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arXiv 2024年

作者： Hashmi, Ammarah Shahzad, Sahibzada Adil Lin, Chia-Wen Tsao, Yu Wang, Hsin-Min Social Networks and Human-Centered Computing Program Taiwan International Graduate Program Institute of Information Science Academia Sinica Taipei11529 Taiwan Institute of Information Systems and Applications National Tsing Hua University Hsinchu300044 Taiwan Department of Computer Science National Chengchi University Taipei11529 Taiwan Department of Electrical Engineering Institute of Communications Engineering National Tsing Hua University Hsinchu300044 Taiwan Research Center for Information Technology Innovation Academia Sinica Taipei11529 Taiwan Institute of Information Science Academia Sinica Taipei11529 Taiwan

The emergence of contemporary deepfakes has attracted significant attention in machine learning research, as artificial intelligence (AI) generated synthetic media increases the incidence of misinterpretation and is difficult to distinguish from genuine content. Currently, machine learning techniques have been extensively studied for automatically detecting deepfakes. However, human perception has been less explored. Malicious deepfakes could ultimately cause public and social problems. Can we humans correctly perceive the authenticity of the content of the videos we watch? The answer is obviously uncertain;therefore, this paper aims to evaluate the human ability to discern deepfake videos through a subjective study. We present our findings by comparing human observers to five state-of-the-art deepfake detection models. To this end, we used gamification concepts to provide 110 participants (55 native English speakers and 55 non-native English speakers) with a web-based platform where they could access a series of 40 videos (20 real and 20 fake) to determine their authenticity. Each participant performed the experiment twice with the same 40 videos in different random orders. The videos are manually selected from the FakeAVCeleb dataset. We found that all AI models performed significantly better than humans when evaluated on the same 40 videos. The study also reveals that while deception is not impossible, humans tend to overestimate their detection capabilities. Our experimental results may help benchmark human versus machine performance, advance forensics analysis, and enable adaptive countermeasures. © 2024, CC BY.

关键词： Audiovisual

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Understanding Audiovisual Deepfake Detection: Techniques, Challenges, Human Factors and Perceptual Insights

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arXiv 2024年

作者： Hashmi, Ammarah Shahzad, Sahibzada Adil Lin, Chia-Wen Tsao, Yu Wang, Hsin-Min The Social Networks and Human-Centered Computing Program Taiwan International Graduate Program Institute of Information Science Academia Sinica Taipei11529 Taiwan The Institute of Information Systems and Applications National Tsing Hua University Hsinchu300044 Taiwan The Department of Computer Science National Chengchi University Taipei11529 Taiwan The Department of Electrical Engineering The Institute of Communications Engineering National Tsing Hua University Hsinchu300044 Taiwan The Research Center for Information Technology Innovation Academia Sinica Taipei11529 Taiwan The Institute of Information Science Academia Sinica Taipei11529 Taiwan

Deep Learning has been successfully applied in diverse fields, and its impact on deepfake detection is no exception. Deepfakes are fake yet realistic synthetic content that can be used deceitfully for political impersonation, phishing, slandering, or spreading misinformation. Despite extensive research on unimodal deepfake detection, identifying complex deepfakes through joint analysis of audio and visual streams remains relatively unexplored. To fill this gap, this survey first provides an overview of audiovisual deepfake generation techniques, applications, and their consequences, and then provides a comprehensive review of state-of-the-art methods that combine audio and visual modalities to enhance detection accuracy, summarizing and critically analyzing their strengths and limitations. Furthermore, we discuss existing open source datasets for a deeper understanding, which can contribute to the research community and provide necessary information to beginners who want to analyze deep learning-based audiovisual methods for video forensics. By bridging the gap between unimodal and multimodal approaches, this paper aims to improve the effectiveness of deepfake detection strategies and guide future research in cybersecurity and media integrity. © 2024, CC BY.

