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29th International Scientific Conference Electronics, ET 2020

作者： Marinova, Ginka Todorova, Maya Technical University of Varna Faculty of Faculty of Computer Sciences and Automation Department of Computer Science and Engineering Department of Software and Internet Technologies 1 Studentska str Varna9010 Bulgaria

ISBN: (纸本)9781728174266

The subject of analysis and research is data in the field of medical oncology through machine learning methods. The types of classification in machine learning are presented, and three methods are described-K-Nearest Neighbors, Naive Bayes Classifier, Support Vector Machines. Two classification tasks in the field of medicine have been formulated, implemented, and researched. Classifiers are created and trained with the methods KNN, SVM, and NBC. The solved classification tasks aim to support patients and clinical psycho-oncologists. © 2020 IEEE.

关键词： Support vector machines

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Adaptive Prompt Learning With Distilled Connective Knowledge for Implicit Discourse Relation Recognition

IEEE Transactions on Audio, Speech and Language Processing

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IEEE Transactions on Audio, Speech and Language Processing 2025年 33卷 586-597页

作者： Bang Wang Zhenglin Wang Wei Xiang Yijun Mo School of Software Engineering and Hubei Key Laboratory of Smart Internet Technology Huazhong University of Science and Technology (HUST) Wuhan China School of Electronic Information and Communications Huazhong University of Science and Technology Wuhan China Faculty of Artificial Intelligence in Education Central China Normal University Wuhan China School of Computer Science and Technology Huazhong University of Science and Technology Wuhan China

Implicit discourse relation recognition (IDRR) aims at recognizing the discourse relation between two text segments without an explicit connective. Recently, prompt learning has been applied to the IDRR task with great performance improvements over various neural network-based approaches. However, the discrete nature of the state-art-of-art prompting approach requires manual design of templates and answers, a big hurdle for its practical applications. In this paper, we propose a continuous version of prompt learning together with connective knowledge distillation, called AdaptPrompt, to reduce manual design efforts via continuous prompting while further improving performance via knowledge transfer. In particular, we design and train a few virtual tokens to form continuous templates and automatically select the most suitable one by gradient search in the embedding space. We also design an answer-relation mapping rule to generate a few virtual answers as the answer space. Furthermore, we notice the importance of annotated connectives in the training dataset and design a teacher-student architecture for knowledge transfer. Experiments on the up-to-date PDTB Corpus V3.0 validate our design objectives in terms of the better relation recognition performance over the state-of-the-art competitors.

关键词： Training Encoding Adaptation models Text recognition Knowledge engineering Feature extraction Bidirectional control Annotations Vocabulary Vectors

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Deep Learning Approach for COVID-19 Identification 18

Deep Learning Approach for COVID-19 Identification

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18th International computer Conference on Wavelet Active Media Technology and Information Processing, ICCWAMTIP 2021

作者： Ul Haq, Amin Li, Jian Ping Khan, Riaz Ullah Mawuli, Cobbinah Bernard Agbley, Bless Lord Y. Raj, Mordecai F. Zhou, Wang Khan, Jalaluddin Haq, Abdul Saboor, Abdus Habib, Faiza Khan, Zafar University of Electronic Science and Tech. of China School of Computer Science and Engineering Chengdu China 313000 China Xihua University School of Computer and Software Engineering Chengdu Sichuan China University of Electronic Science and Tech. of China School of Computer Science and Engineering Chengdu China Gomal University Department of Computer Science D.I. Khan29220 Pakistan Hazzra University Department of Computer Science and IT Manshera KPK 21120 Pakistan Northern University Faculty of Engineering and I.T Nowshera Pakistan

ISBN: (纸本)9781665413640

Accurate diagnostic system is significantly important for timely COVID-19 identification. Diagnosing COVID-19 from chest x-ray images employing the CNN model is recommended for accurate recognition of COVID-19. The existing diagnosis techniques of COVID-19 still lack high accuracy. To handle this problem in this work, we have proposed accurate detection method for COVID-19. In the proposed method, a CNN is incorporated for the diagnosis of COVID-19 using chest x-ray images data. The experimental results illustrate that our technique is good for COVID-19 accurate diagnosis and can be easily implemented in health care systems. © 2021 IEEE.

