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2024 International Conference on information technology and Computing, ICITCOM 2024

作者： Alita, Debby Ahmad, Imam Jafar Rumandan, Rhaishudin Erkamim, Moh Widyasmoro Universitas Teknokrat Indonesia Faculty of Engineering and Computer Science Bandarlampung Indonesia Institut Agama Islam Negeri Ambon Islamic Education Management Study Program Ambon Indonesia Universitas Tunas Pembangunan Smart City Information Systems Study Program Surakarta Indonesia Universitas Muhammadiyah Yogyakarta Faculty of Engineering Department of Electrical Engineering Yogyakarta Indonesia

ISBN: (纸本)9798350379839

Stunting in toddlers is a chronic nutritional issue that affects the physical and cognitive development of children, with serious long-term consequences such as reduced cognitive function and an increased risk of chronic diseases in adulthood. Therefore, early identification and prevention efforts for stunting are crucial. Classifying toddlers into categories of at-risk for stunting or not is essential to provide timely and appropriate interventions. This study employs data mining techniques using the decision tree algorithm to expedite the stunting detection process and improve the accuracy of nutritional status classification in children. The results indicate that the constructed decision tree model can classify children's nutritional status with an accuracy of 83.26%. The decision tree achieves high accuracy in classifying stunting in toddlers due to its ability to handle complex data and identify significant patterns within the data. © 2024 IEEE.

关键词： Classification Data Mining Decision Tree Stunting

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HTSA: A Hybrid Tree Seed Algorithm based on Differential Evolution with Dynamic Population Diversity Maintenance 4

HTSA: A Hybrid Tree Seed Algorithm based on Differential Evo...

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4th International Conference on Artificial Intelligence, Robotics, and Communication, ICAIRC 2024

作者： Han, Dongliang Chang, Hui Wang, Xuance Chen, Mengyao Ji, Yvzhu Hao, Xinran Zhang, Shengwei Cui, Hao Jilin University of Finance and Economics School of Management Science and Information Engineering Changchun China Zhengzhou University of Light Industry College of Electrical and Information Engineering Zhengzhou China Henan University of Science and Technology Modong Polytechnic Faculty Luoyang China

ISBN: (纸本)9798331531225

Based on the problem of Tree Seed Algorithm (TSA), this paper proposes a Hybrid Tree Seed Algorithm (Hybrid-Tree Seed Algorithm, HTSA) based on Differential Evolution and Dynamic Population Diversity Maintenance. HTSA effectively overcomes the limitations of the original TSA by introducing key enhancement mechanisms. By combining Bernoulli mapping initialization, HTSA ensures that the population distribution is more balanced and efficient compared to the stochastic mapping of TSA. Moreover, the introduction of a positional update formula inspired by the Sparrow Search Algorithm in the seed updating enhances population diversity and convergence, especially in the late optimization stages. Integration with Differential Evolution (DE) further enhances global exploration capabilities. Together, these modifications address issues such as premature convergence and sensitivity to local optimal values in *** experiments showed that HTSA outperformed TSA,EST-TSA and other benchmark algorithms, showing significant advantages in optimization power, convergence rate and population diversity. © 2024 IEEE.

关键词： Anthropogenic

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Investigating technology Issues for Smart City Development 20

Investigating Technology Issues for Smart City Development

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20th IEEE International Colloquium on Signal Processing and Its Applications, CSPA 2024

作者： Agarwal, Vernika Benmamoun, Zoubida Anjum, Misbah Apeejay School Of Management New Delhi Dwarka India Liwa College Of Technology Faculty Of Engineering Abu Dhabi United Arab Emirates Amity University Amity Institute Of Information Technology Noida India

ISBN: (纸本)9798350382310

Smart cities have gained attention in times offering the promise of enhancing urban infrastructure, sustainability and overall quality of life. The reliability and resilience of the software systems that support the interconnected technologies driving a smart city are crucial. Any glitches or disruptions, to these systems can have repercussions on the being and living standards of residents. Additionally flawed software can result in losses. Damage the reputation of communities. Since technology plays a role in smart city development it is essential to address technology related challenges to achieve urban growth. This research study explores obstacles associated with technology, in smart city development through identification and discussion using the Best-Worst method. © 2024 IEEE.