关键词： Audiovisual

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Dynamic programming Algorithm using Furniture Industry 0/1 Knapsack Problem

Dynamic Programming Algorithm using Furniture Industry 0/1 K...

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International Conference on Cybernetics and Intelligent System (ICORIS)

作者： Mietha Anditta Natashya Amartya Laurens Spits Warnars Harco Leslie Hendric Spits Warnars Arief Ramadhan Teddy Siswanto Teddy Mantoro Nurulhuda Noordin Computer Science Departement School of Computer Science Bina Nusantara University Jakarta Indonesia Information Systems Departement School of Information Systems Bina Nusantara University Jakarta Indonesia Computer Science Departement BINUS Graduate Program - Computer Science Bina Nusantara University Jakarta Indonesia PJJ Informatika Telkom University Bandung Indonesia Information Systems Department Trisakti University Jakarta Indonesia Faculty of Engineering and Technology Sampoerna University Jakarta Indonesia School of Computing Sciences College of Computing Informatics and Mathematics Universiti Teknologi MARA Selangor Malaysia

Dynamic programming is a fundamental algorithm that can be found in our daily lives easily. One of the dynamic programming algorithm implementations consists of solving the 0/1 knapsack problem. A 0/1 knapsack problem can be seen from industrial production cost. It is prevalent that a production cost has to be as efficient as possible, but the expectation is to get the proceeds of the products higher. Thus, the dynamic programming algorithm can be implemented to solve the diverse knapsack problem, one of which is the 0/1 knapsack problem, which would be the main focus of this paper. The implementation was implemented using C language. This paper was created as an early implementation algorithm using a Dynamic program algorithm applied to an Automatic Identification System (AIS) dataset.

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The role of input imaging combination and ADC threshold on segmentation of acute ischemic stroke lesion using U-Net

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European Radiology 2023年第9期33卷 6157-6167页

作者： Li, Ya-Hui Lin, Shao-Chieh Chung, Hsiao-Wen Chang, Chia-Ching Peng, Hsu-Hsia Huang, Teng-Yi Shen, Wu-Chung Tsai, Chon-Haw Lo, Yu-Chien Lee, Tung-Yang Juan, Cheng-Hsuan Juan, Cheng-En Chang, Hing-Chiu Liu, Yi-Jui Juan, Chun-Jung Graduate Institute of Biomedical Electronics and Bioinformatics National Taiwan University Taipei Taiwan Department of Medical Imaging China Medical University Hsinchu Hospital No. 199 Sec. 1 Xinglong Rd. Zhubei City Hsinchu County 302 Hsinchu Taiwan Ph.D. Program in Electrical and Communication Engineering Feng Chia University Taichung Taiwan Department of Electrical Engineering National Taiwan University Taipei Taiwan Department of Management Science National Yang Ming Chiao Tung University Hsinchu Taiwan Department of Biomedical Engineering and Environmental Sciences National Tsing Hua University Hsinchu Taiwan Department of Electrical Engineering National Taiwan University of Science and Technology Taipei Taiwan Department of Radiology School of Medicine College of Medicine China Medical University Taichung Taiwan Department of Medical Imaging Medical University Hospital Taichung Taiwan Department of Neurology China Medical University Hospital Taichung Taiwan Cheng Ching Hospital Taichung Taiwan Master’s Program of Biomedical Informatics and Biomedical Engineering Feng Chia University Taichung Taiwan Department of Automatic Control Engineering Feng Chia University No. 100 Wenhwa Rd. Seatwen Taichung 40724 Taiwan Department of Biomedical Engineering The Chinese University of Hong Kong ERB1112 11/F William M.W. Mong Engineering Building N.T Shatin Hong Kong Multi-Scale Medical Robotics Center The Chinese University of Hong Kong N.T Shatin Hong Kong Department of Biomedical Engineering National Defense Medical Center Taipei Taiwan Department of Computer Science and Information Engineering National Taiwan University Taipei Taiwan

