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Study of Disease Identification in Pomegranate Using Leaf Detection Technique 4

Study of Disease Identification in Pomegranate Using Leaf De...

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4th IEEE international conference on Emerging Smart computing and Informatics, ESCI 2022

作者： Wakhare, Prashant B. Neduncheliyan, S. thakur, Kshitij R. Computer Science and Engineering Bharath Institute of Higher Education and Research Tamil Nadu India All India Shri Shivaji Memorial Society's Institute of Information Technology Department of Computer Engineering Maharashtra India

ISBN: (纸本)9781665400732

Internet of things (IoT) and Artificial Intelligence (AI) powered by 5G has opened new doors of technology and innovations in the field of agriculture. there is a vast scope of application and development of the above mentioned technologies to detect any shortcomings that may lead to heavy losses for farmer. this paper surveys the use of Internet of things (IoT) to implement leaf detection on pomegranate plant. It also surveys the use of Artificial Intelligence (AI) to analyze the data collected from leaf detection and identify the diseases that may affect the pomegranate yield. © 2022 IEEE.

关键词： Internet of things

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Method and system of power load classification and decomposition based on deep learning 4

Method and system of power load classification and decomposi...

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4th international conference on Smart Grid and Energy Engineering, SGEE 2023

作者： Sun, Hao Yuan, Hongtai Geng, Yudong Chen, Jing Zhang, Chuanfu Li, Wen Qilu University of Technology Shandong Academy of Sciences Key Laboratory of Computing Power Network and Information Security Ministry of Education Shandong Computer Science Center National Supercomputer Center in Jinan Jinan China Shandong Fundamental Research Center for Computer Science Shandong Provincial Key Laboratory of Computer Networks Jinan China

ISBN: (纸本)9798350359619

this paper introduces a system for the classification and decomposition of electrical loads, addressing the shortcomings of current non-intrusive load decomposition methods that are prone to errors. We propose a method that first classifies electrical loads and then performs decomposition, along with the corresponding system workflow. Initially, we collect household electricity consumption data using a proprietary load collection device developed by the company, constructing an electrical load dataset. Subsequently, we train classification and decomposition methods using this dataset, conducting comparative experiments with various methods to select the most effective one. Based on the trained electrical load classification and decomposition models, we develop an electrical load inference program. the key implementation lies in applying the electrical load classification and decomposition inference program to edge devices. Leveraging the cloud server hosting a backend web service for the mobile app, we interact with users through the app, achieving precise decomposition and monitoring of electrical loads. Integrating edge computing and cloud computing, coupled with a mobile app serving as the interaction platform, this paper presents a high-precision, simplified, and highly scalable solution for electrical load analysis and management. In experimental comparisons, we find that using the Gated Recurrent Unit (GRU) method from deep learning and the Sequence-to-Point Neural Network (Seq2point) method outperform other methods in classification and decomposition, significantly improving the accuracy of electrical load classification. therefore, we select the GRU method and Seq2Point method as the core techniques for the electrical load classification and decomposition system. this system not only demonstrates significant advantages in performance but also possesses high accuracy, model simplification, and scalability, providing an efficient and reliable solution for elec

关键词： Edge computing

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Document information similarity calculation method based on multi-feature fusion 4

Document information similarity calculation method based on ...

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4th international Academic Exchange conference on science and Technology Innovation, IAECST 2022

作者： Li, Wen-Qing Tian, Hao-Yi Li, Yong Electric Power Company Electric Power Science Research Institute of Shanghai Municipal Shanghai China Shanghai Jiulong Enterprise Management Consulting Co. Ltd Shanghai China

ISBN: (纸本)9798350320008

In the era of Big data, the Internet constantly penetrates people's lives, work and research. People are generating new data all the time. In order to separate new data from a large amount of data and get satisfactory results, search engines came into being. One of the essential branches of research in natural language is text similarity computing. this paper proposes a weight-based optimisation algorithm based on a multi-feature fusion algorithm. Using a non-uniform partitioning method, the granularity of the feature fingerprints is varied, resulting in a wide variation of accuracy. the most important feature is the flexible and fast resizing of the partition number to change the vector value. It has been demonstrated experimentally that the method in this paper can save partitioning time. the method in this paper can solve the problem of many vector dimensions in word frequency statistics methods and can better measure the similarity between texts. the method can be widely used in various query scenarios, such as searching taxi maps, orders and routes. © 2022 IEEE.

关键词： Vector spaces

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A Lightweight Authentication Scheme and Security Key Establishment for Internet of Medical things 4th

A Lightweight Authentication Scheme and Security Key Establi...

