive Mobility-based IoT LoRa Clustering Communication (AMILCC) strategy addressed to solve these problems. AMILCC partitions the network into optimal Spreading Factor (SF) areas by using a 2D random waypoint mobility model. The Hybrid Adaptive Data Rate (HADR) technique, which combines intra-and inter-SF region modifications to improve resource allocation for mobile IoT LoRa devices, is a key component of AMILCC. The simulation findings demonstrate the advantages of AMILCC over conventional stationary techniques, even under low mobility conditions (up to 5 m/s). In particular, AMILCC decreases energy usage by 56.5%, improves packet success ratio (PSR) by 72 %, and decreases end-to-end delay by 45.32%. These outcomes demonstrate how well AMILCC works to enhance efficiency and performance for mobile LoRa applications. © 2024 IEEE.

关键词： Resource allocation

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Keeping things simple: Finding frequent item sets by recursive elimination

Keeping things simple: Finding frequent item sets by recursi...

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1st International Workshop on Open Source Data Mining: Frequent Pattern Mining Implementations, OSDM 2005, held in conjunction with the 11th ACM SIGKDD International Conference on knowledge Discovery and Data Mining

作者： Borgelt, Christian Department of Knowledge Processing and Language Engineering School of Computer Science Otto-von-Guericke-University of Magdeburg Universitätsplatz 2 39106 Magdeburg Germany

ISBN: (纸本)1595932100

Recursive elimination is an algorithm for finding frequent item sets, which is strongly inspired by the FP-growth algorithm and very similar to the H-mine algorithm. It does its work without prefix trees or any other complicated data structures, processing the transactions directly. Its main strength is not its speed (although it is not slow, even outperforms Apriori and Eclat on some data sets), but the simplicity of its structure. Basically all the work is done in one simple recursive function, which can be written with relatively few lines of code. Copyright 2005 ACM.

关键词： Recursive functions

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Integrity Estimation of Twitter Based Event Recognition Using Scrutiny of Analyzed Data 2

Integrity Estimation of Twitter Based Event Recognition Usin...

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2nd International Conference on Emerging Trends in Information Technology and engineering, ic-ETITE 2024

作者： Siva Rama Lingham, N. Parameswari, M. Karthick, P. Priya, T. Subha Rathi Rajesh, G. Jagannathan, J. Vel Tech Rangarajan Dr.Sagunthala R&d Institute of Science and Technology Department of Computer Science and Engineering Chennai India Knowledge Institute of Technology Department of Computer Science and Engineering Salem India Vel Tech Multi Tech Dr.Rangarajan Dr.Sakunthala Engineering College Department of Computer Science and Engineering Chennai India School of Engineering and Technology Jeppiaar University Chennai India School of Computer Science Engineering and Information Systems Vellore Institute of Technology Department of Software and Systems Engineering Vellore Katpadi632014 India

ISBN: (纸本)9798350328202

Twitter has been observed to be one of the essential data resources for dependable event accreditation. In any case, Twitter-based event affirmation structures can't guarantee assessment concerning their attestation results. Talk statement has been locked in starting late to enable liberal event Recognition. This problem is not yet evident in light of the assumption that most people tend to think that they have a specific limit to the data on Twitter that have frames based on events based on Twitter. Current appraisals see new pieces by seeing and looking at the significant psychological aspects of hitting the details on Twitter. No matter, the scale of the visual cues can be well established, with the intention that it is essential to design an integrated Twitter experiment with another set of extensible data resources to rectify this problem. The problem is the processes by which you should wholeheartedly investigate all converted data because it has different data structures, transfer times, etc. This issue of address, the paper proposes a framework for evaluating the use of Twitter-based events and examines two types of data resources for the reliability of impact testing. Our framework uses the resultant of the request obtaining by various events and relevant to the articles on it. This paper has improved the cleaning test with the proposed process how the integrity estimation of twitter based event can be recognized with the help of group of analyzed data. The evaluation indicates that the proposed system provides visible high-level testing events and a variety of low-level testing events. © 2024 IEEE.

