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Metaheuristic Based Clustering with Deep Learning Model for Big Data Classification

computer Systems Science & engineering 2023年第1期44卷 391-406页

作者： R.Krishnaswamy Kamalraj Subramaniam V.Nandini K.Vijayalakshmi Seifedine Kadry Yunyoung Nam Department of Electronics and Communication Engineering University College of Engineering AriyalurAriyalur621704India Department of Biomedical Engineering Faculty of EngineeringKarpagam Academy of Higher EducationCoimbatore641021India Department of Computer Science and Engineering Sona College of TechnologySalem636005India Department of Electronics and Communication Engineering Saveetha School of EngineeringSaveetha Institute of Medical and Technical SciencesChennai600077India Deparmtent of Applied Data Science Noroff University CollegeKristiansandNorway Department of Computer Science and Engineering Soonchunhyang UniversityAsanKorea

Recently,a massive quantity of data is being produced from a distinct number of sources and the size of the daily created on the Internet has crossed two *** the same time,clustering is one of the efficient techniques for mining big data to extract the useful and hidden patterns that exist in ***-based clustering techniques have gained significant attention owing to the fact that it helps to effectively recognize complex patterns in spatial *** data clustering is a trivial process owing to the increasing quantity of data which can be solved by the use of Map Reduce *** this motivation,this paper presents an efficient Map Reduce based hybrid density based clustering and classification algorithm for big data analytics(MR-HDBCC).The proposed MR-HDBCC technique is executed on Map Reduce tool for handling the big *** addition,the MR-HDBCC technique involves three distinct processes namely pre-processing,clustering,and *** proposed model utilizes the Density-Based Spatial Clustering of Applications with Noise(DBSCAN)techni-que which is capable of detecting random shapes and diverse clusters with noisy *** improving the performance of the DBSCAN technique,a hybrid model using cockroach swarm optimization(CSO)algorithm is developed for the exploration of the search space and determine the optimal parameters for density based ***,bidirectional gated recurrent neural network(BGRNN)is employed for the classification of big *** experimental validation of the proposed MR-HDBCC technique takes place using the benchmark dataset and the simulation outcomes demonstrate the promising performance of the proposed model interms of different measures.

关键词： Big data data classification clustering mapreduce dbscan algorithm

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Leveraging AI to Unlock the Potential of Data Science 15

Leveraging AI to Unlock the Potential of Data Science

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15th International Conference on Computing Communication and Networking Technologies, ICCCNT 2024

作者： Yadav, Rakesh Kumar Sudhamsu, Gadug Goyal, Manish Kumar Yuvaraj, S. Deshpande, Leena A. Maharishi University of Information Technology Maharishi School of Engineering and Technology Uttar Pradesh India Faculty of Engineering and Technology Department of Computer Science and Engineering Karnataka Bangalore India Vivekananda Global University Department of Computer Science & Application Jaipur India Prince Shri Venkateshwara Padmavathy Engineering College Department of Electronics and Communication Engineering Chennai127 India Vishwakarma Institute of Technology Department of Computer Engineering Pune India

ISBN: (纸本)9798350370249

The application of synthetic Intelligence (AI) to records science has spread out a massive array of new possibilities. Via the combination of advanced evaluation strategies, effective understanding-pushed system gaining knowledge of algorithms, and modern computing architectures, AI is allowing researchers to quick and as it should be discover insights from huge and complicated datasets. Furthermore, AI tools are offering corporations with the ability to make higher and more knowledgeable choices from the evaluation of hundreds of thousands of statistics points. The skills of information technology powered by means of AI are revolutionizing industries which includes healthcare, finance, and manufacturing-producing savings, uncovering efficiencies, and identifying new opportunities. As AI-driven records technology maintains to strengthen, organizations that capitalize on its ability stand to gain precious insights and unlock new degrees of overall performance. © 2024 IEEE.

关键词： Smart manufacturing

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FreqEmo: A Twitter Dataset Comprising Users' Tweeting Frequency and Emotions

FreqEmo: A Twitter Dataset Comprising Users' Tweeting Freque...

