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

作者： Sheril, S. More, Priyanka D. Mishra, Rahul Das, Neeraj Ramachandran, T. Ahmed, Zahid Prince Shri Venkateshwara Padmavathy Engineering College Department of Mechanical Engineering Chennai127 India Vishwakarma Institute of Information Technology Department of Computer Engineering Pune India Centre of Interdisciplinary Research in Business and Technology Chitkara University Institute of Engineering and Technology Chitkara University Punjab India Maharishi School of Engineering and Technology Maharishi University of Information Technology Uttar Pradesh India Faculty of Engineering and Technology Department of Mechanical Engineering Karnataka Bangalore India Vivekananda Global University Department of Computer Science & Application Jaipur India

ISBN: (纸本)9798350319125

This examines examines the cutting-edge state of security protocols for wi-fi sensor networks within the mobile communications area. We examine the performance of present protection protocols for wi-fi sensor networks that specialize in their effectiveness, strength-efficiency, and scalability. We then endorse an advanced protection protocol which can higher cope with the security challenges of wi-fi sensor networks. Our new protection protocol incorporates cryptographic algorithms tailored for the unique necessities of wi-fi sensor networks, as well as key trade mechanisms that offer more desirable scalability and energy-performance. We evaluate our proposed security protocol, and examine its tradeoffs in evaluation with existing security protocols. Our consequences display that the proposed protocol is extra comfortable, gives higher scalability, and achieves more electricity-efficiency. We also check out the impact of different routing protocols on the security of wireless sensor networks in cellular communications and analyze how they may be tormented by exclusive security protocols. Our findings advise that a hybrid of two current routing protocols provides suitable security for wireless sensor networks. © 2023 IEEE.

关键词： Networks Protocols Scalability Security Wireless

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Review of Water Quality Prediction Methods 8th

Review of Water Quality Prediction Methods

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8th International Conference on Water Resource and Environment, WRE 2022

作者： Chen, Zhen Liu, Limin Wang, Yongsheng Gao, Jing College of Data Science and Application Inner Mongolia University of Technology Hohhot China Inner Mongolia Autonomous Region Software Service Engineering Technology Research Center Based on Big Data Inner Mongolia Autonomous Region Hohhot China School of Computer and Information Engineering Inner Mongolia Agricultural University Hohhot China

ISBN: (纸本)9789819919185

Water quality prediction plays a crucial role in environmental monitoring, ecosystem sustainability, and aquaculture, and it plays an important role in both economic and ecological benefits. For many years, researchers have been working on how to improve the accuracy of water quality prediction. However, at this stage, with the increase in external climate change, external noise, precipitation, and many other uncertainties, water quality prediction is facing the problem of insufficient accuracy. This paper analyzes the research methods of water quality prediction at home and abroad in recent years and summarizes the introduction through two aspects: mechanical water quality prediction methods and non-mechanical water quality prediction methods. Firstly, the mechanism of water quality prediction method is introduced, which uses various hydrological data information such as initial water head, bottom slope, hydraulic radius, etc. to predict water quality;Secondly, it introduces the non-mechanical water quality prediction method that uses historical water quality index data to analyze and mine to predict water quality. Finally, after introducing the existing prediction methods, the development direction of water quality prediction is analyzed and summarized. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Water quality

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Intelligent Time Management Recommendations Using Bayesian Optimization

Intelligent Time Management Recommendations Using Bayesian O...

