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A Generalized Net Model of the Hybrid System for Diagnostics 15th

A Generalized Net Model of the Hybrid System for Diagnostics

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15th National conference of Operational and Systems Research, BOS 2018 and 17th international Workshop on Intuitionistic Fuzzy Sets and General Nets, IWIFSGN 2018

作者： Sotirova, Evdokia Bozov, Hristo Stoyanov, Valentin Popov, Ilia Faculty of Public Health and Health Care Prof. Asen Zlatarov University Burgas8010 Bulgaria Department of Anesthesiology Military Medical Academy Sofia Bulgaria Trakian University Stara Zagora Bulgaria

ISBN: (纸本)9783030470234

A generalized net model, which describes the diagnostic process of diseases using intelligent techniques is constructed in the paper. By analyzing the retrospective physiological, medical, individual-behavioral parameters of the patient we can find correlation to a particular disease, its progression and the likelihood of a response to treatment. The model can be used for monitoring and analysis of the process of assessment. © 2021, Springer Nature Switzerland AG.

关键词： data mining

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Bringing Energy into Utility-Privacy Tradeoff in IoT

Bringing Energy into Utility-Privacy Tradeoff in IoT

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international conference on Smart computing (SMARTCOMP)

作者： Henrique Pö tter Daniel Mossé Stephen Lee Computer Science Dept Univ of Pittsburgh

ISBN: (数字)9781665481526

ISBN: (纸本)9781665481533

With billions of the Internet of Things (IoT) world-wide, the proliferation of IoT technologies will increase the global energy footprint. To date, much of the focus has been on addressing privacy exposure with approaches that remove sensitive information and, at the same time, ensure that users still derive utility from the data. In this paper, we bring the energy aspects of privatizers into the modeling and analysis of utility-privacy (UP) tradeoffs in IoT. We present a framework that enables users to examine (a) the energy cost of privatizing data, (b) the effect on the utility of the data, and (c) the privacy achieved. We evaluate our model with audio and image data and show that we can reduce energy consumption while retaining the user's chosen UP tradeoff point.

关键词： Performance evaluation Privacy data privacy Energy consumption Analytical models Costs conferences

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A Brief Systematic Review of the Latest advances in IOT Platforms in Agriculture 7th

A Brief Systematic Review of the Latest Advances in IOT Plat...

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7th international conference on technologies and Innovation, CITI 2021

作者： Yerovi, Elke Delgado-Vera, Carlota Molina-Oleas, Wilson Ortega-Ponce, Laura School of Engineering in Computing and Informatics Faculty of Agrarian Sciences Agrarian University of Ecuador Av. 25 de Julio y Pio Jaramillo P.O. BOX 09-04-100 Guayaquil Ecuador

ISBN: (纸本)9783030882617

IoT or Internet of Things is an innovative advance in technology that helps interconnectivity between smart devices and machines helping to reduce human intervention. The use of IOT platforms, their architectures, network technologies and devices allow to improve the efficiency and productivity of any type of industry or mass production, this research is focused on one of the most important fields which is agriculture. The Internet of Things (IoT) is related to millions of applications and various devices throughout the world that communicate with each other and can exchange data and perform cooperative tasks without the intervention of human beings. Considering the aforementioned facts, relevant information is provided for farmers and researchers with a clear perspective of the technologies, devices, architecture, network and sensors used in IoT, in addition to the solutions that IoT provides in the agriculture field. © 2021, Springer Nature Switzerland AG.

关键词： Agriculture

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A Privacy-preserving Users' Power Load Prediction Method Based on Federated Learning

A Privacy-preserving Users' Power Load Prediction Method Bas...

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computing and Big data (ICCBD), international conference on

作者： Kangqian Huang Rui Zhou Xin Hu Dejun Xiang Yuhang Xie Jiaxin Lai Jiaqi Deng Yang Liu Guangdong Power Exchange Center Co. Ltd Guangzhou China School of Computer Science and Technology Harbin Institute of Technology Shenzhen Shenzhen China

The new power system deeply integrates new digital technologies such as cloud computing, big data, Internet of Things, mobile Internet, artificial intelligence, etc., which enables different levels of the electricity grid to develop cooperatively and improves the ability to allocate power grid resources. Particularly, the smart meters located on the electricity consumers' side play an important role in collecting and aggregating users' data. Based on the collected data, users' power load data can be analyzed, which can efficiently allocate power resources and avoid resource waste caused by the limitation of power resource storage. However, the data collected by smart meters involves a large amount of users' private information. How to efficiently and legally use these data for joint data mining without violating users' privacy has become a challenge. In this paper, a privacy-preserving users' power load prediction method based on federated learning technology and RSA-AES encryption system is proposed. Experimental results show that our method can predict users' power load with high accuracy while protecting users' privacy.

关键词： Training Privacy Federated learning Time series analysis Prediction methods Big data Smart meters

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Information Construction of University Labor Union Based on “Internet +”

Information Construction of University Labor Union Based on ...