关键词： Impact testing

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Thermal performance optimization of microchannel heat sinks with triangle wave fin designs and various heat transfer fluids using GA/RSM/TOPSIS

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Case Studies in Thermal engineering 2025年 72卷

作者： Amr S. Abouzied Ali Basem Talib K. Ibrahim Ahmad Almadhor Khalid Almutairi Hind Albalawi Salem Alkhalaf Dilsora Abduvalieva Ibrahim Elbadawy Samah G. Babiker Department of Pharmaceutical Chemistry College of Pharmacy University of Hail Hail 81442 Saudi Arabia Faculty of Engineering Warith Al-Anbiyaa University Karbala 56001 Iraq Department of Petroleum Engineering College of Engineering Knowledge University Erbil 44001 Iraq Department of Petroleum Engineering Al-Kitab University Altun Kupri Iraq Department of Computer Engineering and Networks College of Computer and Information Sciences Jouf University Saudi Arabia Applied College Mechanical Engineering Technology University of Hafr Al Batin Hafr Al Batin Saudi Arabia Department of Physics College of Sciences Princess Nourah bint Abdulrahman University P.O. Box 84428 Riyadh 11671 Saudi Arabia Department of Computer Engineering College of Computer Qassim University Buraydah Saudi Arabia Department of Mathematics and Information Technologies Tashkent State Pedagogical University Bunyodkor avenue 27 Tashkent 100070 Uzbekistan College of Engineering and Technology American University of the Middle East Kuwait Department of Electronic Physics Faculty of Applied Science Red Sea University Port Sudan Sudan

Microchannel heat sinks (MHSs) stand out as a promising solution for dissipating heat in high-performance systems. The development and optimization of these systems are vital to meeting the growing demands of modern, power-dense electronics. The present study introduces a novel approach to enhance heat dissipation in microchannel systems. The design incorporates two sets of fins with a distinctive triangle wave pattern within the microchannels. The acquired results for the introduced fins were compared with the data of a non-finned MHS and a device with straight fins. The maximum temperature of the non-finned MHS was 307.222 K, while the incorporation of the mentioned fins reduced the temperature by approximately 2 K. This reduction is significant, as lower maximum temperatures improve the reliability and longevity of electronic components. Response surface methodology (RSM) was utilized to develop predictive models, reducing reliance on complex simulations and costly prototypes. The effects of fin folding angle ( θ ) and spacing from side walls ( S ) on thermo-hydraulic performance were systematically analyzed. Optimization was achieved by integrating genetic algorithms with the predictive models. Three distinct optimization targets (maximizing the Nusselt number, minimizing the pressure drop, and maximizing the device's overall efficiency) were considered, and three optimum designs were proposed for each target. Additionally, Pareto front analysis and TOPSIS evaluation provided a comprehensive multi-objective assessment. In RSM-based anticipation models, the R 2 values were 0.971 for the Nusselt number and 0.977 for pressure drop. The remarkable R 2 values indicated that the models for both responses had a high level of accuracy. Based on the results, heat sink design 3 (HSD3) with geometric parameters of θ = 97.785° and S = 70 μm was recommended for enhancing the overall performance of the MHS. By utilizing just two triangle wave fins configured according to th

关键词： TOPSIS and Pareto fronts Optimization Response surface methodology Microchannel heat sink design Triangle wave fins Genetic Algorithm

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Innovative feature selection and classification model for heart disease prediction

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Journal of Reliable Intelligent Environments 2022年第4期8卷 333-343页

作者： Nagarajan, Senthil Murugan Muthukumaran, V. Murugesan, R. Joseph, Rose Bindu Meram, Munirathanam Prathik, A. School of Computer Science and Engineering VIT-AP University Andhra Pradesh Amaravati India Department of Mathematics School of Advance Sciences REVA University Bangalore India Department of Mathematics Christ Academy Institute for Advance Studies Bangalore India Department of Mathematics Rajiv Gandhi University of Knowledge Technologies R. K. Valley Andhra Pradesh Nuzividu India Department of Computer Science and Engineering Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology Chennai India

