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2023 International Conference on Evolutionary Algorithms and Soft Computing Techniques, EASCT 2023

作者： Savitha, G. Hithyshi, K. Harshitha, J. Dhanya Shree, J.N. Soori, Pratiksha Rv Institute of Technology and Management Department of Computer Science and Engineering Bengaluru India

ISBN: (纸本)9798350313413

Email categorization is crucial in business and academia, filtering spam emails that risk phishing, fraud, and theft. This study employs a hybrid approach, considering group and individual strengths and weaknesses in email classification. It prioritizes identifying spam, particularly phishing, using data mining and the UCI spam base dataset. The primary objective is to enhance automated learning for accurate detection and filtering, differentiating legitimate messages from spam. Radial Basis Function Neural Networks (RBFNN) are central to this work, a key component of artificial neural networks (ANNs) for data classification. The paper encompasses various algorithms: Support Vector Machine (SVM), Neural Network, Naive Bayes, K-Nearest Neighbor (KNN), Decision Tree, Random Forest, Harris Hawk's Optimizer (HHO), and Extreme Learning Machines (ELM). This research advances email classification, bolstering digital communication's security and efficiency. © 2023 IEEE.

关键词： Email Email classification Emailcommunication fraud phishing robbery Spam email

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Vision Based Detection and Analysis of Human Activities 7

Vision Based Detection and Analysis of Human Activities

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7th International Conference on Trends in Electronics and informatics, ICOEI 2023

作者： Ravipati, Abhiram Kondamuri, Rakesh Krishna Mary Posonia, A. Albert Mayan, J. Sathyabama Institute of Science and Technology Department of Computer Science and Engineering Chennai India

ISBN: (纸本)9798350397284

These days, it's not uncommon to see video cameras installed to keep an eye on pedestrians and motorists alike in a variety of public spaces. The proliferation of camera footage necessitates the creation of some means of deducing the nature of the activity captured on film. Due to the widespread availability of acquisition devices like handsets & camcorders, HAR may be used in a wide variety of contexts. The proliferation of electronic gadgets and software has been matched by a revolution in data extraction made possible by breakthroughs in AI. Difficulties such backdrop congestion, partly blockage, variations in size, perspective, illumination, & look, make it difficult to recognize human actions in video frame or still photographs. Multimodal recognition is necessary in several fields, such as CCTV, human computer interaction for characterizing human behavior. This study surveys the most current and cutting-edge findings from the study of how to categorize human actions. This research proposes a taxonomy for studying human activity and explore the benefits and drawbacks of this diverse set of approaches. Disabled people's daily routines, including resting, moving, traveling down & up the stairs, speaking, & laying, have been frequently tracked using cellphones. Human motion detection often makes use of well-established ML & DL techniques include CNN, & LSTM Network. © 2023 IEEE.

关键词： Video cameras

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The Algorithm and VLSI Architecture of High-Throughput and Highly Efficient Tensor Decomposition Engine

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IEEE Transactions on Circuits and Systems I: Regular Papers 2024年第7期71卷 3134-3145页

作者： Tsai, Ting-Yu Shen, Chung-An Wu, Tsung-Lin Huang, Yuan-Hao National Taiwan University of Science and Technology Department of Electronic and Computer Engineering Taipei106335 Taiwan MediaTek Corporation Hsinchu300 Taiwan National Tsing Hua University Department of Electrical Engineering The Institute of Communications Engineering Hsinchu300 Taiwan

Tensor decomposition is critical for compressing data and extracting key features in novel high-dimensional signal processing systems. However, due to the enormous amount of data and the highly complicated computations, designing an efficient tensor decomposition processor is very challenging. This paper presents the algorithm and VLSI architecture design of a low-latency and high-throughput tensor decomposition processor. A parallel higher-order orthogonal iteration (P-HOOI) algorithm is proposed where multiple updated matrices are computed concurrently. Thus, a low-latency tensor decomposition is achieved. Furthermore, a novel VLSI architecture is presented so that the efficiency of the component utilization is improved and the hardware complexity is greatly reduced. Therefore, the proposed tensor decomposition processor enhances the processing throughput with minimum employment of hardware components. Performance evaluations based on the post-layout estimations in the ASIC flow and based on the FPGA platform are reported in this paper. Compared with state-of-the-art designs in the literature the proposed tensor decomposition engine greatly enhances the throughput and hardware efficiency. © 2004-2012 IEEE.

关键词： Engines

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Multi-Task Improve Domain Generalization in EEG-based Emotion Classification using Feature Fusion Learning Model 14

Multi-Task Improve Domain Generalization in EEG-based Emotio...