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2024 International Conference on Artificial Intelligence and Emerging technology, Global AI Summit 2024

作者： Agrawal, Aryan Arora, Anshika Chakraborty, Pinaki Netaji Subhas University of Technology Department of Electronics and Communication Engineering New Delhi India School of Computer Science Engineering and Technology Bennett University Greater Noida India Netaji Subhas University of Technology Department of Computer Science and Engineering New Delhi India

ISBN: (纸本)9798350379716

Social media is now indispensable, used by all social, economic, age, and demographic groups. It provides extensive user-generated data, offering insights into users' mental states. This paper introduces a novel Twitter dataset comprising users' tweeting frequency and emotions shared. The dataset is based on Tweets collected from the USA and India during a 60-day period using adjectives representing emotions. Further, for frequently tweeting users, NRC emotion lexicon has been implemented which extracted sentiment and emotion scores of the users. The final dataset includes users' tweeting patterns along with the distribution of emotions and sentiments in their tweets. This dataset has been made publicly available and this project aims to help researchers develop models to assess users' emotional states based on social media activity without self-reporting, with applications in correlating usage patterns with well-being, clustering users by emotions and tweeting patterns, and analyzing temporal, spatial, and demographic trends. To provide baseline performance, k-means clustering is implemented in this study to cluster the users with similar usage patterns. Clusters are analyzed to determine the types of emotions and sentiments shared by users within each cluster. Based on the analysis, it is concluded that as Twitter usage increases within the clusters, the proportion of users dominated by negative sentiment also rises significantly, peaking at 41.67%. Additionally, the percentage of users whose predominant emotion is joy decreases with increased usage, reaching a low of 8.33% as opposed to the peak value of 69.44% in the group characterized by least usage, while the percentage of users dominated by anger and disgust grows to 17.24% and 4.17% as their usage intensifies. © 2024 IEEE.

关键词： Tweets

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Analysis of Cs2TiBr6 Single-Halide Perovskite Solar Cell by Introducing IDL 24

Analysis of Cs2TiBr6 Single-Halide Perovskite Solar Cell by ...

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24th IEEE International Conference on Numerical Simulation of Optoelectronic Devices, NUSOD 2024

作者： Kaur, Jaspinder Gupta, Syamantak Basu, Rikmantra Sharma, Ajay Kumar National Institute of Technology Delhi Department of Electronics and Communication Engineering New Delhi India National Institute of Technology Delhi Department of Computer Science and Engineering New Delhi India

ISBN: (纸本)9798350390537

Lead-based perovskite solar cells (PSCs) are popular in the photovoltaic industry for their remarkable properties, but issues like toxicity and instability limit their use. To address these problems, eco-friendly, lead-free, and stable Cesium Titanium Bromide (Cs2TiBr6) absorber material has been introduced. This work simulates an FTO/SnO2/IDL1/Cs2TiBr6/IDL2/MoOX/Au structure using SCAPS-1D incorporating the use of interfacial defect layer (IDL), examining factors such as layer thickness, doping, defect density, and quantum efficiency. The optimized structure achieves a power conversion efficiency (PCE) of 20.11%, having a fill factor of 82.17, VOC of 1.488 V, and JSC of 16.34 mA/cm2. This research supports the development of efficient, low-toxic, and stable PSCs for the solar industry. © 2024 IEEE.

关键词： Perovskite solar cells

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Resource Allocation and Energy Efficient Dynamic Particle Swarm Optimisation in Heterogeneous Wireless Communication Networks 4

Resource Allocation and Energy Efficient Dynamic Particle Sw...

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4th IEEE Asian Conference on Innovation in technology, ASIANCON 2024

作者： Pawar, Anuradha Bhalerao Kannan, G. Anuradha, T. Vignesh, V. Kesavan, R. Jose Anand, A. Mit Academy of Engineering Department of Electronics Engineering Alandi Maharastra Pune412105 India Amrita College of Engineering and Technology Department of Electronics and Communication Engineering Tamil Nadu 629 901 India Kcg College of Technology Department of Electrical and Electronics Engineering Tamil Nadu 600097 India Karpagam College of Engineering Department of Computer Science and Engineering Tamil Nadu 641032 India Simts Institute of Computer Science and Engineering Saveetha School of Engineering Tamil Nadu 602105 India Kcg College of Technology Department of Electronics and Communication Engineering Tamil Nadu 600097 India

ISBN: (纸本)9798350354218

This paper investigates the difficult of beam policy in a multi-user peer-to-peer web linkage setting as part of our research. Using a network simulator, the dynamic particle swarm optimization is suggested for this. The challenge is to limit the maximum power consumption per relay, according to minimal Signal to Noise Ratio (SNR) guarantees, after a complete Channel State Information (CSI) is established. It has been established that the non-convex problem satisfies a potent duality. The twofold problem with the highest polynomial complexity was given as Semi Definite Programming (SDP). On the basis of the standards of the optimal dual variables, we looked at the best beam forming vectors for the initial problems in 3 different scenarios. This demonstrated whether the minimum Signal-to-Noise Ratio (SNR) prerequisite for each S-D pair has been met as well as whether a relay's electricity consumption varies among relays. © 2024 IEEE.