Heart disease is a complex disease that affects a large number of people worldwide. The timely and accurate detection of heart disease is critical in healthcare, particularly in the field of cardiology. In this article, we proposed a system for diagnosing heart disease that is both efficient and accurate, and it is based on machine-learning techniques. The diagnosis of heart disease is found to be a serious concern, so the diagnosis has to be done remotely and regularly to take the prior action. In the present world, finding the prevalence of heart disease has become a key research area for the researchers and many models have crown proposed in the recent year. The optimization algorithm plays a vital role in heart disease diagnosis with high accuracy. Important goal of this work is to develop a hybrid GCSA which represents a genetic-based crow search algorithm for feature selection and classification using deep convolution neural networks. From the obtained results, the proposed model GCSA shows increase in the classification accuracy by obtaining more than 94% when compared to the other feature selection methods. © 2021, The Author(s), under exclusive licence to Springer Nature Switzerland AG.

关键词： Genetic algorithms

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Performance Evaluation of RPL Protocol Under Decreased and Increased Rank Attacks: A Focus on Smart Home Use-Case

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SN computer science 2023年第4期4卷 329页

作者： Bang, Ankur Rao, Udai Pratap Knowledge Associate Centre for Development of Advanced Computing (C-DAC) Maharashtra Mumbai 400049 India Computer Science and Engineering Department National Institute of Technology Bihar Patna 800005 India

The rank value of a node in Routing Protocol for Low Power and Lossy Networks (RPL) plays a significant role in preventing loops and route optimization. Advertising a fake rank value creates a false topology and can degrade network performance to a great extent. This manuscript aims to study the effects of increased and decreased variants of the rank attack on the RPL performance. We consider a smart home network topology to evaluate the RPL performance, and the simulation experiments are performed using the Cooja simulator. Through this study, we portray a rational analysis and discuss how the network performance can be degraded by each variant of the rank attack and the position of the attacker node in the network topology. The simulation results obtained in our work demonstrate how each variant of the rank attack can disrupt the default RPL working. We notice significant effects of both the studied rank attacks on the crucial parameters like packet overhead, average inter-packet time, packet delivery ratio and average power consumption. Researchers working in this field can take advantage of our research findings and extend their study to develop new defence mechanisms against these attacks. © 2023, The Author(s), under exclusive licence to Springer Nature Singapore Pte Ltd.

关键词： IoT Performance evaluation Rank attack RPL Smart home

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A machine learning approach for instance matching based on similarity metrics

A machine learning approach for instance matching based on s...

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11th International Semantic Web Conference, ISWC 2012

作者： Rong, Shu Niu, Xing Xiang, Evan Wei Wang, Haofen Yang, Qiang Yu, Yong APEX Data and Knowledge Management Lab Shanghai Jiao Tong University China Department of Computer Science and Engineering Hong Kong University of Science and Technology Hong Kong Hong Kong

ISBN: (纸本)9783642351754

The Linking Open Data (LOD) project is an ongoing effort to construct a global data space, i.e. the Web of Data. One important part of this project is to establish owl:sameAs links among structured data sources. Such links indicate equivalent instances that refer to the same real-world object. The problem of discovering owl:sameAs links between pairwise data sources is called instance matching. Most of the existing approaches addressing this problem rely on the quality of prior schema matching, which is not always good enough in the LOD scenario. In this paper, we propose a schema-independent instance-pair similarity metric based on several general descriptive features. We transform the instance matching problem to the binary classification problem and solve it by machine learning algorithms. Furthermore, we employ some transfer learning methods to utilize the existing owl:sameAs links in LOD to reduce the demand for labeled data. We carry out experiments on some datasets of OAEI2010. The results show that our method performs well on real-world LOD data and outperforms the participants of OAEI2010. © 2012 Springer-Verlag Berlin Heidelberg.

