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2024 International Symposium on Intelligent Signal Processing and Communication Systems, ISPACS 2024

作者： Kunitake, Yukihito Iwakiri, Munetoshi Tanaka, Kiyoshi Graduate School of Medicine Science and Technology Shinshu University Nagano Japan Department of Computer Science National Defense Academy of Japan Yokosuka Japan Shinshu University Nagano Japan

ISBN: (纸本)9798350389210

3D point clouds are represented object shapes in 3D space as a collection of points. The data are captured by an optical device, which eliminats the difference of the point density by the spesify of the device and limits the range measured. When we use data acquired from multiple directions, we need to registrate between 3D point clouds. However, if the overlap area is small, it is necessary to identify the overlapping areas. When we registrate between the low overlap point clouds, we put the merkers knowing the shape before and estimate the relation of the point cloud position from the relation of the markers. When we measure the shape of object where we cannot put the markers, it is difficult to registrate the point clouds. Therefore, our research objective was to develop a method to registate the 3D point cloud regardless of each point density. We introduced a weighted constraint function during patch selection for registration using the genetic algorithm of CSVP(Convex-hull SuperVoxel Patch). Experimental results confirm the high registration accuracy equivalent to those of previous studies, even in the registration of 3D point cloud datasets that failed in previous studies. In addition, CSVP that were registreted by SVP(SuperVoxel Patch) were processed half time. © 2024 IEEE.

关键词： Genetic algorithms

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Adopting Centroid and Bandwidth to Shape Security Line 4

Adopting Centroid and Bandwidth to Shape Security Line

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4th IEEE International Conference of computer science and Information technology, ICOSNIKOM 2022

作者： Pratiwi, Heni Ispur Kartowisastro, Iman Herwidiana Soewito, Benfano Budiharto, Widodo Doctorate Program School of Computer Science Bina Nusantara University Jakarta Indonesia Bina Nusantara University Binus Graduate Program Doctorate Program of Computer Science Computer Science Department Jakarta Indonesia Bina Nusantara University Faculty of Engineering Computer Engineering Department Jakarta Indonesia Bina Nusantara University Computer Science Binus Graduate Program Computer Science Jakarta Indonesia School of Computer Science Bina Nusantara University Computer Science Department Jakarta Indonesia

ISBN: (纸本)9798350399073

The voice patterns of gender and age have been used as speaker's identity and implied into sectors such as smart cards, healthcare, banking, and other security access controls. However, age, illness, and ambient noise factors exist challenging issues of voice changes in speech recognition systems to be resolved. This paper presents experiment results of observing those issues, and its goal was obtaining the elements of voice features to secure the speaker's identity. Mel-frequency Cepstral Coefficient (MFCC) was used to conduct observations on spectral centroid and bandwidth, it has effectively performed capturing features of individual speech signal. The experiment was conducted with data split into three groups: under 13, range 13 to 19, and above 19 years old for both male and female. The results showed that both gender under 13 have centroid voices reached to 98%, age of 13 to 19 remain with centroid reached 98% of bandwidth for male and passing over 100% for female, then above 19 for both genders speak lower with centroid 50% of bandwidth, and male above age of 19 remains to keep centroid about 50% and female changes to 95%. MFCC fits to expose the speech spectrum for the purpose of an analysis frame on specific local spectral properties of voices, and the finding is to form a security line or an individual profiling adoption. © 2022 IEEE.

关键词： Bandwidth

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Accuracy Improvement of Semantic Segmentation Trained with Data Generated from a 3D Model by Histogram Matching Using Suitable References

Accuracy Improvement of Semantic Segmentation Trained with D...