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14th International Conference on Computing Communication and Networking Technologies, ICCCNT 2023

作者： Menaka, S. Joshi, Riddhi. S. Varun, M. SRM Institute of Science and Technology Department of Computer Science and Engineering Chennai India

ISBN: (纸本)9798350335095

The use of Electroencephalography (EEG) signals for emotion identification tasks is common. However, the domain shift issue may cause EEG-based emotion detection models' performance to decline when used in new domains. In this article, we present a feature fusion learning model-based multi-task learning strategy to enhance domain generalization in EEG-based emotion classification. By simultaneously learning a shared feature extractor and numerous domain-specific classifiers, we train a single model to categorize emotions across various domains. Additionally, we present a feature fusion module that combines time-domain, frequency-domain, and wavelet-domain EEG characteristics. We run trials on the DEAP and SEED EEG emotion recognition datasets to assess our suggested methodology. The experimental findings show that our suggested strategy outperforms a number of cutting-edge techniques in terms of classification accuracy, both within- and across-domains. © 2023 IEEE.

关键词： Electroencephalography

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Analyzing Social Media texts for Suicidal Risk Identification using Natural Language Processing 9

Analyzing Social Media texts for Suicidal Risk Identificatio...

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9th International Conference on Signal Processing and Communication, ICSC 2023

作者： Rai, Shanskar Upadhyaya, Biraj Bhattarai, Sumiran Sharma, Kalpana Dhar, Premjyoti Gurung, Sandeep Department of Computer Science & Engineering Sikkim Manipal Institute of Technology Majitar India

ISBN: (纸本)9798350383201

Suicide is a pressing public health concern, with nearly 700,000 people taking their own lives annually, equating to one life lost every 45 seconds as per the World Health Organization. Recognizing that individuals contemplating suicide may exhibit identifiable behavioral patterns prior to their attempts, this work aims to employ Natural Language Processing (NLP) algorithms for prediction of risk of committing suicide by analyzing these patterns in social media posts. The system presented in this study uses machine learning to predict and identify suicidal ideation in online social content. To detect suicidal ideas via digital communication, the framework uses machine learning approaches. In this work, the machine learning algorithms SVM, logistic regression and CNN provide accuracy of 94.02%, 93.7% and 92.09% respectively. © 2023 IEEE.

关键词： Public health

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A Secure Remote Monitoring as a Service (MaaS) for Solar Power Plant 1

A Secure Remote Monitoring as a Service (MaaS) for Solar Pow...

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1st IEEE International Conference on Networking and Communications, ICNWC 2023

作者： Sophy Priya, C. Thangakumar, J. Sambath, M. Hindustan Institute of Technology and Science Department of Computer Science & Engineering Chennai India

ISBN: (纸本)9798350336009

In the field of Renewable energy, data processing is occurring in the photovoltaic plant using the IoT data logger. A data logger is a piece of technology that records and stores data over time, where SCADA systems are also indulged in data transfer and monitoring. Using these systems, we are transferring data from the data logger to cloud where a cloud-based platform is allowed users to manage and monitors the data loggers and as the result of analysis of various plants, the issues will be reported in the ticketing system and the further storage will be done in another cloud. This will result a cloud-cloud data flow where we are concentrating in ensuring the security of the data logger, Ethernet, WIFI, router connectivity, external web pages where data is viewed should be protected and the data backup, storage should be a secured area. RS485/RS422 bus provides the highest data transmission rate in data logger. Data encryption technique that involves Internet-cloud data transfers. This project mainly focus on introducing some new technologies in MaaS, where MaaS is a collection of tools and apps used to monitor a specific aspect of an application, server, system, or IT component. In the solar industry, this implies combining hardware, software, and services to monitor, evaluate, and troubleshoot solar plant faults throughout the solar array's lifetime, where we can monitor the amount of energy and control it securely. And this will help to introduce a secure wide range of global monitoring and reporting techniques in the renewable energy sector where data and data loggers are rising along with the risks. Cyber threats have a significant impact on smart grid performance due to the fast proliferation of real system in power electronic systems for connecting renewable energy sources with cyber frameworks. These electrical equipment in systems are linked by communication networks, which may be vulnerable to major cyber-attacks by malicious attackers. We have shown the d

关键词： Data transfer

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An Efficient Blockchain-based Auditing Scheme for EHR in Intelligent Healthcare System 2

An Efficient Blockchain-based Auditing Scheme for EHR in Int...

