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IEEE Transactions on technology and Society 2023年第2期4卷 125-145页

作者： Godage, Sankini Rancha Lovasdal, Froy Venkatesh, Sushma Raja, Kiran Ramachandra, Raghavendra Busch, Christoph Norwegian University of Science and Technology Department of Computer Science Trondheim 22 Gjovik2815 Norway National Police Directorate National Technology Team Euis Program Oslo0369 Norway Norwegian University of Science and Technology Department of Information Security and Communication Technology Trondheim 22 Gjovik2815 Norway

Morphing attacks are based on the technique of digitally fusing two (or more) face images into one, with the final visage resembling the contributing faces. Morphed images not only pose a challenge to Face-Recognition Systems (FRS) but also challenge experienced human observers due to high quality, postprocessing eliminating any visible artifacts, and further the printing and scanning process. Few studies have concentrated on examining how human observers can recognize morphing attacks, even as several publications have examined the susceptibility of automated FRS to morphing attacks and offered morphing attack detection (MAD) approaches. MAD approaches base their decisions either on a single image with no reference to compare against (Single-Image MAD (S-MAD)) or using a reference image (Differential MAD (D-MAD)). One prevalent misconception is that an examiner's or observer's capacity for facial morph detection depends on their subject expertise, experience, and familiarity with the issue. No works have reported the specific results of observers who regularly verify identity (ID) documents for their jobs. As human observers are involved in checking ID documents having facial images, a lapse in their competence can result in significant societal challenges. To assess the observers' proficiency, this research first builds a new benchmark database of realistic morphing attacks from 48 different subjects, resulting in 400 morphed images. Unlike the previous works, we also capture images from Automated Border Control (ABC) gates to mimic realistic border-crossing scenarios in the D-MAD setting with 400 probe images, to study the ability of human observers to detect morphed images. A new dataset of 180 morphing images is also produced to research human capacity in the S-MAD environment. In addition to creating a new evaluation platform to conduct S-MAD and D-MAD analysis, the study employs 469 observers for D-MAD and 410 observers for S-MAD who are primarily governmenta

关键词： Face recognition

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Optimizing Random Forest Classification Using Chi-Square and SMOTE-ENN on Student Drop-Out Data 8

Optimizing Random Forest Classification Using Chi-Square and...

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8th International Conference on Informatics and Computing, ICIC 2023

作者： Andri Yunis, Roni Tanti Universitas Mikroskil Undergraduate Program of Computer Science Department Medan Indonesia Universitas Mikroskil Undergraduate Program of Information Systems Department Medan Indonesia Universitas Mikroskil Undergraduate Program of Information Technology Department Medan Indonesia

ISBN: (纸本)9798350342604

Dropout is a particular concern for countries striving to increase human capital. Various attempts have been made by universities to minimize the number of dropouts. Machine learning has also developed various predictive models to determine the likelihood of students dropping out. However, there is a challenge in dropout data, specifically the problem of class imbalance, where the number of students who drop out (minority class) is significantly less than those who do not drop out (majority class). This imbalance can reduce the model's ability to classify students at risk of dropping out. This study proposes classification optimization using the Random Forest algorithm to handle class imbalances in student dropout data. To overcome class imbalance, the Synthetic Minority Oversampling Technique (SMOTE) and Edited Nearest Neighbors (ENN) techniques are used. Additionally, the attribute selection method is also applied to enhance the predictive results. The test results demonstrate that the combination of implementing feature selection with Chi-Square, followed by class imbalance handling with SMOTE-ENN, provided the most optimal predictive performance for identifying the status of both dropouts and graduates. © 2023 IEEE.

关键词： Students

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Into 3D-Reconstructed Apparel over Virtual Try-On with Virtual Reality

Into 3D-Reconstructed Apparel over Virtual Try-On with Virtu...