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2022 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2022

作者： Adachi, Miho Komatsuzaki, Hayato Wada, Marin Miyamoto, Ryusuke Meiji University Graduate School of Science and Technology Department of Computer Science Kawasaki Japan Meiji University School of Science and Technology Department of Computer Science Kawasaki Japan

ISBN: (数字)9781665452588

ISBN: (纸本)9781665452588

Visual navigation based on the results of semantic segmentation requires high classification accuracy. Previous research has proven that a classifier of semantic segmentation trained upon a dataset generated from a 3D model performs well when the input images are also generated from a 3D model. However, when the input images are real 2D images captured at the same location by a camera mounted on a robot, the average classification accuracy deteriorates. To overcome this issue, a novel scheme is proposed to improve the classification accuracy of semantic segmentation when the training data is generated from a 3D point cloud. The key features of the proposed scheme are filling in the missing data by inpainting and domain adaptation by histogram matching. To evaluate the proposed scheme, datasets composed of real images captured during a variety of seasons, weathers, and times were created. Experimental results showed that ICNet trained upon our dataset could provide accurate results for visual navigation. © 2022 IEEE.

关键词： Semantic Segmentation

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Relationship between Embedment and Compressive Properties with Grain Direction of Hardwood Species

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Zairyo/Journal of the Society of Materials science, Japan 2024年第8期73卷 669-674页

作者： Takuro, Mori Tagawa, Riho Inoue, Ryo Tanaka, Kei Hiroshima University Graduate School of Advanced Science and Engineering Kagamiyama Higashi-Hiroshima739-8527 Japan Kumamoto University Faculty of Advanced Science and Tchnology Kurokami Chuo-ku Kumamoto860-8555 Japan Oita University Faculty of Science and Technology Architecture Program Dannoharu Oita870-1124 Japan

In general, softwoods are used as the main structural material for wooden structures, while hardwoods are less used. Some hardwoods show superior mechanical performance due to the high density about 1.0 x 103 kg/m3. Therefore, the utilizing hardwoods as structural materials are supposed to more flexible structural design proposals. Studies on the mechanical performance of hardwoods for structural design are not enough, especially as an embedment performance. In this study, it was conducted embedment and compression tests related to the joint performance of wooden structures using three species of hardwoods (Ulin, Buna, and Kuri) and a softwood (Sugi) to investigate the effects of strength performances such as density and woody structure. As a result, hardwoods with higher density showed higher strength performance. Embedment strength relative to compressive strength was 0.94 to 1.49 times higher in the direction parallel to the grain and 3.46 to 5.08 times higher in the direction perpendicular to the grain. About embedment strength, the ring-porous wood, Kuri, showed a similar trend (TR⨫RT, TL⨫RL) to that of a softwood, Sugi, while the diffuse-porous wood, Ulin and Buna, showed different trends (RTRL). © 2024 Society of Materials science Japan. All rights reserved.

关键词： Hardwoods

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Lighter Student Engagement Recognition in a Classroom Environment Using Skeletal Keypoints

IAENG International Journal of Computer Science

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IAENG International Journal of computer science 2025年第6期52卷 1997-2014页

作者： Tarigan, Gabriel Asael Elwirehardja, Gregorius Natanael Nugroho, Kuncahyo Setyo 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 Jakarta1140 Indonesia Bioinformatics and Data Science Research Center Bina Nusantara University Jakarta11480 Indonesia BINUS Graduate Program – Master of Computer Science Program Bina Nusantara University Jakarta11480 Indonesia

Student retention is crucial for educational institutions, influencing reputation, finances, and ranking metrics. Engagement, reflecting a student’s connection, interest, and effort, plays a vital role in learning, fostering critical thinking, and supporting retention. Recent advancements use students’ poses to predict engagement, providing valuable insights without disrupting the teaching-learning dynamic. The prevailing research trend leans toward employing multi-modal approaches, such as a combination of pose detection with object detection. However, current methods use out-of-date object detection methods and manual dataset creation, which is cumbersome, requiring thousands of manually annotated data. This problem is then addressed by proposing a novel method of student engagement detection, using a combination of You Only Look Once Version 8 Mini (YOLOv8m) and MediaPipe as state-of-the-art alternatives to improve both object detection and human pose estimation. The (YOLOv8m + MediaPipe) method surpasses the baseline (YOLOv4 + OpenPose) with higher accuracy (0.70 vs. 0.41) and lower cross-entropy loss (0.40 vs. 0.60) on the test set, confirmed by a statistically significant paired t-test. It also exhibits a remarkable speed advantage, around 16 times faster than the baseline in pose detection data collection rates. Despite not being designed for it, the proposed method achieves multiple keypoint detection, matching the baseline’s amount. © (2025), (International Association of Engineers). All rights reserved.

