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23rd International Conference on Machine Learning and Cybernetics, ICMLC 2024

作者： Tokuda, Haruto Bilguunmaa, Myagmardulam Takagi, Noboru Fuse, Yotato Motoyoshi, Tatsuo Sawai, K.E.I. Masuta, Hiroyuki Graduate School of Intelligent Robotics Program Toyama Prefectural University Japan Toyama Prefectural University Department of Data Science Japan Toyama Prefectural University Department of Intelligent Robotics Japan

ISBN: (纸本)9798331528041

Standing in line poses a significant challenge for the visually impaired. Existing queue guidance systems, which recognize line locations and estimate personal orientation, require highspecification computers, making them impractical for everyday use. This study proposes a smartphone-based queue guidance system that leverages the device's camera and sensors to estimate personal orientation efficiently. By optimizing computationally efficient algorithms for smartphone hardware, we aim to create an accessible, cost-effective solution. This system will enhance the independence and mobility of visually impaired individuals, providing real-time guidance to navigate queues seamlessly. Initial testing indicates promising usability and accuracy, paving the way for broader implementation. © 2024 IEEE.

关键词： Smartphones

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Investigation of Robot's Eye Gaze Affecting Human Pedestrian Behavior by Robot in Virtual Space 23

Investigation of Robot's Eye Gaze Affecting Human Pedestrian...

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23rd International Conference on Machine Learning and Cybernetics, ICMLC 2024

作者： Takata, R.Y.O. Fuse, Yotaro Takagi, Noboru Myagmardulam, Bilguunmaa Motoyoshi, Tatsuo Sawai, K.E.I. Masuta, Hiroyuki Graduate School of Intelligent Robotics Program Toyama Prefectural University Toyama Japan Toyama Prefectural University Department of Data Science Toyama Japan Toyama Prefectural University Department of Intelligent Robotics Toyama Japan

ISBN: (纸本)9798331528041

We investigate the effects of robot's gaze on human behavior when a human and a robot pass each other in a virtual reality space (VR). Nonverbal communication, particularly eye contact, influences physical proximity between individuals in human-to-human interaction. Results of a study indicate that the robot's gaze affects the physical distance between a human and a robot in human-robot communication. Studies on robot's gaze tend to focus on experimental scenarios in which robots and humans communicate. However, robot's gaze in environments with interactions, such as crossing paths, has not been extensively investigated. Therefore, we hypothesize that the robot's gaze exhibits an influence on the physical distance between humans and robots during encounters. In our experiment, we compare three conditions: a robot with a rotating neck and gaze directed at the subject, a faceless robot with a rotating neck, and a faceless robot with a rotating neck and gaze directed at the subject. We analyze the subject's paths of movement and physical distance between the subjects and the robot. Results suggest that the hypothesis that 'intimacy equilibrium model' works when humans and robot's cross paths in the VR environment is not supported. © 2024 IEEE.

关键词： Human robot interaction

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Consideration of Constructing a Weed Detection Method for an Agricultural Robot in Perilla Fields 23

Consideration of Constructing a Weed Detection Method for an...

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23rd International Conference on Machine Learning and Cybernetics, ICMLC 2024

作者： Sugie, Tatsuya Takagi, Noboru Motoyoshi, Tatsuo Sawai, Kei Masuta, Hiroyuki Graduate School of Intelligent Robotics Program Toyama Prefectural University Toyama Japan Toyama Prefectural University Department of Data Science Toyama Japan Toyama Prefectural University Department of Intelligent Robotics Toyama Japan

ISBN: (纸本)9798331528041

In recent years, the number of farmers in Japan has been decreasing, and the automation of agriculture using robots, AI, and IoT, known as 'smart agriculture,' is being promoted. In this context, Toyama city is promoting a project to build a robot for automatic weeding between plants in a perilla fields. In this research, we are in charge of the system part that detects weeding regions and informs the weeding mechanism. In the field, a wide variety of weeds form vegetation, and it is necessary to prevent food crops from being cut. Therefore, we detect crop regions and the rest of the area should be the weeding regions. In this study, we construct a system to detect crop regions by transfer learning the object detection model YOLO-v8, which is a convolutional neural network (CNN), and evaluate the system in terms of detection accuracy and processing speed. © 2024 IEEE.

