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Student Conference on Research and Development (SCOReD)

作者： Joshu Leonardy Nawal Zuhdaniel Aflah Mohd Rashidi Bin Salim Mohd Haniff Bin Ibrahim Hadi Bin Manap Wildan Panji Tresna Faculty of Electrical Engineering Universiti Teknologi Malaysia JohorBahru Malaysia Military Physics Study Program The Republic of Indonesia Defense University Bogor Indonesia Faculty of Electrical & Electronic Engineering Technology University Malaysia Pahang Al Sultan Abdullah Pekan Malaysia Research Center for Photonics National Research and Inovation Agency Indonesia South Tangerang Indonesia

ISBN: (数字)9798331510077

ISBN: (纸本)9798331510084

This research explores the use of a modified infrared (IR) camera equipped with a high-pass filter to distinguish between natural objects (vegetation) and artificial objects (synthetic military uniforms) in an environment where vegetation makes objects difficult to detect. In military operations, especially guerrilla warfare in tropical forests, detecting enemies camouflaged in vegetation makes it difficult to distinguish targeted objects. Visible light cameras usually struggle to distinguish between synthetic and natural colors. This methodology involves the use of Python programming and various libraries, such as Computer Vision (CV), to process images captured by modified cameras. A graphical user interface (GUI) was developed to analyze color values, focusing on the red, green, and blue spectra. The results show that the modified IR camera can more effectively separate synthetic and natural object color peaks compared to a standard visible light camera, offering potential applications in military reconnaissance and sniper operations. This research demonstrates how image processing can improve object detection in complex environments.

关键词： Image color analysis Vegetation mapping Object detection Reconnaissance programming Cameras Standards Research and development Graphical user interfaces Python

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Faults Identification of Induction Motor Based on Vibration Using Backpropagation Neural Network

Faults Identification of Induction Motor Based on Vibration ...

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2020 International Conference on Smart Technology and Applications, ICoSTA 2020

作者： Kuspijani, K. Watiasih, Richa Prihastono, Prihastono Bhayangkara Surabaya University Electrical Engineering Study Program Engineering Faculty Surabaya Indonesia

ISBN: (纸本)9781728130835

Vibration analysis is very important in predictive maintenance in the industry today. In this paper, has designed a vibration detection system that can identify the condition of the induction motor by online. Induction motor vibration data is read from two vibration sensors, accelerometer1 and accelerometer2, displayed using ATMEGA16 microcontroller and can directly identify the condition of the induction motor by using artificial intelligence-based analysis that is Backpropagation-Neural Network (B-NN). After testing, the system managed to perform fault identification induction motor with the rank of success of 95 percent. © 2020 IEEE.

关键词： Accelerometers

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Java Bali Grid Mean Time To Failure Prediction using Machine Learning

Java Bali Grid Mean Time To Failure Prediction using Machine...

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Technology, engineering, and Computing Applications (ICTECA), International Conference on

作者： Priyo Adi Sesotyo M.M. Lanny W. Pandjaitan Lukas Professional Engineer Study Program Faculty of Engineering Universitas Katolik Indonesia Atma Jaya Jakarta Indonesia Electrical Engineering Dept. Universitas Semarang Semarang Indonesia Electrical Engineering Master Program Universitas Katolik Indonesia Atma Jaya Jakarta Indonesia Cognitive Engineering Research Group (CERG) Universitas Katolik Indonesia Atma Jaya Jakarta Indonesia

The role of Mean Time To Failure (MTTF) is critical to maintain cost-efficient in smart grids, as the predictive maintenance means for ensuring their reliability. Java Bali grid is the most important power network in Indonesia, because it holds 75% energy sales and the foundation of the Indonesian government, business and industrial sectors. One method for prediction in the machine learning is the Linear Regression, as part of the Supervised Learning technique. The regression model extracts the grid overload variable from MV distribution system, where connected load (MVA) divided by the number of MV customers. The model constructs the Linear Regression function, where the slope and intercept values found from the correlation between predicted response and actual response. After confronting the function f(x) and the coefficient of determination (R2), the test results for the MTTF prediction values for Java-Bali’s region shows the higher accuracy when the R2 shows highest value.

