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检索条件"任意字段=3rd IEEE Intelligent Data Acquisition and Advanced Computing Systems"

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Evaluation of the Effectiveness of Information Technology Methods for Processing Diagnostic Information Based on Complex data 3

Evaluation of the Effectiveness of Information Technology Me...

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3rd ieee International Conference on System Analysis and intelligent computing, SAIC 2022

作者： Ivanytska, Anastasiia Zubyk, Liudmyla Dudnik, Andriy Gololobov, Dmitry Kurchenko, Oleh Berestov, Denis Taras Shevchenko National University of Kyiv Department of Software Systems and Technologies Kyiv Ukraine Interregional Academy of Personnel Management Department of Computer Information Systems and Technologies Kyiv Ukraine National Aviation University Department of Software Engineering Kyiv Ukraine

ISBN: (数字)9798350396744

ISBN: (纸本)9798350396744

The developed models were tested for adequacy and the effectiveness of information technology methods for processing diagnostic information based on complex data was evaluated. The obtained indicators of informativeness of diagnostic tools showed high values of sensitivity, specificity and accuracy, the latest coincides with the actual one by no less than 94.39. A control study of the effectiveness of the methods showed that it was possible to reduce the time spent on diagnosis by at least 8.97%. © 2022 ieee.

关键词： Diagnosis

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A Novel Text Resemblance Index Method for Reference-based Fact-checking 3

A Novel Text Resemblance Index Method for Reference-based Fa...

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3rd ieee International Conference on computing, Communication, and intelligent systems, ICCCIS 2022

作者： Barve, Yashoda Saini, Jatinderkumar R. Suryadatta College of Management Information Research and Technology Pune India Pune India

ISBN: (纸本)9781665462006

As in electronic era, data is transmitted via social network and web, people are harmed by false and deceptive content, such as misinformation. A fact-checker will examine specific indicators of falsity to determine the veracity of a piece of content. To perform automated fact-checking, retrieving information from the web, cleaning the contents, and using machine learning techniques are required. Prior research has focused on linguistic and literary characteristics as well as approaches based on similarity measurements. All the details and intricacies of the problem are not adequately covered by any of the papers referenced in the resource. We advanced a Text Resemblance Index (TRI) algorithm with a veracity-scanning model for the purpose of automating fact-checking URLs in the healthcare industry. To execute fact-checking in a journalistic manner, a set of innovative content, domain-specific, and sentimental scores based on polarity are applied. The Text Resemblance Score (TRS), a newly generated feature, outscored comparable properties with an accuracy of 88.27%, according to a thorough analysis of the proposed approach in contrast to traditional distance measures. In comparison to the Jaccard distance-based algorithm accuracy of 75.56% when leveraging an algorithm, TRI showed enhanced accuracy of 90%. Compared to the prior study, the TRS feature-based technique produced an accuracy improvement of 2.40%. © 2022 ieee.

关键词： Learning systems

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SensordAO: A New Framework of Sensor Governance for Internet of Vehicles 3

SensorDAO: A New Framework of Sensor Governance for Internet...

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3rd ieee International Conference on Digital Twins and Parallel Intelligence, DTPI 2023

作者： Liu, Yuhang Jiang, Tai Li, Juanjuan Ding, Wenwen Wang, Fei-Yue Chinese Academy of Science Institute of Automation Beijing China Macau University of Science and Technology Faculty of Innovation Engineering China Macau University of Science and Technology Macao Institute of Systems Engineering China

ISBN: (纸本)9798350318470

High-performance sensors play a crucial role in IoV (Internet of Vehicles) to achieve advanced autonomous driving. Typically, IoV involves extensive data sharing and centralizes data storage, posing significant security challenges for sensors. Although blockchain offers a decentralized platform for data exchange, it can't guarantee the reliability and trustworthiness of each sensor in IoV. Besides, blockchain primarily focuses on technical aspects and falls short of establishing a comprehensive organizational and operational framework for sensors. To address these challenges, we introduce the concept of DAO (Decentralized Autonomous Organization and Operation) into sensors and propose a new framework for reliable sensor operations in IoV, namely SensordAO. It utilizes the collaboration of on-chain and off-chain layers to support various scenarios at the application layer. We also provide key technical elements to construct SensordAO, including distributed storage, intelligent algorithms, governance, and incentive mechanisms. © 2023 ieee.

