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An efficient task of floading mechanism using Genetic Operator Adaptive Firefly Algorithm (GOAFA) in an Edge-Cloud environment

An efficient task of floading mechanism using Genetic Operat...

引用

2023 International Conference on Innovative Computing, Intelligent Communication and Smart Electrical Systems, ICSES 2023

作者： Murugesan, R. Devaki, K. Paavai College of Engineering Department of Computer Science and Engineering Namakkal Pachal India Rajalakshmi Engineering College Department of Computer Science and Engineering Chennai India

ISBN: (纸本)9798350319200

Over the last few decades, cloud has been treated as the popular computing techniques over the internet. This cloud ecosystem should be reliable, and flexible with dynamic load balancing. The users on the internet are becoming billions and the resources are dynamically allocated to them in a demand fashion and their services have increased at an alarming rate. The load balancing is the major issue of cloud computing where the workload is dynamically distributed to every one (nodes) in the network. Moreover, edge computing assists with the cloud to enhance the system performance where the generated data are processed by edge computing nodes. Edge computing makes the computing resources that are closer to the user's location of the cloud. This will decrease the response time and minimize the network bandwidth. Nevertheless, it is still a challenge to maintain the load balance in edge nodes while minimizing the event completion time. With this perspective, this paper proposed an efficient task offloading method to ensure the load balance of the edge-cloud environment with reduced propagation time and load balance variance. Technically, first, construct the system model and then defined the multi-objective problem using the proposed Meta heuristic algorithm. Afterward, proposed a Genetic Operator Adaptive Firefly Algorithm (GOAFA) to optimize the propagation time and solves issues on load balancing in Edge-cloud environment (ECE). Finally, few simulations are done to prove the efficiency of the proposed system model. © 2023 IEEE.

关键词： adaptive firefly Edge cloud environment genetic operator load balance Meta-heuristic algorithm Task offloading

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A Review and Comprehensive Analysis of Recent Research in Crop Yield Prediction using Machine Learning Algorithms 6

A Review and Comprehensive Analysis of Recent Research in Cr...

引用

6th IEEE International Conference on Recent Advances in Intelligent Computational Systems, RAICS 2024

作者： Selvakumar, R.K. Tanoj, Salehundam Sai Goud, Tigulla Hrushitha Cvr College Of Engineering Department of Computer Science and Engineering Hyderabad India Hyderabad India

ISBN: (纸本)9798350381689

Traditional farming based on conventional methods has been the pillar of agricultural practices for a long time. But, due to the escalating global population, unstable climatic patterns and limited resources, the efficiency of traditional methods is facing challenges. The introduction of data-driven and artificial intelligence based approaches involving machine learning and deep learning have gained significant popularity capturing the interest of numerous researchers. This review examines various algorithms, including Random Forest, Decision Trees, K-Nearest Neighbours, Lasso Regression, Stacked Regression, and XGBoost, along with deep learning techniques like LSTM, RNN, and SVM. The study highlights their performance across multiple metrics such as accuracy, RMSE, MAE, R2, and MSE. Notably, Random Forest emerges as a highly effective model due to its excellent performance in accuracy, RMSE, MAE, and R2. Lasso Regression and XGBoost also show remarkable results in RMSE and MSE, respectively. Deep learning models like LSTM, RNN, and SVM are recognized for their high accuracy, underlining their potential in handling complex agricultural data. Through an examination of diverse approaches and data sources, this review seeks to explain and define the capabilities of these innovative technologies for sustainable agrarian applications. © 2024 IEEE.

关键词： Adversarial machine learning

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Child Safety and Activity Monitoring System Using IoT 2

Child Safety and Activity Monitoring System Using IoT

引用

2nd IEEE International Conference on Advances in Information Technology, ICAIT 2024

作者： Kadhiresh, S. Saran Kumar, C. Tamizhan, M. Vidya Prabha, C.V. Department of Computer Science and Engineering Karpagam College of Engineering Tamilnadu Coimbatore641032 India

ISBN: (数字)9798350383867

ISBN: (纸本)9798350383867

Child safety and tracking are pressing concerns that garner widespread attention due to the escalating incidence of crimes against children. In response to this, an innovative Internet of Things (IoT) device has been developed to ensure the safety and monitoring of children. This monitoring system aids parents in tracking and overseeing their children's activities, catering to those who seek to maintain constant awareness of their child's whereabouts. It utilizes GPS and telephony services within an Android application to accurately pinpoint the child's location, allowing parents to discreetly monitor messages and track their child without their knowledge. Notably, the application operates discreetly in the background of the child's phone, even after rebooting. The system, coded in embedded C, interfaces with various sensors including temperature, heartbeat, and tactile sensors, as well as GPS, GSM, and a digital camera. Its standout feature lies in its automated module system, which promptly notifies parents or caregivers via real-time SMS alerts. This proactive approach ensures swift action during emergency situations, emphasizing the importance of continuous monitoring. Additionally, factors such as the child's tactile sensations, body temperature, and heart rate are considered, with parametric analysis facilitating visualization of the obtained results. © 2024 IEEE.

