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2022 IEEE International Conference on Current Development in Engineering and Technology, CCET 2022

作者： Khujamatov, Halimjon Akhmedov, Nurshod Lazarev, Amir Arsheen, Sobiya Tashkent University of Information Technologies Dean of the Faculty of Computer Engineering Tashkent Uzbekistan Tashkent University of Information Technologies Data Transmission Networks and Systems Department Tashkent Uzbekistan Maulana Azad National Urdu University Department of Computer Science and Information Technology India

ISBN: (纸本)9781665454155

This article is devoted to the actual topic of studying scenarios for adapting a network infrastructure to a network of remote patient monitoring systems (PCMS). The paper presents an overview and analysis of scenarios for adapting the network infrastructure of monitoring systems. The stages of scenario execution have been studied and simulation models of the RPMS network infrastructure have been developed that implement various adaptation scenarios. A comparative analysis of adaptation scenarios was carried out according to several criteria, such as the speed of request delivery, delivery time, and network load. Simulation models built in the Anylogic environment, a powerful simulator of mass service system, showed the effectiveness of the mesh topology in relation to the ad-hoc topology according to several criteria. The theoretical significance of the work lies in carrying out analytical work on scenarios for adapting the network infrastructure of the RPMS, as well as in studying the network architecture. The practical significance of the work lies in the development of a simulation model that allows you to explore scenarios for adapting the network architecture. © 2022 IEEE.

关键词： Network architecture

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Implementation of expert systems in potassium deficiency in cocoa plants using forward chaining method

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Procedia computer science 2023年 216卷 136-143页

作者： Muhammad Titan Hafizal Dian Pratama Putra Herry Wirianata Nanda Satya Nugraha Teddy Suparyanto Alam Ahmad Hidayat Bens Pardamean Faculty of Forestry STIPER Institute of Agriculture Yogyakarta 55282 Indonesia Bioinformatics and Data Science Research Center Bina Nusantara University Jakarta 11480 Indonesia Computer Science Department BINUS Graduate Program Bina Nusantara University Jakarta 11480 Indonesia

As one of the largest exporters in the world, cocoa (Theobroma cacao L.) production in Indonesia provides an important contribution to the plantation sector that can, directly and indirectly, attribute to the national economic development. However, recent data shows a decline in cocoa productivity in Indonesia. This is arguably caused by various factors, including poor agricultural management and practices in cocoa plantations, that may lead to lower fertility in the soil and an increased risk of diseases and pests. Potassium deficiency is a major contributing factor to the low soil fertility that affects cocoa yields. Therefore, in this work, we implement an application with an expert system utilizing the forward chaining method to detect potassium deficiency in cocoa plants and then give a fertilization-based recommendation based on the plants’ condition. The system employs a set of rules to identify symptoms related to the deficiency on the sample photo of a cocoa leaf according to the channels of red, green, and blue of the image. The sample images of cocoa leaves are submitted to the application with an easy-to-use interface that can show the scanning result and proceed to display the suggested quantity of fertilizers to prevent potassium deficiency. Implementing the system can contribute constructive impacts to improve current practices in the overall cropping system of cocoa plants.

关键词： agriculture cocoa expert system forward chaining recommendation system

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A Temporal Graphlet Kernel for Classifying Dissemination in Evolving Networks

arXiv

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arXiv 2022年

作者： Oettershagen, Lutz Kriege, Nils M. Jordan, Claude Mutzel, Petra Institute of Computer Science University of Bonn Bonn Germany Faculty of Computer Science University of Vienna Vienna Austria Research Network Data Science University of Vienna Vienna Austria

We introduce the temporal graphlet kernel for classifying dissemination processes in labeled temporal graphs. Such dissemination processes can be spreading (fake) news, infectious diseases, or computer viruses in dynamic networks. The networks are modeled as labeled temporal graphs, in which the edges exist at specific points in time, and node labels change over time. The classification problem asks to discriminate dissemination processes of different origins or parameters, e.g., infectious diseases with different infection probabilities. Our new kernel represents labeled temporal graphs in the feature space of temporal graphlets, i.e., small subgraphs distinguished by their structure, time-dependent node labels, and chronological order of edges. We introduce variants of our kernel based on classes of graphlets that are efficiently countable. For the case of temporal wedges, we propose a highly efficient approximative kernel with low error in expectation. We show that our kernels are faster to compute and provide better accuracy than state-of-the-art methods. Copyright © 2022, The Authors. All rights reserved.

关键词： computer viruses

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Capability Level of SPBE Application and Infrastructure Audit Tools Using COBIT 2019 6

Capability Level of SPBE Application and Infrastructure Audi...