关键词： COVID-19

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Backscatter Communication-Based Wireless Sensing (BBWS): Performance Enhancement and Future Applications

TechRxiv

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TechRxiv 2022年

作者： Toro, Usman Saleh ElHalawany, Basem M. Wong, Aslan B. Wang, Lu Wu, Kaishun Shenzhen University College of Computer Science and Software Engineering Gaungdong Shenzhen518060 China Information Hub Gaungdong Guangzhou511453 China Benha University Faculty of Engineering at Shoubra Cairo11629 Egypt

Wireless Sensing (WS) provides a low-cost means of monitoring humans and objects for the next generation of IoT. However, the deployment of WS for various applications is limited by;the heterogeneous nature of underlying technology in IoT devices, limited battery, and computational power of sensing devices. Backscatter Communication (BackCom) enables wireless sensing and communication by reflecting wireless signals (such as radio frequency (RF), acoustic and visible light (VL)) from a source to a receiver using a backscatter tag at an ultra-low (microwatt) power level. Hence, backscatter communication-based wireless sensing (BBWS) could enable ubiquitously and battery-free applications (such as human and plant physiology, orientation sensing, and localization). Despite existing surveys and literature on BackCom, a study on leveraging BackCom for WS is still lacking. This paper takes the first approach in discussing applications of BackCom in WS and techniques for enhancing performance (such as power management, channel model, range and coverage, throughput, security, quality of backscatter signal, modulation, and coding) in BBWS applications. It also discusses future sensing applications where BBWS is applicable and research issues related to such applications. © 2022, CC BY.

关键词： Internet of things

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A Model-Driven Approach for IoT-Based Monitoring Systems in Industry 4.0 4

A Model-Driven Approach for IoT-Based Monitoring Systems in ...

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4th International Conference on Smart Cities, Internet of Things and Applications, SCIoT 2020

作者： Ziaei, Mahdi Zamani, Bahman Bohlooli, Ali University of Isfahan Mdse Research Group Department of Software Engineering Isfahan Iran University of Isfahan Faculty of Computer Engineering Isfahan Iran

ISBN: (纸本)9781728196114

Industry 4.0 provides a framework for applying new technologies in industrial environments to boost the efficiency and intelligence. A recently blossomed technology in Industry 4.0 is Internet of Things (IoT), which allows us to create a smart environment by connecting various equipment. One of the main applications of IoT in a smart factory is to design monitoring systems, which helps put the behavior of devices under permanent and comprehensive supervision. However, the rapid growth and change in the monitoring facilities creates a big challenge for people who either want to use that equipment in Industry 4.0, or want to update the systems to benefit from this technology. To address this problem, this paper presents new approach based on model-driven engineering paradigm, for simplifying the design and development of real-Time monitoring systems in an industrial environment. Our approach includes a domain-specific modeling language, a graphical editor, and model-To-code transformations that generate a hardware descriptive code, a mobile application, and a web application for a monitoring system. To evaluate the applicability of our approach, a scenario in the power industry has been designed, which offers user a VHDL code, a mobile application, and a web application for monitoring processes of the plant. © 2020 IEEE.

