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2nd International Conference on sciences and technology Applications, ICOSTA 2020

作者： Retno Susilorini, Rr M. I. Pamudji, Andre Kurniawan Sanjaya, Ridwan Ismail, Amrizarois Amasto, Ardhito Hayyu Department of Infrastructure and Environmental Engineering Faculty of Environmental Science and Technology Soegijapranata Catholic University Semarang Indonesia Master Program of Environmental and Urban Studies Faculty of Environmental Science and Technology Soegijapranata Catholic University Semarang Indonesia Department of Information System Faculty of Computer Science Soegijapranata Catholic University Semarang Indonesia

Indonesia had been suffered by earthquake and tsunami for many centuries. Since many lives have taken by tsunami strikes, alert and response system are very important as important part of Disaster Risk Reduction, especially in area with high population density. This research conducted in Kangkung fishing village in Bandar Lampung coastal area which is an earthquake and tsunami prone area. The aim of the research is to study alert and response of Community Based Disaster Risk Reduction. The research conducted by qualitative method and purposive-descriptive approach. There were 53 respondents which participated in the survey and interview. It is reported that "Smart Resilient City"model suitable for community needs of alert and response of earthquake and tsunami disaster. This research meets conclusion that "Smart Resilient City"model may become a great solution in Community Based Disaster Risk Reduction to cope with the hazard of earthquake and tsunami comprehensively and sustainably. © Published under licence by IOP Publishing Ltd.

关键词： Surveys

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AV-Lip-Sync+: Leveraging AV-HuBERT to Exploit Multimodal Inconsistency for Video Deepfake Detection

arXiv

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arXiv 2023年

作者： Shahzad, Sahibzada Adil Hashmi, Ammarah Peng, Yan-Tsung Tsao, Yu Wang, Hsin-Min The Social Networks and Human-Centered Computing Program Taiwan International Graduate Program Academia Sinica Taipei11529 Taiwan The Department of Computer Science National Chengchi University Taipei11605 Taiwan The Institute of Information Systems and Applications National Tsing Hua University Hsinchu30013 Taiwan The Research Center for Information Technology Innovation Academia Sinica Taipei11529 Taiwan The Institute of Information Science Academia Sinica Taipei11529 Taiwan

Multimodal manipulations (also known as audiovisual deepfakes) make it difficult for unimodal deepfake detectors to detect forgeries in multimedia content. To avoid the spread of false propaganda and fake news, timely detection is crucial. The damage to either modality (i.e., visual or audio) can only be discovered through multi-modal models that can exploit both pieces of information simultaneously. Previous methods mainly adopt uni-modal video forensics and use supervised pre-training for forgery detection. This study proposes a new method based on a multi-modal self-supervised-learning (SSL) feature extractor to exploit inconsistency between audio and visual modalities for multi-modal video forgery detection. We use the transformer-based SSL pre-trained Audio-Visual HuBERT (AV-HuBERT) model as a visual and acoustic feature extractor and a multi-scale temporal convolutional neural network to capture the temporal correlation between the audio and visual modalities. Since AV-HuBERT only extracts visual features from the lip region, we also adopt another transformer-based video model to exploit facial features and capture spatial and temporal artifacts caused during the deepfake generation process. Experimental results show that our model outperforms all existing models and achieves new state-of-the-art performance on the FakeAVCeleb and DeepfakeTIMIT datasets. © 2023, CC BY.

关键词： Audio acoustics

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Prediction of Consumer Purchase Intention on Green Product

Prediction of Consumer Purchase Intention on Green Product

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2021 International Seminar on Application for technology of information and Communication, iSemantic 2021

作者： Hariyadi, Guruh Taufan Purwanto Isnanto, R Rizal Wibowo, Adi Warsito, Budi Universitas Diponegoro Doctoral Program of Information Systems Semarang Indonesia Universitas Diponegoro Faculty of Engineering Department of Chemical Engineering Semarang Indonesia Universitas Diponegoro Faculty of Engineerig Department of Computer Engineering Semarang Indonesia Universitas Diponegoro Faculty of Science and Mathematics Departement of Informatics Semarang Indonesia

