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3rd International Conference on Electronic and electrical engineering and Intelligent System, ICE3IS 2023

作者： Mustar, Muhamad Yusvin Tryatmojo, Bintang Surya Hidayat, Maulana Wiyagi, Rama Okta Ulfa, Maria Fredianto, Meiky Ihsan, Muhammad Universitas Muhammadiyah Department of Electrical Engineering Yogyakarta Indonesia Research and Innovation Institute Universitas Muhammadiyah Center of Artificial Intelligence and Robotic Studies Yogyakarta Indonesia Universitas Muhammadiyah Postgraduate Program Master of Hospital Administration Yogyakarta Indonesia Universitas Muhammadiyah Faculty of Medicine and Health Sciences Yogyakarta Indonesia

ISBN: (纸本)9798350327762

This research offers an alternative for health workers to monitor the rehabilitation of a patient's Range of Motion (ROM) without using a goniometer instrument and attaching various sensors to the patient's body, based on a detection system using the MediaPipe library. The developed detection system measures angles concerning the patient's body ROM patterns. The algorithm in the MediaPipe library helps to produce line graphs of landmark pose which are then processed using the trigonometric gradient equation so that it can have to measure angles from ROM. The angle of ROM measured includes Flexion-Extension and Abduction-Adduction movements of the arms, legs, and body. The results of testing the detection system between the goniometer measurements and the detection results differ from the Right Arm Elbow Flexion-Extension movement to the Trunk Flexion-Extension movement having an angle difference. The most significant angle difference is in the Right Arm Elbow Abduction - Adduction movement of 9.1388°, and the minor difference is in the Right Leg Hip Abduction - Adduction movement of 2.15°. The most significant overall system error is in the Left Arm Elbow Flexion - Extension movement, with a general system error of 27%. The minor system error in Left Arm Elbow Abduction - Adduction movement is 11 %. © 2023 IEEE.

关键词： Errors

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Objective Sleep Quality Measurement based on Fuzzy Logic and Wearable Device

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Procedia Computer Science 2023年 227卷 1153-1162页

作者： Jason A. Wijaya Pauw D. Andersen Nico Surantha Computer Science Department BINUS Graduate Program – Master of Computer Science Bina Nusantara University Jakarta 11480 Indonesia Department of Electrical Electronic and Communication Engineering Tokyo City University Japan

Sleep is the natural state of relaxation for human being. Sleep quality is an essential yet frequently neglected aspect of sleep in general. Sleep quality is essential because it allows the body to restore itself and prepare for the next day. The standard method for evaluating sleep quality was subjective evaluation. Actigraphy devices, which can measure the sleep cycle, are now widely available. This study developed a method using Fuzzy Logic and an actigraphy device to measure and classify sleep quality. The fuzzy logic method was developed in several stages, which are determining the sleep quality measurement parameters, constructing the fuzzy set for each input variable, and developing the fuzzy rules. To evaluate the proposed fuzzy model, five individuals were invited to participate in the experiment and required to complete the PSQI subjective sleep questionnaire. The evaluation result shows that our proposed Fuzzy model achieves lower error compared to the existing method.

关键词： sleep sleep quality actigraphy artificial intelligences fuzzy logic

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Computational Network-on-Chip as Convolution Engine

Computational Network-on-Chip as Convolution Engine

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Technology, Systems and Applications (VLSI-TSA/VLSI-DAT), International VLSI Symposium on

作者： Zhonghai Lu Mingrui Liu Department of Electrical Engineering School of EECS KTH Royal Institute of Technology Stockholm Sweden Embedded Systems master program School of EECS KTH Royal Institute of Technology Stockholm Sweden

ISBN: (数字)9798350360349

ISBN: (纸本)9798350360356

Inspired by PiN, Processing in Network-on-Chip (NoC), we propose a computational NoC as a convolution engine for accelerating convolutional neural networks in hardware. In contrast to traditional compute architectures where computation and communication are conducted serially and in separation, our computational NoC enables in-transit computation, meaning that computation is performed while packets are transferred in the network. In the paper, we present the router architecture that supports the novel in-transit computation concept, and use a running example to detail the entire convolution process in the computational NoC. Finally, we show simulated performance results in comparison with traditional NoC-based convolution engine.

关键词： Convolution Simulation Computer architecture Network-on-chip Very large scale integration Hardware Pins

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Sales forecasting for life insurance on primary and supplementary policies using seasonal and trend methods

Sales forecasting for life insurance on primary and suppleme...

