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4th International Conference on Electrical, Electronics, Informatics, and Vocational Education, ICE-ELINVO 2021

作者： Hadinata, Alan Mashoedah Graduate Program of Electronics and Informatics Engineering Education State University of Yogyakarta Indonesia

Hydroponics is a method of growing crops without using soil, with the benefits of controlling the environment and nutrients, conserving water, and reducing labor. The applied technology is used to improve results that have consistency. This research was conducted with the aim of knowing the IoT devices and platforms used in the development of IoT-based hydroponics. Data obtained from the website *** and *** from 2016 to 2021. This study is a literature review using the PRISMA method. This method is used for literature review using a systematic and structured basic framework. The results of this study indicate that the variables measured are Temperature, Potential Hydrogen (pH), Total Dissolve Solid, Water Temperature, Humidity, UV, Carbon Dioxide, Soil Moisture and Electrical Conductivity. The device used is the ESP8266, Arduino, and Raspberry PI with the MySQL, Thingspeak, Firebase, Domoticz, and Wyliodrin IoT Platforms. © 2021 Institute of Physics Publishing. All rights reserved.

关键词： Hydroponics

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Toward Learning Factory for Industry 4.0: Virtual Reality (VR) for Learning Human–Robot Collaboration 1

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

作者： Ariansyah, Dedy Colombo, Giorgio Pardamean, Bens Bioinformatics and Data Science Research Centre Bina Nusantara University Jakarta11480 Indonesia Department of Mechanical Engineering Politecnico di Milano Milan20156 Italy Computer Science Department BINUS Graduate Program Master of Computer Science Program Bina Nusantara University Jakarta11480 Indonesia

ISBN: (数字)9783031290787

ISBN: (纸本)9783031290770

Industry 4.0 will bring not only transformation to the manufacturing technologies but also to the profile of the workforce. Education system should be revised to prepare the future graduates embracing the knowledge of the ongoing revolution. Initiatives on the modification of curriculum and tools to deliver the concepts of Industry 4.0 must be taken. This paper examines limitations of current engineering tools and proposes a virtual reality (VR)-based learning platform to support the teaching and learning activity for Industry 4.0, focusing on the design of Human–robot Collaboration (HRC). The development process began with the identification of the general Intended Learning Outcomes (ILOs) which were extracted from the review of the HRC design issues, followed by the evaluation of the current teaching tool. From these results, the new requirements of the tools to achieve ILOs are redefined. The implementation of the system is demonstrated to show the feasibility of the proposed learning platform. This workflow can serve as initial development of another learning platform for the other innovative concepts that form the building blocks of Industry 4.0. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023.

关键词： Industry 4.0

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Path Planning Method for Mobile Robots in Pedestrian-Friendly Environments Using Drone Bird's-Eye View

Path Planning Method for Mobile Robots in Pedestrian-Friendl...

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2025 IEEE/SICE International Symposium on System Integration, SII 2025

作者： Ye, Linghao Chugo, Daisuke Muramatsu, Satoshi Yokota, Sho Hashimoto, Hiroshi Kwansei Gakuin University Graduate School of Science and Technology Hyogo Sanda6691330 Japan Tokai University School of Information Science and Technology Kanagawa Hiratsuka2591292 Japan Toyo University Faculty of Science and Engineering Saitama Kawagoe3508585 Japan Advanced Institute of Industrial Technology Master Program of Innovation for Design and Engineering Shinagawa Tokyo1400011 Japan

ISBN: (纸本)9798331531614

The objective of this paper is to develop a robot system that can transmit the video taken by the drone to the computer in real time, use YOLO to recognize the image of pedestrians, and enable the ground robot to plan the path to avoid pedestrians. External sensors, such as laser range finders (LRF) and CCD cameras, are often used on mobile robots. As we all know, these sensors are susceptible to occlusion. Therefore, even if the mobile robot avoids the pedestrian in front of it, it is likely to collide with other pedestrians that cannot be detected due to occlusion. In this study, we used a drone to shoot videos at high altitudes, transferred the videos to a computer, used YOLO on the computer to perform image recognition of pedestrians around the robot, and passed the recognition results to ROS, which enabled it to plan a path to avoid pedestrians around it. As a result, showed that the videos shot at high altitudes could effectively identify pedestrians around the robot after being recognized by YOLO. © 2025 IEEE.

关键词： Drones

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Development of a Gesture Analysis System for Human System Interaction

Development of a Gesture Analysis System for Human System In...

