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29th International Conference on Systems Engineering, ICSEng 2022

作者： Yasue, Koki Kikuchi, Masato Ozono, Tadachika Department of Computer Science Graduate School of Engineering Nagoya Institute of Technology Gokiso-cho Showa-ku Aichi Nagoya466-8555 Japan

ISBN: (纸本)9783031274695

Visualizing the local environment for remote people is necessary for augmented reality (AR) and remote people between local and remote participants. Three dimensional (3D) reconstruction is a promising method for capturing the shapes and appearances in a local space, but accurate reconstruction requires high-precision sensors and high-performance computers. However, general-purpose smartphones and tablets have distance sensors like LiDAR, and we realized a meta-AR space based on such devices. Through synchronized AR and virtual spaces, local and remote users can collaborate in our meta-AR space. The performance and coverage of a smartphone-based 3D reconstruction system are two issues, though. First, 3D reconstruction using a conventional ray cast is slow;however, using a depth map, improvement is possible. Second, users are unable to see the captured space’s coverage;however, doing so is useful. The system cannot adequately reconstruct the space when the coverage is too low. This paper describes a quick 3D reconstruction system that supports the reconstruction with a depth map and mapping coverage visualization. Our experimental findings show its effectiveness, mapping coverage, and utility. The mapping coverage is adequate and our proposed method is 258 times faster than the ray cast method. Moreover, our mapping-coverage visualization increased the texture by 15%. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Augmented reality

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A Software Design Method for Creation and Utilization of Experiential Knowledge

A Software Design Method for Creation and Utilization of Exp...

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2022 IEEE International Conference on Electrical, computer, and Energy Technologies, ICECET 2022

作者： Hoshino, Takayuki Yoshioka, Rentaro University of Aizu BIPROGY Inc. Technology Research & Innovation The Graduate School of Computer Science and Engineering Tokyo Japan University of Aizu The Graduate School of Computer Science and Engineering Aizu-Wakamatsu Japan

ISBN: (数字)9781665470872

ISBN: (纸本)9781665470872

Until now, knowledge-related efforts in engineering, including software engineering, have aimed to automate human activities. But, unfortunately, the use of knowledge for automation leads to the black-boxing of the system, making it difficult to respond flexibly to changes and shaking the reliability, safety, and trustworthiness of computer processing results. When it is necessary to respond to change and diversity and realize a sustainable society, knowledge must be used for change, diversity, and creation for sustainability, not for automating existing mechanisms. To realize such knowledge creation and utilization, it is necessary to design a software support environment and make it available as a platform for knowledge creation. This paper will show the design and effect of a knowledge creation platform for human beings to use knowledge in their activities and evolve, deepen, continue, and maintain their activities. © 2022 IEEE.

关键词： Software design

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Area-wise Augmentation on Segmentation Datasets from 3D Scanned Data Used for Visual Navigation

Area-wise Augmentation on Segmentation Datasets from 3D Scan...

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International Conference on Control, Decision and Information Technologies (CoDIT)

作者： Marin Wada Yuriko Ueda Miho Adachi Ryusuke Miyamoto Dept. of Computer Science Graduate School of Science and Technology Meiji University Kawasaki Japan Dept. of Computer Science School of Science and Technology Meiji University Kawasaki Japan

ISBN: (数字)9798350373974

ISBN: (纸本)9798350373981

Visual navigation rely heavily on semantic segmentation outcomes, which is invaluable for practical applications. However, the efficacy of this navigation method is compromised when the accuracy of semantic segmentation falls short. Crucially, the availability of an appropriate dataset containing pixel-wise class labels is imperative for constructing a robust classifier. To alleviate the burden of manual annotation, the authors have endeavored attempt to implement a semi-automatic process for generating a training dataset from 3D scanned data. To enhance the versatility of the approach, the present study introduces augmentation techniques that consider the semantic attributes of images within the target scenario: DMIT and ToD are employed to address color variations caused by seasonal changes lawn growth and fluctuations on the sun’s height, respectively. Experimental results based on images captured during the Tsukuba Challenge, a competition featuring autonomous moving robots in Japan, showed that the proposed methodology substantially enhances classification accuracy, particularly for images taken under conditions different from those during the creation of the 3D model.