关键词： Modeling languages

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software Project Management Effectiveness Evaluation Tool 9

Software Project Management Effectiveness Evaluation Tool

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9th International Conference on software and Information engineering, ICSIE 2020

作者： Barghoth, Mohamed Ellithey Salah, Akram Ismail, Manal A Master in Software Engineering Program Egyptian E-Learning University Giza Egypt Faculty of Computer and Artificial Intelligence Cairo University Giza Egypt Department of Computer Engineering and Systems Faculty of Engineering Helwan University Helwan Egypt

ISBN: (纸本)9781450377218

Project management is important for the success of a software project. Enhancing software project management effectiveness measurements should lead the project manager to advance practices that contribute to the successful development of software projects. This study aims to enhance project management effectiveness measurements in the direction of increase the likelihood of software project success. An enhanced evaluation model of software project management effectiveness has been proposed in this study. Correspondingly, the model fed into a developed software project management effectiveness evaluation tool. This measurement tool helps software development managers to evaluate, monitor and improve project management effectiveness in software projects. The developed software project management effectiveness evaluation tool has been validated by a feedback survey. Feedback survey participants have been demonstrated the importance of the developed project management effectiveness measurement tool. © 2020 ACM.

关键词： Project management

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Efficient Server-Aided Personalized Treatment Recommendation with Privacy Preservation

Efficient Server-Aided Personalized Treatment Recommendation...

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GLOBECOM 2022 - 2022 IEEE Global Communications Conference

作者： Dan Zhu Hui Zhu Cheng Huang Rongxing Lu Xuemin Shen Dengguo Feng Department of Cyber Engineering Xidian University Xi'an China Department of Electrical and Computer Engineering University of Waterloo Waterloo Canada Faculty of Computer Science University of New Brunswick Fredericton Canada State Key Laboratory of Computer Science Institute of Software Chinese Academy of Sciences Beijing China

ISBN: (纸本)9781665435413

With AI-derived knowledge graph (KG), medical centers can recommend appropriate treatment options to physicians as references based on their patients' personal healthcare information (PHI). However, the treatment recommendation services may also cause serious privacy concerns. In this paper, we propose an efficient and privacy-preserving personalized treatment recommendation scheme with the aid of a third-party server. Specifically, a medical center denotes the KG of each disease by a directed graph with conditional edges and vertices that describe the treatment options and costs in different states. To prevent privacy leakage while reducing computational and management cost, the graphs are encrypted and then delegated to an honest-but-curious server. With the assistance of the server, physicians can set proper illness states and cost requirements according to patients' PHI, and correspondingly generate personalized ciphertexts to retrieve appropriate treatment options. The key component of the proposed scheme is a novel designed secure and flexible path comparison protocol, by tailoring a symmetric homomorphic encryption algorithm and combining it with a secure hash function. The protocol can enable the server to compare the uploaded ciphertexts with encrypted graphs in a secure and efficient way. Comprehensive security analysis indicates that the proposed scheme can meet desirable privacy requirements, and extensive experimental results demonstrate its practicality.

关键词： Hash functions Privacy Protocols Costs Medical services Servers Cryptography

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3D Modeling Surveying Tasks in Photogrammetry

3D Modeling Surveying Tasks in Photogrammetry

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2020 International Russian Automation Conference, RusAutoCon 2020

作者： Izvozchikova, V.V. Shardakov, V.M. Mezhenin, A.V. Orenburg State University Department of Informatics Orenburg Russia Itmo University Faculty of Software Engineering and Computer Engineering Saint-Petersburg Russia

ISBN: (数字)9781728161303

ISBN: (纸本)9781728161303

The research is aimed at the development of virtual environments of various configurations created by means of 3D computer modeling in such areas as photogrammetry, computer vision systems, robotics at the design stages of devices and systems. In addition, virtual simulators simulating real operating conditions, it is proposed to use for testing and modeling methods of shooting mobile video systems. It is assumed that the means of 3D-graphics emulates not only the environment, shooting conditions, but also the video systems themselves: means of technical vision, onboard cameras of robots and UAVs. The use of such simulators will allow to create, improve and test various algorithms of applied intelligent systems without creating complex expensive stands, will save time for various experiments. The article deals with the evaluation of the quality of recognition and reconstruction systems using a polygonal grid as a data representation. The results of testing these methods: the use of virtual environments and the assessment of the similarity of the polygon meshes. At the stage of segmentation and finding the vertices and segments of the objects under study demonstrated the use of both real images obtained by a real camera and synthesized images. During the reconstruction phase, a set of synthesized images was also used to test one of the reconstruction systems. To assess the similarity of polygonal objects based on the Hausdorff dimension, the corresponding functions were developed and the result of their work is given. © 2020 IEEE.