关键词： Blockchain

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An intelligent Chatbot Haggling with Ensemble ML Model 3

An Intelligent Chatbot Haggling with Ensemble ML Model

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3rd International Conference on Pervasive computing and Social Networking, ICPCSN 2023

作者： Naseeba, Beebi Sathwik, Abbaraju Sai Kiran, Jinka Chandra Challa, Nagendra Panini VIT-AP University Andhra Pradesh Amaravati India

ISBN: (纸本)9798350322842

In recent years online shopping has gained a huge boom. With this increase, most of the features of online shopping are developed but some features like negotiating with shopkeepers are not available which is sometimes possible in offline purchasing. In this paper we have proposed a Chatbot to conduct product negotiations. Customers can interact with the Chatbot to receive help obtaining a fair price for a product (s). With such a system, which has an impact on key aspects of online buying, there is a chance that the budget of the customer or the product seller could be compromised. To avoid such situations, we have developed an algorithm in Machine learning which works along with prediction of old available data to provide a product price. Sometimes, price prediction is less accurate because some algorithms are inappropriate for a given dataset or because irrelevant features or properties of the data are employed. Due to the potential financial losses associated with even one incorrect price prediction, Ecommerce businesses do not only rely on price prediction systems. Some models also fail when data scales or some feature is unavailable after time on which model prediction was dependent. Our model's accuracy and dependability are maintained by managing these modifications. © 2023 ieee.

关键词： Electronic commerce

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Hybrid 9-Port Power Divider and Combiner for Enhanced Wireless Energy Harvesting in Passive RFID Tag systems 3

Hybrid 9-Port Power Divider and Combiner for Enhanced Wirele...

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3rd ieee International Conference on intelligent Techniques in Control, Optimization and Signal Processing, INCOS 2024

作者： Rajeswari, P. Gobinath, A. Suresh Kumar, N. Nivetha, J. Swetha, V. Anandan, M. Velammal College of Engineering and Technology Department of Ece Madurai India Velammal College of Engineering and Technology Department of It Madurai India Vel Tech Rangarajan Dr. Sagunthala R&d Institute of Science and Technology Department of Ece Chennai India

ISBN: (数字)9798350361186

ISBN: (纸本)9798350361186

This research introduces innovative configurations for hybrid power divider combiners (HPDCs) featuring five and nine ports, aligning with the standards set by ieee 802.11b, g, ISM, and 802.11. The HPDCs are designed to operate at multiple bands - 2.45 GHz, 5.8 GHz, and 6 GHz - corresponding to ieee 802.11n, a, and 802.11ac, respectively. These tailored designs are specifically crafted to address the energy-efficient requirements of applications spanning the DC to 6-GHz frequency range. Notable applications include 5Genabled Passive Internet of Things (IoT) sensors, Energy Harvesting (E.H) tags, and Multiple-Input Multiple-Output (MIMO) antenna beamforming. When implemented on an FR4 substrate, the proposed HPDC configurations demonstrate consistent power distribution, robust port isolation, and excellent port matching, particularly at a central design frequency of 3 GHz. These designs hold great promise in the context of satellite-cellular convergence, finding potential applications in RF energy harvesting, adaptive intelligent energy-efficient data transmission, and seamless connectivity. Of significance is the achievement of return and isolation losses falling below -7 dB, meeting the criteria for Wi-Fi 6E. This underscores the suitability of the proposed HPDCs for advanced wireless applications, affirming their potential contribution to RF energy harvesting, adaptive data transmission, and enhanced connectivity within the specified frequency range. © 2024 ieee.