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2023 International Conference on Consumer Electronics - Taiwan, ICCE-Taiwan 2023

作者： Doungtap, Surasachai Petchhan, Jirayu Phanichraksaphong, Varinya Wang, Jenq-Haur International Graduate Program of Electrical Engineering and Computer Science Taiwan National Taiwan University of Science & Technology Dept. of Electrical Engineering Taiwan National Taipei University of Technology Department of Computer Science and Information Engineering Taiwan

ISBN: (纸本)9798350324174

Virtualization technologies are still growing bigger and faster. Despite the greatness of its advancement, the costume industry is still very accessible when it comes to real trials. Off-the-shelf stuff are inadequate details for the desired individual to assess its in-depth utility for each garment trying on for a second, including custom stuff are much harder to try out right away. To this end, 2D image-based 3D reconstruction inclusive of touchable-virtualized space is accessible easier to stuff details for mans' decision making in purchasing. We establish the overall end-to-end pipeline from reconstruction until visualization for one instance to be triable on its stuff for a moment. As an expectation, our proposed approach can bring objects into the experimental area and use them immediately without any obstacle. © 2023 IEEE.

关键词： Virtual reality

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Application of Digital Gamification Systems in Intelligent Automated Learning 10th

Application of Digital Gamification Systems in Intelligent A...

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10th International Conference on Kansei Engineering and Emotion Research, KEER 2024

作者： Lee, Chein-Hui Saputri, Evelyn Chiu, Min-Chi Department of Information Technology Ling Tung University Taichung Taiwan Doctoral Program of Intelligent Engineering National Taichung University of Science and Technology Taichung Taiwan Department of Intelligent Manufacturing Technology Ling Tung University Taichung Taiwan Department of Multimedia Design National Taichung University of Science and Technology Taichung Taiwan

ISBN: (纸本)9789819798896

This study aims to develop an innovative digital game-based teaching platform designed to facilitate students’ learning of intelligent automation-related knowledge through immersive game scenarios. This method offers significant advantages, including the provision of an engaging and challenging learning environment that encourages active student participation while fostering critical thinking and problem-solving skills. Students can apply the knowledge they acquire in practical game contexts, thereby enhancing their learning outcomes, aligning with the contemporary educational demand for diversified teaching approaches. Furthermore, this pedagogical strategy effectively stimulates students’ motivation to learn by engaging them in problem-solving and task completion activities, consequently improving their learning efficiency. More importantly, it emphasizes not just the transmission of knowledge but also the cultivation of students’ cognitive abilities and problem-solving skills, which are crucial for their future academic and professional development. By integrating educational content with interactive game elements, the platform can adapt to various learning paces and styles, making education more personalized and accessible. Overall, this study aims to provide students with a highly engaging and efficient learning method that meets the modern educational requirements for innovative teaching models, thereby significantly improving students’ learning outcomes and addressing their educational needs. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Contrastive Learning

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Based-on computer Vision Applications for Bus Stop Passenger Detection System 3

Based-on Computer Vision Applications for Bus Stop Passenger...

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3rd IEEE International Conference on Electronic Communications, Internet of Things and Big Data, ICEIB 2023

作者： Chang, Yu-Cheng Tsai, Hua-Wen Huang, Chao-Yi Wu, Zong-Rong Department of Computer Information and Network Engineer Lunghwa University of Science and Technology Taiwan Department of Bachelor's Program in Intelligent Robot National Yunlin University of Science and Technology Taiwan

ISBN: (纸本)9798350333862

Passenger transport is one of the most common ways of commuting in Taiwan. It plays an important role in the transportation system due to its large number of stations, dense frequency, and cheap transportation. Due to the unfriendly transportation environment and a large number of passengers, a blind spot of passenger transportation exists, which leads to traffic accidents at the station. We research to make the Bus Stop Passenger Detection System. Taking the object detection of Wheelchairs into consideration, it is more convenient to assist the disabled to find the passenger transportation system, which makes Taiwan's transportation system more convenient. © 2023 IEEE.

关键词： Object detection

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Mapping the Scientific Landscape of Integrated Scheduling Towards Industry 5.0 with A Bibliometric Analysis 6

Mapping the Scientific Landscape of Integrated Scheduling To...

