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检索条件"机构=Master Program of Information Technology"

共 352 条记录，以下是11-20 订阅

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High-Precision and Large-Range Deflection of Light Beam with Fast Steering Mirrors

High-Precision and Large-Range Deflection of Light Beam with...

引用

CLEO: Science and Innovations in CLEO 2024, CLEO: S and I 2024 - Part of Conference on Lasers and Electro-Optics

作者： Mei, Tianjin Huang, Ke Fang, Haoran Zhang, Zixiao Liu, Chen School of Optical and Electronic Information Huazhong University of Science and Technology Wuhan430074 China Master Program Physics Graduate School Paris-Saclay University France

We proposed a combined kinematic model and mechanical decoupling method to extend FSM's operation range. Experimental result demonstrates pointing error is smaller than 0.05° in the range of -30° to 36&#... 详细信息

关键词： Kinematics

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Renewable Energy Transition Towards Sustainable Development: Benefits, Constraints, and Policy Guidance 11

Renewable Energy Transition Towards Sustainable Development:...

引用

11th International Conference on Cyber and IT Service Management, CITSM 2023

作者： Ardi Ma'ruf, Imam Faridah, Ida Saka, David Arayoga Santoso, Nuke Puji Lestari Yusuf, Maulana Sunarya, Po. Abas University of Pelita Harapan Tangerang Indonesia University of Raharja Master of Information Technology Tangerang Indonesia University of Indonesia Nursing Program Jakarta Indonesia University of Raharja Master of Information System Tangerang Indonesia University of Raharja Department of Information System Tangerang Indonesia

ISBN: (纸本)9798350305968

The Renewable Energy (REY) has undergone modifications, laying a strong foundation for the 'Renewable Energy Transition' (RET). The majority ownership of the 'Renewable Energy Transition' lies with local members or shareholders, empowering it to distribute energy in the transition process. This, in turn, has the potential to unlock separate property and funding for renewable energy sources while providing social benefits. However, it's important to note that technical solutions must be accompanied by increased public participation, considering aspects like interpretation, manufacturing expertise, spatial planning, and social sciences to ensure the successful implementation of any energy transformation. We recognize that investments and governance principles that account for the complementarity of renewable energy, spatial potential, demographics, potential resistance from incumbents, and the inclusion of traditionally marginalized communities are crucial for implementing REY and achieving a just energy transition in all Member States. This study employs a literature review to highlight the benefits and conducts a comparative analysis, considering recent literature, to address the constraints associated with the broad development of the Renewable Energy Transition. It also offers policy guidance for effective implementation, drawing examples from instances of delayed transition processes. © 2023 IEEE.

关键词： Renewable energy

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Camera-Only Perception System for Traffic Jam Assistance

Camera-Only Perception System for Traffic Jam Assistance

引用

2023 International Automatic Control Conference, CACS 2023

作者： Huang, Xiao-Wei Chen, Xiu-Zhi Chen, Yen-Lin National Taipei University of Technology Master Program in Artificial Intelligence Technology Taipei Taiwan National Taipei University of Technology Department of Computer Science and Information Engineering Taipei Taiwan

ISBN: (纸本)9798350306354

Traditional perception systems for TJA (Traffic Jam Assistance) are mostly implemented by fusing images with radar or lidar. As computer vision techniques become more powerful, cameras can almost replace the need for radar and lidar in perception tasks, which reduces the hardware cost of the system. In this research, we propose a camera-only perception system for TJA, which is able to provide the information of the vehicles ahead and the drivable area. The proposed system has been evaluated through real-world scenario sequences, and proved that it achieves high robustness, which is highly possible to be adopted for TJA development. © 2023 IEEE.

关键词： Cameras

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Robust Object Detection Model for UAV Application

Robust Object Detection Model for UAV Application

引用

2023 International Automatic Control Conference, CACS 2023

作者： Ku, Chun Chen, Xiu-Zhi Chen, Yen-Lin National Taipei University of Technology Master Program in Artificial Intelligence Technology Taipei Taiwan National Taipei University of Technology Department of Computer Science and Information Engineering Taipei Taiwan

ISBN: (纸本)9798350306354

Not only common issues on object detection task need to be deal with, for Unmanned Aerial Vehicle (UAV) applications, small object is one of the critical problems that needs to be solved. YOLOv7 is a powerful network architecture that provides high efficiency and accuracy object detection results. This paper adopts YOLOv7 as an object detection model for two different kinds of targets, one is vehicle, and the other is ocean flotsam. By training the model with open datasets and fine-tuning the model with self-collected datasets, we prove through sequences collected from real-world scenarios that YOLOv7 is able to provide robust and accurate object detection results, including vehicles and ocean flotsam, with real-time efficiency. Based on such experimental result, we confirmed that YOLOv7 can be the baseline for object detection model development. © 2023 IEEE.

