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4th International Conference on Intelligent Cybernetics technology and Applications, ICICyTA 2024

作者： Ginting, Dewi Sartika Br Efendi, Syahril Amalia Sihombing, Poltak Universitas Sumatera Utara Department of Computer Science and Technology Informtion Medan Indonesia

ISBN: (纸本)9798331506490

Stunting is a problem that always appears in our midst. Stunting prevalence data is important for observing and monitoring the condition of stunting that occurs. However, data with bad values affects the accuracy of the data, so it has a big impact on the information that will bereceived when the data is processed. For this reason, stunting data is processed using the Cure-Sne model to group stunting prevalence which produces good information. With the Cure- Sne model, the processed dataset also detects a number of outiers that interfere with the values of other real data. In the Cure-Sne process, the amount of data used is 120K rows with5 attributes which are processed with Cure-Sne to produce 4 Clusters. In Cluster 1, the predominant gender is male, and the nutritional status is classified as normal. Cluster 2 shows a predominance of females with a severely undernourished status. In Cluster 3, males dominate with a normal nutritional status, while Cluster 4 consists mainly of females, also with a normal nutritional status. From 120,000 rows in the dataset, many data were detected as outliers. There are 6,060 outlier data points identified from a total of 120,000 records with 4 attributes. This indicates that a significant portion of the datamay not conform to the expected patterns or distributions, suggesting the presence of anomalies that warrant further investigation. Evaluation of Cure-Sne is carried out with the Sillhoute Score. The evaluation or accuracy of the Cure-Sne model in analyzing stunting data is determined to be 0.8450, equivalent to 84.50%. © 2024 IEEE.

关键词： Data assimilation

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Trigger Systems: Reusability and applicability in Serious Games 27

Trigger Systems: Reusability and applicability in Serious Ga...

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27th International Conference on System Theory, Control and Computing, ICSTCC 2023

作者： Grosu, Mihai-Alexandru Brumar, Raul Nicola, Stelian Ciocârlie, Horia Computer and Informtion Technology University Politehnica Timisoara Timisoara Romania Automation and Applied Informatics University Politehnica Timisoara Timisoara Romania

ISBN: (纸本)9798350337983

The integration of technology in education has provided a more interactive and engaging experience through the creation of Serious Games. By using 3D virtual environments and Virtual Reality, interactive experiences which simulate real-life situations and environments can be created. The development process of such applications often proves to be slow and cumbersome. However, the addition of a trigger system or scenario editor could enable educators to easily create scenarios for students without requiring much programming knowledge. Designing the trigger system should be based on the principles of reusability, applicability and extensibility. This paper focuses on the creation of such a trigger system and its uses throughout the development of a 3D VR Serious game called Visit UPT. This game enables students to explore the university campus and simulate small scientific experiments. © 2023 IEEE.

关键词： Virtual reality

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Protecting machine learning systems using blockchain: solutions, challenges and future prospects

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Multimedia Tools and Applications 2024年 1-28页

作者： Hajlaoui, Rejab Dhahri, Salah Mahfoudhi, Sami Moulahi, Tarek Alotibi, Gaseb Department of Computer and Informtion Sciences College of Computer Science and Engineering University of Hail Hail City Saudi Arabia Laboratory of Advanced Multifunctional Materials and Technological Applications Faculty of Science and Technology of Sidi Bouzid University of Kairouan Sidi Bouzid Tunisia Department of Information and Technology Management Mediterranean School of Business South Mediterranean University Tunis Tunisia Department of Information Technology College of Computer Qassim University Buraidah Saudi Arabia Department of Computers and Information Technology Alwajah College University of Tabuk Tabuk Saudi Arabia

Machine learning-based systems have emerged as the primary means for achieving the highest levels of productivity and efficiency. They have become the most influential competitive factor for many technologies and business companies such as Cloud AI Companies (Google, Facebook…) and Health Care AI Companies (Tempus, Nanox …). However, privacy and security issues have become the biggest challenge facing all ML applications. These threats are known as Adversarial Machine Learning (AML). Their main goal is to maliciously manipulate training data and model parameters to obtain misleading results. To overcome these challenges, several research studies have proven that Blockchain, which relies on cryptographic technologies, constitutes a promising solution for securing ML applications. It provides high guarantees to make the system scalable, reliable and more secure. In this survey, we provide an overview of ML applications and the most hostile attacks they face. Then, we define the blockchain technique and its distinctive features. After that, we conduct a comprehensive and detailed survey of the latest and best blockchain-based research to address security issues in ML applications (integrity, confidentiality and availability). We analyze, compare and comment on all the proposed solutions. In the end, we discuss in detail the various challenges that hinder the adoption of blockchain technology and we extract the most important scientific trends that will serve as guidance and support for researchers in their future works. © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2024.