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international conference on Business and Information Management

作者： Fang Pei School of Business Macau University of Science and Technology Macau China

In view of the problems and situations faced by the informatization construction of the trade union service system in colleges and universities during the “Internet +” era and against the background of the increasingly personalized demands of university staff groups, this paper conducts a deep analysis of how college and university trade unions in the “Internet +” era should use new Internet technologies to improve service functions and promote the construction of a service system. The analysis shows that the deep integration of the service system construction and “Internet +” is an irresistible trend. Cloud computing, big-data analysis, and other technologies should be used to provide technical support for the service system construction of labor unions in colleges and universities, improve their work efficiency, enhance the experience of college staff, and create a more civilized and harmonious campus.

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Exploring the Incremental Improvements of YOLOv7 over YOLOv5 for Character Recognition 14th

Exploring the Incremental Improvements of YOLOv7 over YOL...

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12th international Advanced computing conference, IACC 2022

作者： Boby, Alden Brown, Dane Connan, James Marias, Marc Department of Computer Science Rhodes University Grahamstown South Africa

ISBN: (纸本)9783031356438

Technological advances are being applied to aspects of life to improve quality of living and efficiency. This speaks specifically to automation, especially in the industry. The growing number of vehicles on the road has presented a need to monitor more vehicles than ever to enforce traffic rules. One way to identify a vehicle is through its licence plate, which contains a unique string of characters that make it identifiable within an external database. Detecting characters on a licence plate using an object detector has only recently been explored. This paper uses the latest versions of the YOLO object detector to perform character recognition on licence plate images. This paper expands upon existing object detection-based character recognition by investigating how improvements in the framework translate to licence plate character recognition accuracy compared to character recognition based on older architectures. Results from this paper indicate that the newer YOLO models have increased performance over older YOLO-based character recognition models such as CRNET. © 2023, Springer Nature Switzerland AG.

关键词： Object detection

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Breakthroughs in Cognitive Robots and AI Programming Underpinned by Discoveries in Intelligence science and Software science

Breakthroughs in Cognitive Robots and AI Programming Underpi...

引用

Frontiers of Robotics and Software Engineering (FRSE), international conference on

作者： Yingxu Wang International Institute of Cognitive Informatics and Cognitive Computing (I2CICC) Stanford Univ. (2008|2016) MIT (2012) UC Berkeley (2008) Oxford Univ. (1995|2018-’23) Tsinghua Univ. (2019-2022) Schulich School of Engineering and Hotchkiss Brain Institute University of Calgary 2500 University Drive NW Calgary Alberta Canada

Breakthroughs of basic research in Intelligence science (IS) [1], [2], [3], [4], [5], [6], [7], [8], [9], [10], [11], [12], [13], Cognitive computing (CC) [14], [15], [16], [17], [18], [19], [20], [21], [22], [22], [23], [24], [25], [26], and Cognitive Informatics (CI) [27], [28], [29], [30], [31], [32], [33], [34], [35], [36], [37], [38], have triggered the emergence of Cognitive Robots (CR) [39], [40], [41], [42], [43], [44], [45], [46], [47], [48], [49] towards software science (SS) [50], [51], [52], [53], [54], [55] and autonomous software engineering (SE) [56], [57], [58], [59], [60], [61], [62], [63], [64], [65], [66]. These latest advances have enabled the synergy of classical pre-programmed software engineering and pre-trained AI to an unprecedented platform of training-free machine intelligence generation mimicking human brains and Brain-Inspired Systems (BIS) [67], [68], [69], [70], [71], [72], [73], [74]. It is discovered in IS and CC in general, as well as in CR and SE in particular, that the target entities across these contemporary fields had already out of the denotational power of the classic mathematical domains of real (R) and binary (B) numbers [76]. This leads to the latest discovery that the basic unit of human knowledge as a hyperstructure [50] is a binary relation (bir) [74]. Therefore, a new framework of Intelligence Mathematics (IM) [75], [76], [77], [78], [79], [80], [81], [82], [83], [84], [85], [86], [87], [88], [89], [90], [91], [92], [93], [94], [95], [96], [97], [98], [99], [100] has been created for rigorously manipulating the cognitive entities in the brain and CRs spanning from formal concepts, semantics, knowledge, causalities, inferences, and consciousness by contemporary IMs for advancing both AI [1], [2], [3] and SE [56], [58]. This keynote lecture presents fundamental theories and ground-breaking technologies for designing and implementing cognitive robots based on AI Programming (AIP) [101], [102], [103], [104], and Autonomous

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IoT Research on Healthcare data to Control Illness of Oncology

IoT Research on Healthcare Data to Control Illness of Oncolo...