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6th International Conference on Informatics, Multimedia, Cyber and Information System, ICIMCIS 2024

作者： Irzavika, Nindy Mahda, Friyogi Resvy Universitas Pembangunan Nasional Veteran Jakarta Faculty of Computer Science Jakarta Indonesia Badan Riset dan Inovasi Nasional Research Center of Data and Information Sciences Jakarta Indonesia

ISBN: (纸本)9798331533243

SPBE, an electronic government system, uses IT infrastructure and applications to deliver services. IT audits, conducted using tools like 'SPBE Audit Tools,' ensure effective service delivery. COBIT 2019 can improve governance and align IT with business goals. This study aims to evaluate its capability level using COBIT 2019. The research flow involves problem identification, literature review, data analysis, goal alignment, design, and recommendation. This process ensures that the governance system effectively supports the organization's strategic goals and addresses the identified research problem. Gap analysis is conducted to indicate areas where improvements are necessary to align with desired capabilities. It compares the current capability levels to the target levels. The domains APO02, APO04, and BAI03 are below respective targets. Based on the gap analysis results, recommendations will be formulated to minimize the gap and improve the capability levels. © 2024 IEEE.

关键词： Recommender systems

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Assessing the Validity of Automated data Analysis Methods Based on Artificial Intelligence 3

Assessing the Validity of Automated Data Analysis Methods Ba...

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

作者： Yuvaraj, K. Balakumar, P. Kadam, Prema S. Mishra, Prakash Raja Kumar, Jambi Ratna Verma, Anupama Karpagam Academy of Higher Education Department of Computer Science Coimbatore India Prince Shri Venkateshwara Padmavathy Engineering College Department of Information Technology Chennai India Vishwakarma Institute of Information Technology Department of Artificial Intelligence & Data Science Pune India Mangalayatan University Department of Management Jabalpur India Genba Sopanrao Moze College of Engineering Balewadi Department of Computer Engineering Maharashtra Pune India Usha Martin University Faculty of Business Mangagement & Commerce Ranchi India

ISBN: (纸本)9798350319125

Automated records analysis strategies primarily based on artificial intelligence (AI) have become increasingly famous in recent years because of their capability to quickly and effectively method enormous quantities of facts. However, concerns about the validity of those methods and their potential for introducing bias or mistakes have been raised. This study aims to assess the validity of automatic facts evaluation methods based on AI. It entails evaluating those methods' accuracy, reliability, and consistency compared to conventional guide evaluation methods. An expansion of study methods may be used, which includes experimental research, case research, and surveys. Facts will be gathered from computerized AI techniques and manual strategies, after which they will be compared and evaluated to decide the extent of agreement between them. One capability mission in this research is the dearth of a gold standard for statistics analysis. Unlike in medical fields wherein there may be a clean popular for prognosis, information analysis methods can also vary depending on the unique dataset and research question. Expanding a hard and fast of criteria or metrics for evaluating the validity of different AI techniques is essential. Another challenge is the rapidly evolving nature of the AI era. As new techniques and algorithms constantly evolve, keeping up with modern-day improvements and their potential impact on records analysis could be challenging. © 2023 IEEE.

关键词： evolved mission modern potential research

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Multi-view Graph Convolutional Networks with Differentiable Node Selection

arXiv

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arXiv 2022年

作者： Chen, Zhaoliang Fu, Lele Xiao, Shunxin Wang, Shiping Plant, Claudia Guo, Wenzhong College of Computer and Data Science Fuzhou University China School of Systems Science and Engineering Sun Yat-sen University China Faculty of Computer Science University of Vienna Austria

Multi-view data containing complementary and consensus information can facilitate representation learning by exploiting the intact integration of multi-view features. Because most objects in real world often have underlying connections, organizing multi-view data as heterogeneous graphs is beneficial to extracting latent information among different objects. Due to the powerful capability to gather information of neighborhood nodes, in this paper, we apply Graph Convolutional Network (GCN) to cope with heterogeneous-graph data originating from multi-view data, which is still under-explored in the field of GCN. In order to improve the quality of network topology and alleviate the interference of noises yielded by graph fusion, some methods undertake sorting operations before the graph convolution procedure. These GCN-based methods generally sort and select the most confident neighborhood nodes for each vertex, such as picking the top-k nodes according to pre-defined confidence values. Nonetheless, this is problematic due to the non-differentiable sorting operators and inflexible graph embedding learning, which may result in blocked gradient computations and undesired performance. To cope with these issues, we propose a joint framework dubbed Multi-view Graph Convolutional Network with Differentiable Node Selection (MGCN-DNS), which is constituted of an adaptive graph fusion layer, a graph learning module and a differentiable node selection schema. MGCN-DNS accepts multi-channel graph-structural data as inputs and aims to learn more robust graph fusion through a differentiable neural network. The effectiveness of the proposed method is verified by rigorous comparisons with considerable state-of-the-art approaches in terms of multi-view semi-supervised classification tasks, and the experimental results indicate that MGCN-DNS achieves pleasurable performance on several benchmark multi-view datasets. Copyright © 2022, The Authors. All rights reserved.