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2024 IEEE International Conference on Communication, Computing and Signal Processing, IICCCS 2024

作者： Chandramowleeswaran, G. Sindhu, M. Alabdeli, Haider Mishra, Anshu Vinod, Priya Kaur, Harmeet Vel Tech Rangarajan Dr. Sagunthala R&d Institute of Science and Technology Department of Commerce and Business Administration Chennai600062 India Prince Shri Venkateshwara Padmavathy Engineering College Chennai India The Islamic University College Of Technical Engineering Department Of Computers Techniques Engineering Najaf Iraq The Islamic University Of Al Diwaniyah College Of Technical Engineering Department Of Computers Techniques Engineering Al Diwaniyah Iraq Ies University Ies Institute of Technology and Management Department of Computer Science & Engineering M.P. Bhopal India Christ University School Of Business And Management India Chandigarh Group of Colleges Chandigarh Engineering College Department of Computer Application Punjab Jhanjeri Mohali140307 India

ISBN: (纸本)9798350390759

This paper focuses on the improvement of the intelligent time management system which employ Bayesian optimization for suggesting time management plans for each particular person. In this sense, through historical data of input-output patterns and users' preferences, the system aims at increasing productivity and user satisfaction. In the study, Gaussian Processes are used as the surrogate model in the Bayesian optimization so that the required evaluations by the algorithm to realize optimal scheduling methodologies are kept to a minimum. Implementation is done as a web application where users submit their tasks and get the recommended schedule instantly. Indicators like, the degree of task accomplishment, time, and scheduling compliance, and probably the users' satisfaction suggest that system helped enhance time management results. Lack of feedback from the users is removed through questionnaire that reveals the simplicity of the system and the quality of its recommended times, thereby supporting the idea of Bayesian optimization as a game changer in the management of time. This research significance points to the need for maintaining efficient and individualized approaches to time management strategies and agrees with others' findings, which suggest that this is an area ample fiction research needs to acknowledge and pursue. © 2024 IEEE.

关键词： Scheduling algorithms

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Analyzing the Potential Benefits of Data Mining for Customer Relationship Management 1

Analyzing the Potential Benefits of Data Mining for Customer...

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1st IEEE International Conference on Emerging Research in Computational science, ICERCS 2023

作者： Aravind, A.R. Katikar, Shilpa M. Acharjya, Kalyan Ezhilarasan, G. Yadav, Surendra Mishra, Abhinav Prince Shri Venkateshwara Padmavathy Engineering College Department of Electronics and Communication Engineering Chennai127 India Vishwakarma Institute of Information Technology Department of Computer Engineering Pune India Maharishi University of Information Technology Maharishi School of Engineering and Technology Uttar Pradesh India Faculty of Engineering and Technology Department of Electrical and Electronics Engineering Karnataka Bangalore India Vivekananda Global University Department of Computer Science & Application Jaipur India Chitkara University Institute of Engineering and Technology Chitkara University Centre of Interdisciplinary Research in Business and Technology Punjab India

ISBN: (纸本)9798350359756

Data mining for client dating control (CRM) is figuring out patterns and traits in customer records to inform selections about product imparting, pricing, sales, advertising and marketing, and different consumer techniques. Companies can use automated records mining strategies to outline client profiles, section clients, and better recognize purchasing conduct. Through knowledge of client conduct, corporations can target their customers greater correctly, grow revenue, and enhance customer satisfaction and loyalty. The advantages of fact mining for CRM are several, which include spotting purchaser needs and options, improving marketing effectiveness, increasing client acquisition, and boosting sales. Additionally, records mining can enable an employer to perceive lost sales possibilities, lessen operational costs, and optimize customer retention efforts. Essential data mining allows CRM-targeted organizations to recognize clients higher, optimize operations, and broaden strategically centered initiatives to improve consumer loyalty. © 2023 IEEE.

关键词： Data mining

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Implementing Long Short-Term Memory Network for Enhancing Hyper Spectral Time Series Modeling

Implementing Long Short-Term Memory Network for Enhancing Hy...