Background: To evaluate the effect of the weighting of input imaging combo and ADC threshold on the performance of the U-Net and to find an optimized input imaging combo and ADC threshold in segmenting acute ischemic stroke (AIS) lesion. Methods: This study retrospectively enrolled a total of 212 patients having AIS. Four combos, including ADC-ADC-ADC (AAA), DWI-ADC-ADC (DAA), DWI-DWI-ADC (DDA), and DWI-DWI-DWI (DDD), were used as input images, respectively. Three ADC thresholds including 0.6, 0.8 and 1.8 × 10^–3 mm²/s were applied. Dice similarity coefficient (DSC) was used to evaluate the segmentation performance of U-Nets. Nonparametric Kruskal–Wallis test with Tukey–Kramer post-hoc tests were used for comparison. A p <.05 was considered statistically significant. Results: The DSC significantly varied among different combos of images and different ADC thresholds. Hybrid U-Nets outperformed uniform U-Nets at ADC thresholds of 0.6 × 10^–3 mm²/s and 0.8 × 10^–3 mm²/s (p <.001). The U-Net with imaging combo of DDD had segmentation performance similar to hybrid U-Nets at an ADC threshold of 1.8 × 10^–3 mm²/s (p =.062 to 1). The U-Net using the imaging combo of DAA at the ADC threshold of 0.6 × 10^–3 mm²/s achieved the highest DSC in the segmentation of AIS lesion. Conclusions: The segmentation performance of U-Net for AIS varies among the input imaging combos and ADC thresholds. The U-Net is optimized by choosing the imaging combo of DAA at an ADC threshold of 0.6 × 10^–3 mm²/s in segmentating AIS lesion with highest DSC. Key Points: • Segmentation performance of U-Net for AIS differs among input imaging combos. • Segmentation performance of U-Net for AIS differs among ADC thresholds. • U-Net is optimized using DAA with ADC = 0.6 × 10^–3mm²/s. © 2023, The Author(s), under exclusive licence to European Society of Radiology.

关键词： Deep Learning Diffusion Magnetic Resonance Imaging Ischemic Stroke Neural Networks, computer Retrospective Study

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A Heuristic Approach using Block Chain to Fight Novel COVID-19 During an Election

A Heuristic Approach using Block Chain to Fight Novel COVID-...

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IEEE Conference on Innovative Technologies in Intelligent Systems and Industrial Applications (CITISIA)

作者： Ira Nath Pratnadeep Biswas Kankana Ganguly Dharmpal Singh Sardar M.N. Islam Ton Quang Cuong Souvik Pal Computer Science & Engineering JIS College of Engineering Kalyani India ISILC and Decision Sciences and Modeling Program Victoria University Australia Vietnam National University Hanoi Vietnam Computer Science & Engineering Global Institute of Management and Technology Krisnanagar India

ISBN: (纸本)9781665417853

India is a highly densely populated country. India is facing a very serious challenge due to the novel COVID-I9 outbreak. In this situation, the economic state of the people is very unstable. Blockchain technology proves helpful to subdue the situation. A voting system with ballot papers is quite tuff now. It is very costly for the government. The pandemic may also spread very quickly. The system of developing ledger serves the idea of developments of a new e-voting system that is economical, easy to use, and highly secure. This paper proposes ways and solutions to design an e-voting system using blockchain technology. The paper's primary goal is to develop a highly secure e-voting technique using which people can cast their valuable votes from their home, working place - anywhere from the world. This e-voting technique is least costly, highly secure, and able to prevent further spreading of any infectious disease in the near future. In this paper, an e-voting system using blockchain has been designed to overcome all these difficulties mentioned above during traditional voting using ballot. The significance of the proposed work is to design of a highly safe and least costly e- voting system using blockchain. Using this system the people can cast their vote easily, securely and without wasting any time. Casting vote will be now just from few clicks away and from any place with a stable internet connection.