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Advance computing and Innovative technologies in Engineering (ICACITE), international conference on

作者： Dhiraj Kapila Prince Tehseen Ganai G.Sreenivasa Raju Lims Thomas Manisha Girase José Luis Arias Gonzales Assistant Professor Department of Computer Science &#x0026 Engineering Lovely Professional University Phagwara India Research Scholar Department of Information Technology Shri Jagdishprasad Jhabarmal Tibrewala University Rajasthan India Assistant Professor Department of Electronics and Communication Engineering Anurag University Assistant Professor Department of Social Work Vimala College (Autonomous) Thrissur Professor &#x0026 Head Dept. Of Microbiology K SK W Arts Science &#x0026 Commerce College CIDCO Nashik Maharashtra Departrnent of business University of British Columbia

Let us begin with the internet of things that empowers software programmers to start increasing prediction without being done with full to do so. With today's data availability, machine learning techniques are being developed to improve performance and maintenance prediction. Cancer, according the Health Organisation, is a global disease and the second leading cause of death worldwide. People with cancer have been identified as having an increased risk of dying in the current worldwide epidemic. With the disease's incidence growing decade after decade, the need for a continuously and then round surveillance apparatus has become crucial. A cancer monitoring system known as the internet of Things (IoT) has the potential to identify cancer-related indications in their initial phases, continue to monitor disease individuals, and screen someone who has been cured through post-treatment operations. This research presents a multi-layered architectural for an IoT-based disease monitoring and control system that might be utilised as a foundation for remotely cancer diagnosis and management.

关键词： Wireless communication Hospitals Surveillance Machine learning Maintenance engineering Oncology Software

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Securing Cyber Infrastructure of IoT-Based Networks using AI and ML

Securing Cyber Infrastructure of IoT-Based Networks using AI...

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international conference on Parallel Distributed and Grid computing (PDGC)

作者： Kapil Mehta Vandana Mohindru Sood Jashanpreet Singh Divyam Sharma Pratham Chhabra Department of Computer Science and Engineering Chandigarh Group of Colleges Mohali Punjab India Department of Computer Science and Engineering Chitkara University Institute of Engineering & Technology Chitkara University Punjab India

ISBN: (纸本)9781665454025

The Internet of Things (IoT) has emerged as one of the most advanced technologies, a subject of interest or field of study to researchers, and a sector with promising economic prospects. Numerous gadgets must be connected to one another and people in order for them to work. To handle its data interchange and processing, IoT needs a cloud computing environment. To achieve the automation process in many applications, artificial intelligence (AI) is required to evaluate the data stored in cloud infrastructure and make quick, accurate judgments. IoT paired with Machine Learning (ML) and Deep Learning (DL) models are used to increase the functionality of complicated applications. Cloud vulnerability and IoT device networking remain significant dangers, although AI is presently playing a significant role in enhancing traditional cybersecurity. Huge volumes of data are generated by the rapidly evolving IoT devices and networks in many different ways, which calls for careful authentication and security. One of the most efficacious methods for confronting cybersecurity breaches and encrypting data is artificial intelligence (AI). In this paper, we have investigated the effectiveness of Artificial Intelligence (AI), deep learning (DL) and machine learning (ML) techniques for IoT security. Additionally, this investigation sheds light on the AI roadmap for identifying risks based on attack types.

关键词： Deep learning Economics Cloud computing Automation Computational modeling Biological system modeling Authentication

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Minimization of energy consumption in MANET using optimized k-medoid PSO Clustering Model

Minimization of energy consumption in MANET using optimized ...

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Smart technologies in computing, Electrical and Electronics (ICSTCEE), international conference on

作者： Jebakumar Immanuel D Aby K Thomas Prasath B Kanchana M Narasimharaj V Anandhasilambarasan D Department of Computer Science and Engineering SNS College of Engineering Coimbatore India Department of Electronics and Communication Engineering Alliance College of Engineering and Design Alliance University Bangalore India Department of Computer Science and Engineering KPR Institute of Engineering and Technology Coimbatore India Department of Mechatronics Engineering Sri Krishna College of Engineering and Technology Coimbatore India Department of Computer Science and Engineering Karpagam Academy of Higher Education Coimbatore India

The (MANET) mobile ad hoc network connect with one another across wireless networks without relying on a central hub for network operations. In a decentralised network, individual mobile nodes take on more and more responsibility for the overall architecture of the system. Given that the routing and data transmission between nodes are impacted by the network's changing topology. The nodes' role as routers in the constant routing and transmission of data bundles is made necessary by this inherent volatility. The problem is that the mobile nodes, which rely on batteries instead of a constant power source, are the biggest consumers of energy in the network because they have to constantly recharge their power. The proposed work takes into account the delinquent of energy consumption in MANET, and finds that the optimization of energy constraint completely dominates the problem space. To begin, the MANET's mobile nodes are clustered using the suggested K-medoid clustering procedure, which helps to lessen the high cost of data routing in extremely large and dense networks. Modification of discrete particle swarm optimization procedure is a metaheuristic algorithm used to bargain the best possible value for the k-medoid algorithm, which is then used to develop a low-power protocol for exchanging information. packet delivery ratio, and throughput are the metrics used to compare different protocols. The results of the simulation analysis show that using this approach reduces the time needed for the method to run and boosts the nodes' energy efficiency.

关键词： Measurement Energy consumption Clustering algorithms Quality of service Routing Throughput Routing protocols

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