关键词： Convolutional neural networks

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Design of an Automatic Price Tag System for Web-Based Retail Business 9

Design of an Automatic Price Tag System for Web-Based Retail...

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9th International Conference on Information Management and Technology, ICIMTech 2024

作者： Liawatimena, Suryadiputra Gunawan, Devina Bina Nusantara University Automotive & Robotics Program Computer Engineering Department BINUS ASO School of Engineering Computer Science Deparment BINUS Graduate Program Master of Computer Science Jakarta11480 Indonesia Bina Nusantara University Automotive & Robotics Program Computer Engineering Department BINUS ASO School of Engineering Jakarta11480 Indonesia

ISBN: (纸本)9798350390025

Modern retail businesses face a significant challenge with the inefficiency of manually changing price labels on shelves. This manual process not only consumes valuable time and resources but also increases the likelihood of errors, leading to potential inaccuracies in pricing and a less streamlined shopping experience for customers. The proposed solution is the implementation of an Electronic Shelf Label (ESL) system that automatically displays the prices of goods on retail business shelves. This system connects a website (front end and back end) to e-paper via a Wi-Fi network and microcontroller, allowing retail business owners to update prices more easily. Additionally, buyers can search for desired items through the website. The results are the time to send data from the website to the e-paper, namely, to know the performance of the e-paper used. The average time required from 10 attempts to send data from the website to the e-paper is 20.935 seconds. Since the data is connected to the server and will be updated automatically, using this system will be more efficient than manually changing the price label, although it takes time to transfer data from the website to the e-paper. © 2024 IEEE.

关键词： Sales

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Traffic Signs Detection System Using YOLO (You Only Look Once) That Provides Notification 1

Traffic Signs Detection System Using YOLO (You Only Look Onc...

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1st International Conference on Smart Mechatronics, ICSMech 2024

作者： Setiawan, Yosua Puji, Muhammad Nurul Astuti, Winda Binus Aso School of Engineering Bina Nusantara University Automotive & Robotics Program Computer Engineering Department Jakarta11480 Indonesia

ISBN: (纸本)9798350368918

Road accidents have become a problem for many road users in many countries. It may affect human daily activity and tasks, potentially influencing productivity and safety. Therefore, reducing road accidents as swiftly and effectively as possible is critical. For this reason, a Traffic signs detection system has been developed in this work to improve road safety. The detection system can detect traffic signs on the road such as traffic lights, speed limits, and no U-turn signs, and then it will provide users with the corresponding text on an LCD and vibration feedback using a motor. Throughout this work, the You Only Look Once (YOLO) algorithm is proposed for detecting traffic signs on the road. Moreover, a camera is used to extract live videos which serve as an input for the Raspberry Pi 4 model B containing custom YOLOv5 and YOLOv8 models. The system then sends the output to an LCD, a vibration motor, and a radio frequency (RF) module as notifications for users. In the end, the performance of the proposed method has been collected and it is found to produce good accuracy within an inconsiderable amount of 1.677 images and 2.263 annotations. Therefore, the accuracy of 0.69 for YOLOv5 and 0.7 for YOLOv8 were obtained from the training and validation process. Furthermore, the system accurately detects the traffic signs on the road. © 2024 IEEE.

关键词： Traffic signs

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Development of Detection Lung Disease Stand Alone System Based on Convolutional Neural Network (CNN) 7

Development of Detection Lung Disease Stand Alone System Bas...