ISBN: (纸本)9781665428040

Education to the public on green products has been widely carried out. Consumers who buy green products can be profiled by segmenting green consumers. In green marketing, consumer education on sustainable consumption is increasingly needed in recent years due to the problem of environmental pollution which poses a serious threat to the world population. Concern for the environment is an important topic in most countries, and individuals also study environmental issues. Individuals or groups of individuals who are 'ecologically aware' are also referred to as 'green consumers.' Such consumers are considered to have more concern for the environment. This study examined the predictions on the effect of the Green Perceived Value variables consisting of functional, conditional, and social values on the purchase intention of green consumers. It also tested the comparisons with other classification models. The models used in this research were Random Forest, Decision Tree, and Neural Network.. © 2021 IEEE.

关键词： Consumer behavior

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Adaptive Curriculum Learning for Semi-supervised Segmentation of 3D CT-Scans 28th

Adaptive Curriculum Learning for Semi-supervised Segmentati...

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28th International Conference on Neural information Processing, ICONIP 2021

作者： Nartey, Obed Tettey Yang, Guowu Agyapong, Dorothy Araba Yakoba Wu, JinZhao Sarpong, Asare K. Frempong, Lady Nadia Big Data Research Center School of Computer Science and Engineering University of Electronic Science and Technology of China Chengdu611731 China The School of Computer Science and Electronic Information Guangxi University Nanning530004 China Biomedical Engineering Program Kwame Nkrumah University of Science and Technology Kumasi Ghana School of Information and Software Engineering University of Electronic Science and Technology of China Chengdu China School of Medicine Department of Radiology and Imaging Sciences Emory University 1364 Clitton Rd. AtlantaGA30322 United States

ISBN: (纸本)9783030921842

Semi-supervised learning algorithms make use of both labelled training data and unlabelled data. However, the visual domain gap between these sets poses a challenge which prevents deep learning models from obtaining the results they have achieved most especially in the field of medical imaging. Recently, self-training with deep learning has become a powerful approach to leverage labelled training and unlabelled data. However, a challenge of generating noisy pseudo-labels and placing over-confident labelling belief on incorrect classes leads to deviation from the solution. To solve this challenge, the study investigates a curriculum-styled approach for deep semi-supervised segmentation which relaxes and treats pseudo-labels as continuous hidden variables by developing an adaptive pseudo-label generation strategy to jointly optimized the pseudo-label generation and selection process. A regularization scheme is further proposed to smoothen the probability outputs and sharpen the less represented pseudo-label regions. The proposed method was evaluated on three publicly available computer Tomography (CT) scan benchmarks and extensive experiments on all modules have demonstrated the efficacy of the proposed method. © 2021, Springer Nature Switzerland AG.

关键词： Curricula

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The Impact of Middle and High School Students Participation in the Innovation Nation Competition on Their Education

The Impact of Middle and High School Students Participation ...

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information technology (ACIT)

作者： Dheya Mustafa Samah Zriqat Intisar Ghazi Mustafa Qutaibah AlThebyan dept. of Computer Engineering College of Engineering The Hashemite University Zarqa Jordan dept. of Information Technology and Computer Science Yarmouk University Irbid Jordan dept. of Educational Sciences College of Education Qatar University Doha Qatar Cybersecurity Program Al Ain University Al Ain UAE Jordan University of Science and Technology Irbid Jordan

The Innovative Nation competition is a Jordanian initiative that uses workshops, training camps, and competitions to improve students' general and soft skills, problem-solving, creativity, and invention. The curriculum is divided into three parts, each of which has the potential to increase interest in science, technology, Engineering, and Mathematics (STEM). The goal of this research is to determine how much the STEM competition has influenced students' education and decision to pursue jobs in science and technology. Personal interviews with students and mentors were employed in this study to assess their skill sets, prospective career paths, and interests. The collected data was reviewed, and it was found that participation in the Innovation Nation competition increased students' interest in STEM vocations.

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Integrated-Regression and Whale Optimisation Algorithms to post stroke rehabilitation analysis: A case study for serious games

Integrated-Regression and Whale Optimisation Algorithms to p...