关键词： Training Visualization Solid modeling Three-dimensional displays Accuracy Navigation Image color analysis Semantic segmentation Semantics Robots

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Robust Facial Biometric Authentication System Using Pupillary Light Reflex for Liveness Detection of Facial Images

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computer Modeling in Engineering & sciences 2024年第4期139卷 725-739页

作者： Puja S.Prasad Adepu Sree Lakshmi Sandeep Kautish Simar Preet Singh Rajesh Kumar Shrivastava Abdulaziz S.Almazyad Hossam M.Zawbaa Ali Wagdy Mohamed CSE Department Geethanjali College of EngineeringHyderabadTelangana501301India Department of Computer Science LBEF CampusKathmandu44600Nepal School of Computer Science Engineering and Technology(SCSET) Bennett UniversityGreater Noida201310India Department of Computer Engineering College of Computer and Information SciencesKing Saud UniversityP.O.Box 51178Riyadh11543Saudi Arabia CeADAR Ireland’s Centre for AI Technological University DublinDublinD07 EWV4Ireland Operations Research Department Faculty of Graduate Studies for Statistical ResearchCairo UniversityGiza12613Egypt Applied Science Research Center Applied Science Private UniversityAmman11937Jordan

Pupil dynamics are the important characteristics of face spoofing *** face recognition system is one of the most used biometrics for authenticating individual *** main threats to the facial recognition system are different types of presentation attacks like print attacks,3D mask attacks,replay attacks,*** proposed model uses pupil characteristics for liveness detection during the authentication *** pupillary light reflex is an involuntary reaction controlling the pupil’s diameter at different light *** proposed framework consists of two-phase *** the first phase,the pupil’s diameter is calculated by applying stimulus(light)in one eye of the subject and calculating the constriction of the pupil size on both eyes in different video *** above measurement is converted into feature space using Kohn and Clynes model-defined *** Support Vector Machine is used to classify legitimate subjects when the diameter change is normal(or when the eye is alive)or illegitimate subjects when there is no change or abnormal oscillations of pupil behavior due to the presence of printed photograph,video,or 3D mask of the subject in front of the *** the second phase,we perform the facial recognition ***-invariant feature transform(SIFT)is used to find the features from the facial images,with each feature having a size of a 128-dimensional *** features are scale,rotation,and orientation invariant and are used for recognizing facial *** brute force matching algorithm is used for matching features of two different *** threshold value we considered is 0.08 for good *** analyze the performance of the framework,we tested our model in two Face antispoofing datasets named Replay attack datasets and CASIA-SURF datasets,which were used because they contain the videos of the subjects in each sample having three modalities(RGB,IR,Depth).The CASIA-SURF datasets showed an 89.9%Equal Err

关键词： SIFT pupil CASIA-SURF pupillary light reflex replay attack dataset brute force

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BERT and ULMFiT Ensemble for Personality Prediction from Indonesian Social Media Text

BERT and ULMFiT Ensemble for Personality Prediction from Ind...

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2022 International Symposium on Information technology and Digital Innovation, ISITDI 2022

作者： Halimawan, Noptovius Suhartono, Derwin Gema, Aryo Pradipta Yunanda, Rezki Binus Graduate Program-Master Of Computer Science Bina Nusantara University Computer Science Department Jakarta11480 Indonesia School Of Computer Science Bina Nusantara University Computer Science Department Jakarta11480 Indonesia Epigene Labs Paris France

ISBN: (数字)9781665461160

ISBN: (纸本)9781665461160

Predicting personality is a growing topic in the field of natural language processing. The study of personality prediction has been proven to benefit the development of recommender systems and automated personality assessments by previous studies. Additionally, the widespread usage of social media in Indonesia such as Twitter has served as a potential source of data for developing such models. Existing personality prediction models has explored the implementation of both traditional machine learning models and deep learning models, with the latter proven to perform better with more data. Despite so, there is not much development of deep learning-based personality prediction models in the domain of Indonesian text. We propose a deep learning-based ensemble model based on Universal Language Model Fine Tuning (ULMFiT) and Bidirectional Encoder Representations from Transformers (BERT), the state-of-the-art pre-trained models for text classification. The model is trained with Indonesian tweets labelled with Five Factor Model (FFM) personality traits along with the users' metadata. The model is tested with five predetermined scenarios to prove the robustness of its performance. The final evaluation of the model proves that it has successfully achieved optimal performance of 76.41 % macro-average accuracy and 75.55% macro-average F-1 score, exceeding the state-of-the-art BERT and ULMFiT © 2022 IEEE.

关键词： Classification (of information)

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Creation of Day-Night Visible-Thermal Paired Image Dataset via Image Registration

Creation of Day-Night Visible-Thermal Paired Image Dataset v...

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IEEE International Conference on Robotic Computing (IRC)

作者： Michiya Kibe Takeru Inoue Junya Morioka Ryusuke Miyamoto Dept. of Computer Science Graduate School of Science and Technology Meiji University Kawasaki Japan Dept. of Computer Science School of Science and Technology Meiji University Kawasaki Japan

ISBN: (数字)9798331521554

ISBN: (纸本)9798331521561

Thermal imaging is challenging because of the lack of color and contrast information. Therefore, translating thermal images to visible color images is crucial for human scene interpretation. Recent advancements in deep learning have significantly improved image translation tasks. Nonethe-less, RGB-Thermal (RGB-T) paired image datasets, particularly for nighttime images, remain scarce. In this study, we propose a method for creating RGB-T paired images by aligning daytime RGB color images with nighttime thermal images at the pixel level by using an image registration technique. Our approach combines the robust RoMa matching method, which effectively handles environmental changes, with simple preprocessing to address modality differences, thus enabling high-precision matching between different modalities. We validate the effectiveness of this method through experiments using the Caltech Aerial RGB-Thermal Dataset captured from drones. As a result, our approach achieves a high matching score of over 95% and facilitates the conversion of nighttime thermal images to interpretable visible images.