引用

4th international conference on computing, Communications, and Cyber-Security, IC4S 2022

作者： Nissar, Gousia Khan, Riaz A. Mushtaq, Saba Lone, Sajaad A. Moon, A.H. Depaertment of Computer Science and Engineering Islamic University of Science and Technology Kashmir192122 India Department of IT&SS University of Kashmir Kashmir190006 India

ISBN: (纸本)9789819914784

the Internet of things (IoT) in health care has remained elusive, mostly because of the threat of unwanted access to protected health care because of a weak wireless channel. Furthermore, administrators cannot employ sophisticated and resource-intensive security measures on IoT devices due to their limited computing and storage capabilities. In addition to this, the ad-hoc nature of such networks makes them even more vulnerable to security threats. To address these issues, our research proposes an authentication protocol that uses a minimally intrusive data security approach for communicating data in real time. In the proposal, a secure authentication and key agreement mechanism for the Internet of Medical things (IoMT) is presented. the proposed protocol employs zero knowledge proof (ZKP), Ayushman Bharat Health Account (ABHA) number, biometrics, symmetric cryptography, message digest, and other techniques to achieve the protocol’s goal with low storage, computing, and communication costs. the proposed protocol is evaluated using the Automated Validation of Internet Security Protocols and Applications (AVISPA) tool, and it is observed that it protects data anonymity, confidentiality, integrity, and safety from major cyber threats. © 2023, the Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Internet of things

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data-driven modeling method based on hybrid neural network 4

Data-driven modeling method based on hybrid neural network

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4th international Academic Exchange conference on science and Technology Innovation, IAECST 2022

作者： Qiu, Xiaolin Gan, Zhikai Qiu, Cheng Zhang, Wenzhan Liao, Dan Nanchang Institute of Technology Jiangxi330044 China

ISBN: (纸本)9798350320008

In recent years, with the rapid progress of computer computing power and the easier acquisition and storage of data, data-driven non-parametric models have been applied by more and more scholars in the study of option pricing, which includes neural network models. the emergence of neural network option pricing model undoubtedly promotes the development of option pricing theory, but most of the existing neural network option pricing models are based on the fully connected neural network framework, and only innovate in the selection of input variables and output variables, and few studies innovate in the neural network framework. this paper discusses the photovoltaic module output characteristics of hybrid neural network, and proposes some solutions to its problems, aiming to speed up the progress of photovoltaic module output characteristics of hybrid neural network. Photovoltaic power generation technology has certain advantages in sustainability, energy conversion efficiency, technology maturity and other aspects, and has become one of the very favored clean energy sources. As China takes energy Internet construction as a long-term strategic goal, photovoltaic power generation technology will present great potential in the future energy system. © 2022 IEEE.

关键词： Big data

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Digital Transformation and Smart Sensors 4

Digital Transformation and Smart Sensors

引用

4th international conference on Advances in computing, Communication Control and Networking, ICAC3N 2022

作者： Saini, Kavita Chabaque, Aakash Kumar, Abhishek Kumar, Aadarsh Galgotias University School of Computer Science and Engineering Delhi NCR India Kite Group of Institutions Meerut India

ISBN: (纸本)9781665474368

the "new economy"is approaching, and it will necessitate new rules, adjustments, and ways of thinking. A step toward the digital economy is digital ***-driven work practices are at the heart of digital transformation. Sensors provide real-time data, automating manual data collection. there is no digital transformation without sensors. Any number of variables can be transmitted by a sensor using digital communication, Digital signals must be supported by *** Technologies has been powered by an electronic circuit that operates at a very high speed and low cost. Due to different method that are novel Processing method and very Advanced Manufacturing Technology which make it low *** Availability and the very wide range of application sensors of low cost are in very high *** sensors are being develop to met all the criteria of designer's need for simple design. now a days smart Sensors are becoming the integrals parts of the system performing functions ,that previous sensors could not able to performed or were not that economically variable. the presence of digital processing power has a liberating effect on a sensors design. © 2022 IEEE.

关键词： Costs

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Design of wirelessly charged temperature and humidity monitoring system for large-scale facilities 4

Design of wirelessly charged temperature and humidity monito...

引用

4th IEEE international conference on Power, Intelligent computing and Systems, ICPICS 2022

作者： Wei, Yue Lei, Yang Ruitong, Wei School of Computer Science and Technology Dongguan University of Technology Dongguan China School of Electronic Engineering and Intelligence Dongguan University of Technology Dongguan China

ISBN: (数字)9781665467735

ISBN: (纸本)9781665467735

In a large-scale scientific facility experiment, it is crucial to monitor the temperature and humidity around the plexiglass when it is polymerized. the monitoring system is equipped with a lithium-ion battery, which is wirelessly recharged when the power is too low and can work continuously for 175 days in a fully charged state. Based on these, a wireless temperature and humidity monitoring system with wireless charging is designed in this paper. the system mainly includes a 433Mhz wireless communication module, a wireless charging module, and a temperature and humidity collection module. the temperature and humidity collection module collects the data and sends it to the host computer through the 433Mhz wireless communication module to realize real-time monitoring. After testing, the system can work normally in a fully charged state and ensure no data loss to meet the needs of large-scale scientific facility experiments. © 2022 IEEE.