关键词： Learning systems

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Finding Informative Comments for Video Viewing

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SN computer science 2020年第1期1卷 1-14页

作者： Choi, Seungwoo Segev, Aviv Knowledge Service Engineering KAIST 291 Daehak-ro Daejeon South Korea Department of Computer Science University of South Alabama 150 Jaguar Drive Mobile AL United States

Of all the information-sharing methods on the Web, video is a factor with increasing importance and will continue to influence the future Web environment. Various services such as YouTube, Vimeo, and Liveleak are information-sharing platforms that support uploading UGC (user-generated content) to the Web. Users tend to seek related information while or after watching an informative video when they are using these Web services. In this situation, the best way of satisfying information needs of this kind is to find and read the comments on Web services. However, existing services only support sorting by recentness (newest one) or rating (high LIKES score). Consequently, the search for related information is limited unless the users read all the comments. Therefore, we suggest a novel method to find informative comments by considering original content and its relevance. We developed a set of methods composed of measuring informativeness priority, which we define as the level of information provided by online users, classifying the intention of the information posted online, and clustering to eliminate duplicate themes. The first method of measuring informativeness priority calculates the extent to which the comments cover all the topics in the original contents. After the informativeness priority calculation, the second method classifies the intention of information posted in comments. Then, the next method picks the most informative comments by applying clustering methods to eliminate duplicate themes using rules. Experiments based on 20 sampled videos with 1000 comments and analysis of 1861 TED talk videos and 380,619 comments show that the suggested methods can find more informative comments compared to existing methods such as sorting by high LIKES score. © 2019, Springer Nature Singapore Pte Ltd.

关键词： Information needs Information sharing Informativeness Online comments Video service

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A fast and simple graph kernel for RDF

A fast and simple graph kernel for RDF

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International Workshop on Data Mining on Linked Data, with Linked Data Mining Challenge, DMoLD 2013 - Collocated with the European Conference on Machine Learning and Principles and Practice of knowledge Discovery in Databases, ECMLPKDD 2013

作者： De Vries, Gerben Klaas Dirk De Rooij, Steven System and Network Engineering Group Informatics Institute University of Amsterdam Netherlands Knowledge Representation and Reasoning Group Department of Computer Science VU University Amsterdam Netherlands

In this paper we study a graph kernel for RDF based on constructing a tree for each instance and counting the number of paths in that tree. In our experiments this kernel shows comparable classification performance to the previously introduced intersection subtree kernel, but is significantly faster in terms of computation time. Prediction performance is worse than the state-of-the-art Weisfeiler Lehman RDF kernel, but our kernel is a factor 10 faster to compute. Thus, we consider this kernel a very suitable baseline for learning from RDF data. Furthermore, we extend this kernel to handle RDF literals as bag-of-words feature vectors, which increases performance in two of the four experiments.

关键词： Forestry

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Open framework middleware for intelligent WSN topology adaption in smart buildings

Open framework middleware for intelligent WSN topology adapt...

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2009 International Conference on Ultra Modern Telecommunications and Workshops

作者： Brennan, Rob Tai, Wei O'Sullivan, Declan Aslam, Muhammad S. Rea, Susan Pesch, Dirk Knowledge and Data Engineering Group School of Computer Science and Statistics Trinity College Dublin Ireland Centre for Adaptive Wireless Systems Department of Electronic Engineering Cork Institute of Technology Ireland

ISBN: (纸本)9781424439416

Modern smart buildings utilize sensor networks for facilities management applications such as energy monitoring. However as buildings become progressively more embedded with sensor networks, the challenge of managing and maintaining the sensor networks themselves becomes ever more significant. As a cost-sensitive activity, facilities management deployments are less likely to deploy node redundancy and specialized technical staff to maintain these networks. Hence there are strong requirements for the network to efficiently self-diagnose, self-heal and integrate with standard buildings management systems. This paper introduces a solution for WSN management in smart buildings that addresses these issues. It is based on the deployment of the Open Framework Middleware for sensor networks coupled with a structured knowledge and rule-based fault analysis engine to perform network event correlation and root cause analysis. The system also explicitly interfaces with a Building Management System (BMS) or the scheduling of network maintenance activities such as sensor battery replacement. ©2009 IEEE.

关键词： Topology

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