关键词： Software reliability

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Heart Disease Prediction with Hyperparameter Analysis 1

Heart Disease Prediction with Hyperparameter Analysis

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1st International Conference on Computer Science and Emerging Technologies, CSET 2023

作者： Bansal, Aashish Nallakaruppan, M.K. Mon, Feslin Anish Grover, Veena Balusamy, Balamurugan School of Information Technology and Engineering Vellore Institute of Technology Vellore India University of Technology and Applied Sciences Faculty in Department of Information Technology Ibri Oman School of Management Noida Institute of Engineering and Technology Greater Noida India Shiv Nadar University Delhi-NCR India

ISBN: (纸本)9798350341737

I propose to develop an application which would be able to predict whether someone would be suffering from a coronary heart disease in the coming years. I propose to develop a simple user interface through which the user would just need to answer certain questions which would be provided to the Machine Learning Model as an input and the prediction would be provided to the user on the interface itself. Since this interface is a ready-to-use interface, there is no need for the user to create an account or sign-up. The questions being asked here to relate to the information obtained from the tests which the user might have undergone, or the user might simply be aware of the information about himself in general. The Machine Learning model is created from the algorithms which are highly effective and could be used to deploy in the real-world scenario. While executing the program, the interface program predicts through the machine learning model which has been trained on similar kind of data. However, at this stage, this project is meant for educational purpose only with a real aim of being deployed into the real-world. This project is also helpful in processing the claims for the company because many companies tend to provide medical and insurance loans and this project can help them in custom analysis for the certain situations. © 2023 IEEE.

关键词： User interfaces

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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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Teamwork Optimization with Deep Learning Based Fall Detection for IoT-Enabled Smart Healthcare System

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Computers, Materials & Continua 2023年第4期75卷 1353-1369页

作者： Sarah B.Basahel Saleh Bajaba Mohammad Yamin Sachi Nandan Mohanty E.Laxmi Lydia Department of Management Information Systems Faculty of Economics and AdministrationKing Abdulaziz UniversityJeddahSaudi Arabia Department of business Administration Faculty of Economics and AdministrationKing Abdulaziz UniversityJeddah21589Saudi Arabia Department of Management Information Systems Faculty of Economics and AdministrationKing Abdulaziz UniversityJeddah21589Saudi Arabia School of Computer Science&Engineering(SCOPE) VIT-AP UniversityAmaravatiAndhra PradeshIndia Department of Computer Science and Engineering GMR Institute of TechnologyAndhra PradeshRajam 532127India

The current advancement in cloud computing,Artificial Intelligence(AI),and the Internet of Things(IoT)transformed the traditional healthcare system into smart *** services could be enhanced by incorporating key techniques like AI and *** convergence of AI and IoT provides distinct opportunities in the medical *** is regarded as a primary cause of death or post-traumatic complication for the ageing ***,earlier detection of older person falls in smart homes is required to improve the survival rate of an individual or provide the necessary ***,the emergence of IoT,AI,smartphones,wearables,and so on making it possible to design fall detection(FD)systems for smart home *** article introduces a new Teamwork Optimization with Deep Learning based Fall Detection for IoT Enabled Smart Healthcare Systems(TWODLFDSHS).The TWODL-FDSHS technique’s goal is to detect fall events for a smart healthcare ***,the presented TWODL-FDSHS technique exploits IoT devices for the data collection ***,the TWODLFDSHS technique applies the TWO with Capsule Network(CapsNet)model for feature *** last,a deep random vector functional link network(DRVFLN)with an Adam optimizer is exploited for fall event detection.A wide range of simulations took place to exhibit the enhanced performance of the presentedTWODL-FDSHS *** experimental outcomes stated the enhancements of the TWODL-FDSHS method over other models with increased accuracy of 98.30%on the URFD dataset.