关键词： Object detection

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Risk Management of Bank and FinTech Collaboration: A Phenomenological Research 6

Risk Management of Bank and FinTech Collaboration: A Phenome...

引用

6th International Conference on Computer and Informatics Engineering, IC2IE 2023

作者： Legowo, Mercurius Broto Sorongan, Fangky Antoneus Subanidja, Steph Institute of Perbanas Study Program of Information System Faculty of Information Technology Jakarta Indonesia Institute of Perbanas Study Program of Accounting Faculty of Economic and Business Jakarta Indonesia Post Graduate School Institute of Perbanas Program of Master of Management Jakarta Indonesia

ISBN: (纸本)9798350345162

Banking and Fintech are encouraged to collaborate to fill each other's deficiencies and further grow the digital economy. This collaboration will create benefits for both banks, Fintech, and customers. However, this collaboration also comes with risks. The Financial Services Authority has stated that several risk phenomena can occur in the collaboration of banks and Fintech. First, no law guarantees the protection and exchange of customer personal data. Second, the risk of customer data leakage. Third, the risk of cyberattacks. The fourth is the risk of outsourcing. This research aims to analyze the risk phenomenon of bank and fintech collaboration through the Enterprise Risk Management Framework approach. This study uses a phenomenological research approach, which is a study to study how individuals subjectively experience and give meaning to the phenomenon. Data analysis based on this phenomenon data uses qualitative methods involving banking and fintech practitioners. The results of this study describe the phenomenon of risks that occur in banking-fintech collaboration, as approached by the Enterprise Risk Management framework. Proper risk management will minimize risks when the Bank collaborates with FinTech. This study hopefully contributes to making brief policy recommendations on bank and fintech collaboration risk management for Indonesian financial regulators. © 2023 IEEE.

关键词： bank collaboration ERM framework fintech risk management

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A Note on Even-Sized Spectral Clustering 13

A Note on Even-Sized Spectral Clustering

引用

Joint 13th International Conference on Soft Computing and Intelligent Systems and 25th International Symposium on Advanced Intelligent Systems, SCIS and ISIS 2024

作者： Miyakawa, Hiroki Endo, Yasunori Graduate School of Science and Technology Degree Programs in Systems and Information Engineering Master's Program in Risk and Resilience Engineering University of Tsukuba Ibaraki Tsukuba Japan Institute of Systems and Information Engineering University of Tsukuba Ibaraki Tsukuba Japan

ISBN: (纸本)9798350373332

Clustering is a typical unsupervised learning method for classifying unsupervised data. One of the clustering meth-ods, even-sized clustering based on optimization (ECBO), is a clustering algorithm that imposes a constraint to equalize the size of each cluster. ECBO has been suggested to be effective in delivery and other problems. However, it is limited to Euclidean space. On the other hand, spectral clustering with a wide range of applicability for partitioning graph data has been proposed. In this paper, we propose even-sized spectral clustering, which imposes a size-equal constraint on spectral clustering, and show that it is an extension of the graph partitioning problem. We also verify the validity of the results through numerical examples. © 2024 IEEE.

关键词： Unsupervised learning

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A ShuffleNet Architecture-Based Multi-Layer Feature Scaling and Fusion Approach for Underwater Net Cage Damage Detection in Aquaculture

A ShuffleNet Architecture-Based Multi-Layer Feature Scaling ...

引用

2024 IEEE International Conference on Consumer Electronics-Asia, ICCE-Asia 2024

作者： Huang, Xiang-Rui Chen, Yi-Cheng Chen, Liang-Bi Hu, Wu-Chih National Penghu University of Science and Technology Master Program in Electrical Engineering and Computer Science Department of Electrical Engineering Penghu Taiwan National Penghu University of Science and Technology Department of Computer Science and Information Engineering Penghu Taiwan

ISBN: (纸本)9798331530839

In offshore aquaculture operations, personnel equipped with diving gear are often necessary to inspect the underwater net cages for damage, particularly on the sea floor. This manual inspection process is time-consuming and complex. To overcome this problem, this paper proposes a computer vision solution for identifying damage in underwater net cages to address the inefficiencies and challenges of traditional manual inspections. The proposed scheme utilizes a high-performance multi-branch computational architecture designed based on ShuffleNet architecture to detect net cage damage more efficiently. Experimental results demonstrate that this work performs well on the ImageNet ILSVRC-2010 dataset and achieves an accuracy of 88.54% in underwater net damage detection. © 2024 IEEE.