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7th International Conference of Computer and Informatics Engineering, IC2IE 2024

作者： Liewarnata, Edgar Caesar Mariana, Yosica Tan, Sofyan Liawatimena, Suryadiputra Astuti, Winda Bina Nusantara University Binus Aso School of Engineering Automotive and Robotics Program Computer Engineering Department Jakarta11480 Indonesia Bina Nusantara University Binus Aso School of Engineering Product Design Program Industrial Engineering Department Jakarta11480 Indonesia Bina Nusantara University Binus Graduate Program - Master of Computer Science Automotive and Robotics Program Computer Engineering Department Binus Aso School of Engineering Computer Science Department Jakarta11480 Indonesia

ISBN: (纸本)9798331505530

Lung disease, especially Tuberculosis (TBC), placed the highest death rate in Indonesia. Tuberculosis (TB) in Indonesia is ranked second after India. Therefore, it is important to reduce or early detection of the lung disease, to prevent this disease and speed up handling. The system can recognize the disease lung identification, and the system applied as standalone system. In this work, the Convolutional Neural Network (CNN) approach for identifying diseases lung identification is proposed. The Mel Frequency Cepstral Coefficient (MFCC) applied to process the stethoscope sounds which will used as input to the CNN. The performance of the proposed system has been investigated and resulted. The accuracy of 99% and 98%, for training and testing accuracy respectively. Furthermore, the system accurately detects lung diseases identification. © 2024 IEEE.

关键词： Lung cancer

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Design and Development of an Internet of Things (IoT)-Based Application and System to Detect Stunting in Infants and Toddlers 10

Design and Development of an Internet of Things (IoT)-Based ...

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10th International HCI and UX Conference in Indonesia, CHIuXiD 2024

作者： Tiffany, Theresa Jeremia, James Lie, Zener Sukra Bina Nusantara University Binus Aso School of Engineering Automotive and Robotics Engineering Program Computer Engineering Department Jakarta11480 Indonesia

ISBN: (纸本)9798350380439

Currently, the process of monitoring children's growth in Indonesia relies on manual methods for collecting anthropometric data. These methods pose a risk of data recording errors. Additionally, the ratio of healthcare workers to children in Indonesia is 1:90, a significant disparity that hinders efforts to reduce the prevalence of stunting in the country. To support the third Sustainable Development Goal (SDG), which emphasizes 'Good Health and Well-being,' it is crucial to address issues in the stunting management process, from data collection to monitoring. The design and development of this iOS-based mobile application aim to assist in monitoring child growth and provide guidance and steps for prevention and treatment. Besides application development, it also involves the design and development of an Internet of Things (IoT) system to aid in the collection of children's anthropometric data. The research methodology includes studying stunting cases in Indonesia, anthropometric data calculation methods, stunting prevention and management steps, application design and development, automatic anthropometric data collection, and online data storage and transmission using IoT technology. The developed application and system have been tested and successfully integrated. The IoT device has an accuracy rate of 99.83% for weight measurement calibration and 98.68% for height or length measurement calibration. From the testing results of the child condition calculation method in the application, an accuracy rate of 100% was achieved. © 2024 IEEE.

关键词： Anthropometry

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Separation of microalgae from bacterial contaminants using spiral microchannel in the presence of a chemoattractant

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Bioresources and Bioprocessing 2024年第1期11卷 511-525页

作者： Leticia F.Ngum Y.Matsushita Samir F.El-Mashtoly Ahmed M.R.Fath El-Bab Ahmed L Abdel-Mawgood Institute of Basic and Applied Sciences Biotechnology ProgramEgypt-Japan University of Science and TechnologyAlexandria 21934Egypt Institute of Basic and Applied Sciences Nanoscience ProgramEgypt-Japan University of Science and TechnologyAlexandria 21934Egypt Mechatronics and Robotics Engineering Department Egypt-Japan University of Science and TechnologyAlexandria 21934Egypt.