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International Symposium on Soft Computing and Intelligent Systems (SCIS)

作者： Chifuyu Matsumoto Yuka Sone Jinseok Woo Yasuhiro Ohyama Sustainable Engineering Program Graduate School of Engineering Tokyo University of Technology Hachioji Tokyo Japan Department of Mechanical Engineering School of Engineering Tokyo University of Technology Hachioji Tokyo Japan

ISBN: (数字)9798350373332

ISBN: (纸本)9798350373349

Recently, Japan has been facing various social issues, and to solve these problems, it is necessary to create a society where diverse people can live comfortably. To build such a society, appropriate support tailored to individuals is required, necessitating the analysis of various types of information to understand the people's needs at any given moment. In particular, analyzing non-verbal elements such as posture, facial expressions, and gestures is crucial, as these naturally indicate a person's condition. Therefore, this study focuses on human gestures, one of the non-verbal elements, and proposes a gesture recognition method using Dynamic Time Warping (DTW) and K-Means. We demonstrated that symbolic gesture recognition is possible by recording arm trajectories from skeletal measurements with an RGB-D camera.

关键词： Shape Time series analysis Gesture recognition Cameras Trajectory Recording

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Predicting Types of Urinary Crystals and Diameter Using Image Processing Techniques and Deep Learning Models 24

Predicting Types of Urinary Crystals and Diameter Using Imag...

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8th International Conference on Medical and Health Informatics, ICMHI 2024

作者： Huang, Yu-Ju Tseng, Yi-Shiou Chen, Tzu-Jung Chien, Ting-Ying Department of Computer Science and Engineering Yuan Ze University Taoyuan City Taiwan Department of Surgery Far Eastern Memorial Hospital Graduate Institute of Medicine Yuan Ze University Taiwan Graduate Program in Biomedical Informatics Yuan Ze University Taoyuan City Taiwan Innovation Center for Big Data and Digital Convergence Yuan Ze University Taoyuan City Taiwan

ISBN: (纸本)9798400716874

Kidney stones are primarily crystals formed from ion oversaturation in urine. Currently, the diagnosis of kidney stones involves experienced professionals manually interpreting images of urinary crystals under a microscope. In recent years, with the rapid development of artificial intelligence (AI), many researchers have proposed various methods to assist in diagnosis, hoping to improve medical quality. This study explored the application of AI in the medical field, aiming to automate the interpretation of urinary crystal images, such as red blood corpuscles (RBCs), calcium oxalate monohydrate (COM), calcium oxalate dihydrate octahedron (COD-OCT), calcium oxalate dihydrate dodecahedron (COD-DOD), debris, and others, and to use image processing techniques to classify urinary crystal types. This research is expected to assist medical personnel in quickly determining the categories of urinary crystals. Ultimately, our model achieved an F1-score of 0.93, indicating that this architecture has significant potential. © 2024 Copyright ACM.

关键词： Deep learning

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Plant Maintenance Budgeting Prioritization Based on Reliability Prediction of Repairable System 5th

Plant Maintenance Budgeting Prioritization Based on Reliabil...

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5th International Conference on Mechanical engineering, ICOME 2021

作者： Setia, Fandi Wibawa, Agus Yuniarto, Muhammad Nur Graduate Program of Mechanical Engineering Institut Teknologi Sepuluh Nopember Surabaya Indonesia PT Pembangkitan Jawa Bali Jl. Ketintang Baru No. 11 Surabaya60231 Indonesia Department of Mechanical Engineering Institut Teknologi Sepuluh Nopember Surabaya60111 Indonesia

ISBN: (纸本)9789811908668

A reliability prediction study has been carried out using failure data from the gas turbine system at a combined cycle power plant in Indonesia. From this study, the prediction value of the equipment reliability of the gas turbine subsystem was obtained along with the value of Failure Cost (FC), Component Risk (CR), and Maintenance Cost (MC) which is then processed further to produce a Benefit to Cost Ratio (BCR) which is useful for preparing priority rankings for the allocation of very limited maintenance budgets. This research also leads to a conclusion that the more the failures experienced by the equipment in one observation period, the lower the predictive value of its reliability. In addition, it is also discovered the fact that subsystems with the same number of failures but with different times of failure will produce different reliability values. And lastly, the subsystem risk rating obtained from Component Risk (CR) does not necessarily become a budget priority rating;this rating can change when the risk rating is combined with Maintenance Cost (MC) to produce a more objective budget priority rating with broader considerations. The methodology that combines the prediction of equipment reliability with budget prioritization in this research can also be used in other power generation plants that predominantly manage physical assets in order to obtain optimal asset life cycle management without compromising the performance of the equipment in the power plant due to limited maintenance budgets. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Gas turbines

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Dynamic Magnesiothermic Reduction of Various Silica to Porous Silicon Structures for Lithium Battery Anodes

SSRN

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SSRN 2024年

作者： Choi, Wondo Bae, JeongWoo Kim, Hyeonbin Sohn, Chansik Karuppaiah, Murugesan Lee, Jung Kyoo Department of Chemical Engineering BK21 FOUR Graduate Program Dong-A University Busan49315 Korea Republic of