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Development of contactless human vital signs monitoring device with remote-photoplethysmography using adaptive region-of-interest and hybrid processing methods

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Intelligence-Based Medicine 2024年 10卷

作者： Novita, Dessy Adikusuma, Fajar Wira Rohadi, Nanang Wibawa, Bambang Mukti Trisanto, Agus Defi, Irma Ruslina Fauziah, Sherllina Rizqi Department of Electrical Engineering Universitas Padjadjaran Department of Physical Medicine and Rehabilitation Hasan Sadikin General Hospital/Faculty of Medicine Universitas Padjadjaran Nursing Science Study Program Faculty of Nursing Universitas Padjadjaran

Vital sign assessment is an examination that indicates changes in health. Direct contact during vital signs assessment can increase the risk of disease transmission. This research aimed to develop a contactless vital sign monitoring prototype that includes heart rate, respiratory rate, blood pressure, and oxygen saturation using a digital camera based on remote photoplethysmography with an adaptive region of interest. The adaptive region-of-interest method uses face detection and skin segmentation to generate red-green-blue signals, taking only the skin pixels of the patients while also minimising the effect of motion artefacts. The hybrid processing method combines several vital sign extraction methods to filter external irrelevant factors and produce heart rate, respiratory rate, blood pressure, and blood oxygen saturation values. In addition, the prototype was tested on 50 participants using standard vital sign assessment tools for comparison. The technical specification test of the prototype concluded that the optimal distance of this prototype was up to 2 m with a processing time of 2 s for every 1-s video. The vital signs results were presented using Bland-Altman, which showed that although the Bland-Altman plots revealed a substantial variance in the limits of agreement (±15–20 mmHg for blood pressure, ±15–17 bpm for heart rate, ±4–6 bpm for respiratory rate, and ±1–3 % for blood oxygen saturation), the mean differences for all vital signs were small (±0.7–5 mmHg for blood pressure, ±0.4–0.6 bpm for heart rate, ±0.5–0.7 bpm for respiratory rate, ±0.4–0.6 for blood oxygen saturation) and most data points were within the limits. While further clinical studies are needed to assess its reliability in monitoring specific medical conditions, the prototype has shown an acceptable agreement in assessing vital signs compared to the conventional methods, making it feasible for further development into a medical device. © 2024

关键词： Contactless monitoring Face detection Medical device Remote photoplethysmography Vital signs assessment

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The Use of Geogebra Software in Learning Geometry Transformation to Improve Students' Mathematical Understanding Ability 2

The Use of Geogebra Software in Learning Geometry Transforma...

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2nd International Conference on Computer, Science, engineering, and Technology, ICComSET 2019

作者： Ridha, Moch. Rasyid Pramiarsih, Euis Eka Widjajani Mathematic Study Program Faculty of Teacher Training and Education Universitas Langlangbuana Bandung Indonesia Economic Education Study Program Faculty of Teacher Training and Education Universitas Langlangbuana Bandung Indonesia Industrial Engineering Study Program Faculty of Engineering Universitas Langlangbuana Bandung Indonesia

This article reports the findings of one pretest-posttest design experiment with the control group and with GeoGebra software learning application to examine the mathematical understanding abilities and responses of students taking Geometry Transformation course. The subjects of this study were 24 students of mathematics education study program in Universitas Langlangbuana. The research instrument consisted of a mathematical comprehension ability test and a student response questionnaire. Based on data analysis using SPSS 2.0.0 and Microsoft Excel 2013, the study found that achievement and improvement in mathematical understanding skills and responses of students who received learning with GeoGebra software were better than achievement and improvement in student's ability who obtain conventional approach for the high, middle and low categories. The study also found a moderate relationship between mathematical understanding ability and student response. © 2020 Published under licence by IOP Publishing Ltd.

