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3rd International Conference on Power, Energy, Control and Transmission Systems, ICPECTS 2022

作者： Arul, U. Prasath, A. Arul Mishra, Suman Shirisha, J. Department of Artificial Intelligence and Machine Learning Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Tamil Nadu Chennai India Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology Department of Computer Science and Engineering Tamil Nadu Chennai India CMR Engineering College Department of Electronics and Communication Engineering Telangana Hyderabad India Department of Electronics and Communication Engineering Telangana Hyderabad India

ISBN: (纸本)9781665462754

In today's environment, traditional shopping is a time-consuming activity. Customers must wait in huge lines at the pay counter in traditional shopping. As a result, both the client and the clerk waste a lot of time and energy. To combat this interaction, we're pushing a fantastic shopping framework built on an Android app. The user must first download and install the software on his or her Android phone in this framework. He then scans the item's QR code and enters the required amount. After that, the object is put onto the car. Customers buy the items and put them into the trucks in this manner. The client can add or remove items from the vehicle. The customer will be given the recommended items as well as the most convenient method of obtaining them. When the items are purchased, the bill is generated. This bill might be sent to the client's mobile device via internet banking, allowing the consumer to make a quick payment and leave the business sooner. © 2022 IEEE.

关键词： Machine learning

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Improvement in Facial Emotion Recognition using Synthetic Data Generated by Diffusion Model

arXiv

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arXiv 2024年

作者： Roy, Arnab Kumar Kathania, Hemant Kumar Sharma, Adhitiya Dept. of Computer Science and Engineering Sikkim Manipal Institute of Technology Sikkim India Dept. of Electronics and Communication Engineering National Institute of Technology Sikkim India

Facial Emotion Recognition (FER) plays a crucial role in computer vision, with significant applications in human-computer interaction, affective computing, and areas such as mental health monitoring and personalized learning environments. However, a major challenge in FER task is the class imbalance commonly found in available datasets, which can hinder both model performance and generalization. In this paper, we tackle the issue of data imbalance by incorporating synthetic data augmentation and leveraging the ResEmoteNet model to enhance the overall performance on facial emotion recognition task. We employed Stable Diffusion 2 and Stable Diffusion 3 Medium models to generate synthetic facial emotion data, augmenting the training sets of the FER2013 and RAF-DB benchmark datasets. Training ResEmoteNet with these augmented datasets resulted in substantial performance improvements, achieving accuracies of 96.47% on FER2013 and 99.23% on RAF-DB. These findings shows an absolute improvement of 16.68% in FER2013, 4.47% in RAF-DB and highlight the efficacy of synthetic data augmentation in strengthening FER models and underscore the potential of advanced generative models in FER research and applications. The source code for ResEmoteNet is available at https://***/ArnabKumarRoy02/ResEmoteNet © 2024, CC BY.

关键词： Human computer interaction

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Deep Dive On Various Security Challenges, Threats And Attacks Over The Cloud Security

Deep Dive On Various Security Challenges, Threats And Attack...

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International Conference on Advanced Computing and communication Systems (ICACCS)

作者： C Jansi Sophia Mary K Mahalakshmi B Senthilkumar Computer Science and Engineering Idhaya Engineering College for Women Kallakurichi India Computer Science and Engineering Kalaignar karunanidhi Institute of Technology Coimbatore India Electronics and Communication Engineering Kalaignar Karunanidhi Institute of Technology Coimbatore India

Cloud computing has received more attention in recent years due to the obvious, ever-increasing demand. With cloud storage, there seem to be a number of benefits that businesses can reap. Cloud computing provides a simplified IT infrastructure and strategic planning, as well as the ability to access your data from all over the universe with a reliable Internet connection. More research is needed into cloud computing’s security and privacy issues. In existing studies, academic, industrial, and standards organisation researchers offered possible solutions to such problems. Cloud security issues and specifications, identified threats, as well as vulnerabilities are all discussed in this systematic review. In reality, the goal of this work is to investigate the various aspects of cloud computing, such as the present-day privacy and security issues that the systems face. Moreover, this study aims to introduce classification of security related mitigation strategies in this work. It also addressed unresolved issues and future directions of various kinds of security threats that threaten cloud computing. A deep understanding of the security concerns confronting various entities such as cloud users, data owners and cloud service providers will be the emphasis of this paper, which will be explored in great length.