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2023 IEEE International Conference on Paradigm Shift in Information Technologies with Innovative applications in Global Scenario, ICPSITIAGS 2023

作者： Eti, Muktha Shekhawat, Jyoti Nagpal, Manish Srisainath, R. Chavhan, Pranali G. Yadav, Rakesh Kumar Faculty of Engineering and Technology Department of Electrical and Electronics Engineering Karnataka Bangalore India Vivekananda Global University Department of Computer Science & Application 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 Mechanical Engineering Chennai127 India Vishwakarma Institute of Information Technology Department of Computer Engineering Pune India Maharishi School of Engineering and Technology Maharishi University of Information Technology Uttar Pradesh India

ISBN: (纸本)9798350329773

This take a look at proposes using lengthy quick-time period reminiscence (LSTM) networks as a tool for enhancing the accuracy of Hyper Spectral Time series (HSTS) fashions. via the use of this recurrent neural community approach, the model can account for the temporal dating among the hyper spectral spectral time collection variables. additionally, with this utility, the version can research from the spectral time series over a longer time period. This study examined the efficacy of the carried out LSTM network with the aid of comparing the results to the Hyper Spectral Time collection model performance performed prior to using this method. The effects recommend that the addition of the LSTM network accelerated the accuracy of the version through about 25%. This generation has the potential to substantially beautify the accuracy of temporal records inside the discipline of faraway sensing records analysis. In conclusion, this examine indicates that LSTM networks are a promising tool for boosting the predictive energy of HSTS models. long quick-term memory Networks (LSTM) are a type of Recurrent Neural Networks (RNNs) that have been applied to many duties in synthetic Intelligence including language information, herbal language processing, and image processing. more recently, they had been used to enhance hyper spectral time series modeling. The shape of LSTM permits it cope with and keep lengthy-term sequences of statistics, making it particularly suitable for modeling hyper-spectral time series. At whenever step, an LSTM community takes as input a vector representing the hyper-spectral values, and outputs a vector which represents the intermediate representation of the time series. these intermediate representations are then used to generate the output at every next time step. LSTM networks are for his or her ability to capture lengthy-time period dependencies, and because of their structure, they are additionally nicely-appropriate to hyper-spectral time collecti

关键词： Time series

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Timeliness-Selective Incentive Federated Crowdsourcing

Timeliness-Selective Incentive Federated Crowdsourcing

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IEEE International Conference on Web Services (ICWS)

作者： Xiaoqian Jiang Haiyang Diao Cangqi Zhou Jing Zhang School of Cyber Science and Engineering Southeast University China Siemens (China) Co. Ltd. School of Computer Science and Engineering Nanjing University of Science and Technology China Engineering Research Center of Blockchain Application Supervision and Management (Southeast University) Ministry of Education China

ISBN: (数字)9798350368550

ISBN: (纸本)9798350368567

Crowdsourcing offers an efficient means of gathering labeled data and training machine learning models. However, the exposure of crowd workers to potential privacy breaches during data collection diminishes their willingness to participate. This paper proposes TsIFedCrowd, a novel incentive mechanism within the federated learning paradigm, aimed at mitigating privacy risks for crowd workers while achieving high-quality crowdsourced data and learning models at minimal expense. TsIFedCrowd enables clients to retain privacy-sensitive data locally, requiring only the upload of trained models to the server, which aggregates them into a global model. By modeling the federated crowdsourcing process as a two-stage Stackelberg game, TsIFedCrowd incentivizes workers to complete tasks with heightened quality and efficiency. It also provides a timeliness selection mechanism, which makes TsIFedCrowd suitable for both real-time crowdsourcing, where the generation time of task results (data) needs to meet the established requirements of the application, and non-real-time crowdsourcing. TsIFedCrowd mandates clients to complete federated crowdsourcing tasks while maximizing utility for both clients and the server, achieved through Nash equilibrium resolution. TsIFedCrowd is also extended to the multiple heterogeneous federated crowdsourcing scenario. Extensive experiments demonstrate TsIFedCrowd’s effectiveness in ensuring incentive fairness and universality, accelerating convergence speed, and budget savings. Real-world crowdsourcing tasks further validate its efficacy.