关键词： Object detection

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Effect of Graphite Addition on Microstructure, Mechanical Properties and Thermal Properties of Injection Molded AZ91D Alloy+1

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Materials Transactions 2024年第4期65卷 374-380页

作者： Hideshima, Yasutoshi Maeda, Fumiya Fukuta, Tadao Ozaki, Koichi Course of Advanced Systems Engineering Graduate School of Computer Science and Systems Engineering Okayama Prefectural University Soja719-1197 Japan Process Technology Development Department Technology Development Division Seiko Epson Corp. Suwa399-0211 Japan Department of Systems Engineering Faculty of Computer Science and Systems Engineering Okayama Prefectural University Soja719-1197 Japan

Magnesium chips were coated with a high concentration of graphite using a binder and were used as the raw material for injection molding. The microstructure of the magnesium injection-molded product with added graphite exhibited a dispersion of needle-like graphite particles. No significant voids were observed at the interfaces between the graphite and the matrix. The addition of more than 0.5 mass% graphite decreased the proof stress and tensile strength of the injection-molded products. The Young’s modulus of the graphite-added products tended to decrease with an increase in the graphite content, which is consistent with the lower limit of the rule of mixtures. The thermal conductivity of the 6.9 mass% graphite-added product increased compared with that of the AZ91D magnesium alloy and the coefficient of linear thermal expansion decreased. Both values are within a range that satisfied the rules of mixtures. © 2024 The Japan Institute of Metals and Materials.

关键词： Thermal expansion

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Nge-BatikVR: Innovative Batik Learning and Marketing Through Virtual Reality Serious Games with Immersive Hands-On Experience 15

Nge-BatikVR: Innovative Batik Learning and Marketing Through...

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15th International Congress on Advanced Applied Informatics Winter, IIAI-AAI-Winter 2023

作者： Ramdhan, Dimas Pratama, Galih Dea Wijaya, Michael Francis Syahputra, Muhammad Edo Wihendro Game Application & Technology Program School of Computer Science Bina Nusantara University Computer Science Department Jakarta Indonesia School of Computer Science Bina Nusantara University Computer Science Department Jakarta Indonesia School of Information Systems Bina Nusantara University Information Systems Department Jakarta Indonesia

ISBN: (纸本)9798350383829

Batik is a cultural heritage of Indonesia, recognized by WHO as an Intangible Cultural Heritage. Batik is dyed by skilled craftsmen who make patterns with dots and lines on the fabric from melted wax. The process is complicated, so few people can experience all the steps in crafting Batik. From these problems, immersive learning media are needed so everyone can learn and gain experience in Batik crafting from start to finish. In this study, we will present Nge-BatikVR, a serious game application that introduces Batik through Virtual Reality and offers an immersive experience of learning Batik from various regions with interactive hands-on feature aimed at people to better understand and learn Batik. Nge-BatikVR offers four main features called Sinau (Learn), Kuis (Quiz), Nge-Batik (Simulation) and Toko (Shopping), with the main purpose to present interactive and engaging media useful for introducing and learning Batik with a fully immersive experience. © 2023 IEEE.

关键词： Serious games

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PentaPen: Combining Penalized Models to Identify Important SNPs on Whole-genome Arabidopsis thaliana Data 24

PentaPen: Combining Penalized Models to Identify Important S...

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16th International Conference on Bioinformatics and Biomedical technology, ICBBT 2024

作者： Kohli, Nikita Tomal, Jabed H. Lin, Wenjun Yan, Yan Program of Data Science Thompson Rivers University KamloopsBC Canada Department of Mathematics and Statistics Thompson Rivers University KamloopsBC Canada School of Computer Science and Technology Algoma University BramptonON Canada School of Computer Science University of Guelph GuelphON Canada