Cell separation using microfluidics has become an effective method to isolate biological contaminants from bodily fluids and cell cultures,such as isolating bacteria contaminants from microalgae cultures and isolating bacteria contaminants from white blood *** this study,bacterial cells were used as a model contaminant in microalgae culture in a passive microfluidics device,which relies on hydrodynamic forces to demonstrate the separation of microalgae from bacteria contaminants in U and W-shaped cross-section spiral microchannel fabricated by defocusing CO_(2) laser *** a flow rate of 0.7 ml/min in the presence of glycine as bacteria chemoattractant,the spiral microfluidics devices with U and W-shaped cross-sections were able to isolate microalgae(Desmodesmus sp.)from bacteria(***)with a high separation efficiency of 92%and 96%*** the same flow rate,in the absence of glycine,the separation efficiency of microalgae for U-and W-shaped cross-sections was 91%and 96%,*** was found that the spiral microchannel device with a W-shaped cross-section with a barrier in the center of the channel showed significantly higher separation *** microchannel chips with U-or W-shaped cross-sections were easy to fabricate and exhibited high *** these advantages,these devices could be widely applicable to other cell separation applications,such as separating circulating tumor cells from blood.

关键词： W-shaped cross-section CO_(2)laser ablation Glycine Separation efficiency Removal ratio

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Histogram of Oriented Gradients (HOG) and Haar Cascade with Convolutional Neural Network (CNN) Performance Comparison in the Application of Edge Home Security System 1

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International Conference on Innovative Technologies in Intelligent Systems and Industrial Applications, CITISIA 2022

作者： Asy’ari, Muhammad Zacky Filbert, Sebastian Sukra, Zener Lie Automotive and Robotics Program Computer Engineering Department BINUS ASO of Engineering Bina Nusantara University Jakarta Indonesia

ISBN: (数字)9783031290787

ISBN: (纸本)9783031290770

In recent years, security has played a significant role in our daily lives. House security has become more popular with the enhancement of the Internet of Things (IoT) in intelligent home automation. This paper aims to build a system that can detect faces and the presence of unknown people using computer vision methods combined with the Internet of things. Two algorithms, Histogram of Oriented Gradients (HOG) and Haar Cascade classifiers with the enhancement of Convolutional Neural Network (CNN), were used to compare their performance. The system utilizes Nvidia Jetson Nano as an edge device, HD camera, Light Emitting Diode (LED), and sound buzzer as peripheral hardware. Telegram messenger application was used to notify the homeowner when uninvited guests passed through the pre-defined security area. In the result, the HOG method has 100% accuracy compared to 75% Haar Cascade with 720p video quality in the proposed developed system. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023.

关键词： Internet of things

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ED-NERF: EFFICIENT TEXT-GUIDED EDITING OF 3D SCENE WITH LATENT SPACE NERF 12

ED-NERF: EFFICIENT TEXT-GUIDED EDITING OF 3D SCENE WITH LATE...

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12th International Conference on Learning Representations, ICLR 2024

作者： Park, Jangho Kwon, Gihyun Ye, Jong Chul Kim Jaechul Graduate School of AI Korea Republic of Robotics Program Korea Republic of Department of Bio and Brain Engineering KAIST Korea Republic of

Recently, there has been a significant advancement in text-to-image diffusion models, leading to groundbreaking performance in 2D image generation. These advancements have been extended to 3D models, enabling the generation of novel 3D objects from textual descriptions. This has evolved into NeRF editing methods, which allow the manipulation of existing 3D objects through textual conditioning. However, existing NeRF editing techniques have faced limitations in their performance due to slow training speeds and the use of loss functions that do not adequately consider editing. To address this, here we present a novel 3D NeRF editing approach dubbed ED-NeRF by successfully embedding real-world scenes into the latent space of the latent diffusion model (LDM) through a unique refinement layer. This approach enables us to obtain a NeRF backbone that is not only faster but also more amenable to editing compared to traditional image space NeRF editing. Furthermore, we propose an improved loss function tailored for editing by migrating the delta denoising score (DDS) distillation loss, originally used in 2D image editing to the three-dimensional domain. This novel loss function surpasses the well-known score distillation sampling (SDS) loss in terms of suitability for editing purposes. Our experimental results demonstrate that ED-NeRF achieves faster editing speed while producing improved output quality compared to state-of-the-art 3D editing models. Code and rendering results are available at our project page. © 2024 12th International Conference on Learning Representations, ICLR 2024. All rights reserved.

关键词： Distillation

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