关键词： Convolution

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Offline Text-Independent Writer Identification Using a Codebook with Structural Features

SSRN

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SSRN 2022年

作者： Ahmed, Bashar Qase Hassan, Yaser F. Elsayed, Ashraf S. Department of Mathematics and Computer Science Faculty of Science Alexandria University Elshatbi Alexandria Egypt Faculty of Computing and Data Science Alexandria University Smoha Alexandria Egypt Faculty of Computer Science and Engineering AlAlamein International University El Alamein Marsa Matroh Egypt

Understanding handwritten documents is a vital and challenging problem that attracts many researchers in the fields of forensic and authentication science. This paper presents an offline system for text-independent writer identification of handwritten documents. The system extracts a handwritten connected component contour, which in turn is divided into segments of specific length. The system utilizes the concept of a bag of features in the writer recognition domain and considers handwritten contour segments to extract two conceptually simple and effective structural features. These features are the contour point curve angle and the CONtour point CONcavity/CONvexity. The system uses the proposed features to train a k-means clustering algorithm to construct a codebook of size K. The method then uses occurrence histograms of the extracted features in the codebook to create a final feature vector for each handwritten document. The effectiveness of the proposed features is evaluated in the writer identification domain using two widely used classification methods: the nearest neighbor and the support vector machine techniques. The proposed writer identification is evaluated on two large and public datasets from different language domains, the Arabic KHATT and English IAM datasets. The experimental results show that the proposed system outperforms state-of-the-art methods on the IAM dataset and provides competitive results on the KHATT dataset with respect to the identification rate. © 2022, The Authors. All rights reserved.

关键词： Graphic methods

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The Smart Optimization and Estimating the Performance of Encapsulating Security Payload in Wireless Network Security 3

The Smart Optimization and Estimating the Performance of Enc...

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

作者： Sripriya, T. Borade, Monali R. Deepaware, Neeta Kumar, Jambi Ratna Raja Khalid, Md. Saifullah Singh, K. Ranjith Prince Shri Venkateshwara Padmavathy Engineering College Department of Electronics and Communication Engineering Chennai India Vishwakarma Institute of Information Technology Department of Artificial Intelligence & Data Science Pune India Mangalayatan University Department of Management Jabalpur India Genba Sopanrao Moze College of Engineering Balewadi Department of Computer Engineering Maharashtra Pune India Usha Martin University Faculty of Business Mangagement & Commerce Ranchi India Karpagam Academy of Higher Education Department of Computer Science Coimbatore India

ISBN: (纸本)9798350319125

The Encapsulating Security Payload (ESP) is the primary issue of safety structure for wireless networks. It inspires to make specific cozy switches of records across a wireless network by offering encrypted messages, information integrity guarantee, and authentication of communications. ESP can also provide excellent selective filtering of community site visitors and provides levels of authentication required for ease of network access. Due to the advances in the wireless era, the overall performance of ESP in Wi-Fi networks is becoming increasingly essential. Consequently, intelligent optimization and estimating the overall performance of ESP in wireless networks is an important task. Clever optimization of ESP in Wi-Fi networks determines the most reliable parameters for ESP to maximize its performance and reduce the network overhead that may arise while looking to take care of records transmission and information protection. Traditional optimization techniques, including Genetic Algorithms, can be used for this project, as they give more accurate outcomes and might effortlessly be implemented in the community infrastructure. Clever optimization can't only decorate the performance of ESP but can also reduce the variety of false alarms in the machine. Moreover, developing an accurate estimation for the overall performance of ESP in Wi-Fi networks is essential to get the most out of its talents. The usage of mathematical models, including a Markov Chain modeling technique, to symbolize various. © 2023 IEEE.

关键词： authentication encapsulating optimization

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A Bibliometric and Social Media Analysis of the Nexus Between Blockchain Technology and Finance 2nd

A Bibliometric and Social Media Analysis of the Nexus Betwee...

