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7th International Conference on Intelligent Computing and Control Systems, ICICCS 2023

作者： Saravanan, V. Ranjana, P. Hindustan Institute of Technology & Science Department of Computer Application Chennai603103 India

ISBN: (纸本)9798350397253

Cost is the primary justification for outsourcing an organization's IT hardware acquisition. By avoiding the need to hire more staff members and reducing the number of hours your present workers are required to work, outsourcing the purchase of hardware may help the business save money. Additionally, you won't need to continually purchase brand-new IT hardware or software. Additionally, outsourcing can boost production and enable you to provide your consumers with a better and more effective good or service. An iterative technique for maximizing an objective function with sufficient smoothness qualities is stochastic gradient descent or SGD for short. Given that it substitutes an estimate for the real gradient, it may be thought of as a stochastic approximation of gradient descent optimization. This lightens the computational load, especially in high-dimensional optimization problems, leading to quicker iterations at the cost of a reduced convergence rate. We suggest a Stochastic Gradient Descent model for use in a commercial setting where large corporations must purchase the necessary hardware with their software. Our approach assists in determining the necessary hardware requirements based on the demands of the customers. © 2023 IEEE.

关键词： Machine learning

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A UAV swarm simulation system for operator cognitive analysis 7

A UAV swarm simulation system for operator cognitive analysi...

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7th International Conference on Advanced Electronic Materials, computers, and Software Engineering, AEMCSE 2024

作者： Feng, Yunduo Zhao, Xiaochuan Liu, Huapeng Jin, Leiming Hong, Tiange Computer Application Technology Institute of China North Industries Group Corporation Haidian Beijing100080 China

ISBN: (纸本)9781510681866

In recent years, UAVs have played an increasingly important role in the military and civilian fields, especially UAVs swarm with high mission execution and diverse execution scenarios. The operator should have high proficiency in manipulation due to the complexity of UAV swarm, and cognitive analysis is an efficacious method used to train and assess operators of UAV swarm. This paper put forward an UAV swarm simulation system for operator cognitive analysis. First the requirements of simulation system for operator cognitive analysis is introduced. Subsequently the architecture and detailed module design of simulation system is proposed. Finally, the result of vehicle searching mission simulation and EEG data of operator verify the effectiveness of the simulation system. © 2024 SPIE.

关键词： Unmanned aerial vehicles (UAV)

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Towards Exploring Large Molecular Space:An Efficient Chemical Genetic Algorithm

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Journal of computer Science & technology 2022年第6期37卷 1464-1477页

作者： Jian-Fu Zhu Zhong-Kai Hao Qi Liu Yu Yin Cheng-Qiang Lu Zhen-Ya Huang En-Hong Chen Anhui Province Key Laboratory of Big Data Analysis and Application School of Computer Science and TechnologyUniversity of Science and Technology of ChinaHefei 230026China

Generating molecules with desired properties is an important task in chemistry and *** efficient method may have a positive impact on finding drugs to treat diseases like *** mining and artificial intelligence may be good ways to find an efficient ***,both the generative models based on deep learning and the work based on genetic algorithms have made some progress in generating molecules and optimizing the molecule’s ***,existing methods have defects in the experimental evaluation *** methods also need to be improved in efficiency and *** solve these problems,we propose a method named the Chemical Genetic Algorithm for Large Molecular Space(CALM).Specifically,CALM employs a scalable and efficient molecular representation called molecular *** we design corresponding crossover,mutation,and mask operators inspired by domain knowledge and previous *** apply our genetic algorithm to several tasks related to molecular property optimization and constraint molecular *** results of these tasks show that our approach outperforms the other state-of-the-art deep learning and genetic algorithm methods,where the z tests performed on the results of several experiments show that our method is more than 99%likely to be *** the same time,based on the experimental results,we point out the defects in the experimental evaluation standard which affects the fair evaluation of all previous *** these defects helps to objectively evaluate the performance of all work.

关键词： data mining molecular generation genetic algorithm drug discovery artificial intelligence

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Location Prediction from Social Media Contents using Location Aware Attention LSTM Network

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Journal of Harbin Institute of technology(New Series) 2024年第5期31卷 68-77页

作者： Madhur Arora Sanjay Agrawal Ravindra Patel Department of Computer Application University Institute of TechnologyRajiv Gandhi Proudyogiki VishwavidyalayaBhopal(M.P.)462033India Department of Computer Application National Institute of Technical Teachers Training and ResearchBhopal(M.P.)462002India

Location prediction in social media,a growing research field,employs machine learning to identify users' locations from their online *** technology,useful in targeted advertising and urban planning,relies on natural language processing to analyze social media content and understand the temporal dynamics and structures of social networks.A key application is predicting a Twitter user's location from their tweets,which can be challenging due to the short and unstructured nature of tweet *** address this challenge,the research introduces a novel machine learning model called the location-aware attention LSTM(LAA-LSTM).This hybrid model combines a Long Short-Term Memory(LSTM) network with an attention *** LSTM is trained on a dataset of tweets,and the attention network focuses on extracting features related to latitude and longitude,which are crucial for pinpointing the location of a user's *** result analysis shows approx.10% improvement in accuracy over other existing machine learning approaches.