关键词： Energy harvesting

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ML_BrainDetection: An intelligent Model for Brain Tumor Identification Using Machine Learning 3

ML_BrainDetection: An Intelligent Model for Brain Tumor Iden...

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3rd International Mobile, intelligent, and Ubiquitous computing Conference, MIUCC 2023

作者： Abdelminaam, Diaa Salama Madbouly, Magda M. Farag, Mohamed S Gomaa, Ibrahim A Abd-Elghany Zeid, Magdy Abualigah, Laith Misr International University Faculty of Computer Science Cairo Egypt Benha University Faculty of Computers and Artificial Intelligence Benha Egypt Alexandria University Faculty of Computer and Data Science Alexandria Egypt Alobour High Institute for Computer and Informatics Computer Science Department Cairo Egypt Lebanese American University Department of Electrical and Computer Engineering Byblos13-5053 Lebanon Al-Ahliyya Amman University Hourani Center for Applied Scientific Research Amman19328 Jordan Middle East University Meu Research Unit Amman11831 Jordan School of Computer Sciences Universiti Sains Malaysia Pulau Pinang11800 Malaysia

ISBN: (纸本)9798350306231

Brain tumors are one of the greatest causes of death worldwide. Due to that, early diagnosis and classification of the tumor would surely help increase the chance of survival for patients worldwide. However, classifying and identifying brain tumors requires certain tools, including using Magnetic Resonance Imaging (MRI) to detect brain tumors. Moreover, many researchers in the past have also built up Computer-Aided Diagnosis (CAD) systems to aid radiologists in their purpose of detecting brain abnormalities and tumors effectively. In this research, extracted multi-modal features like texture, morphological, entropy-based, Scale Invariant Features are proposed, and consequently, certain robust machine learning techniques, which are k-nearest neighbors (KNN), Decision Tree (DT), Support Vector Machine (SVM), Naive Bayes, as well as the Logistic Regression classifier were used to analyze the two data-sets included in the paper, detect tumors found in the brain, not to mention, examining their results, which have then shown the highest accuracy when using the Logistic regression classifier in both data sets, with the Support Vector Machine (SVM) classifier following it, which further support the argument made in the paper. © 2023 ieee.

关键词： Support vector machines

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A No-Code Approach to Classifying Neurological Disorders Using Orange data Mining 3

A No-Code Approach to Classifying Neurological Disorders Usi...

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3rd International Conference on intelligent systems, advanced computing, and Communication, ISACC 2025

作者： Davidraj, Yabez Elavarasan, S. Vivek, T. Munirathinam, Ramesh Karpagam Academy of Higher Education Department of Biomedical Engineering Coimbatore India

ISBN: (纸本)9798331523893

Neurodegenerative diseases are progressive disorders causing neuron damage, leading to cognitive and motor impairments. This study presents a machine learning approach for classifying multiple neurological disorders using MRI data with the Orange data analytics software. A total of 165 MRI images representing conditions such as Alzheimer's disease, Huntington's disease, motor neuron disease, and Pick's disease were sourced from the AANLIB database. Image features were extracted using the VGG-16 deep learning model, and classification was conducted via Support Vector Machine (SVM) with polynomial, linear, radial basis function (RBF), and sigmoid kernels. The polynomial and sigmoid kernels achieved the highest classification accuracy of 93.3%, outperforming the linear and RBF kernels. These findings highlight that MRI-based classification using deep learning features and SVM in Orange can effectively differentiate neurological disorders, showing promise for early and accurate diagnosis. © 2025 ieee.

关键词： Neurodegenerative diseases

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Class-Based Grid Field Area Communication with Named data Networking Approach 3

Class-Based Grid Field Area Communication with Named Data Ne...