关键词： Lithium-ion batteries

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Design and Research of Smart Agriculture Fine Planting System Based on YOLOv3 Algorithm 4

Design and Research of Smart Agriculture Fine Planting Syste...

引用

4th international conference on Industrial IoT, Big data and Supply Chain, IIoTBDSC 2023

作者： Zhu, Shaoping Zhu, Leping Zeng, Yan Yang, Yu Liu, Yujie Guan, Jingxin Yan, Yupei Xiao, Yongliang Department of Artificial Intelligence Zhuhai City Polytechnic 519090 China Department of Sports and Health Guangdong Polytechnic of Science and Technology Zhuhai519090 China Department of Information Management Hunan University of Finance and Economics 410205 China

ISBN: (纸本)9798350341690

With the application of artificial intelligence and big data technology in the field of agricultural production, modern information technology means such as the Internet of things, big data and cloud computing are used to deeply integrate with agriculture. An intelligent agricultural fine planting system based onYOLOv3 algorithmis researched and designed, in order to realize theinformation perception and intelligent control in the agricultural production. In order to improve the intelligent management level of agricultural fine planting, it has good feasibility, and has important significance in promoting and serving Chinese agricultural modernization and national economic development. © 2023 IEEE.

关键词： Big data

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Research on Comprehensive Early Warning and Monitoring System of Satellite Remote Sensing Positioning for UHV Transmission Channel 4

Research on Comprehensive Early Warning and Monitoring Syste...

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4th IEEE international conference on Power, Intelligent computing and Systems, ICPICS 2022

作者： Shen, Jianliang Yin, Zhimin Lu, Liping Dai, Jianhua Liu, Pingping Miao, Chengguang State Grid Huzhou Power Supply Zhejiang313000 China EarthView Image Co. Ltd Beijing100101 China

ISBN: (数字)9781665467735

ISBN: (纸本)9781665467735

Real-time online monitoring of the safety status of UHV transmission towers is an important means to ensure the security of the national power grid. the complex environment of strong interference and weak wireless signals in UHV transmission towers puts forward higher requirements for reliable data transmission. this paper studies the theory and method of early warning of geological disasters in the construction of ultra-high AC power transmission and transformation based on Chinese Baidoo satellite navigation system and high-resolution remote sensing technology. the combination of multiple factors such as climate and environment has formed a set of geological disaster early warning and prevention mechanism for UHV AC power transmission and transformation projects, and developed a mobile APP early warning information release function. the construction practice of UHV AC power transmission and transformation project proves that the theoretical and technical methods of this paper are scientific and practical. © 2022 IEEE.

关键词： data handling

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1st international Workshop on Ethical and Philosophical Issues in Medical Imaging, EPIMI 2022, the 12th international WorksEthical and Philosophical Issues in Medical Imaginghop on Multimodal Learning and Fusion Across Scales for Clinical Decision Support, ML-cds 2022, and the 2nd international Workshop on Topological data Analysis for Biomedical Imaging, TDA4BiomedicalImaging 2022, held in conjunction with the 25th international conference on Medical Image computing and Computer-Assisted Intervention, MICCAI 2022

1st International Workshop on Ethical and Philosophical Issu...

引用

1st international Workshop on Ethical and Philosophical Issues in Medical Imaging, EPIMI 2022, the 12th international Workshop on Multimodal Learning and Fusion Across Scales for Clinical Decision Support, ML-cds 2022, and the 2nd international Workshop on Topological data Analysis for Biomedical Imaging, TDA4BiomedicalImaging 2022, held in conjunction with the 25th international conference on Medical Image computing and Computer-Assisted Intervention, MICCAI 2022

ISBN: (纸本)9783031232220

the proceedings contain 11 papers. the special focus in this conference is on Ethical and Philosophical Issues in Medical Imaging. the topics include: Fetal Cortex Segmentation with Topology and thickness Loss Constraints;disproportionate Subgroup Impacts and Other Challenges of Fairness in Artificial Intelligence for Medical Image Analysis;separable vs. End-to-End Learning: A Critical Examination of Learning Paradigms;a 35-Year Longitudinal Analysis of Dermatology Patient Behavior Across Economic and Cultural Manifestations in Tunisia, and the Impact of Digital Tools;user-Centered Design for Surgical Innovations: A Ventriculostomy Case Study;visually Aware Metadata-Guided Supervision for Improved Skin Lesion Classification Using Deep Learning;predicting Osteoarthritis of the Temporomandibular Joint Using Random Forest with Privileged Information;hybrid Network Based on Cross-Modal Feature Fusion for Diagnosis of Alzheimer’s Disease;future Unruptured Intracranial Aneurysm Growth Prediction Using Mesh Convolutional Neural Networks.

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