关键词： Cloud computing Privacy Systematics Cloud computing security Strategic planning Safety Security

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Development of Healthcare Model Using AR-DVAE with Mayfly-MLP-BPN for Parkinson's Disease Detection

Development of Healthcare Model Using AR-DVAE with Mayfly-ML...

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2023 International Conference on Data science and Network Security, ICDSNS 2023

作者： Murthy, G. N. Keshava Pareek, Piyush Kumar Manjunath, T.N. Shwetha, N. Deepak, R. Rashmi, P. Siddaganga Institute of Technology Department of Electronics and Instrumentation Engineering Tumakuru India Nitte Meenakshi Institute of Technology Department of Artificial Intelligence and Machine Learning Bengaluru India East West Institute of Technology Department of Computer Science and Engineering Bengaluru India Bgs Institute of Technology Adichunchanagiri University Department of Electronics and Communication Engineering B G Nagara India Inventuriz Labs Private Limited Bengaluru India

ISBN: (纸本)9798350301595

Research on reliable biomarkers that permit the creation of medical-decision support technologies is currently a major focus in healthcare biometrics. These gadgets aid in the analysis and nursing of conditions like Parkinson's disease (PD). If PD patients' vocal alterations could be detected, this would allow for early diagnosis and treatment, thereby preventing the onset of physically disabling symptoms. More recent research has centred on the suggestion of new automatic and objective tools to aid in diagnosis and severity assessment. In this study, we provide a dual approach to detecting PD. The first section extracts features mechanically with the help of an AR-DVAE model (autoregressive deep variational autoencoder). Lastly, the Mayfly Algorithm is used to maximise the bias weight in a modified multilayer perceptron utilising a backpropagation network (MLP-BPN). To conduct this research, we used the publicly available PD Using Digitized Graphics Tablet dataset. In comparison to other models, the suggested model performed better across the board, as shown by the validation analysis. © 2023 IEEE.

关键词： Decision support systems

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Role of Empathy to Identify Unmet Needs in Indian Villages through Service Learning Program - A Case of the Unnat Bharat Abhiyan Program

Role of Empathy to Identify Unmet Needs in Indian Villages t...

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2022 IEEE IFEES World engineering Education Forum - Global engineering Deans Council, WEEF-GEDC 2022

作者： Kandakatla, Rohit Penta, Samyuktha Lingam, B. Sinha, Shiwani Chandraprakash, D. Udaya Sri, K. Kg Reddy College of Engineering and Technology Department of Electronics and Communication Hyderabad India Kg Reddy College of Engineering and Technology Department of Computer Science and Engineering Hyderabad India Kg Reddy College of Engineering and Technology Department of Civil Engineering Hyderabad India Kg Reddy College of Engineering and Technology Department of Mechanical Engineering Hyderabad India

ISBN: (纸本)9781665475280

Service learning in India is witnessing a large-scale adoption in higher education through the Unnat Bharat Abhiyan (UBA) program, a national-level service-learning program launched by India's Ministry of Education to promote community engagement and foster social responsibility among undergraduate students. The mission of UBA is to enable higher education institutions to partner with communities who live in rural India and engage in service-learning activities. The program advocates to build long-term engagement between academic institutions and nearby communities so that they could collaborate toward sustainable reciprocal partnerships. One of the goals of UBA is to establish linkages between academia and the community so that the knowledge created in the institutions could be targeted to solve complex societal problems. Higher education institutions that are part of this service-learning initiative were encouraged to do field studies through household surveys and informal interaction with the community members with a goal to identify unmet needs in the community. However, it was observed through prior research that the members of the community are only comfortable sharing their problems after faculty and students gain their trust. The paper presents a case study of a rural immersion experience that was introduced as part of the Unnat Bharat Abhiyan program at a private engineering institution in India. The 2-day rural immersion experience was designed to facilitate discussions among faculty and students with the community's various stakeholders, build trustworthy relationships, and empathize with their problems. The study employed a qualitative approach to investigate how students who were part of the rural immersion exercise described their experiences in the villages. Seven focus group discussions were conducted with 28 students who shared their highlights from visiting the villages and the process taken by them to identify unmet needs in the community. Themati

关键词： Rural areas

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Speech emotion recognition system using gender dependent convolution neural network

Speech emotion recognition system using gender dependent con...