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3rd International Conference on Electronic and Electrical Engineering and intelligent System, ICE3IS 2023

作者： Satriawan, Gregorius Pradana Yovita, Leanna Vidya Mayasari, Ratna School of Electrical Engineering Telkom University Bandung Indonesia

ISBN: (纸本)9798350327762

Using electricity from new and renewable energy sources is a potential solution to combat climate change. With the introduction of renewable energy, an intelligent control system must address the issues of intermittent and non-dispatchable renewable energy generators. A reliable communication system with minimal packet loss and latency is required for grid systems, especially to support advanced distributed and renewable grid control systems. The Named data Network (NDN), which has effective routing, forwarding, and caching methods, provides options to meet the communication needs of grid communications. This study proposes a grid-based Field Area Network communication design with the NDN approach. Based on the simulation results, the FAN traffic meets the QoS specifications required to travel over the NDN network. Queuing combined with traffic arrangement can improve the network's QoS, lowering latency in priority packets and reducing packet loss & interest timeout in the network. However, queuing can result in longer delays for lower-priority traffic. © 2023 ieee.

关键词： Control systems

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Decentralized data Privacy Protection and Cloud Auditing Security Management 3

Decentralized Data Privacy Protection and Cloud Auditing Sec...

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3rd ieee International Conference on computing, Communication, and intelligent systems, ICCCIS 2022

作者： Mageshwari, M. Naresh, R. Srm Institute of Science and Technology Department of Computer Science and Engineering Kattankulathur Chengalpattu Tamilnadu Chennai603 203 India Srm Institute of Science and Technology Department of Networking and Communications Kattankulathur Chengalpattu Tamilnadu Chennai603 203 India

ISBN: (纸本)9781665462006

Decentralized data protection is becoming more important as more firms employ Cloud resources. Securing, protecting, and processing user data are primary issues that Cloud computing faces. This study's primary goal is to detect and address attack protection in Cloud. Our objectives are to comprehend the present state of cloud computing security concerns and methods, identify future cloud computing security concerns to offer countermeasures for potential. Preventative measures to employing cloud services include data security and privacy concerns. The challenge is to create cloud platforms for integrating decentralized information systems to ensure the user's privacy. For management units of distributed systems, the requirements analysis yielded a model for organizational levels of cloud systems. By bypassing the single-point-of-failure of TPA, our suggested approach may prevent service disruption and privacy-preserving concerns. The extensive security analysis proves that our suggested solution meets all the needed security criteria. We also implement our suggested method with PSO-Homomorphic Algorithm (PSO-HA) and evaluate its efficiency in real-world situations, demonstrating its efficacy, high efficiency, and portability. Our results show that our methodology for simultaneously-integrated recovery can be implemented in polynomial time and is thriving. © 2022 ieee.

关键词： Cloud security

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2022 ieee 3rd International Conference on System Analysis and intelligent computing, SAIC 2022 - Proceedings

2022 IEEE 3rd International Conference on System Analysis an...

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3rd ieee International Conference on System Analysis and intelligent computing, SAIC 2022

ISBN: (纸本)9798350396744

The proceedings contain 70 papers. The topics discussed include: modeling of potential flooding zones with geomatics tools;modeling of complex systems instability under risks and uncertainty;new classes of unconstrained permutation-based problems and their solutions;digital twin simulation for cyber-physical systems on electric heater example;detecting and handling flawed input data in modified morphological analysis method;estimation of the accuracy of methods for calculating interval weight vectors based on interval multiplicative preference relations;comparison analysis of prioritization quality criteria using paired comparison method of prioritization;horizontal method application to multiobjective combinatorial optimization over permutations;fractal analysis in urban studies: a case study on Ukrainian cities;extracting and identifying relationships of key phrases in information flows;intersubjective paradigm and oracle conceptualization as an open-closed platform for programming technologicalization;and problem-oriented model in technical specialized applications of transport systems management.

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