关键词： Students

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Effect of feedback on learning motivation of primary teacher education students in primary school physics courses 10

Effect of feedback on learning motivation of primary teacher...

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10th National Physics Seminar, SNF 2021

作者： Sianipar, L.K. Sitompul, H. Sanjaya, L.A. Puspa, R.W.D. Pertiwi, W.A. Qoiriyah, W. Department of Physics Education Universitas Pelita Harapan Tangerang15811 Indonesia Department of Physics Faculty of Mathematics and Natural Science Universitas Negeri Jakarta Indonesia Kartika VIII-1 Senior High School Jakarta Indonesia Islamic Education Management Study Program Faculty Islamic of Education and Teacher Training Muhammad Azim Institute Jambi Indonesia Informatics Engineering Study Program Faculty of Engineering Sheikh Yusuf Islamic University Tangerang Indonesia

Based on the results of the questionnaire distributed to Primary Teacher education Students, 96% of students said that Physics is difficult to understand because the material is very complex, many formulas, especially the learning process is done online. This study aims to describe the influence of providing feedback on the motivation of Primary Teacher education Students in primary school physics courses. The method used in this research is descriptive qualitative. Meanwhile, the instrument used was a questionnaire which was distributed to 115 elementary school education students. The result of the research shows that giving feedback consistently is able to motivate students. This can be seen from the results of the questionnaires distributed, each indicator is of very good value. © 2021 Institute of Physics Publishing. All rights reserved.

关键词： Students

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Used cooking oil catalytic cracking using Cr-charcoal ion-exchanged catalyst 6

Used cooking oil catalytic cracking using Cr-charcoal ion-ex...

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6th International Conference on Mathematics, Science, and education, ICMSE 2019

作者： Nazarudin Ulyarti Alfernando, O. Fitri, S. Chemistry Engineering Study Program Faculty of Engineering Universitas Jambi Indonesia Chemistry Education Study Program Faculty of Teacher Training and Education Universitas Jambi Indonesia Center of Energy and Nanomaterial Study Universitas Jambi Indonesia

Used cooking oil is the largest waste that can be converted into biofuel as a renewable alternative energy source with catalytic cracking process. In this study, used cooking oil was cracked using a Cr-Carbon catalyst. The charcoal was produced from solid waste (shell) of oil palm industry. Three different chromium concentrations (1, 2, and 3%) were used for the ion-exchange process of Cr-charcoal to produce the catalyst. These catalysts were used for the catalytic cracking of used cooking oil at three levels of temperature (450, 500, and 550°C). X-ray diffraction (XRD) and scanning electron microscopy (SEM) analysis were used for catalyst characterization. SEM-energy dispersive X-ray spectroscopy (EDX) analysis indicates that Cr was successfully adsorbed into the catalyst. The highest oil fraction was obtained from catalytic cracking of used cooking oil at 450°C using Cr-charcoal catalyst synthesized using 1% Cr solution. © Published under licence by IOP Publishing Ltd.

关键词： Catalysts

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ML-Agents in Kart Racing Game using Microgame

ML-Agents in Kart Racing Game using Microgame

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International Conference on Telecommunication Systems, Services, and Applications (TSSA)

作者： Afina Anfa Ana Vitradisa Pratama Agus Sukoco Ary Setijadi Prihatmanto Rin Rin Nurmalasari Agus Juhana School of Electrical Engineering and Informatics Institut Teknologi Bandung Bandung Indonesia Departement of Informatics Universitas Mayasari Bakti Tasikmalaya Indonesia Department of Electrical Engineering UIN Sunan Gunung Djati Bandung Indonesia Multimedia Education Study Program Universitas Pendidikan Indonesia Bandung Indonesia

This paper presents an innovative approach to integrating ML-Agents into a microgame-based kart racing environment, showcasing the potential for enhancing gameplay experiences through AI-driven opponents. Kart Unity Game is a racing game that uses small motorized vehicles but still uses the concept of racing in the real world. One of the racing game development platforms is Unity. Unity has developed a platform, Unity Karting Microgame, which users can modify. Unity Karting Microgame applies self-driving to ML-Agents trained and designed to drive their karts with suitable sensors and actuators. The method used to develop the game is to modify the racetrack and modify ML-Agents to make the game more exciting and fun. As a result of this study, successful implementation of ML-Agents in a microgame-based kart racing environment. The study highlights the potential of using Unity ML-Agents to create AI-driven opponents that enrich gameplay experiences. Games can run well and seem varied. ML-Agents can also control their karts on their lanes. Thus, kart racing games can be implemented.