ISBN: (纸本)9798400717666

In the rapidly advancing field of genomics, the identification of Single Nucleotide Polymorphisms (SNPs) plays a crucial role in understanding complex phenotypic *** study introduces "PentaPen", an innovative computational workflow which combines the strengths of five penalized models to achieve improved accuracy in SNP *** compare the performance of PentaPen with existing models, highlighting its advantages in solving problems arising from when the number of predictors exceeds the number of *** model comparison, we provide insights into PentaPen's effectiveness in utilizing all SNPs as input, streamlines data pre-processing, and leverages parallel computation, enabling the workflow a considerable stride in SNP ***, a thorough evaluation and comparison of computational complexities signifies competitive edge of the workflow over individual penalized *** future research directions, we propose applications of PentaPen to plant-specific characteristics and suggest further explorations to assess the robustness of its *** summary, this manuscript presents the genomics community with a tool that combines computational efficiency with high-precision SNP detection, making a strong contribution to the field of genomic research. © 2024 Copyright held by the owner/author(s).

关键词： Genome

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Braille Character Recognition Independent of Lighting Direction Using Object Detection Models 13

Braille Character Recognition Independent of Lighting Direct...

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

作者： Yamashita, Akihiro Shirakawa, Taichi Matsubayashi, Katsushi National Instituteo of Technology Tokyo College Dept. of Computer Science Tokyo Japan Graduate School of Media Design Keio University Kanagawa Japan

ISBN: (纸本)9798350373332

Braille text is widely used around the world as a means of communication for the visually impaired. Although Braille is often regarded as a tool for the visually impaired, there are instances where sighted individuals may want to verify Braille documents. For example, teachers at schools for the visually impaired may need to check homeworks or assignments written in Braille, or care workers supporting the daily lives of visually impaired people may need to verify Braille documents. To meet such social demands, optical Braille recognition (OBR) technologies have typically been developed using cameras and scanners. In particular, methods using object detection models based on Deep Learning have achieved high accuracy in recent years. Since Braille is represented by embossed dots on thick paper, the appearance of shadows varies greatly depending on the angle of the lighting. Therefore, the angle and intensity of the light significantly affect the accuracy of Braille recognition. Specifically, in the case of double-sided Braille, where Braille is embossed on both sides, it is necessary to distinguish between raised and recessed dots. Previous studies have mostly imposed constraints on the angle of illumination, such as limiting the imaging method to scanners or requiring the light source to be positioned on the top of the Braille document when using a camera. However, for practical use in daily life, it is preferable to recognize Braille documents regardless of the direction and lighting conditions. In this study, we created a dataset of Braille images captured under various angle of lighting and developed a Braille recognition model that is independent of the lighting angle by fine-tuning the object recognition model. We implemented and compared RetinaNet, which has been used in previous research, and the anchor-free model YOLOX as object detection models. As a result, we achieved a model capable of detecting Braille images with an accuracy of mAP50=O.98 or higher, reg

关键词： Deep learning

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Probabilistic Model Building Evolutionary Algorithm Using the Same Type and Size of Model for Any Binary Optimization Problems 13

Probabilistic Model Building Evolutionary Algorithm Using th...

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

作者： Kishimoto, Atushi Ohnishi, Kei Graduate School of Computer Science and Systems Engineering Kyushu Institute of Technology 680-4 Kawazu Iizuka-shi Fukuoka820a-8502 Japan

ISBN: (纸本)9798350373332

We propose a new probabilistic model building evolutionary algorithm that uses the same type and size of probabilistic model for any binary optimization problems. The proposed method represents a population as a binary matrix for any binary optimization problems and solves a given problem by transforming the population in the form of matrix to better one with 512 production rules of cellular automaton. Concretely, the proposed method builds a probabilistic model for generating new solution candidates while applying the 512 production rules to the matrix representing the population. The probabilistic model consists of the 512 inverse production rules and their application probabilities. The strong point of the proposed method is to be able to transform any binary optimization problems to the same size of 512-bit production rule optimization problem. Since the proposed method treats any binary optimization problems in a unified manner, we can easily explore a robust method for various binary optimization problems as the proposed method with particular configurations. As the first evaluation of the proposed method, we apply the proposed method to the same kind but different sizes of problems. The results show that depending strongly on the bit patterns of the global optima, the proposed method with the same configurations realizes a good scalability of the number of function evaluations required for obtaining near optimum to the problem size growth. © 2024 IEEE.

关键词： Cellular automata

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