关键词： COVID-19 Economics Casting Pandemics Infectious diseases Blockchains Electronic voting

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GNN-Based Point Cloud Maps Feature Extraction and Residual Feature Fusion for 3D Object Detection

GNN-Based Point Cloud Maps Feature Extraction and Residual F...

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IEEE International Conference on Robotics and Automation (ICRA)

作者： Wei-Hsiang Liao Chieh-Chih Wang Wen-Chieh Lin Graduate Degree Program of Artificial Intelligence National Yang Ming Chiao Tung University Hsinchu Taiwan Department of Electrical and Computer Engineering National Yang Ming Chiao Tung University Hsinchu Taiwan Mechanical and Mechatronics Systems Research Laboratories Industrial Technology Research Institute Hsinchu Taiwan Institute of Multimedia Engineering National Yang Ming Chiao Tung University Hsinchu Taiwan

LiDAR detection of long-range vehicles is challenging because very few and sparse points are measured in long distances and vehicles with similar shapes of targets could lead to false positives easily. To tackle these challenges, taking the environment information (HD maps) into account could be beneficial to predetermine where targets are more or less likely to appear. Compared with semantic maps, HD maps formed by point clouds provide much richer information from surrounding static objects and scenes. In this work, we construct a GNN-based feature extraction of point cloud maps to increase the receptive fields of learning map features. Our work is based on PVRCNN, the state-of-the-art LiDAR object detection method. With point-wise and voxel-wise features obtained from PVRCNN, residual feature fusion is proposed to fuse the features from PVRCNN and the map features from GNN. Our approach is evaluated on NuScenes dataset. It achieves a 24.78% average precision improvement for long-range objects at 40–50 meters, the farthest areas with ground truth annotation. Our approach also has a 4.22% reduction of false positives in the entire sensing areas.

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Automated Eight-Arm Maze Trajectory Tracking System for Feature Extraction of TBI Animals

Automated Eight-Arm Maze Trajectory Tracking System for Feat...

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ACIS International Conference on Software engineering, Artificial Intelligence, Networking, and Parallel/Distributed Computing (SNPD)

作者： Shu-Cing Wu Chi-Yuan Lin Liang-Jyun Hong Chi-Chun Chen Ph.D. Program Prospective Technology of Electrical Engineering and Computer Science National Chin-Yi University of Technology Taichung Taiwan National Chin-Yi University of Technology Taichung Taiwan

ISBN: (纸本)9781665447324

Traumatic Brain Injury (TBI) is most commonly accident injury in modern society. The deterioration of cognition and memory is a common phenomenon caused by TBI. Most of the basic experiments used rats for pathological research. Moreover, an eight-arm maze was often used to test the spatial learning behavior of brain diseases, such as Alzheimer’s disease and TBI. However, most of maze experimental data were collected in manual records. This process would take a lot of manpower and time. Therefore, the research built an automatic tracking trajectory system of the eight-arm maze to collect experiment data. Furthermore, the path trajectory of the rat can be recorded in time. Finally, these path trajectory data were used to analysis behavior feature of TBI animals. The results showed that TBI rats have a 40%~80% chance of having a trajectory to the right.

关键词： Pathology Trajectory tracking Manuals Rats Feature extraction Cognition Trajectory

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Mechatronic Design of an Amphibious Drone

Mechatronic Design of an Amphibious Drone

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International Conference on Autonomous Robots and Agents, ICARA

作者： Nikolaos Evangeliou Dimitris Chaikalis Nikolaos Giakoumidis Anthony Tzes Electrical Engineering Program New York University Abu Dhabi United Arab Emirates Electrical & Computer Engineering Department New York University Brooklyn NY USA Kinesis Lab Core Technology Platform New York University Abu Dhabi United Arab Emirates Center for Artificial Intelligence and Robotics New York University Abu Dhabi United Arab Emirates