关键词： Twitter social media location machine learning attention network

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Risk Assessment of Global Temperature Anomalies Using Intelligence Frameworks: Evaluating the Impact of Socioeconomic Factors and with a Case Study on Heatstroke Deaths in India

Risk Assessment of Global Temperature Anomalies Using Intell...

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2025 International Conference on Ambient Intelligence in Health Care, ICAIHC 2025

作者： Pati, Alok Kumar Patnaik, Jemmut Dash, Sruti Mohanty, Tuheena Tripathy, Alok Ranjan Ravenshaw University Department of Computer Science Cuttack03 India Siksha 'O' Anusandhan Deemed to be University Department of Computer Application Bhubaneswar30 India Kalinga Institution of Industrial Technology Department of Computer Application Bhubaneswar24 India Imit Department of Computer Science & Engg Cuttack India

ISBN: (纸本)9798331530259

Rising global temperatures due to climate change have significantly increased the risk of heat-related illnesses, particularly heatstroke, in various regions. As global warming continues, it is crucial to understand patterns in heatstroke occurrences to predict and address future impacts. This study uses Machine Learning (ML) techniques to explore the connection between increasing temperatures and heatstroke incidents. ML models analyze extensive datasets containing meteorological data, health records, and geographical variables to uncover correlations between temperature spikes and heatstroke prevalence. The research incorporates supervised learning models such as linear Regression, lasso regression, ridge regression and voting regressor to predict high-risk periods and regions vulnerable to heatstroke. Additionally, time-series analysis and Prophet model is used to forecast future heatstroke cases by identifying climate data trends. These models are trained and validated using historical temperature and heatstroke fatality data from different regions. Preliminary findings indicate that extreme heatwaves, along with humidity and urbanization factors, significantly contribute to heatstroke occurrences. This study, leveraging ML, aims to improve the ability to predict and prevent heat-related health crises, offering valuable insights for public health planning, early-warning systems, and climate adaptation strategies to protect populations from the adverse effects of global warming. © 2025 IEEE.

关键词： Supervised learning

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Predictive Analytics for Future Air Pollution Levels Based on Population Growth 9th

Predictive Analytics for Future Air Pollution Levels Based o...

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9th International Conference on computer Science and Computational Intelligence, ICCSCI 2024

作者： Yeshe, Darel Wairooy, Irma Kartika Makalew, Brilly Andro Computer Science Department School of Computer Science Jakarta11480 Indonesia Mobile Application & Technology Program Computer Science Department School of Computer Science Jakarta11480 Indonesia

Air is very beneficial and crucial for every living creature on earth, hence it is very important to protect the air quality in order to avoid diseases. However, due to the increase in population, some human activities have been causing detrimental damage to the air quality. Some people have realized the potential impact of this problem and have done studies on predicting future air pollution. Some implemented machine learning models such as random forest regression, support vector machine, etc, while others have utilized deep learning models in their research.. This study will implement five different models, specifically linear regression, ridge regression, random forest regression, and multilayer perceptron regression. There will be two datasets used in this paper which will be merged and processed. There will be three key evaluation metrics being used in this paper namely root mean squared error, mean absolute error, and r-squared. The results from all of the models have concluded that more optimization and factors are needed in order to boost the final result of this study. © 2024 The Authors.

关键词： Adversarial machine learning

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BeautyShop Recommendation System 14

BeautyShop Recommendation System

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

作者： Saharkar, Anjali Sandeep Thakur, Pallavi Sardar Patel Institute of Technology Dept of Master of Computer Application Mumbai India

ISBN: (纸本)9798350335095

E-commerce will make up 20.4% of global retail sales by 2023.A promising future for online commerce is offered by India's rising Internet user population. With the exponential growth of e-commerce and the abundance of products available online, consumers often face the challenge of choosing the right products that meet their specific needs and preferences. Online shopping recommendation systems have emerged as powerful tools to address this issue by providing personalized product recommendations based on user data and *** the purpose of recommendation there are various techniques namely Collaborative filtering, Content-based filtering, Matrix Factorization, Association rule, Hybrid Recommender System, Demographic Filtering, Context Aware filtering, Deep-learning based recommender system, Popularity based filtering, Sequential recommendation etc. To recommend a right product to the user the preferred algorithm is Apriori. The Presented Recommendation system generates recommendation using python, flask framework and MySQL as backend. Client's happiness is positively impacted by the features of the product recommendation system, thus it's important to meet client demands based on a survey that prioritizes quality. © 2023 IEEE.

关键词： Recommender systems

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Designing a User-Friendly and Responsive AI based Image Generation Website and Performing Diversity Assessment of the Generated Images 4

Designing a User-Friendly and Responsive AI based Image Gene...