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2022 International Conference on Machine Learning and Data engineering, ICMLDE 2022

作者： Singh, Vandana Prasad, Swati Department of Electronics and Communication Engineering Birla Institute of Technology Mesra Jharkhand Ranchi835215 India Department of Computer Science and Engineering Birla Institute of Technology Noida Campus Uttar Pradesh Mesra201301 India

Determining the emotion of a speaker using their speech utterance by a machine is referred to as Speech Emotion Recognition System. It can greatly enhance the human and machine interaction experience. However, the system faces poor performance due to factors like variations in emotion intensity, speaker, language, and culture. In this study, we have used RAVDESS dataset consisting of speech utterances with two emotional intensities, namely, strong, and normal, raising the recognition difficulty level for the development of an efficient framework for the Speech Emotion Recognition System (SER). For SER, Gender Dependent Training for building the emotion detection models in the Speech Emotion Recognition System is proposed in this research work. The proposed system is less complex and is able to demonstrate good performance using only MFCC features and its variants, namely, delta MFCC and delta-delta MFCC features when compared with the baseline system, which has utilized five different features, namely, MFCC, Mel, Chromogram, Spectral Contrast and Tonnetz. When the average of the speech emotion accuracy of 6 emotions, such as, Sad, Fearful, Calm, Surprised, Disgust and Happy are considered, the proposed system has shown a relatively improved result by 6.90 % over the considered baseline system. © 2023 The Authors. Published by Elsevier B.V.

关键词： Emotion Recognition

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Development Of an Intelligent Traffic Navigation System by Wireless Sensor Network System

Development Of an Intelligent Traffic Navigation System by W...

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2023 International Conference on New Frontiers in communication, Automation, Management and Security, ICCAMS 2023

作者： Kaushal, Rajanish Kumar Kumar, B.Anjanee Chauhan, Krupesh A. Munagala, Madhu Singh, Pavitar Parkash Hazela, Bramah Chandigarh University Department of Electrical Engineering Punjab Mohali India Dadi Institute of Engineering and Technology Anakapalle Electronics and Communication Engineering Visakhapatnam India Sardar Vallabhbhai National Institute of Technology Department of Civil Engineering Surat India Koneru Lakshmaiah Education Foundation Department of English Vaddeswaram India Lovely Professional University Department of Management Phagwara India Amity University Amity School of Engineering & Technology Department of Computer Science and Engineering Lucknow India

ISBN: (纸本)9798350317060

The use of automobiles is becoming more important worldwide, especially in densely populated cities. Current transportation infrastructure technologies include wired sensors, inductive loops, and satellite navigation. The installation and upkeep of surveillance equipment (cameras, etc.) are quite costly. In addition, environmental factors affect these instruments' precision. Traditional methods typically aim to optimize traffic light management for a given traffic density and layout. One key draws back all these methods, however, it may be challenging to represent the dynamic behaviour of traffic volumes and configurations, which is always changing. Therefore, in an effort to solve the aforementioned problem, this study proposes methods for adaptive traffic light management via the use of a distributed sensor network. The purpose of this study is to examine approaches to developing a smart system that can integrate and support some of the current technologies of traffic management, therefore decreasing the typical wait time for cars at a junction. The suggested algorithms are flexible enough to adjust to the particulars of traffic at every given crossroads. (GLD) is a traffic simulation tool used to model real-world traffic conditions and provide graphs of average waiting time vs cycle counts. The collected findings validate the efficacy of the suggested strategy for traffic regulation at a real-world road junction. © 2023 IEEE.

关键词： Wireless sensor networks

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An Optimized Intrusion Detection Model Using ML and Explainable AI

An Optimized Intrusion Detection Model Using ML and Explaina...

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International Conference on Computing and Networking Technology (ICCNT)

作者： Nikunj Jain Jawed Hawari Priyanshu Jha H.N. Vishwas Manish Jain Department of Computer Science and Engineering Amrita School of Computing Amrita Vishwa Vidyapeetham Bengaluru India Department of Electronics and Communication Engineering Amrita School of Engineering Amrita Vishwa Vidyapeetham Bengaluru India

ISBN: (数字)9798350370249

ISBN: (纸本)9798350370270

In the maintenance of network security, Intrusion Detection Systems (IDS) are very crucial in identifying unauthorized access and malicious activities. This research assesses how well different machine learning algorithms enhance IDS functionality, highlighting model interpretability through explainable AI techniques. Eight machine learning algorithms were assessed using a dataset from Kaggle that reflects a military network environment with 41 features and 22,544 records. Local Interpretable Model-agnostic Explanations (LIME) was used to analyze the top five models for their decision-making procedures. In several metrics, Random Forest algorithm appeared as the best performing among them all. LIME application provided useful insights into the main features that impact on the predictions being made by the model. The outcomes demonstrate the effectiveness of Random Forest for IDS and indicate how vital explainable AI methods such as LIME are in ensuring that IDS deployment can achieve transparency and reliability concerning its predictions for this model’s purpose.