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6th International Conference on Industry 4.0 and Smart Manufacturing, ISM 2024

作者： Putri Ardyanti, Anak Agung Ayu Xie, Zhiqiang Karnyoto, Andrea Stevens Pardamean, Bens Estiyanti, Ni Made School of Computer Science and Technology Harbin University of Science and Technology Harbin150000 China Faculty of Information Technology and Design Primakara University Bali 80226 Indonesia Bioinformatics and Data Science Research Center Bina Nusantara University Jakarta11480 Indonesia Computer Science Department BINUS Graduate Program Master of Computer Science Bina Nusantara University Jakarta 11480 Indonesia School of Management and Business University of Debrecen Debrecen Hungary

The industry is rapidly transitioning from the 4.0 era to the 5.0 era, prompting renewed interest among scholars in scheduling problems. They allow operations to process and assemble various components simultaneously. This bibliometric analysis provides a comprehensive understanding of the diverse research perspectives on the potential challenges of integrated scheduling within the framework. We identified 357 Scopus articles and analysed co-occurrence keyword (CNK) by VOSViewer tools and Global Citation Score (GCS) by Scopus tools. The research data obtained from 1993 to 2023 mainly in the subject areas of Engineering, computer science, Maths, and others. CNK identified six cluster keywords, and nine most cited articles based on normalised GCS. These results contribute to our understanding of the development of scheduling algorithms, shifting from an emphasis on manufacturing transfers to contemporary demand-centric research directions. Furthermore, this research provides a valuable perspective for policymakers, plant personnel, and manufacturing managers to make informed decisions. © 2025 The Authors. Published by Elsevier B.V.

关键词： Job shop scheduling

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CIMulator: Evaluating Neuromorphic Accelerators with HZO FefinFET-Based Synaptic Device 7

CIMulator: Evaluating Neuromorphic Accelerators with HZO Fef...

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7th International Conference on Green technology and Sustainable Development, GTSD 2024

作者： Le, Hoang-Hiep Lu, Hao-Yu Baig, Md. Aftab De, Sourav Lin, Ing-Chao Lu, Darsen D. Minghsin University of Science and Technology Department of Computer Science and Information Engineering Hsinchu Taiwan National ChengKung University Intelligent Computing Industrial Doctorate Program Tainan Taiwan Institute of Microelectronics National ChengKung University Tainan Taiwan National ChengKung University Department of Computer Science and Information Engineering Tainan Taiwan

ISBN: (纸本)9798350386073

In this study, we use the CIMulator platform to evaluate the performance of neuromorphic accelerators with novel Hf0.5Zr0.5O2 (HZO) ferroelectric fin field-effect transistor (FefinFET) as synaptic device. The MNIST handwritten digit dataset is used for training and inference processes in multilayer perceptron (MLP) neural networks. With the highly optimized synaptic device, the results demonstrate high training and inference accuracy, achieving up to 97% for the MLP, approaching the accuracy of software implementations. © 2024 IEEE.

关键词： Multilayer neural networks

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Q-Learning Energy Management System (Q-EMS) in Wireless Sensor Network

Q-Learning Energy Management System (Q-EMS) in Wireless Sens...

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2024 International Conference on Smart Computing, IoT and Machine Learning, SIML 2024

作者： Ardiansyah, Deden Mustafid Mantoro, Teddy Universitas Diponegoro Doctoral Program of Information Systems School of Postgraduate Central Java Semarang Indonesia Universitas Pakuan Vocational School Computer Engineering Department West Java Bogor Indonesia Sampoerna University Media-Tech-Lab Computer Science Department DKI Jakarta Indonesia

ISBN: (纸本)9798350364101

The energy control of a Wireless Sensor Network (WSN) often leads to an unbalanced state between the battery storage system, energy extraction through photovoltaic systems energy, and energy utilization in the WSN. These disparities result in suboptimal wireless sensor network performance. The reliance on batteries is a major factor contributing to this problem. The Q-Learning Energy Management System (Q-EMS) is designed to address these challenges and improve energy management strategies. The Q-EMS algorithm used a learning process resulting in optimal actions for sensor nodes in different situations. The rewards or punishments nodes receive determine their decisions, which are determined by the Q-EMS algorithm. The Q-learning model approach is aimed at reducing energy consumption and supply in WSNs. Energy supply is categorized into battery-based, transfer-based, and harvesting, while energy consumption can be classified into task-cycle, mobility-based, and data-driven. The development of the Q Learning algorithm model has three scenarios: determining energy needs for WSN, effective energy harvesting strategy, and effective energy transfer. As a result, effective energy demand, harvesting and transfer using the Q-learning algorithm are balanced. However, it needs to be studied in more depth using real data in the field. In future research, I will use real data and optimize the use of the Q-Learning algorithm. © 2024 IEEE.