This paper is concerned with the mechatronic design of a tricopter drone which can move as a ground vehicle and/or as a vessel. The tricopter has three pairs of coaxial rotors and is capable of providing 100N of thrust with a 15 minute flight time using an 8S LiPo 12.5Ah battery. Three waterproof motors are attached to an isosceles triangular omniwheel configuration for operating as a ground vehicle after landing. The customized wheels allow the vehicle to move with a linear velocity up to 2 m/sec at a tilt slope up to 20°. Two submersible parallel water thrusters provide 24N collective force leading to a maximum vessel velocity of 1 m/s and a turn radius of 1.5 m. The design alternatives are highlighted and prioritized according to their weight while the overall amphibious drone is shown in several flight/omniwheel vehicle/vessel modes.

关键词： Mechatronics Navigation Force Wheels Rotors Prototypes Land vehicles

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Combining flow virometry with tree-based machine learning models for rapid virus particle estimation in different wastewater matrices

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Water Research 2025年 284卷 123905页

作者： Myshkevych, Yevhen N'Doye, Ibrahima Medina, Julie Sanchez Aljehani, Fahad K. Xiong, Yanghui Laleg-Kirati, Taous-Meriem Hong, Pei-Ying Environmental Science and Engineering Program Division of Biological and Environmental Science and Engineering King Abdullah University of Science and Technology Thuwal23955 Saudi Arabia KAUST Center of Excellence on Smart Health King Abdullah University of Science and Technology Thuwal23955 Saudi Arabia Electrical and Computer Engineering Program Division of Computer Electrical and Mathematical Science and Engineering King Abdullah University of Science and Technology Thuwal23955 Saudi Arabia Paris-Saclay France

Enumerating virus particles (VPs) at different stages of the wastewater treatment process or along the distribution network is essential for ensuring high performance and reducing public health risks. Herein, we aimed to (i) optimize the flow virometry (FVM) protocol for use in wastewater matrices, (ii) correlate FVM data with specific virus genera of interest, and (iii) develop machine learning (ML) models for determining total VP concentration. We identified and tested a comprehensive set of parameters to determine the optimal conditions for wastewater FVM. Specifically, we tested various sample preprocessing steps to enhance FVM detection sensitivity, including the use of different nucleic acid staining dyes, surfactant addition and concentration optimization, glutaraldehyde fixation, and the effect of sample freezing before FVM analysis. Spearman's rank correlation of FVM data with virus genera concentration using a conventional qPCR-based method in 206 samples showed a positive correlation for all five virus genera, ranging from 0.21 to 0.44 (p © 2025 The Author(s)

关键词： Water recycling

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Web Interactive Animation and Information for Electrodialysis to Desalinate Water

Web Interactive Animation and Information for Electrodialysi...

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2020 Annual Conference Northeast Section, ASEE-NE 2020

作者： Lehoe, James A. Whitlow, Joseph T. Alborz, Nakisa Dow, Douglas E. Program in Computer Eng. Wentworth Institute of Technology BostonMA United States Dept. of Iterdisciplinary Eng. Wentworth Institute of Technology BostonMA United States Dept. of Electrical and Computer Engineering Wentworth Institute of Technology BostonMA United States

ISBN: (纸本)9781665405256

Access to safe drinking water has progressively declined. Methods of purifying saltwater include reverse osmosis and distillation, but require cost and energy that may not be accessible to many. Another method for desalination is electrodialysis that imposes a voltage field to induce net movement of chlorine and sodium ions through two semipermeable membranes, resulting in water having a lower salt concentration. Electrodialysis has lower financial cost and energy requirements, showing promise as a potential method that may be more accessible in developing regions. To encourage education and exploration of this method for desalination, this project is developing an educational web-based informational site and interactive graphical program. Users can interact and visualize net movement of charged ions within voltage fields, and in the presence of semipermeable membranes. As these educational webbased tools would be available globally to anyone with a web assessible device, many people may be able to access and become knowledgeable about and interested in the potential of electrodialysis. © 2020 IEEE.

关键词： Desalination

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