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An experimentation of objective functions used for multilevel thresholding based image segmentation using particle swarm optimization

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International Journal of Information technology (Singapore) 2024年第3期16卷 1717-1732页

作者： Ahmed, Saifuddin Biswas, Anupam Khairuzzaman, Abdul Kayom Md Department of Computer Science and Engineering National Institute of Technology Silchar Cachar 788010 India School of Electronics Engineering VIT-AP University Andhra Pradesh Amaravati 522237 India

For image segmentation, multilevel thresholding is treated as one of the widely used approach. However, this approach has a major issue that is it suffers of high computational complexity problem with the increase threshold levels. This paper presented a comparative performance analysis of some objective functions used for image segmentation using the concept of multilevel thresholding and a modified version of adaptive inertia weight Particle Swarm Optimization (PSO) technique. The PSO algorithm is applied to multilevel thresholding based image segmentation using either Otsu’s inter class variance, Kapur’s entropy or Masi entropy as an objective function. Each method is tested over various standard image dataset like Berkeley image database, USC-SIPI image dataset etc. The evaluated result of each method has been compared and the overall experimentation is performed in three different ways such as, PSO and Otsu’s method, PSO and Kapur’s entropy and PSO with Masi entropy. The performance and quality of the segmented images are measured using the following parameters such as, average Mean Structural Similarity Index (MSSIM), average Peak Signal to Noise Ratio (PSNR) values, average mean objective functions values and average CPU rum time values. The experimental analysis shows that the performance of Otsu’s inter-class variance function shows comparatively a better result than Kapur’s and Masi’s entropic method. © 2024, The Author(s), under exclusive licence to Bharati Vidyapeeth's Institute of computer Applications and Management.

关键词： Kapur’s entropy Masi entropy Meta-heuristic Multilevel thresholding Non-parametric Otsu’s method Parametric Particle swarm optimization

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Enhancing Sentiment Analysis of Twitter Data Using Recurrent Neural Networks with Attention Mechanism 4

Enhancing Sentiment Analysis of Twitter Data Using Recurrent...

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4th International Conference on Smart electronics and Communication, ICOSEC 2023

作者： Nithya, S. Presskila, X. Arogya Sakthivel, B. Krishnan, R. Santhana Narayanan, K. Lakshmi Sundararajan, S. PSNA College of Engineering and Technology Department of Information Technology Dindigul India Scad College of Engineering and Technology Department of Computer Science and Engineering Cheranmahadevi India Vivekananda College of Engineering for Women Department of Electronics and Communication Engineering Tiruchengode India Scad College of Engineering and Technology Department of Electronics and Communication Engineering Cheranmahadevi India Francis Xavier Engineering College Department of Electronics and Communication Engineering Tirunelveli India Scad College of Engineering and Technology Department of Mechanical Engineering Cheranmahadevi India

ISBN: (纸本)9798350300888

Sentiment analysis, the intricate task of discerning and classifying the myriad of sentiments conveyed within textual data, has captured substantial interest and intrigue, primarily driven by the pervasive utilization and influence of social media platforms. In this study, a novel approach to enhance sentiment analysis of Twitter data by employing Recurrent Neural Networks (RNNs) with an attention mechanism is proposed. The proposed model leverages the sequential nature of tweets and the attention mechanism to capture the inherent dependencies between words and highlight salient information. The RNN-based model on a large-scale dataset of annotated Twitter data, encompassing diverse sentiments is trained. The model effectively learns the contextual information and sentiment patterns, enabling accurate sentiment classification. A comprehensive set of tests were run to evaluate the effectiveness of this methodology, and the outcomes were meticulously compared to those of traditional machine learning algorithms and established deep learning models. The empirical findings demonstrate that proposed attention-based RNN model performs better than competing methods and achieves cutting-edge performance on sentiment analysis of Twitter data. Moreover, an in-depth analysis of the attention weights generated by the model, shedding light on the significant words and phrases influencing sentiment classification is conducted. This provides valuable insights into the underlying sentiment dynamics in Twitter data. Proposed research contributes to the field of sentiment analysis by proposing an effective and robust approach for Twitter sentiment classification. The findings highlight the potential of RNNs with attention mechanisms in capturing the nuanced sentiment expressions prevalent in social media text. The proposed model can facilitate various applications, including real-time sentiment monitoring, brand reputation analysis, and public opinion tracking, benefiting industries a

关键词： Sentiment analysis

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Optimization and Representation of Non-Slicing VLSI Floorplanning 4

Optimization and Representation of Non-Slicing VLSI Floorpla...