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2nd International Conference on Intelligent Manufacturing and Robotics, ICIMR 2024

作者： Ayodele, Olamide Emmanuel Ajibade, Temiloluwa Iyanuoluwa Oyebode, Oluwadare Joshua Akintoye, Kayode Akinlekan Ajayi, Babatunde Adedotun Adediran, Anthonia Oluwatosin Ajibade, Samuel-Soma M. Majeed, Anwar P. P. Abdul Luo, Yang Department of Banking and Finance Ekiti State University Ekiti State Ado Ekiti Nigeria Department of Business Management Scholar School System Birmingham United Kingdom Civil and Environmental Engineering Afe Babalola University Ekiti State Ado Ekiti Nigeria Department of Computer Science The Federal Polytechnic Ekiti State Ado Ekiti Nigeria Department of Cyber Security Faculty of Computing and Informatics Ladoke Akintola University of Technology Ogbomoso Nigeria Department of Real Estate Faculty of Built Environment Universiti Malaya KL Kuala Lumpur Malaysia Department of Data Science and Artificial Intelligence Faculty of Engineering and Technology Sunway University Selangor Malaysia Department of Computer Engineering Istanbul Ticaret University Istanbul Turkey Suzhou Taicang215400 China

ISBN: (纸本)9789819639489

This study explores Blockchain technology in the global financial industry using trends analysis, bibliometric analysis, and a literature appraisal using Elsevier Scopus data from 2016 to 2023. The Blockchain in Finance (BCF) study produced 185 publications: 53.5% papers, 45.4% conference proceedings, and 1.1% reviews. Analysis of the subject area revealed three important computer science, Engineering, and Decision sciences articles. However, source title analysis showed that ACM International Conference Proceeding Series, Sustainability Switzerland, and E3S Web of Conferences publish BCF research most often. According to the stakeholders study, Jon M. Truby and Qatar University (Qatar) are the top BCFin researchers and affiliations with 4% and % publications, respectively. China produces the most research on the topic. Due to active support from funding sources like the Chinese National Natural science Foundation (NNSF), 18 publications have been funded. Co-occurrence of keywords The investigation indicated that BCFin’s top keywords include Blockchain, Finance, and Supply Chain Finance. Three clusters with 4–8 keywords, 132 linkages, and 866 TLS were found via cluster analysis. Keywords classify the clusters as Integrated Business Solutions (Cluster 1), Digital Commerce Infrastructure (Cluster 2), and Decentralized Financial Network (Cluster 3). The findings indicate that BCFin is a dynamic and influential multidisciplinary study field. BCFin has transformed the global financial sector by improving trust, transaction security, and communication. It still struggles with interoperability, system integration, and sustainability. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Decentralized finance

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Adaptive fast-reaching nonsingular terminal sliding mode tracking control for quadrotor UAVs subject to model uncertainties and external disturbances

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Ain Shams Engineering Journal 2023年第8期14卷

作者： Mobayen, Saleh El-Sousy, Fayez F.M. Alattas, Khalid A Mofid, Omid Fekih, Afef Rojsiraphisal, Thaned Graduate School of Intelligent Data Science National Yunlin University of Science and Technology 123 University Road Section 3 Douliou Yunlin640301 Taiwan Department of Electrical Engineering Prince Sattam Bin Abdulaziz University Al Kharj Saudi Arabia Department of Computer Science and Artificial Intelligence College of Computer Science and Engineering University of Jeddah Jeddah Saudi Arabia Department of Electrical and Computer Engineering University of Louisiana at Lafayette Lafayette United States Advanced Research Center for Computational Simulation Department of Mathematics Faculty of Science Chiang Mai University Chiang Mai50200 Thailand Data Science Research Center Department of Mathematics Faculty of Science Chiang Mai University Chiang Mai50200 Thailand

This paper proposes an adaptive fast-reaching nonsingular terminal sliding mode control approach for the position and attitude tracking control of a quadrotor UAV subject to model uncertainty and external disturbances. To this end, a fast-reaching nonsingular terminal sliding surface is defined with the aim of fast convergence of the tracking error. The fast reachability of the nonsingular terminal sliding surface is proven using the Lyapunov stability theory. Since, in practice, the upper bounds of model uncertainties and external disturbances are unknown, an adaptive control scheme is considered to approximate them. The fast-reaching nonsingular terminal sliding mode control approach was augmented with the adaptive scheme to ensure both, the fast convergence of the switching surfaces and the rejection of model uncertainties and external disturbances. The effectiveness of the proposed adaptive fast-reaching nonsingular terminal sliding mode control approach is assessed using simulations of a quadrotor system implemented in MATLAB/Simulink software. The obtained results are further compared to those of an existing approach in terms of tracking performance, robustness, and integrator of absolute-value of error criteria. © 2022 THE AUTHORS

关键词： Unmanned aerial vehicles (UAV)

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