关键词： Energy management systems

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Adaptive Strategies and Handover Optimization in 5G Networks to Address High Mobility Challenges

Adaptive Strategies and Handover Optimization in 5G Networks...

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2024 International Conference on Electrical Engineering and Informatics, ICELTICs 2024

作者： Murhaban Syahrial Arif, Teuku Yuliar Arnia, Fitri Doctoral Program School of Engineering Universitas Syiah Kuala Universitas Teuku Umar Departement Information Technology Engineering Banda Aceh Aceh Barat Indonesia Universitas Syiah Kuala Department of Electrical and Computer Engineering Banda Aceh Indonesia

ISBN: (纸本)9798350366822

This study develops an adaptive handover strategy in 5G networks to tackle high mobility challenges and improve service continuity and quality. The research method uses a 5G network emulator with a topology of four base stations (gNBs) to test user equipment (UE) speeds of 20 km/h and 130 km/h. The adaptive algorithm developed utilizes data from the Received Signal Strength Indicator (RSSI) as well as the speed and direction of user mobility to make optimal handover decisions. The results show that at a speed of 130 km/h, the average handover latency reaches 12 ms, compared to 8 ms at 80 km/h. Additionally, the signal quality (RSSI) is lower at higher speeds, negatively affecting service quality. This adaptive algorithm successfully reduces handover latency and improves the stability and efficiency of the overall network. The testing also indicates that this adaptive algorithm can predict handover targets by considering UE speed and direction and uses hysteresis mechanisms to prevent overly frequent handovers. By employing technologies such as Multiple Input Multiple Output (MIMO) and beamforming, this strategy is expected to maintain high service quality even under high mobility conditions. © 2024 IEEE.

关键词： 5G mobile communication systems

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Detect Areas of Upward and Downward Fluctuations in Bitcoin Prices Using Patterned Datasets 9

Detect Areas of Upward and Downward Fluctuations in Bitcoin ...

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9th IEEE information technology International Seminar, ITIS 2023

作者： Parlika, Rizky Mustafid Rahmat, Basuki Pascasarjana School Diponegoro University Department of Doctoral Program of Information System Semarang Indonesia University of Pembangunan Nasional 'Veteran' Jawa Timur Department of Informatics Faculty of Computer Science Surabaya Indonesia

ISBN: (纸本)9798350306835

Many researchers have proposed various theories and techniques to estimate the value of Bitcoin. However, there is still a great opportunity to suggest a new approach to Bitcoin forecasting. This research will examine the concept of forming a patterned dataset to prove the hypothesis regarding the start of a bitcoin price fluctuation until the end of the fluctuation using patterned dataset pairs in conditions of price decline (moon) and in conditions of price decline (crash). Patterned datasets were initially built from data on the movement of all cryptocurrency assets on a digital cryptocurrency trading market. The Patterned Dataset is programmed based on the response of all crypto assets to changes in the price of bitcoin over time. Patterned datasets are better able to describe the conditions of the digital cryptocurrency market, along with patterns of potential increases and decreases in Bitcoin prices in particular and cryptocurrencies in general. To deepen the observations, resampling of the patterned dataset was carried out with a 4-hour timeframe using the mean, median, min, max, and sum filter functions on pairs of crash and moon conditions per month. The results show that filter functions other than sum, namely mean, median, min, and max, provide markings of fluctuation area patterns that are easier to recognize. Two hypotheses related to fluctuations were also successfully proven in this research. © 2023 IEEE.

关键词： Bitcoin

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