关键词： Aquaculture

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Real Time Classification System of Black Soldier Fly Larva

Real Time Classification System of Black Soldier Fly Larva

引用

IEEE VTS Asia Pacific Wireless Communications Symposium (APWCS)

作者： Chayanon Pookunngern An-Chao Tsai International Master Program in Information Technology and Applications National Pingtung University Taiwan

ISBN: (数字)9798350361704

ISBN: (纸本)9798350361711

Food waste presents a significant issue, contributing extensively to greenhouse gas emissions and climate change. When food waste decomposes in landfills, it generates methane, a greenhouse gas that is significantly derogation effective to the atmosphere than carbon dioxide. Additionally, the production, transportation, and disposal of food waste significantly contribute to global greenhouse gas emissions. This study explores an innovative approach to mitigate the environmental impact of food waste by using food scraps to create compost for animal feed, specifically utilizing the Black Soldier Fly Larva (BSFL). Accurate control of food quantity for various larval stages is essential, necessitating precise stage classification. This process is complex due to the larvae's similar and small color variations. In this paper, we introduce a mobile application designed to classify and detect the growth stages of BSFL, ranging from stage 1 to stage 4, which are high in protein and beneficial for animal feed, to stages 5 and 6, which are ideal for preparing pupae that can be used in skincare products. Our approach employs the YOLOv8 model for larval stage classification and detection, achieving an impressive mAP50-95 of 0.812, surpassing the performance of YOLOv7 (mAP50-95 of 0.781) and YOLOv5 (mAP50-95 of 0.789).

关键词： Food waste YOLO Waste management Wireless communication Accuracy Animals Transportation

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Using Machine Learning to Predict the Language Proficiency of Thai Students Studying in Taiwan

Using Machine Learning to Predict the Language Proficiency o...

引用

International Conference on Applied System Innovation (ICASI)

作者： Charoenwat Moocharoen Wen-Chih Chang International Master Program in Information Technology and Applications National Pingtung University Taiwan

ISBN: (数字)9798350394924

ISBN: (纸本)9798350394931

Currently, there are students from Thailand who wish to study abroad. The researchers have chosen Taiwan as the focus. Among the students who come for further studies, there are those proficient in the English language and those who are not. Factors such as language readiness, financial preparedness, scholarship availability, and the university's reputation are crucial in the decision-making process for choosing an educational institution. Simultaneously, some students had the opportunity to study in Taiwan but, due to language unpreparedness, had to withdraw from their studies and return to their home country. The researchers emphasize the importance of language readiness among students. Data has been collected from 316 data including undergraduate, master's, doctoral, and language students of Thai students throughout Taiwan, and a model has been developed to predict the English language proficiency of Thai students. The goal is to create a model with the highest level of accuracy to produce reliable results. This model can be utilized by educational institutions to tailor their courses to match the language abilities of Thai students, thereby enhancing the overall learning experience.

关键词： Logistic regression Technological innovation Machine learning algorithms Scholarships Neural networks Forestry Medical services

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Finding the Best Techniques for Predicting Term Deposit Subscriptions (Case Study UCI Machine Learning Dataset) 4

Finding the Best Techniques for Predicting Term Deposit Subs...

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4th International Conference on Sustainable Engineering and Creative Computing, ICSEC 2022

作者： Setiyani, Lila Indahsari, Ayu Rosalina Wansen, Tjong President University Master of Science Information Technology Study Program Bekasi Indonesia President University Informatics Study Program Bekasi Indonesia

ISBN: (纸本)9798350322002

Knowing a lot about attributes, such as bank client data, marketing campaigns, social and economic context, and so on, is necessary to predict which bank customers are likely to sign up for time deposits. The direct marketing campaigns dataset for the bank institution was made available by the UCI machine learning repository. This dataset had previously been used in studies to forecast customers who would sign up for time deposits, but the outcomes of the two studies were different. The purpose of this study is to determine which machine learning methods are most effective for predicting customers who will sign up for time deposits. In this study, researchers used machine learning methods like random forests, K-nearest neighbors, decision trees, naive bayes, logistic regression, SVM, and XGBoost to uncover the truth. Results showed that XGBoost had the highest accuracy (91.73%), followed by the DT classifier (88.79%), LR classifier (91.2%), NB classifier (84.78%), KNN classifier (90.6%), SVM (89.6%), and XGBoost (91.44%). © 2022 IEEE.

关键词： Forecasting

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