关键词： Particle swarm optimization (PSO)

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Voting Classifier and Metaheuristic Optimization for Network Intrusion Detection

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computers, Materials & Continua 2023年第2期74卷 3183-3198页

作者： Doaa Sami Khafaga Faten Khalid Karim Abdelaziz A.Abdelhamid El-Sayed M.El-kenawy Hend K.Alkahtani Nima Khodadadi Mohammed Hadwan Abdelhameed Ibrahim Department of Computer Sciences College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of Computer Science Faculty of Computer and Information SciencesAin Shams UniversityCairo11566Egypt Department of Computer Science College of Computing and Information TechnologyShaqra University11961Saudi Arabia Department of Communications and Electronics Delta Higher Institute of Engineering and TechnologyMansoura35111Egypt The Department of Civil and Environmental Engineering Florida International UniversityMiamiFLUSA Department of Information Technology College of ComputerQassim UniversityBuraydah51452Saudi Arabia Computer Engineering and Control Systems Department Faculty of EngineeringMansoura UniversityMansoura35516Egypt

Managing physical objects in the network’s periphery is made possible by the Internet of Things(IoT),revolutionizing human *** attacks and unauthorized access are possible with these IoT devices,which exchange data to enable remote *** attacks are often detected using intrusion detection methodologies,although these systems’effectiveness and accuracy are *** paper proposes a new voting classifier composed of an ensemble of machine learning models trained and optimized using metaheuristic *** employed metaheuristic optimizer is a new version of the whale optimization algorithm(WOA),which is guided by the dipper throated optimizer(DTO)to improve the exploration process of the traditionalWOA *** proposed voting classifier categorizes the network intrusions robustly and *** assess the proposed approach,a dataset created from IoT devices is employed to record the efficiency of the proposed algorithm for binary attack *** dataset records are balanced using the locality-sensitive hashing(LSH)and Synthetic Minority Oversampling Technique(SMOTE).The evaluation of the achieved results is performed in terms of statistical analysis and visual plots to prove the proposed approach’s effectiveness,stability,and *** achieved results confirmed the superiority of the proposed algorithm for the task of network intrusion detection.

关键词： Voting classifier whale optimization algorithm dipper throated optimization intrusion detection internet-of-things

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Circadian Effect on Luminance Contrast Sensitivity

Transactions of Japanese Society for Medical and Biological ...

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Transactions of Japanese Society for Medical and Biological engineering 2022年第6期60卷 158-163页

作者： Yoshikawa, Mayu Nagai, Midori Koida, Kowa Department of Electronics Engineering College of Engineering National Institute of Technology Tokyo College Japan Electronics-Inspired Interdisciplinary Research Institute Toyohashi University of Technology Japan Department of Computer Science and Engineering Toyohashi University of Technology Japan

All biological functions, including vision, areaffected by timeof day. It is known that theretinal response to visual stimuli changes according to circadian rhythms. However, the effects on visually guided behavior were poorly understood, and previous results have been inconsistent. The previous studies examined the effect of time on contrast sensitivity were also inconsistent, one reason for this could be the order effects, such as fatigue due to long measurement times. To overcome this issue, we applied a tablet PC based measurement system which made the measuring contrast sensitivity quick and easy. Observers participated in the experiment every morning, noon, evening, and night, and performed a task to detect a Gabor patch. The results showed that sensitivity improved from morning to night, and this trend was more pronounced in the mid-to high-frequency band. The improvement was reproduced even when measurements were taken once daily at random times. These results suggest that the improvement was not due to intraday learning or fatigue. We confirmed that our experimental system is useful for measuring the diurnal variation in contrast sensitivity, as it is quick and easy to use. © 2022, Japan Soc. of Med. electronics and Biol. engineering. All rights reserved.

关键词： Fatigue of materials

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Modelling and Performance Analysis of Non-Toxic MASnI3Perovskite Solar Cell with 28.93% Efficiency 1

Modelling and Performance Analysis of Non-Toxic MASnI3Perovs...