关键词： Global system for mobile communications

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Virtual board

Virtual board

引用

International Conference on Artificial Intelligence, Blockchain, Computing and Security, ICABCS 2023

作者： Ravindhar, N.V. Praharsha Reddy, P.V. Sathvik Reddy, P. Ajay Kumar, Boyapati Department of Computer Science and Engineering Saveetha Engineering College Tamil Nadu Chennai India

ISBN: (纸本)9781032669663

The entire world revolves around technology. This began with the advancement of computer technology. The input and output mechanisms of computers changed dramatically as they evolved. Initially, the computer was controlled via switches. Later on, punch cards were introduced. A mouse, a keyboard, a monitor, a joystick, and other input devices were designed. Touch sensors are built in the screens for smart phones, smart watches, computers, and other devices. Hand gestures are used as input by the most advanced systems. "Leap Motion Sensors" are used. These systems are expensive to install and maintain. As a result, our concept "Virtual Board" is to create software that allows us to write on the screen without exerting additional effort. This system makes use of the well-known Open computer Vision library. This algorithm examines the movement of targets between video frames is given as output in a sequential manner to conduct video tracking. © 2024, CRC Press/Balkema. All rights reserved.

关键词： Touch screens

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Person Image Generation To Enhance The Input Training Image For Re-Identification 14

Person Image Generation To Enhance The Input Training Image ...

引用

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

作者： Anjali, P.S. Rahamathulla, K. Swaraj, K.P. Government Engineering College Department of Computer Science and Engineering Thrissur India Government Engineering College Sreekrishnapuram Department of Computer Science and Engineering Palakkad India

ISBN: (纸本)9798350335095

The process of recognizing a person from photos or videos taken with a different camera is called re-identification (reID). In today's world, the widespread use of extensive networks of CCTV and security cameras makes it difficult for a human operator to trace a person. This is where re-identification technology comes into play. However, person re-identification in real-world applications is very challenging due to the size of the existing dataset, the lack of human motions, and the inability to supply enough training samples. In this paper, proposed a method for person image generation using Generative Adversarial Networks (GANs). GANs allow us to build additional person images that look as realistic as possible. © 2023 IEEE.

关键词： Generative adversarial networks

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Crime rate prediction using K-means algorithm

Crime rate prediction using K-means algorithm

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International Conference on Artificial Intelligence, Blockchain, Computing and Security, ICABCS 2023

作者： Julian, Anitha Somasekhar, Darisi Venkata Veera Harsh Vardhan, R. Naidu, Harsh Vardhan Department of Computer Science and Engineering Saveetha Engineering College Tamil Nadu Chennai India

ISBN: (纸本)9781032669663

Preventative measures are preferable to corrective measures. Crime prevention is preferable to crime detection. With the world’s crime rate at an all-time high and more violent crimes occurring every day, we must implement a vaccination system to protect children from being victims of crime. By "vaccinating society against crime," we mean using a variety of techniques to reduce the prevalence of criminal activity in a community. The term "data mining" refers to the technique of gleaning useful information and revealing hidden patterns from massive datasets. Data mining for the sake of criminal investigation may be rather fruitful. Utilizing data held in repositories, data mining may be used to forecast and assess criminal activity. India’s rising crime rate has become a critical concern and is preventing the nation from moving toward functional government. The crime statistics and trends that are relevant to this project are analyzed in depth. © 2024, CRC Press/Balkema. All rights reserved.

关键词： Crime

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Python-Based Free and Open-Source Web Framework Implements Data Privacy in Cloud Computing 4th

Python-Based Free and Open-Source Web Framework Implements D...

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4th International Conference on IoT Based Control Networks and Intelligent Systems, ICICNIS 2023

作者： Veeresh, V. Parvathy, L. Rama Department of Computer Science and Engineering Saveetha School of Engineering Tamil Nadu Chennai India

ISBN: (纸本)9789819965854

Data sharing turn into a remarkably striking service delivered by cloud computing architecture due to its suitability and reduced cost. As a probable practice for understanding finely secured distribution of data, using a technique called Attribute-Based Encryption (ABE) with a different variety of users. In real time, ABE technique has its own drawbacks like high computation overhead and less security in cloud data storage with fine-grained data files. Processing tasks could be transferred to remote computing resources utilizing cloud computing. Cyber insurance is a realistic way of passing on cyber security risks, but data security can or cannot be improved depending on the environment's key characteristics. This paper focused on one income insurer, client participants, and insured volunteers, focusing on two different cybersecurity aspects and their impact on the standard form of contracts. Since cyber security is linked, an entity's degree of security is determined not just by its own effort and effort but also by the efforts of others operating within the same system. As such, effective resource utilization could be performed, reducing manufacturer costs, but the only drawback of cloud services is that data will be secured and reasonably priced in the cloud. Hence, before going to the cloud, all content must be encrypted. Consumers of a collision protection information-sharing system are given secure private keys so they may add or remove consumers. © 2024, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Digital storage