关键词： Blockchain

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Cure-Sne Model Detects Outliers in Data to Optimize the Process of Clustering Using Representatives

Cure-Sne Model Detects Outliers in Data to Optimize the Proc...

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Intelligent Cybernetics technology & Applications (ICICyTA), International Conference on

作者： Dewi Sartika Br Ginting Syahril Efendi Amalia Poltak Sihombing Department of Computer Science and Technology Informtion Universitas Sumatera Utara Medan Indonesia

ISBN: (数字)9798331506490

ISBN: (纸本)9798331506506

关键词： Analytical models Pediatrics Data analysis Accuracy High dimensional data Computational modeling Refining Pressing Public healthcare Monitoring

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Using Ethereum Platform to Securely Register Students' Extracurricular Activities

Using Ethereum Platform to Securely Register Students' Extra...

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IEEE Southeastcon

作者： Chafic W. Bou-Saba Alexis Guillen Computer Technology & Informtion Systems Dept. Guilford College Greensboro NC USA

An official transcript is a document that is produced by the registrar's office and that provides a complete representation of a student's academic record. Yet, an official transcript does not record any of the student's extracurricular activities despite the fact that such activities can shape the student's personal and professional development. It is usually the student's responsibility to keep a running log to document the attended events and the participated activities, their dates and locations, and the number of participants in such activities. These activities, not only improve the student's communications level, expand the learned skills, and develop the pursued interests, but also open the door to present an in-depth path of the student's professional and personal growth. However, students in general, have hard time documenting and providing proof of all of their extracurricular activities during their educational years. This project addresses and solves this problem and present an innovative, reliable, secure, and even portable (possibly across educational institutions) solution. Our solution encompasses a decentralized Web3 App (dApp), Ethereum smart contract and blockchain, and Metamask crypto wallet. The dApp registers the students' activities using tokens applied to smart contracts that are saved/inserted on the Ethereum blockchain. The student can then use the combination of Etherscan block explorer and the crypto wallet's public address, to provide a detailed and certified extracurricular transcript or log of the extracurricular activities participated in or attended. The extracurricular transcript could be requested by a recruiter or an employee of the human resources department as a part of the hiring process or a promotion.

关键词： Codes Shape Smart contracts Documentation Decentralized applications Software Blockchains

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Streamlining Serious Game Development: An Extensible System for Unifying Controls in Cross-Platform Serious Game Development

Streamlining Serious Game Development: An Extensible System ...

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International Symposium on Applied Computational Intelligence and Informatics ( SACI)

作者： Raul Brumar Mihai-Alexandru Grosu Stelian Nicola Horia Ciocârlie Automation and Applied Informatics University Politehnica Timisoara Timisoara Romania Computer and Informtion Technology University Politehnica Timisoara Timisoara Romania

ISBN: (数字)9798350329520

ISBN: (纸本)9798350329537

In recent years, serious games have gained traction as an aid to traditional teaching and training methods. While releasing a serious game which can run on multiple platforms is desired, this comes with its own problems, mainly the need to develop multiple projects in parallel. We have identified this as a significant obstacle preventing people from developing cross-platform serious games, and in this paper propose a solution in the form of a system which unifies platform-specific controls. This results in the need to maintain a single code base, with platform-specific code being written only for reading and processing the inputs. The system identifies on which platform the game is currently running and selects the correct code to process inputs. The processed inputs are abstracted, and the rest of the game uses the abstracted inputs, regardless of the current platform.

关键词： Training Human computer interaction Codes Control systems Serious games Task analysis Informatics

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Deep Learning-Based Multiple Detection Techniques of Covid-19 Disease From Chest X-Ray Images Using Advanced Image Processing Methods and Transfer Learning 1st

Deep Learning-Based Multiple Detection Techniques of Covid-1...

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1st Analytics Global Conference, AGC 2023

作者： Hussain, Arif Basak, Rohini Mandal, Sourav Department of Informtion Technology Jadavpur University West Bengal Kolkata700098 India School of Computer Scinece and Engineering XIM University Odisha Bhubaneswar752050 India