关键词： Deep learning Image registration Translation Accuracy Image color analysis Computational modeling Imaging Color Robots Drones

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A systematic literature review of machine learning application in COVID-19 medical image classification 7

A systematic literature review of machine learning applicati...

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7th International Conference on computer science and Computational Intelligence, CSCI 2022

作者： Daniel Cenggoro, Tjeng Wawan Pardamean, Bens Computer Science Department BINUS Graduate Program - Master of Computer Science Program Bina Nusantara University Jakarta11480 Indonesia Computer Science Department School of Computer Science Bina Nusantara University Jakarta11480 Indonesia Bioinformatics and Data Science Research Center Bina Nusantara University Jakarta11480 Indonesia

Detecting COVID-19 as early as possible and quickly is one way to stop the spread of COVID-19. Machine learning development can help to diagnose COVID-19 more quickly and accurately. This report aims to find out how far research has progressed and what lessons can be learned for future research in this sector. By filtering titles, abstracts, and content in the Google Scholar database, this literature review was able to find 19 related papers to answer two research questions, i.e. what medical images are commonly used for COVID-19 classification and what are the methods for COVID-19 classification. According to the findings, chest X-ray were the most commonly used data to categorize COVID-19 and transfer learning techniques were the method used in this study. Researchers also concluded that lung segmentation and use of multimodal data could improve performance. © 2022 Elsevier B.V.. All rights reserved.

关键词： COVID-19

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Using SYCLomatic to Migrate CUDA Code to oneAPI Adapting NVIDIA GPU

Using SYCLomatic to Migrate CUDA Code to oneAPI Adapting NVI...

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IEEE International Conference on Cluster Computing Workshops and Posters (CLUSTER WORKSHOPS)

作者： Wentao Liang Norihisa Fujita Ryohei Kobayashi Taisuke Boku Master's Program in Computer Science Degree Program in Systems and Information Engineering Graduate School of Science and Technology University of Tsukuba Center for Computational Sciences University of Tsukuba

ISBN: (数字)9798350383454

ISBN: (纸本)9798350383461

Nowadays, the use of accelerators in high performance computing has become more common than ever before. The most used accelerators must be the Graphics Processing Unit (GPU). It has emerged as an important component in most of the parallel computing scenarios, surpassing the capabilities of the traditional Central Processing Unit (CPU) in perspective of both performance and energy efficiency.

关键词： Codes Conferences High performance computing Graphics processing units Cluster computing Parallel processing Energy efficiency Central Processing Unit

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Nonlinear transient contact deformation-electric current-thermal conduction triply coupled finite element analysis for resistance spot welding

Yosetsu Gakkai Shi/Journal of the Japan Welding Society

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Yosetsu Gakkai Shi/Journal of the Japan Welding Society 2021年第3期90卷 177-181页

作者： Niho, Tomoya Graduate School of Computer Science and Systems Engineering Kyushu Institute of Technology Japan

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Finite-time robust performance improvement for non-linear systems in the presence of input non-linearity and external disturbance

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IET Control Theory and Applications 2023年第6期17卷 672-682页

作者： Wang, Haoping Ghaffari, Valiollah Mobayen, Saleh Bartoszewicz, Andrzej Fekih, Afef Assawinchaichote, Wudhichai School of Automation Nanjing University of Science and Technology Nanjing China Department of Electrical Engineering Persian Gulf University Bushehr Iran Graduate School of Intelligent Data Science National Yunlin University of Science and Technology Yunlin Douliou Taiwan Institute of Automatic Control Lodz University of Technology Lodz Poland Department of Electrical and Computer Engineering University of Louisiana at Lafayette LafayetteLA United States Department of Electronic and Telecommunication Engineering Faculty of Engineering King Mongkut's University of Technology Thonburi Bangkok Thailand

The main focus of this research is on improving the performance of dynamic systems with actuator non-linearities and time-varying disturbances. To this end, using the concept of finite-time stability, a novel observer is presented to estimate the disturbances in systems with input non-linearities. Then, introducing an innovative sliding manifold, a robust observer-based technique is derived to guarantee the finite-time stability of the sliding surface. Hence, the closed-loop system would be stable in the presence of hard non-linearities and time-varying disturbances. The performance of the proposed approach was assessed in using a simulation study of two numerical examples. The obtained results and comparison with a conventional method confirmed the benefits of the suggested approach. © 2022 The Authors. IET Control Theory & Applications published by John Wiley & Sons Ltd on behalf of The Institution of Engineering and technology.

关键词： Closed loop systems

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