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4th International Conference on Smart electronics and Communication, ICOSEC 2023

作者： Jeyarohini, R. Britto, K. R. Aravind Ramkumar, M.P. PSNA College of Engineering and Technology Department of Electronics and Communication Engineering Dindigul India Thiagarajar College of Engineering Department of Computer Science and Engineering Madurai India

ISBN: (纸本)9798350300888

The recent advances in the semiconductor nano technologies increase the complexity of very large-scale integration circuits. With the fabrication technology entering the deep Nanoscale era more demand at greater huge complication of integrated chip design arises. The development of eccentric floor plan without over-lapping is the intention of VLSI floor planning. The major objective of VLSI is concerned with floor plan area minimization and wire length optimization. Floor planning is the important step that creates an optimal layout solution for the VLSI circuits. This article attempted to collect the necessary information in reducing the floor plan layout by means of reducing the wire length, white space area with the employment of computer aided metaheuristic algorithms. In order to ease the process of execution the best local search algorithms like a Particle Swarm Optimization and Simulated Annealing algorithms is compared. © 2023 IEEE.

关键词： Simulated annealing

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A Novel Approximate Message Passing Detection for Massive MIMO 5G System

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computer Systems Science & engineering 2023年第6期45卷 2827-2835页

作者： Nidhi Gour Rajneesh Pareek Karthikeyan Rajagopal Himanshu Sharma Mrim M.Alnfiai Mohammed A.AlZain Mehedi Masud Arun Kumar Department of Computer Science&Engineering JECRC UniversityJaipurIndia Centre for Nonlinear Systems Chennai Institute of TechnologyChennaiIndia Department of Electronics and Communication Engineering and University Centre for Research&Development Chandigarh UniversityMohaliIndia Department of Information Technology College of Computer and Information TechnologyTaif UniversityP.O.Box 11099Taif21994Saudi Arabia Department of Computer Science College of Computers and Information TechnologyTaif UniversityP.O.Box 11099TaifSaudi Arabia Department of Electronics and Communication Engineering JECRC UniversityJaipurIndia

Massive-Multiple Inputs and Multiple Outputs(M-MIMO)is considered as one of the standard techniques in improving the performance of Fifth Generation(5G)radio.5G signal detection with low propagation delay and high throughput with minimum computational intricacy are some of the serious concerns in the deployment of *** evaluation of 5G promises a high quality of service(QoS),a high data rate,low latency,and spectral efficiency,ensuring several applications that will improve the services in every *** existing detection techniques cannot be utilised in 5G and beyond 5G due to the high complexity issues in their *** the proposed article,the Approximation Message Passing(AMP)is implemented and compared with the existing Minimum Mean Square Error(MMSE)and Message Passing Detector(MPD)*** outcomes of the work show that the performance of Bit Error Rate(BER)is improved with minimal complexity.

关键词： AMP MMSE MPD 5G

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Investigation of Normally-Off β-Ga2 O3 Power MOSFET Using Ferroelectric Gate 3rd

Investigation of Normally-Off β-Ga2 O3 Power MOSFET Using F...