关键词： Crowdsourcing Training Web services Scalability Games Nash equilibrium Privacy breach Data models Real-time systems Servers

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A portable,low-cost lactate measurement system

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Journal of Measurement science and Instrumentation 2025年第1期16卷 37-46页

作者： WANG Qingqing PAN Yu YU Chuanxin WANG Yanyan ZHANG Kaikai LIU Sheng School of Computer Science and Technology Huaibei Normal UniversityHuaibei 235000China Anhui Provincial Engineering Research Center of Cognitive Behavioral Intelligent Computing and Application Huaibei 235000China

Lactate,as a metabolite,plays a significant role in a number of fields,including medical diagnostics,exercise physiology and food *** methods for lactate measurement often involve expensive and cumbersome *** study developed a portable and low-cost lactate measurement system,including independently detectable hardware circuits and user-friendly embedded software,computer,and smartphone *** experiment verified that the relative error of the detection current in the device circuit was less than 1%.The electrochemical performance was measured by comparing the[Fe(CN)_(6)]^(3−)/[Fe(CN)_(6)]^(4−)solution with the desktop electrochemical workstation CHI660E,and a nearly consistent chronoamperometry(CA)curve was *** modified lactate sensors were used for CA testing of *** the concentration range of 0.1 mmol·L^(−1)to 20 mmol·L^(−1),there was a good linear relationship between lactate concentration and steady-state current,with a correlation coefficient(R2)greater than 0.99 and good repeatability,demonstrating the reliability of the developed *** lactate measurement system developed in this study not only provides excellent detection performance and reliability,but also achieves portability and low cost,providing a new solution for lactate measurement.

关键词： lactate measurement portable device embedded development lactate sensor electrochemical analysis

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Probing bundle-wise abnormalities in patients infected with human immunodeficiency virus using fixel-based analysis:new insights into neurocognitive impairments

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Chinese Medical Journal 2023年第18期136卷 2178-2186页

作者： Jing Zhao Bin Jing Jiaojiao Liu Feng Chen Ye Wu Hongjun Li School of Biological Science and Medical Engineering Beihang UniversityBeijing 100069China Department of Radiology Beijing Youan HospitalCapital Medical UniversityBeijing 100069China School of Biomedical Engineering Capital Medical UniversityBeijing 100069China Beijing Key Laboratory of Fundamental Research on Biomechanics in Clinical Application School of Biomedical EngineeringCapital Medical UniversityBeijing 100069China School of Computer Science and Engineering Nanjing University of Science and TechnologyNanjingJiangsu 210094China

Background:Changes in white matter(WM)underlie the neurocognitive damages induced by a human immunodeficiency virus(HIV)*** study aimed to examine using a bundle-associated fixel-based analysis(FBA)pipeline for investigating the microstructural and macrostructural alterations in the WM of the brain of HIV ***:This study collected 93 HIV infected patients and 45 age/education/handedness matched healthy controls(HCs)at the Beijing Youan Hospital between January 1,2016 and December 30,*** HIV patients underwent neurocognitive evaluation and laboratory testing followed by magnetic resonance imaging(MRI)*** order to detect the bundle-wise WM abnormalities accurately,a specific WM bundle template with 56 tracts of interest was firstly generated by an automated fiber clustering method using a subset of ***-based analysis was used to investigate bundle-wise differences between HIV patients and HCs in three perspectives:fiber density(FD),fiber cross-section(FC),and fiber density and cross-section(FDC).The between-group differences were detected by a two-sample t-test with the false discovery rate(FDR)correction(P<0.05).Furthermore,the covarying relationship in FD,FC and FDC between any pair of bundles was also accessed by the constructed covariance networks,which was subsequently compared between HIV and HCs via permutation *** correlations between abnormal WM metrics and the cognitive functions of HIV patients were explored via partial correlation analysis after controlling age and ***:Among FD,FC and FDC,FD was the only metric that showed significant bundle-wise alterations in HIV patients compared to *** FD values were observed in the bilateral fronto pontine tract,corona radiata frontal,left arcuate fasciculus,left corona radiata parietal,left superior longitudinal fasciculus III,and right superficial frontal parietal(SFP)(all FDR P<0.05).In bundle-wise covariance network,HIV patients displayed

关键词： Human immunodeficiency virus Diffusion tensor imaging White matter bundle Fixel-based analysis Covariance network

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Mobile Wireless Sensor Networks And Hierarchical Routing Protocols: A Review 1

Mobile Wireless Sensor Networks And Hierarchical Routing Pro...