A dynamic magnesiothermic reduction (DMR) of various silica having different size and porosity is conducted to study the effects of silica properties on the i) DMR reaction kinetics, ii) properties of resulting pSi microparticles, and iii) performances of pSi/C composites as anodes in lithium batteries. A DMR kinetic study using the Ginstling–Brounstein diffusion model shows that the smaller the silica particle size, the larger the reduction rate and the lower the apparent activation energy. Irrespective of silica properties, all the resulting pSi particles have mesoporous structures. The pSi particles comprise interconnected small primary silicon nanoparticles (approximately 30–40 nm in diameter) to render similar particle morphologies to those of parent silica. Owing to these appealing features of pSi particles, pSi/C composites exhibit excellent cycling performance up to over 200 cycles and high rate capabilities, whereas SiMP/C (prepared with a non-porous silicon microparticles) lose most of its capacity in early cycles owing to high resistance build-up during cycling. Overall, the DMR of silica precursors of several micrometers or less in size (preferentially porous precursors) are desirable for the production of high-purity pSi microparticles for use in high-capacity and stable anodes for advanced lithium batteries. © 2024, The Authors. All rights reserved.

关键词： Anodes

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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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Application of edible films from fermented Opuntia cochenillifera mucilage in the preservation of minimally processed fruits

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Food Chemistry 2025年 488卷 144849页

作者： Monteiro, Shênia Santos dos Anjos, Antônia Isabelly Monteiro de Sousa, Anna Clara Batista da Silva, Mikaelly Batista Monteiro, Shirley Santos Moreira, Emmanuel Pereira Almeida, Renata Duarte de Bittencourt Pasquali, Matheus Augusto Federal University of Campina Grande Graduate Program in Engineering and Natural Resources Management Campina Grande58429-900 Brazil Federal University of Campina Grande Graduate Program in Food Engineering Campina Grande58429-900 Brazil Department of Agronomy Federal University of Paraiba Areia58397-000 Brazil Federal University of Paraiba Bananeiras58220-000 Brazil

This study evaluated a coating based on Opuntia cochenillifera mucilage fermented with Lactobacillus gasseri and starch (MOCF-S) to extend the shelf life of minimally processed melons under refrigeration. The films were characterized according to thickness, solubility, water vapor permeability, optical properties, morphology, Fourier transform infrared spectroscopy (FTIR), and thermal and mechanical properties. The MOCF-S film showed high solubility (96.43 %), greater water vapor permeability (6.13 g/kPa h m2), and a smooth and uniform surface, suggesting compatibility between fermented mucilage and starch. It also demonstrated greater tensile strength and the presence of amide I bands in FTIR, indicating structural interactions. Antimicrobial activity was detected in the contact area against Escherichia coli (6.7 to 7.3 mm) and Staphylococcus aureus (6.7 to 7.7 mm). After 12 days at 5 °C, the coated fruits maintained better titratable acidity and antioxidant compounds compared to the control, demonstrating the potential of the MOCF-S film in postharvest conservation. © 2025 Elsevier Ltd

关键词： Fourier transform infrared spectroscopy

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Enhancing chemical synthesis: a two-stage deep neural network for predicting feasible reaction conditions

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Journal of Cheminformatics 2024年第1期16卷 11页

作者： Chen, Lung-Yi Li, Yi-Pei Department of Chemical Engineering National Taiwan University No. 1 Sec. 4 Roosevelt Road Taipei 10617 Taiwan Taiwan International Graduate Program on Sustainable Chemical Science and Technology (TIGP-SCST) No. 128 Sec. 2 Academia Road Taipei 11529 Taiwan

In the field of chemical synthesis planning, the accurate recommendation of reaction conditions is essential for achieving successful outcomes. This work introduces an innovative deep learning approach designed to address the complex task of predicting appropriate reagents, solvents, and reaction temperatures for chemical reactions. Our proposed methodology combines a multi-label classification model with a ranking model to offer tailored reaction condition recommendations based on relevance scores derived from anticipated product yields. To tackle the challenge of limited data for unfavorable reaction contexts, we employed the technique of hard negative sampling to generate reaction conditions that might be mistakenly classified as suitable, forcing the model to refine its decision boundaries, especially in challenging cases. Our developed model excels in proposing conditions where an exact match to the recorded solvents and reagents is found within the top-10 predictions 73% of the time. It also predicts temperatures within ± 20 ^∘C of the recorded temperature in 89% of test cases. Notably, the model demonstrates its capacity to recommend multiple viable reaction conditions, with accuracy varying based on the availability of condition records associated with each reaction. What sets this model apart is its ability to suggest alternative reaction conditions beyond the constraints of the dataset. This underscores its potential to inspire innovative approaches in chemical research, presenting a compelling opportunity for advancing chemical synthesis planning and elevating the field of reaction engineering. Scientific contribution: The combination of multi-label classification and ranking models provides tailored recommendations for reaction conditions based on the reaction yields. A novel approach is presented to address the issue of data scarcity in negative reaction conditions through data augmentation. Graphical Abstract: [Figure not available: see fullt

关键词： Multi-label classification Multi-task modeling Reaction condition Recommendation system

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