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3rd International Conference on Micro and Nanoelectronics Devices, Circuits and Systems, MNDCS 2023

作者： Singh, Rajan Purnachandra Rao, G. Lenka, Trupti Ranjan Prasad, S.V.S. Dasari, Kiran Singh, Pulkit Nguyen, Hieu Pham Trung Department of Electronics and Communication Engineering MLR Institute of Technology Telangana Hyderabad500043 India Department of Electronics and Communication Engineering National Institute of Technology Assam Silchar788010 India Department of Electrical and Computer Engineering New Jersey Institute of Tech NewarkNJ07102 United States

ISBN: (纸本)9789819944941

In this paper, we present a normally-off beta-gallium oxide (β-Ga2O3) metal–oxide–semiconductor field-effect transistor (MOSFET) with ferroelectric gate (Fe-G). The enhancement-mode (E-Mode) operations are achieved by depleting the charge carriers from the channel using the gate charge trapped in the ferroelectric material at the ferroelectric–dielectric (Fe-De) interface. The enhancement-mode (E-mode) operation has a negligible degradation in saturation current as compared to depletion-mode (D-Mode) operation. Ohmic-contacts access region resistances are minimized in the E-mode using highly-doped ohmic-contacts access regions. Furthermore, device achieves a significant low specific on-resistance (RON,sp) of 48 mΩ-cm2 in E-mode compared to 103 mΩ-cm2 in the D-mode. Furthermore, a high breakdown voltage (VBR) of 2250 V in E-mode combined with RON,sp brings in a figure of merit (VBR2/RON,sp) of 49 MW/cm2, showing its potential for futuristic wide bandgap (WBG) power devices. In addition, the E-mode device shows a hysteresis-free subthreshold swing (SS) of 65 mV/dec, which indicates its suitability for fast switching applications. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Ohmic contacts

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Multi Objective Evaluator Model Development for Analyze the Customer Behavior 3

Multi Objective Evaluator Model Development for Analyze the ...

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3rd International Conference on Advancement in electronics and Communication engineering, AECE 2023

作者： Krishnamoorthy, R. Kaliyamurthie, K.P. Ahamed, B.S.H. Shayeez Harathi, Nimmala Selvan, R.Senthamil Bharath Institute of Higher Education and Research Department of Computer Science and Engineering Chennai India Madanapalle Institute of Technology and Science Department of Computer Science and Engineering Madanapalli India Department of Electronics and Communication Engineering Tirupati India Annamacharya Institute of Technology and Sciences Department of Electronics and Communication Engineering Tirupati India

ISBN: (纸本)9798350330724

Predicting consumer behaviour elucidates demographics, tastes, and underlying patterns. By keeping tabs on consumer activity, businesses may learn more about their wants and requirements, allowing them to provide better suggestions and increase conversion rates. Numerous factors affect consumer choices, including customer economics, buyer segmentation, and product quality. The most pressing problem that needs fixing is extracting actionable insights from these massive data sets to predict customers' actions. Author presented the multi objective evolutionary method to considerably improve the precision of consumption-related predictions as part of a cutting-edge quantitative research approach for predicting and analyzing customers' consumption habits. As the foundation for the whole prediction model, the data is first compiled based on customer preference and behaviours. As part of the data preparation, min-max normalization eliminates extraneous or irrelevant information. The author uses the Word2vec model for extraction of features, and we adopt boosting ant colony optimization (BACO) for feature selection. Multi-objective evolutionary algorithms (MOEAs) are used to make the predictions. The performance of the proposed system is evaluated, and its metrics are compared with those of well-established methods. The results indicate that the proposed multi objective evolutionary algorithm (MOEA) technique outperforms traditional Machine Learning (ML), excessive gradient boosting (XGB), Artificial intelligence (AI), and naive bayes (HNB) algorithms in various performance metrics. These metrics include accuracy (96 per cent), prediction quality (97per cent), accuracy (98 %), Recall (94 %), F1 score (99 %), and forecast time fifty seconds). Therefore, the results indicate that the regression model is viable and can be maintained over time. The proposed system for predicting consumption behaviour has shown its effectiveness in enhancing profitability. © 2023 IEEE.

关键词： Machine learning

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Smart Aeroponic Farms with IoT-Enabled Efficient Automation and Monitoring 2

Smart Aeroponic Farms with IoT-Enabled Efficient Automation ...