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2nd IEEE International Conference on Industrial Electronics: Developments and Applications, ICIDeA 2023

作者： Kumar, Ashish Chatterjee, Kakali National Institute of Technology Patna Department of Computer Science and Engineering Patna India

ISBN: (纸本)9798350381979

Electronic health records (EHRs) are health records that are digitally stored and consist of data about a person's wellness and increasing gradually. To store the EHR, a cloud service provider provides the storage for storing the EHR. By storing the data on the cloud, the integrity of data is a big concern for the EHR owner. Many Blockchain-based data integrity schemes are proposed for data integrity verification in which binary Merkle tree and quad Merkle tree are used, which increases the verification time for the EHR. To reduce the verification time in integrity auditing, the proposed scheme uses the ternary Merkle tree-based Blockchain for integrity auditing. The experiment and results show that verification time is reduced to 3 times lesser than the quad Merkle tree-based Blockchain and also reduces the execution time to 3.5 times lesser than the previous scheme. The security analysis shows that the proposed scheme is secured against some of the potential threats. © 2023 IEEE.

关键词： Blockchain

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Caption based Co-attention Architecture for Open-Ended Visual Question Answering 20

Caption based Co-attention Architecture for Open-Ended Visua...

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20th IEEE India Council International Conference, INDICON 2023

作者： Chatterjee, Chandra Churh Chandra Sekhar, C. Indian Institute of Technology Madras Department of Computer Science and Engineering Chennai India

ISBN: (纸本)9798350305593

Approaches to Visual Question Answering (VQA) revolve around the fusion mechanism to combine the semantic information extracted from the image and the question. The proposed architecture for open-ended VQA architecture has four major components: (1) Vision encoder, (2) Language encoder, (3) Co-attention module, and (4) Answer generator. We explore different combinations of the vision encoder and the language encoder to obtain the representations of the input image and the question. We propose the nonlinear co-attention mechanism and stacked co-attention mechanism to obtain a combined representation of the representations of the image and the question. We also combine the representation of the caption of the input image, with the representations of the image and the question in the caption based stacked nonlinear co-attention mechanism. Results of experimental studies on VQAv2 dataset demonstrate that the open-ended VQA model that uses the caption based stacked nonlinear co-attention module gives an improved performance. © 2023 IEEE.

关键词： Caption based co-attention Image-to-caption attention Nonlinear co-attention Open-ended VQA Question-to-image attention Stacked nonlinear co-attention Visual Question Answering (VQA)

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Smart Farming System using NPK Sensor 9

Smart Farming System using NPK Sensor

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9th International Conference on Advanced Computing and Communication Systems, ICACCS 2023

作者： Cheruvu, Bharadwaj Latha, S. Bhargavi Nikhil, Mada Mahajan, Hitesh Prashanth, Kongari Gokaraju Rangaraju Institute of Engineering and Technology Computer Science Department Hyderabad India

ISBN: (纸本)9798350397376

The human population is only growing, and certain steps are to be implemented to meet the future requirements with respect to food. This paper discusses the implementation of a smart farm using Internet of Thing. IoT has led to a faster form of gathering data and inferring from our surroundings. A farmer, with the help of this smart farm system, will be able to keep track of plant and soil vitals in real-time and use the recommendation system, based on a model trained from a dataset, to suggest the best suitable crop based on sensor values. IoT-enabled Smart Farming will enable growers and farmers to enhance productivity and reduce the wastage of resources. The proposed system is a more reliable concept and can be easily implemented as it consists of sensors that can collect vital information about the environment from soil nutrients, temperature, humidity, and soil moisture regularly which is displayed on an easy-to-understand interface to be interpreted by the growers and farmers to understand the best conditions to give their plants. © 2023 IEEE.

关键词： Python

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Song Recommendation based on Voice Tone Analysis 2

Song Recommendation based on Voice Tone Analysis

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2nd International Conference on Electronics and Renewable Systems, ICEARS 2023

作者： Jaison C, Raichal Rose Rajeswari, M. Karunya Institute of Technology and Sciences Department of Computer Science and Engineering Coimbatore India

ISBN: (纸本)9798350346640

Music suggestions based on elements including user listening history, music genre, etc. have become more popular in recent years. The user's emotional state is not considered by conventional music recommendation algorithms;therefore, they might not offer suggestions that are appropriate for their present mood. This study introduces a song recommendation system that uses artificial intelligence and machine learning to make individualized music suggestions based on the emotional state of the user. The system extracts feature with the help of MFCC to analyze the tone of the user. The suggested method incorporates deep learning models such as Artificial Neural Networks that provide better accuracy to train the model. The major challenge in creating such a system is to successfully determine the data for the recommendation process by accurately and consistently detecting the user's emotional state from speech. The proposed system offers new pathways for research in the fields of artificial intelligence and music recommendation and has the potential to alter the way people listen to music. © 2023 IEEE.

关键词： Music

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