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1st International Conference on Computing, Communication and Green engineering, CCGE 2021

作者： Sharma, Abha Das, Prasenjit Patel, R B Chitkara University School of Engineering and Technology Chitkara University Himachal Pradesh India School of Computer Application Chitkara University Himachal Pradesh India Chandigarh College of Engineering and Technology Department of Computer Science and Engineering Chandigarh India

ISBN: (纸本)9781665415095

A lot of progression has been observed in Mobile Wireless Sensor Network (MWSN) in modern era due to its applications in vicinity. Recent trends show how it is very challenging to retain stability in the network in terms of delay, packet delivery ratio and stability. Nodes mobilization is vital in stabilizing the network, and various routing protocols are used to maintain connectivity, throughput, coverage, minimal energy cost. As a matter of fact it is really demanding that a single routing protocol will be able to cover up for numerous circumstances altogether. Several routing protocols have been worked upon for a variety of network scenarios. The categorization of routing protocols is countered on the basis of type of network structure, information status, network efficiency and mobility. In this paper Hierarchal routing protocols classification is presented which can help enhance network life and save energy consumption. © 2021 IEEE.

关键词： Routing protocols

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Phenotyping of Salvia miltiorrhiza Roots Reveals Associations between Root Traits and Bioactive Components

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Plant Phenomics 2023年第4期5卷 746-756页

作者： Junfeng Chen Yun Wang Peng Di Yulong Wu Shi Qiu Zongyou Lv Yuqi Qiao Yajing Li Jingfu Tan Weixu Chen Ma Yu Ping Wei Ying Xiao Wansheng Chen The SATCM Key Laboratory for New Resources&Quality Evaluation of Chinese Medicine Institute of Chinese Materia MedicaShanghai University of Traditional Chinese MedicineShanghai 201203China School of Medicine Shanghai UniversityShanghai 200444China State Local Joint Engineering Research Center of Ginseng Breeding and Application Jilin Agricultural UniversityChangchun 130118China School of Computer Science Sichuan Normal UniversityChengdu 610066China Shangyao Huayu(Linyi)Traditional Chinese Resources Co. Ltd.Linyi 276000China School of Life Science and Engineering Southwest University of Science and TechnologyMianyang 621010SichuanChina Sichuan Academy of Traditional Chinese Medicine Chengdu 610041China Department of Pharmacy Changzheng HospitalSecond Military Medical UniversityShanghai 200003China

Plant phenomics aims to perform high-throughput,rapid,and accurate measurement of plant traits,facilitating the identification of desirable traits and optimal genotypes for crop *** miltiorrhiza(Danshen)roots possess remarkable therapeutic effect on cardiovascular diseases,with huge market *** great advances have been made in metabolic studies of the bioactive metabolites,investigation for *** roots on other physiological aspects is ***,we developed a framework that utilizes image feature extraction software for in-depth phenotyping of *** *** employing multiple software programs,*** roots were described from 3 aspects:agronomic traits,anatomy traits,and root system *** K-means clustering based on the diameter ranges of each root branch,all roots were categorized into 3 groups,with primary root-associated key *** a proof of concept,we examined the phenotypic components in a series of randomly collected *** roots,demonstrating that the total surface of root was the best parameter for the biomass prediction with high linear regression correlation(R^(2)=0.8312),which was sufficient for subsequently estimating the production of bioactive metabolites without content *** study provides an important approach for further grading of medicinal materials and breeding practices.

关键词： Root utilize anatomy

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