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2nd International Conference on Artificial Intelligence and Machine Learning Applications, AIMLA 2024

作者： Jeyabharath, R. Tamilvani, P. Karthikeyan, G. Vijayakumar, P. Rohini, J. Mohammadha Hussaini, M. Kavin Kumar, K. K.S.R. College of Engineering Department of Electrical and Electronics Engineering Tiruchengode India M.P.Nachimuthu M.Jaganathan Engineering College Department OfElectrical and Electronics Engineering Erode India Sona College of Technology Department of Electrical and Electronics Engineering Salem India Kongu Engineering College Master of Computer Applications Erode Perundurai India Erode Sengunthar Engineering College Department of Computer Science and Engineering Thuduppathi638057 India Government College of Engineering Department of Electrical and Electronics Engineering Erode India Kongu Engineering College Department of Electronics and Communication Engineering Erode India

ISBN: (数字)9798350349221

ISBN: (纸本)9798350349221

The Internet of Things (IoT) has enabled the adoption of automated aeroponics equipment, which has transformed our understanding of horticulture. Aeroponics is a method of vegetative production that does not use soil. Plant cultivation takes place in an airborne or vapour environment. The use of Internet of Things (IoT)-enabled aeroponics devices allows farms to autonomously monitor and manage variables such as temperature, lighting, humidity, and fertiliser concentrations. This allows for real-time adjustments to be made to optimize plant growth and yield. The IoT-enabled automated aeroponics system utilizes sensors and actuators to collect data on environmental conditions and automate the delivery of nutrients and water to the plants. Additionally, the system can be programmed to send alerts and notifications to farmers in case of any irregularities or issues that require attention. This level of automation not only increases efficiency and productivity but also reduces the need for manual labor and minimizes resource wastage. The IoT-enabled automated aeroponics systems have the potential to revolutionize farming by providing a more sustainable and efficient method of crop production. The computer system uses environmental elements to evaluate the results of aeroponics studies. The decision was made to use an automated aeroponics methodology to develop maize plants. According to the findings of this study, applying this method could potentially reduce labour expenses while increasing the value of the product. © 2024 IEEE.

关键词： Internet of things

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Employee Attrition Prediction based on Light Gradient Boosting Machine with Bayesian Optimization 1

Employee Attrition Prediction based on Light Gradient Boosti...

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1st International Conference on Intelligent Systems and Computational Networks, ICISCN 2025

作者： Pramodhini, R. Obbayed, Saif Manju, K. Swarnalakshmi, G. Purushotham, N. Nitte Meenakshi Institute of Technology Department of Electronics and Communication Engineering Bengaluru India The Islamic University of Al Diwaniyah College of Technical Engineering Department of Computers Techniques Engineering Al Diwaniyah Iraq Sona College of Technology Department of Electronics and Communication Engineering Salem India New Prince Shri Bhavani College of Engineering and Technology Department of Mechanical Engineering Chennai India Mohan Babu University Department of Computer Science and Engineering Tirupati India

ISBN: (纸本)9798331529246

In recent days, many organizations struggle to retain the valuable employees with severe consequences of Employee Attrition (EA) rate. The existing Random Forest (RF) was utilized to predict the turnover rate of employees in corporate industries. However, the existing model struggled with interpretability and computation cost issues. To overcome these issues, Light Gradient Boosting Machine with Bayesian Optimization (LightGBM-BO) is proposed. The proposed LightGBM-BO reduced computational complexity with gradient boosting and improved interpretability with hyperparameter tuning. Initially, the data is considered and preprocessed with min-max normalization to rescale the data into significant range. Then, features are extracted with Principal Component Analysis (PCA) by utilizing covariance matrix. After that, Recursive Feature Elimination (RFE) is incorporated to select optimal features based on feature importance. Finally, the EA prediction is done with proposed LightGBM-BO and the performance is improved with hyperparameter tuning. From the results, the proposed LightGBM-BO attained better results when compared to existing eXtreme Gradient Boosting (XGBoost) including accuracy (94.93%) and precision (92.84%) respectively. © 2025 IEEE.