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Biomedical Image Quality Improvement with Spatial Domains 2

Biomedical Image Quality Improvement with Spatial Domains

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2nd International Conference on Innovative and Creative Information Technology, ICITech 2021

作者： Fernando, Erick Siagian, Pandapotan School of Information Systems Bina Nusantara University Information Systems Department Jakarta11480 Indonesia Computer Engineering Study Program Del Institute of Technology Faculty of Informatics and Electrical Engineering North Sumatera22381 Indonesia

ISBN: (纸本)9781728197463

Digital image processing aims to improve the quality of an original image so that it can display an image that is relatively better than the original image, so as to obtain the detailed information needed for an analysis need. Quality degradation Biomedical images in computerization usually experience changes in brightness, blur, and contrast stretching. Because of the deterioration in the image quality, doctors and patients cannot obtain the information needed for analysis, therefore the need for biomedical image processing techniques with spatial domain methods to improve the quality and details of information in the image so that it helps doctors in diagnosing. Data analysis is biomedical images like X-ray images, CT-Scan (Computer Tomographic Scan) images, and USG (Ultrasound Graphic) images. A focused study on improving image quality can be done with digital spatial domain image processing techniques. Digital domain image processing is digital image processing based on the manipulation of pixel values in the image directly, in the form of point processing and mask processing. Process testing for each image for Blur level is CT-scan images with a value of 0.98436, ultrasound images with a value of 0.9875, X-ray images with a value of 0.9836. This value is blur level value get near to 1 which means the image becomes clearer. The analysis results prove that the spatial domain method can clarify the object image in this study. The biomedical image quality processing model is proven to be able to improve the quality of the image that is declining due to the digitization process and assist the user in analyzing the biomedical image. © 2021 IEEE.

关键词： Image quality

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Smartphone Application As An Air Quality Monitor Using Raspberry Pi for Reducing Air Pollution 2

Smartphone Application As An Air Quality Monitor Using Raspb...

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2nd International Conference on Innovative and Creative Information Technology, ICITech 2021

作者： Siagian, Pandapotan Fernando, Erick Computer Engineering Study Program Del Institute of Technology Faculty of Informatics and Electrical Engineering North Sumatera22381 Indonesia School of Information Systems Bina Nusantara University Information Systems Department Jakarta11480 Indonesia

ISBN: (纸本)9781728197463

Good air quality is very important in human health. However, air pollution has been polluted everywhere, whether in the house, in cities. This is caused by a growing industry that produces air pollution. Room air pollution and various cities will contribute to air pollution, which will cause problems for human health. This work measures the carbon monoxide level using the MQ-7 sensor and measures the air's carbon dioxide level with the CCS811 sensor and MH-Z19 sensor. All three sensors are connected to the NodeMCU ESPS266, and we call it a NodeMCU module. Tests are carried out in three rooms in the house, and then three NodeMCU modules are used so that the three modules will send data alternately. Raspberry Pi3 (RPi3) functions as a server that collects data and acquires information data from sensors. Data from the CCS811 (TCOV) sensor, MH-Z19 (co2), will be processed first with fuzzy logic rules to make decisions about CO2, which are right, moderate, nasty conditions. The process is carried out on the Raspberry Pi 3 server with MQTT using publication, customer, fuzzy logic, and broker services. The value of the sensor's measurement results can be accessed via a smartphone and provides good air control values. © 2021 IEEE.

关键词： Air quality

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