关键词： Internet of things smart healthcare deep learning team work optimizer capsnet fall detection

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Evaluation of cloud computing risks using an integrated fuzzy-ANP and FMEA approaches

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International Journal of Applied Decision Sciences 2023年第2期16卷 131-164页

作者： Yazdani, Ata Allah Keramati, Abbas Turetken, Ozgur Palanichamy, Yazwand E-Campus of the Islamic Azad University 9th Neyestan Pasdaran Tehran Iran Ted Rogers School of Information Technology Management Ryerson University TorontoON Canada School of Industrial Engineering Faculty of Engineering University of Tehran Tehran Iran

Despite the considerable benefits of cloud-based services and their effect on the reduction of total investments in information technology (IT) infrastructures, there still exist a plethora of concerns regarding the potential risk of this relatively new method of resource outsourcing. Due to the diversity of activities in the risk management process, it is essential to develop an innovative framework for controlling and streamlining relevant processes. Such processes include the identification, ranking, and determination of relevant exposure strategies and risk responsiveness strategies. The proposed framework developed in this study was based on the risk management process phase of the PMBOK model to analyse the collected data via fuzzy analytical network processing and failure mode effective analysis methods. A survey was then drafted with participating IT experts. Results demonstrate that the three most important risks are data confidentiality, data integrity and reliability. Furthermore, 117 risk-responsiveness solutions such as auditing the scope of access to information, using relevant techniques to control data integrity, and implementing appropriate training programs for the support team within the organisation were recognised and ranked to suggest the most appropriate remedial strategies that extensively mitigate against identified risks. Copyright © 2023 Inderscience Enterprises Ltd.

关键词： Failure modes

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OMNI- CHANNEL RETAILING FOR ENHANCING CUSTOMER ENGAGEMENT AMIDST SUPPLY CHAIN DISRUPTION: AN EMERGING MARKET PERSPECTIVE

Decision Making: Applications in Management and Engineering

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Decision Making: Applications in management and engineering 2023年第1期6卷 449-473页

作者： Joshi, Sudhanshu Sharma, Manu Chatterjee, Prasanjit Operations and Supply Chain Management Research Laboratory School of Management Doon University Dehradun India School of Computer Science Faculty of Engineering & Information Technology University of Technology Sydney Sydney Australia Department of Management Studies Graphic Era Deemed to be University Dehradun India Guidhall School of Business and Law London Metropolitan University London United Kingdom MCKV Institute of Engineering West Bangal India

The research aims to explore the strength of enablers and adoption barriers in omnichannel retailing (OCR) and discuss how organizations may focus on redesigning their business models in emerging markets to manage the disruptive environment. The major enablers may enhance the omnichannel' performance to deliver a unified experience across all channels during the pandemic. The paper has used hybrid Multi-Criteria Decision-Making (MCDM) Methods. Organizations widely use these methods to explore the interrelationship among barriers and enablers affecting their performance. In the current study, 18 experts from different domains have examined and evaluated the 10 barriers and 7 enablers. The study reveals that integration, Visibility, internet accessibility, and advanced distribution centers are the primary enablers and driving the customer analytics enabler to strengthen their customer engagement and providing a unified experience to the. During the pandemic time the usage of the online channels have increased and thus retail channels may consider these enablers to enhance the unified experience level of the customers. The study also shows that inconsistency in price is the main adoption barrier followed by inconsistency in product discounts that should be minimized to engage customers effectively. The retail organizations need to understand the roadblocks in adopting OCR and should take relevant actions to minimize them. The retail organization or marketers may redesign their existing strategies based on price consistency, integration, Visibility, information systems, and coordination to develop a unified experience across channels during the pandemic situation. © 2023 by the authors.