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4th International Conference on Electronics and Sustainable Communication Systems, ICESC 2023

作者： Kanakia, Harshil T. Nair, Suraj Prakkash Sardar Patel Institute of Technology Master of Computer Application Department Mumbai India

ISBN: (纸本)9798350300093

This research paper presents a website that leverages the power of the Image GPT engine for image generation. The website allows users to input a textual prompt and generate a corresponding image using Image GPT's natural language processing and machine learning capabilities. The paper details the architecture of the website, the Image GPT API integration, and the algorithms used for image generation. Additionally, we present the results and evaluate its quality and discuss potential applications of this technology in various industries such as advertising, art and design. We also discuss how the performance of image generation can be potentially improved. Overall, the website demonstrates the potential of combining natural language processing and machine learning for image generation and opens up new avenues for future research in this field. © 2023 IEEE.

关键词： Engines

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Overcoming Spatial Constraints in VR:A Survey of Redirected Walking Techniques

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Journal of computer Science & technology 2024年第4期39卷 841-870页

作者： Jia-Hong Liu Yang-Fu Ren Qi Wen Gan Kui Huang Fiona Xiao Yu Chen Er-Xia Luo Khang Yeu Tang Yue-Yao Fu Cheng-Wei Fan Sen-Zhe Xu Song-Hai Zhang Academy of Arts and Design Tsinghua UniversityBeijing 100084China Department of Computer Science and Technology Tsinghua UniversityBeijing 100084China College of Computer Technology and Application Qinghai UniversityXining 810016China Zhili College Tsinghua UniversityBeijing 100084China School of Computer Beijing Information Science and Technology UniversityBeijing 100192China Department of Physics Tsinghua UniversityBeijing 100084China School of Computer and Communication Engineering University of Science and Technology BeijingBeijing 100083China

As the virtual reality(VR)technology strives to provide immersive and natural user experiences,the challenge of aligning vast virtual environments with limited physical spaces remains *** survey comprehensively explores the advancements in redirected walking(RDW)techniques aimed at overcoming spatial constraints in *** addresses this by subtly manipulating users’physical movements to allow for seamless navigation within constrained *** survey delves into gain perception mechanisms,detailing how slight discrepancies between virtual and real-world movements can be utilized without user awareness,thus extending the effective navigable *** RDW control algorithms for gain-based RDW are analyzed,highlighting their implementation and effectiveness in maintaining immersion and minimizing perceptual ***,novel methods extending beyond traditional gain-based techniques are discussed,showcasing innovative approaches that further refine VR *** practical implications of RDW in enhancing safety and reducing physical collisions in VR environments are underscored,alongside its potential to improve user experience by aligning virtual exploration more closely with natural human behavior *** a thorough review of existing literature and recent advancements,this survey provides a systematic understanding for researchers,developers,and industry *** underscores the importance of RDW in the future of VR,emphasizing RDW's role in making VR more accessible and practical across various applications,from education and training to therapy and *** paper concludes with a forward-looking perspective on the continued evolution and potential of RDW in revolutionizing virtual reality experiences.

关键词： virtual reality(VR) redirected walking(RDW) redirection gain perception

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Fusion of IoT and Blockchain (BIoT): A Novel Architecture for Smart Agriculture 8th

Fusion of IoT and Blockchain (BIoT): A Novel Architecture...

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8th International Conference on Internet of Things and Connected Technologies, ICIoTCT 2023

作者： Das, Priyanka Ray, Sangram Dasgupta, Mou Govil, Mahesh Chandra Department of Computer Science and Engineering National Institute of Technology Sikkim Sikkim Ravangla737139 India Department of Computer Application National Institute of Technology Raipur Chhattisgarh Raipur492010 India

ISBN: (纸本)9789819757855

Internet of Things (IoT) plays a crucial role in automating systems, offering effectual and reliable services with minimal human intervention. To be precise, IoT-enabled smart agriculture is a vital factor in the modern digital world which ensures to provide various functionalities such as—water level monitoring, temperature monitoring, moisture sensing, and plant growth tracking. These functionalities of smart agriculture significantly simplify the work of farmers. But on the contrary, several security and privacy-related concerns were identified such as critical agriculture field data storage and management. Therefore, the evolution of integration of the IoT and blockchain (BIoT) came into the limelight. BIoT-based smart agriculture can enhance efficiency, sustainability, etc., leading to increased productivity, improved resource management, and secure data storing management in a decentralized manner. In this paper, we propose an architecture for a smart agriculture ecosystem based on the fusion of both IoT and blockchain. Primarily, our proposed architecture consists of three stages, PEGASIS-based chain construction phase, mutual authentication and key agreement phase, and blockchain-based data storage in base-station phase. Finally, this paper highlights on security analysis of our proposed architecture and found that it is well-secured against broadly known security attacks. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Smart agriculture

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