ISBN: (纸本)9783031508141

The 2019 new coronavirus (COVID-19), which originally surfaced in the Chinese city of Wuhan in December 2019, expanded quickly, and caused a pandemic. It has created a terrible influence on daily lives, public health, and the global economy. To stop the pandemic from spreading further and to treat the affected individuals as soon as feasible, it is essential to identify positive cases as soon as possible. One of the primary issues in the present COVID-19 pandemic is the early detection and diagnosis of COVID-19, as well as the precise separation of non-COVID-19 cases at the lowest cost and in the early stages of the disease. This study compares the usage of the most recent Convolutional Neural Network (CNN), a deep learning methodology employing networks, with a transfer learning technique using VGG and ResNet. With their assistance, we created models that can recognize COVID-19 in X-Ray photos. We have applied techniques of image preprocessing using Contrast Limited Adaptive Histogram Equalization (CLAHE) and Adaptive Histogram Equalization (AHE). We built the model by applying CNN. We have also applied transfer learning techniques using Visual Geometry Group (VGG16) and Residual Network (ResNet50) after image preprocessing using CLAHE and AHE. We have compared the accuracy of all models. The CLAHE technique along with ResNet50 works well as we achieve an accuracy of 0.99 It can be stated that ResNet50 with CLAHE played a very significant role in determining the covid-19 in X-ray images. © 2024, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： COVID-19

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Trigger Systems: Reusability and applicability in Serious Games

Trigger Systems: Reusability and applicability in Serious Ga...

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International Conference on System Theory, Control, and Computing (ICSTCC)

作者： Mihai-Alexandru Grosu Raul Brumar Stelian Nicola Horia Ciocârlie Computer and Informtion Technology University Politehnica Timisoara Timisoara Romania Automation and Applied Informatics University Politehnica Timisoara Timisoara Romania

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Big Data Analytics for Smart Meter Data in Power Systems 9

Big Data Analytics for Smart Meter Data in Power Systems

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9th International Conference on Science, technology, Engineering and Mathematics, ICONSTEM 2024

作者： Banu, E. Afreen Lavanya, R. Sandhiya, R. Vijayakumar, Bondu Kavitha, K. Vibhakar, Chirag Department of Computer Science And Engineering Chennai Tamil Nadu Thandalam602105 India Vel Tech High Tech Dr. Rangarajan Dr. Sakunthala Engineering College Department of Informtion Technology Chennai Tamil Nadu Avadi600062 India R M K College of Engineering And Technology Department of Computer Science And Engineering Tamil Nadu Puduvoyal601206 India Madanapalle Institute of Technology & Science Department of Electrical & Electronics Engineering Andhra Pradesh Madanapalle517325 India Annamalai University Department of Electrical & Electronics Engineering Tamil Nadu 608002 India Gujarat Power Engineering & Research Institute Gujarat Technological University Department of Electrical Engineering Gujarat Ahmedabad382710 India

ISBN: (纸本)9798350365092

The integration of big data analytics in power systems has surfaced as a promising approach to influence smart cadence data for perfecting functional effectiveness, enhancing grid trustability, and enabling demand- side operation. This paper explores the operation of big data analytics ways to reuse, dissect, and excerpt precious perceptivity from smart cadence data in power systems. By employing the vast quantum of data generated by smart measures, serviceability can gain a deeper understanding of client energy consumption patterns, identify anomalies, and optimize grid operations in real- time. The paper discusses colorful big data analytics methodologies, including machine literacy algorithms, data mining ways, and prophetic analytics models, applied to smart cadence data for cargo soothsaying, fault discovery, and energy optimization. Through a comprehensive review of being literature and case studies, this exploration elucidates the implicit benefits, challenges, and unborn directions of big data analytics for smart cadence data in power systems, offering precious perceptivity for experimenters, interpreters, and policymakers in the energy sector. © 2024 IEEE.

关键词： Big data

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Big Data Analytics for Smart Meter Data in Power Systems

Big Data Analytics for Smart Meter Data in Power Systems

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International Conference on Science technology Engineering and Management (ICONSTEM)

作者： E. Afreen Banu Lavanya R R. Sandhiya Bondu Vijayakumar K. Kavitha Chirag Vibhakar Department of Computer Science and Engineering Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences (SIMATS) Thandalam Chennai Tamil Nadu India Department of Informtion Technology Vel Tech High Tech Dr. Rangarajan Dr. Sakunthala Engineering College Avadi Chennai Tamil Nadu India Department of Computer Science and Engineering R M K College of Engineering and Technology Puduvoyal Tamil Nadu India Department of Electrical & Electronics Engineering Madanapalle Institute of Technology & Science Madanapalle Andhra Pradesh India Department of Electrical & Electronics Engineering Annamalai University Tamil Nadu India Department of Electrical Engineering Gujarat Power Engineering & Research Institute Gujarat Technological University Ahmedabad Gujarat India

ISBN: (数字)9798350365092

ISBN: (纸本)9798350365108

关键词： Reviews Energy measurement Big Data Gain measurement Time measurement Smart meters Real-time systems

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