关键词： Measurement Analytical models Machine learning algorithms Explainable AI Computational modeling Intrusion detection Predictive models Network security Prediction algorithms Random forests

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Optimize Analysis of Combined R2B, R4B and R8B FFT using Single Path Delay Feedback

Optimize Analysis of Combined R2B, R4B and R8B FFT using Sin...

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Big Data & Machine Learning (ICBDML), IEEE International Conference on

作者： Ashish Raghuwanshi Raj Kumar Neha Shrivastava Ashish Nema Amarjeet Kumar Ghosh Neha Khare Department of Electronics and Communication Engineering IES College of Technology Bhopal Madhya Pradesh India Department of Computer Science and Engineering IES University Bhopal Madhya Pradesh India

ISBN: (数字)9798350374100

ISBN: (纸本)9798350374117

FT is generally employed to convert the examined signal to frequency domain. FFT is a proficient method to configure discrete DFT. It is a significant method in DSP field that is used for configuring the DFT proficiently. FFT is just a computational algorithm and not another transform. This DFT modification lessens the calculation time. It firmly limits the execution cost on digital computing systems. In FFT the calculation performances has been improved by applying a divide and conquer approach. This methodology depends on decomposition and it breaks the transform as smaller transforms and the final consolidation leads to derive the complete transform. In FFT, the majority calculations can be dispensed by utilizing the symmetry and the periodicity classifications of the fidget factor. The prime merit of FFT is to decrease the number of computations. In this paper, design FFT 16-point FFT using combine R2B, R4B & R8B and SPDF. The design is implemented Xilinx 14.5i and calculate slice, LUT and delay.

关键词： Fast Fourier transforms Force Discrete Fourier transforms Pipelines Scattering Process control Machine learning

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Determining Network Performance Through Bandwidth Optimization in Underwater Fiber Optic communication 3

Determining Network Performance Through Bandwidth Optimizati...

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3rd International Conference on Smart Generation Computing, communication and Networking, SMART GENCON 2023

作者： Diwakar, Mandar P. Beemkumar, N. Yadav, Dhananjay Mishra, Varun Khandari, Harsimrat Divya, K. Vishwakarma Institute of Information Technology Department of Artificial Intelligence & Data Science Pune India Department of Mechanical Engineering Faculty of Engineering and Technology Karnataka Bangalore India Maharishi School of Engineering and Technology Maharishi University of Information Technology Uttar Pradesh India Vivekananda Global University Department of Computer Science & Engineering Jaipur India Centre of Interdisciplinary Research in Business and Technology Chitkara University Institute of Engineering and Technology Chitkara University Punjab India Prince Shri Venkateshwara Padmavathy Engineering College Department of Electronics and Communication Engineering Chennai127 India

ISBN: (纸本)9798350319125

Information the overall performance of underwater fiber optic (UWFO) communique networks is vital for a hit deployment of this technology in an expansion of applications. That allows you to achieve most efficient community overall performance, bandwidth optimization must be hired. This paper examines distinctive bandwidth optimization techniques and how they're used to improve conversation among UWFO elements. The proposed approach utilizes adaptive modulation and coding techniques, as well as advanced error correction coding schemes, to efficiently utilize the available bandwidth and minimize signal degradation. Through extensive simulations and experiments, we demonstrate the effectiveness of our approach in improving network performance, including increased data transfer rates and reduced error rates, compared to traditional methods. Our findings have significant implications for the design and operation of underwater fiber optic communication systems, potentially enhancing their potential for a wide range of applications in marine environments. In the end, several destiny studies guidelines are diagnosed to in addition enhance the overall performance and reliability of UWFO conversation networks. © 2023 IEEE.

关键词： Communiqué Conversation Investigates Networks Optimization

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