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2021 IEEE Symposium on computers and Informatics, ISCI 2021

作者： Ismail, Waidah Grosan, Crina Abdullah, Zul Hilmi Aldailamy, Ali Y. Zainal, Nurezayana Hendradi, Rimuljo Faculty Science and Technology Universiti Sains Islam Malaysia Bandar Baru Nilai Negeri Sembilan Malaysia International Halal and Fatwa CenterUniversiti Sains Islam Malaysia Bandar Baru Nilai Negeri Sembilan Malaysia Faculty of Information Technology Inti International University Bandar Baru Nilai Negeri Sembilan Malaysia Department of Computer Science Brunel University Uxbridge United Kingdom Faculty of Computer Science and Information Technology Universiti Putra Malaysia Selangor Malaysia Information System Study Program Universitas Airlangga Surabaya Indonesia

ISBN: (纸本)9781665402767

Stroke is one of the leading causes of death and long-term disability worldwide. The primary goal of post-stroke rehabilitation is to maximize the independence of the affected individuals by facilitating both neurological and compensatory functional recoveries in their daily lives. This paper presents an integrated study, using multiple linear regression (MLR) and whale optimization algorithm, for optimizing the post-stroke rehabilitation performance using Medical Interactive Rehabilitation Assistant (MIRA). MIRA is one of the serious games using virtual reality. The research objective finding the best games settings for MIRA. Analysis of variance and F-test were performed to justify the goodness of fit of the developed mathematical models, as well as the significance of the individual MIRA input settings of the games. Results demonstrated that the developed MLR models for average acceleration and distance were significant, with P=0.018 and P © 2021 IEEE.

关键词： Optimization

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Integration of Artificial Intelligence in Software Defined Networking technology through Developing Machine Learning Algorithms

Integration of Artificial Intelligence in Software Defined N...

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Advance Computing and Innovative Technologies in Engineering (ICACITE), International Conference on

作者： Lamhot Naibaho Pulkit Raj Saxena Kuldeep Sharma Badria Sulaiman Alfurhood L. Pallavi Bhasker Pant English Language Education Study Program Faculty of Letters and Languages Christian University of Indonesia College of Computing Science and Information Technology Teer Thanker Mahaveer University Moradabad Uttar Pradesh India Department of Computer Science and Engineering Lovely Professional University Phagwara Jalandhar Punjab India Department of Computer Sciences College of Computer Information Sciences Princess Nourah Bint Abdulrahman University Saudi Arabia CSE B V Raju Institute of Technology Narsapur Telangana India Computer Science & Engineering Graphic Era Deemed to be University Dehradun Uttarakhand India

A future networking design called "software-defined networking" combines network programmability with centralized administration (SDN). Network administration is currently handled by SDN, which, at the regulator, which acts as the cable network processor and divides the data plane into a control plane and a data aircraft. Recent breakthroughs in artificial intelligence (Al) have shown a stronger inclination for the science community to benefit from their ability to give learning capabilities and enhance Indicator. The author of this research provides a comprehensive analysis of initiatives underway to incorporate Al with SDN. The study concluded that the three primary Al thread where scientific research was centered were computer science, conceptual, and fuzzy reasoning systems. The authors of this paper explore the several fields in which these approaches may be used, their potential future applications, and the innovations made possible by the integration of AI-based methods into the SDN paradigm. By choosing the right SDN controller, any large organization may lower network complexity, implementation expenses, and maintenance costs. The focus of this article is software defined networking's benefits and downsides (SDN). Following is a basic explanation of artificial intelligence and a list of some of its most significant applications in SDN.

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Accuracy of the TOPSIS Method with Different Input Data 26

Accuracy of the TOPSIS Method with Different Input Data

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26th International Conference on Knowledge-Based and Intelligent information and Engineering Systems, KES 2022

作者： Król, Robert Wieckowski, Jakub Watróbski, Jaroslaw Doctoral School of University of Szczecin ul. Mickiewicza 16 Szczecin70-383 Poland Research Team on Intelligent Decision Support Systems Department of Artificial Intelligence Methods and Applied Mathematics Faculty of Computer Science and Information Technology West Pomeranian University of Technology Szczecin ul. Zolnierska 49 Szczecin71-210 Poland Institute of Management University of Szczecin ul. Cukrowa 8 Szczecin71-004 Poland

Using fuzzy logic in multi-criteria problems allows real-world problems to be modeled with greater accuracy. In addition, it is possible to solve problems in which all data are incomplete. The difficulty may be the choice of an appropriate technique leading to a ranking calculation. Methods fully integrated with fuzzy logic can be used. It is also possible to convert fuzzy data to crisp values and then apply traditional MCDA methods. In this paper, the performance of the TOPSIS method in a crisp and fuzzy environment was analyzed. The approaches of operating fully on uncertain data when calculating preference values were compared with converting data to crisp values using selected membership functions. The research has shown that significant differences and discrepancies in how the alternatives are classified are noticeable in the rankings. © 2022 The Authors. Published by Elsevier B.V.