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1st International Conference on electronics, Communication and Signal Processing, ICECSP 2024

作者： Kaur, Jaspinder Sharma, Ajay Kumar Basu, Rikmantra Gupta, Syamantak Gahlawat, Devansh National Institute of Technology Delhi Department of Electronics and Communication Engineering New Delhi India National Institute of Technology Delhi Department of Computer Science Engineering New Delhi India

ISBN: (纸本)9798350364590

Recently, lead-based perovskite solar cells (PSCs) grabbed the worldwide popularity in photovoltaic industry owing to its remarkable properties. Few challenges such as toxic elements, instability etc. restricts the use of inorganic-organic lead-based perovskite solar cells. To achieve these objectives inorganic-organic MASnI3 based solar cell with less toxicity is used as a light harvesting layer in the proposed structure. In this work, FTO/ TiO2/ MASnI3/ Cu2O/Au structure has been studied by SCAPS-1D simulation. By choosing the material TiO2 for electron transport layer (ETL) and Cu2O for hole transport layer (HTL), it has been noticed that the cell performed better in comparison to previously existing structures. The characteristics such as thickness of light harvesting layer including electron and hole transport layer thickness, doping of different layers, operating temperature etc. have thoroughly been examined in relation to different characteristics of PSCs. As a result, maximum power conversion efficiency (PCE) reached upto 28.93% along a FF = 88.9, Voc = 1.25 V, and Jsc = 25.89 mA/cm2. Hence, this work motivates the researchers to fabricate the high efficiency low-toxic PSCs in future. © 2024 IEEE.

关键词： Cu2O Efficiency MASnI3 SCAPS-ID TiO2

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Addressing Mobility Based RPL Routing for Low Power Lossy Networks in IoV Networks 2

Addressing Mobility Based RPL Routing for Low Power Lossy Ne...

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

作者： Diniesh, V.C. Murugesan, G. Jude, M. Joseph Auxilius Prabhakaran, A. Haritha, N. Jeevanaa, S.M. Karthikraja, A. Kongu Engineering College Department of Electronics and Communication Engineering Erode India Madanapalle Institute of Technology and Science Department of Computer Applications AP Madanapalle India Kongu Engineering College Department of Electronics and Communication Erode India

ISBN: (纸本)9798350328202

The Internet of Vehicles (IoV) has quickly progressed, linking a myriad of devices to facilitate data-driven applications in several fields. Routing Protocol for Low-power and Lossy Networks (RPL) is crucial to this paradigm, guaranteeing efficient and reliable communication in limited IoT and IoV contexts. In RPL there are two common Objective functions to choose the preferred parent namely Objective Function zero (OF0) and Minimum Rank with hysteresis objective function (MRHOF). OF0 uses Hop count as a metric to choose its preferred parent whereas MRHOF uses Expected Transmission Count (ETX) as a metric. The default Objective function is MRHOF and the metric is ETX. The existing protocols deals only with the static environment and it failed to handle the fast mobility. In this paper, we extend the scenario from IoT to IoV (static and mobile node) under random and grid environment with different network metrics like power, average end-to-end delay and Packet Delivery Ratio. Importantly, simulation is carried on 6LOWPAN/RPL stack with existing objective function on ContikiOS. The simulation result shows that MRHOF achieves 91% packet reception, 24.34% less delay compared against OF0 under fast mobility (10 - 50 m/s). © 2024 IEEE.

关键词： Low power electronics

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Mobility Stick with Haptic Feedback for People with Vision Impairments

Mobility Stick with Haptic Feedback for People with Vision I...

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2024 International Conference on Signal Processing, Computation, electronics, Power and Telecommunication, IConSCEPT 2024

作者： Raghul, J. Durga Devi, K. Sreya, M. Maithreye, S. SRM Institute of Science and Technology Department of Electronic and Computer Engineering Chennai Ramapuram India SRM Institute of Science and Technology Department of Electronics and Communication Engineering Chennai Ramapuram India

ISBN: (纸本)9798331540685

In this research, haptic motor, Node MCU, ultrasonic sensors are used to address the problem associated with the current walking stick for visually disabled people. These problems include disturbing their main sense of survival which is hearing. Hence, a system containing ultrasonic sensors, haptic motor and Internet of Things has been recommended in this study. This study illustrates that the implementation of haptic motors and ultrasonic sensors can successfully address the major issues that current alternatives face and it has a positive ad significant impact on visually disabled people. Using this method, one can monitor the person's movement and whether they fell down. This system makes use of IoT it integrate the data from sensors and update it onto the website for other person monitoring. © 2024 IEEE.

关键词： Ultrasonic sensors

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