关键词： Unmanned aerial vehicles (UAV)

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Application of soft computing algorithms for hybrid modular multilevel inverters

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Measurement: Sensors 2024年 31卷

作者： Gireesh Kumar, Devineni Venkata Sireesha, Nagineni Bhoopal, Neerudi Kumar Gatla, Ranjith Kotb, Hossam AboRas, Kareem M. Elrashidi, Ali Alqarni, Mohammed Yasin Ghadi, Yazeed Oubelaid, Adel Department of Electrical & Electronics Engineering B V Raju Institute of Technology Narsapur502313 India Department of Information Technology Institute of Aeronautical Engineering Hyderabad500043 India Department of Electrical & Electronics Engineering Institute of Aeronautical Engineering Hyderabad500043 India Department of Electrical Power and Machines Faculty of Engineering Alexandria University Alexandria21544 Egypt Electrical Engineering Department University of Business and Technology Ar Rawdah Jeddah23435 Saudi Arabia Engineering Mathematics Department Faculty of Engineering Alexandria University Alexandria21544 Egypt Department of Computer Science and Software Engineering Al Ain University Abu Dhabi15322 United Arab Emirates Laboratoire de Technologie Industrielle et de L'Information Faculté de Technologie Université de Bejaia Bejaia06000 Algeria

This study utilized Harris Hawk optimization to analyze the harmonic distortions of a symmetric capacitor based multilevel converter. The proposed multilevel converter uses identical and symmetric DC sources in its input. The proposed topology for a multilevel converter uses fewer switches than typical cascaded designs. It can output 9-level outputs and can be scaled up to higher levels. The proposed multilevel converter can be improved by implementing a low frequency pulse width modulation technique to reduce the stress on the switches. The optimization of the switching angles using Harris Hawk was able to solve the non-linear aspects of the Selective Harmonic Elimination Pulse Width Modulation. The output voltage's THD was compared with that of other optimization methods, such as ant colony and particle swarm. The comparison shows that the output THD of the Harris Hawk optimizer is lower than that of other methods, which is about 5 %, according to the standards of IEEE-519. © 2023

关键词： Pulse width modulation

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A Soft Tissue Acupuncture Model Based on Mass-Spring Force Ne

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computers, Materials & Continua 2021年第10期69卷 727-745页

作者： Xiaorui Zhang Tong Xu Wei Sun Jiali Duan Sunil Kumar Jha Jiangsu Engineering Center of Network Monitoring Engineering Research Center of Digital ForensicsMinistry of EducationSchool of Computer and SoftwareNanjing University of Information Science&TechnologyNanjing210044China Jiangsu Collaborative Innovation Center of Atmospheric Environment and Equipment Technology(CICAEET) Nanjing University of Information Science&TechnologyNanjing210044China Faculty of Information Technology University of Information Technology and ManagementRzeszow35-225Poland

In the simulation of acupuncture manipulation,it is necessary to accurately capture the information of acupuncture points and particles around ***,a soft tissue modeling method that can accurately track model particles is *** this paper,a soft tissue acupuncture model based on the mass-spring force net is *** is used as the auxiliary model and the SHF model is *** is used to establish a three-layer soft tissue model of skin,fat,and muscle,and a layer of the MSM based force network is covered on the surface of soft tissue to realize the complementary advantages and disadvantages of spherical harmonic function and *** addition,a springback algorithm is designed to simulate the springback phenomenon of soft tissue skin during *** evaluation results show that the soft tissue acupuncture modeling method based on mass-spring force net can effectively simulate the springback phenomenon of soft tissue surface during acupuncture surgery,and has good comprehensive performance in the application of virtual acupuncture surgery simulation.

关键词： Mass-spring model puncture simulation virtual surgery soft tissue simulation

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