关键词： Fuzzy logic

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Optimized Security Mechanism for publicly Secret Key Sharing over Cloud using Blockchain

Optimized Security Mechanism for publicly Secret Key Sharing...

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2024 International Symposium on Securing Next Generation Systems Using Future Artificial Intelligence Technologies, SNSFAIT 2024

作者： Byeon, Haewon Quraishi, Aadam Thuniki, Praveen Keshta, Ismail Soni, Mukesh Shabaz, Mohammad Department of AI and Software Inje University Gimhae50834 Korea Republic of Inje University Medical Big Data Research Center Gimhae50834 Korea Republic of Intervention Treatment Institute HoustonTX United States Sr Program Analyst Georgia CummingGA30040 United States Computer Science and Information Systems Department College of Applied Sciences Al Maarefa University Riyadh Saudi Arabia Dr. D. Y. Patii Vidyapeeth Pune Dr. D. Y. Patii School of Science & Technology Tathawade Pune India Model Institute of Engineering and Technology J&K Jammu India

A publicly verifiable key sharing mechanism based on threshold key sharing is provided to explore the security of users' private keys on the blockchain. Participating nodes check the key fragment after receiving it, effectively preventing it from being abused. The crucial sections of the nodes that participated in the critical splicing are made public during the critical recovery stage to prevent them from performing harmful things during the critical recovery stage. Add IDs to the nodes that participated in the crucial splicing during the key distribution stage;a dynamic threshold system is intended to track and update the status of malicious nodes in real time. When the node that possesses the crucial component fails, the owner of the critical component and the main node relocate a key element to the new participating nodes. To safeguard sensitive information. The experimental results show that this system has a key recovery rate of 80% and threshold qualities such as traceability, enforceability, and recoverability. © 2024 Copyright for this paper by its authors.

关键词： Blockchain Encryption Key sharing mechanism Privacy Secret key Security

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Towards robust results in Multi-Criteria Decision Analysis: ranking reversal free methods case study 26

Towards robust results in Multi-Criteria Decision Analysis: ...

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26th International Conference on Knowledge-Based and Intelligent information and Engineering Systems, KES 2022

作者： Wieckowski, Jakub Król, Robert Watróbski, Jaroslaw Research Team on Intelligent Decision Support Systems Department of Artificial Intelligence Methods and Applied Mathematics Faculty of Computer Science and Information Technology West Pomeranian University of Technology Szczecin ul. Zolnierska 49 Szczecin71-210 Poland Doctoral School of University of Szczecin ul. Mickiewicza 16 Szczecin70-383 Poland Institute of Management University of Szczecin ul. Cukrowa 8 Szczecin71-004 Poland

The practical capabilities of decision support systems are beneficial in many complex problems. They aim to equip the decision-maker with knowledge about the preferred choices from the set under consideration. Often, there are minor differences between the alternatives analyzed, making it necessary to determine whether changes in the parameters characterizing them can influence their final position. For this purpose, a sensitivity analysis of the solutions can be used to examine the resistance of the results to changes. In this paper, we address the problem of performing the sensitivity analysis using MCDA methods. Most studies focus on testing the sensitivity of rankings of popular methods. However, their main disadvantage is their susceptibility to the phenomenon of ranking reversal. It may distort the results obtained in a sensitivity analysis. Therefore, it is worth using methods resistant to the ranking reversal phenomenon for this purpose. The SPOTIS and COMET methods were used in a theoretical multi-criteria problem, where the calculated results were then subjected to sensitivity analysis. The study showed that the SPOTIS method tends to be more robust to the computed results. © 2022 The Authors. Published by Elsevier B.V.

关键词： Sensitivity analysis

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