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Forecasting Crucial Biogeochemical Indicators of the Southern Ocean for Climate Monitoring Using Modified Kernel-Based Support Vector Regression 2nd

Forecasting Crucial Biogeochemical Indicators of the South...

引用

2nd International Conference on Big Data, IoT and Machine Learning, BIM 2023

作者： Saad, Asif Mohammed Mahmud, Rakib Das, Sunanda Department of Computer Science and Engineering Khulna University of Engineering & Technology Khulna9203 Bangladesh

ISBN: (纸本)9789819989362

The ocean is a massive expanse of saltwater that spans over 70.8% of the Earth’s surface and holds nearly 97% of the planet’s water. The Southern Ocean is remarkable because it influences worldwide climate patterns and plays a key role in storing a tremendous amount of heat, carbon dioxide, and nutrients. As a result, we are focusing our efforts on solving the mysteries surrounding the Southern Ocean. Therefore, in this study, we attempted to forecast crucial biogeochemical indicators for climate monitoring such as pH (25 ∘C), nitrate content, and relative density of seawater. More research and analysis on these three components might be beneficial because they are critical aspects for ecology, marine biochemistry, and overall climate patterns. This study is conducted to develop new custom kernels (Hyperbolic Sine Kernel, Gaussian Matrix Multiplier Kernel) for mapping the features into desirable space, effectively making assumptions based on existing relevant features using SVR technique. Further, comparing their efficiency against present kernels (on certain constraints) across three dimensions and suggesting a significantly higher-performing kernel. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Carbon dioxide

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Predictive Analysis for Multiple Disease Identification using Machine Learning 4

Predictive Analysis for Multiple Disease Identification usin...

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4th International Conference on Sustainable Expert Systems, ICSES 2024

作者： Musharuf, A.Mohamed Anand, M. Vijay Saveetha Engineering College Department of Computer Science and Engineering Tamil Nadu Chennai India

ISBN: (纸本)9798331540364

The availability of diverse health data, including medical records, genetic information, and lifestyle details, presents an opportunity to gain a comprehensive understanding of individual health profiles and disease risks. However, effectively integrating these disparate data sources remains a significant challenge. This study proposes a novel approach to address this challenge by combining deep learning techniques and ensemble methods. The proposed model is capable of simultaneously predicting an individual's risks for a range of major chronic and acute diseases, including cardiovascular disease, cancers, diabetes, and more. By integrating advanced machine learning techniques, the model can effectively integrate structured and unstructured data, capturing the complex relationships between different data types and disease outcomes. This approach enables early disease detection and facilitates timely intervention, leading to improved patient outcomes. The study highlights the importance of combining diverse data sources and employing machine learning techniques to develop accurate and comprehensive predictive models for multi-disease risk assessment. This research contributes to the advancement of personalized healthcare and preventive medicine. © 2024 IEEE.

关键词： Electronic health record

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Enhancing Bangla Language Text Recognition in OCR using Levenshtein Distance and Character Grouping Strategy

Enhancing Bangla Language Text Recognition in OCR using Leve...

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2024 IEEE International Conference on Signal Processing, Information, Communication and Systems, SPICSCON 2024

作者： Hasan, Md. Sajid Pal, Avi Ahsan, Sk.Md. Masudul Department of Computer Science and Engineering Khulna University of Engineering & Technology Khulna9203 Bangladesh

ISBN: (纸本)9798331510213

One crucial technology for text digitization from image is optical character recognition (OCR). Character recognition in languages with complex scripts, like Bangla, is still difficult despite recent advancements. This research proposes an innovative approach to enhance OCR’s Bangla text recognition capabilities. In order to improve recognition performance, OCR errors are efficiently corrected and performance is improved by first applying the Levenshtein distance measure. Experiments show a notable improvement, increasing the initial weighted F1-score of Tesseract OCR from 84.96% to 87.26%. In addition, a method of character grouping is demonstrated to address nuances specific to the Bangla script. Characters that share visual similarities are categorized into different groupings. Subsequently, priority is given to dictionary candidate words with characters that belong to the same class as those identified by OCR. Integrating the character grouping technique yields an astounding 90.92% F1-score. © 2024 IEEE.

关键词： Optical data processing

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