关键词： Adaptive boosting

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Development of Novel-Epoxy-Based Transformer Bushing Insulator for High Breakdown Voltage (BDV) 3

Development of Novel-Epoxy-Based Transformer Bushing Insulat...

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3rd International Conference on Emerging Trends in Electrical, Control, and Telecommunication engineering, ETECTE 2024

作者： Siddique, Abubakar Akram, Laraib Aslam, Waseem Mishal, Areeba Shahid, Muhammad Usama Ahmed, Haseeb Department of Electrical and Biomedical Engineering Khwaja Fareed University of Engineering and Information Technology Rahim Yar Khan Pakistan Department of Electrical Electronics & Computer Engineering University of Sargodha Sargodha Pakistan

ISBN: (纸本)9798331504861

In today’s trends, nanocomposites have garnered significant interest due to their potential to enhance dielectric properties and be used as insulators. Incorporating nanoparticles into the base epoxy makes achieving highly efficient dielectric materials feasible. However, the low electric field stress management capability and insufficient relative permittivity of typical epoxy provide a hindrance. Efforts have been made to overcome these limitations by adding nanosized fillers with high relative permittivity to the epoxy to enhance the dielectric properties. This research study focuses on the development of Novel-Epoxy-Based Transformer Bushing Insulator using nanomaterial Al2O3 and SiO2. The epoxy resin served as the base material, with nano-fillers added to improve its dielectric properties. The hardener was added to initiate the curing process and create a highly crosslinked structure. Surfactants were introduced to improve the interaction between the epoxy resin and nanoparticles. The nano-silica and nano-alumina particles were combined in different ratio configurations to create the nanocomposites by using the preparation method;Sol-Gel and Green Synthesis, which were subsequently tested for their dielectric properties. The proposed sample is the nanocomposite made by the green synthesis method and with the combination of 0.3 g + 0.3 g of the nanoparticle. Results show improved dielectric strength of the proposed nanocomposites compared to conventional porcelain materials. This paper presents an environment friendly approach for developing epoxy-based transformer bushing insulators, offering enhanced performance. ©2024 IEEE.

关键词： Permittivity

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Biometric Web based Vote Cast using Blocks 3

Biometric Web based Vote Cast using Blocks

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3rd International Conference on Innovative Mechanisms for Industry Applications, ICIMIA 2023

作者： Abinaya, M. Priya, P.Kaviya Mirza, Mohsina Anbumani, A. Sathya, R. Sethuram, M. Sri Eshwar College of Engineering Department of Computer Science and Engineering Coimbatore India P.A College of Engineering and Technology Department of Computer Science and Engineering Coimbatore India Global College of Engineering and Technology Department of Electrical and Electronic Engineering India Paavai College of Engineering Department of Computer Science and Engineering Coimbatore India Kongunadu College of Engineering and Technology Department of Information Technology Trichy India Hindusthan College of Engineering and Technology Department of Electronics and Communication Engineering Coimbatore India

ISBN: (纸本)9798350343632

Web based vote casting is a form of voting in which the voter is able to cast their votes through any web portal wherever in the world. In the Biometric method, voter can cast the votes using their finger impression. In this method the voter can selects the login portal which is particularly designed for an election commission. Each person needs to register the election commission website, using the registration details substantiate themselves before the machine authorize the user to sight the ballot visible on the screen. The voter is then allowed to pick their selected candidate and then cast the votes which would be passed to the election server for the refining process. In 'E-Voting' method a voter can cast their votes through online without any difficulty. If all the entries provided by the user are precise user can login the system using the user ID and password voter can cast their votes through online wherever in the world. If an information given by the voter is not correct then the entry will be discarded and it shows the error message. This technique is mainly implemented to reduce the difficulty of the election commission and voter. It is a user-friendly approach, also it avoids the unwanted crowds during the election period. Here, this study has used immutable ledger technology that is a blockchain based application, which provides the security and also increase the efficiency of the voting process. © 2023 IEEE.

关键词： Blockchain Electronic Voting (E-Voting) Personnel computer (PC)

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