关键词： Visibility

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Minimizing the Number of Stunting Prevalence Using the Euclid Algorithm Clustering Approach 7

Minimizing the Number of Stunting Prevalence Using the Eucli...

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7th IEEE International Conference of Computer Science and information technology, ICOSNIKOM 2023

作者： Zarlis, Muhammad Oktavia, Tanty Buaton, Relita Ernawan, Ferda Andrian, Kevin Bina Nusantara University Information System Management Department BINUS Graduate Program - Master of Information System Management Jakarta11480 Indonesia STMIK Kaputama Informatics Engineering Binjai20714 Indonesia Universiti Malaysia Pahang Al-Sultan Abdullah Faculty of Computing Pekan26600 Malaysia BINUS Graduate Program-Master of Information Systems Management Bina Nusantara University Department of Information Systems Management Jakarta Indonesia

ISBN: (纸本)9798350360752

Superior and quality human resources are based on healthy human resources with indicators of adequate nutritional intake according to age development. However, the world still faces the problem of hunger and malnutrition today. According to a UNICEF report, the number of people suffering from malnutrition in the world will reach 767.9 million people in 2021. The World Health Organization (WHO) said that malnutrition is a dangerous threat to the health of the world's population. Stunting also has an impact in Indonesia, the prevalence of toddlers experiencing stunting in Indonesia is 24.4% in 2021. The solution created is to classify and cluster the prevalence of stunting to produce a pattern that can be used as best practice to be transmitted to other affected areas. The algorithm used is Euclid. The Euclid algorithm can cluster stunting prevalence data into 4 clusters with the very little category at 79%, the little category at 67%, the many categories at 51%, and the very much category at 21%. The results of the classification and clustering of the best stunting prevalence in cluster one with a very small number, can be used as a source of accurate and updated information that can be used by the government in its efforts to optimize stunting handling in each district/city based on artificial intelligence which can provide handling and optimization patterns. stunting in every district/city. © 2023 IEEE.

关键词： Classification (of information)

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Analysis Geomorphic Flood Index in Determining Flood-Prone Areas in East Kalimantan Province, Indonesia

Analysis Geomorphic Flood Index in Determining Flood-Prone A...

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2024 Annual Conference, ASPRS 2024

作者： Virtriana, Riantini Amalia, Annisa Fitri Ihsan, Kalingga Titon Nur Anggraini, Tania Septi Harto, Agung Budi Deliar, Albertus Geospatial Information Science and Technology Research Group Faculty of Earth Science and Technology Bandung Institute of Technology Bandung40132 Indonesia Center for Remote Sensing Bandung Institute of Technology Bandung40132 Indonesia Geodesy and Geomatic Engineering Faculty of Earth Sciences and Technology Bandung40132 Indonesia Doctor Program in Program Study of Geodesy and Geomatic Engineering Faculty of Earth Sciences and Technology Bandung40132 Indonesia Universitas Pendidikan Indonesia Bandung40111 Indonesia Center for Spatial Data Infrastructure Bandung Institute of Technology Bandung40132 Indonesia

In 2022, there are 1,524 flood events out of a total of 3,531 disasters occurring in Indonesia. East Kalimantan Province ranked 20th among the 35 provinces in Indonesia with 28 flood occurrences in 2022, resulting in two fatalities. This highlights the urgent need for addressing flood hazard to prevent future casualties. There are some methods that can be used to determine the flood hazard in a region. In this research aims to identify flood-prone areas in East Kalimantan Province and evaluate the effectiveness of different mapping methods. The methodology that compares are the Pairwise Comparison method and Geomorphic Flood Index (GFI). The study's results provide flood-prone area maps of East Kalimantan Province using both methods, recommend the more efficient method for flood-prone area identification, and offer mitigation strategies based on the findings. This research is intended to serve as a reference for selecting the best method for identifying flood-prone areas and for informing policy decisions to mitigate flood impacts in East Kalimantan Province. © Author(s) 2025.

关键词： Hazards

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