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IEEE PES Asia-Pacific Power and Energy engineering Conference (APPEEC)

作者： Panrawe Boonsom Chanin Wongyai Duang-Arthit Srimoon Student in Master of Electrical and Computer Engineering Program College of Engineering Rangsit University Pathumthani Lak-Hok Thailand Faculty of Computer Engineering College of Engineering Rangsit University Pathumthani Lak-Hok Thailand

ISBN: (数字)9798350318098

ISBN: (纸本)9798350318104

Sales of insurance are collected monthly or yearly as statistics which most insurance companies haven’t estimated the sales for the next year. The current sales of insurance make it difficult to evaluate the market and organize various campaigns for customers. Therefore, this research has collected sales of life insurance from the website of the Office of Insurance Commission from the year 2018 - 2022. The forecasting of sales for life insurance using 4 forecasting methods which are Holt Winters' Additive, Holt Winters' Multiplicative, Simple Exponential Smoothing, and Double Exponential Smoothing. These forecasting methods are used to forecast insurance premiums one year ahead from the year 2021. The computation of total sales for 3 insurance types which are Primary-General, Primary, and Additional found that the Holt Winters' Multiplicative method is the best forecasting method with an accuracy percentage for forecasting methods of 97.56%.

关键词： Smoothing methods Additives Accuracy Measurement uncertainty Insurance Companies Market research

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Self-Tuning Neural Network Controller Based on Fuzzy Logic for Multiple Positions Tracking of a Pneumatic Driven Soft Endoscope Actuator

Self-Tuning Neural Network Controller Based on Fuzzy Logic f...

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International Conference on Autonomous Robots and Agents, ICARA

作者： Renzo Acosta Julio Tafur Ruth Canahuire Enginnering Department Control and Automation Engineering Master Degree Program Pontificia Universidad Catolica del Peru Lima Peru Department of Electrical and Mechatronics Engineering Universidad de Ingenieria y Tecnologia - UTEC Lima Peru

ISBN: (数字)9798350394245

ISBN: (纸本)9798350394252

This paper presents the dynamic modelling and end effector position control of a soft endoscope. Soft endoscope system under study consists mainly of a pneumatic driven soft actuator (PDSA) with four independently chambers. Recurrent neural network (RNN) and dynamic back propagation (DBP) training algorithm are used to obtain PDSA dynamic model. PDSA position controller is based on a feedforward neural network (FNN) and it is trained using PDSA closed loop system (CLS) and DBP training algorithm. CLS stability analysis concludes that it is not possible control PDSA end effector position using one position controller for different end effector initial and desired positions. Fuzzy logic methodology is used to integrate several positions controllers in a one controller valid for all operation range. The controller implementation and close loop system simulation are performed in MATLAB for different end effector desired position to validate system performance in all range of operation.

关键词： Training Fuzzy logic Backpropagation Recurrent neural networks Endoscopes Heuristic algorithms Artificial neural networks

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Age Feature Enhanced Neural Network for RUL Estimation of Power Electronic Devices

Age Feature Enhanced Neural Network for RUL Estimation of Po...

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International Conference on Prognostics and Health Management, PHM

作者： Zhonghai Lu Rui Shi Chao Guo Mingrui Liu Department of Electrical Engineering KTH Royal Institute of Technology Stockholm Sweden Embedded Systems Master Program KTH Royal Institute of Technology Stockholm Sweden

Like other deep learning problems, critical features are critical to enable effective estimation of Remaining Useful Lifetime (RUL) for power electronic devices using Neural Networks (NNs). However, these critical features are often indirectly obtained after data pre-processing, complicated either in form (high dimension) or in computation (computation-intensive pre-processing). In the paper, we suggest adding a simple direct feature, age, into the NN based RUL estimation technique. The rationale for incorporating this feature is that the device lifetime is a sum of past time (age) plus RUL. Thus it has a strong correlation to RUL. In our experiments using accelerated aging tests, we show that the new age feature enhanced Recurrent Neural Network (RNN) model can significantly improve estimation accuracy and shorten training convergence time. It also outperforms a state-of-the-art RNN model using derived time-domain statistical features.

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Recent Advances in Artificial Intelligence for Defects and Faults Detection in Solar Systems

Recent Advances in Artificial Intelligence for Defects and F...

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International Conference on Control, Mechatronics and Automation (ICCMA)

作者： Ali Thakfan Yasser Bin Salamah Joint Master’s Program in Renewable Energy Sustainable Energy Technologies Center King Saud University Riyadh Saudi Arabia Department of Electrical Engineering College of Engineering King Saud University Riyadh Saudi Arabia

ISBN: (数字)9798331517519

ISBN: (纸本)9798331517526

Renewable solar energy has emerged as a vital alternative to fossil fuels, providing a sustainable solution to the pressing challenges of resource depletion, global warming, and greenhouse gas emissions. As solar energy systems become increasingly widespread, maintaining their efficiency and reliability is of paramount importance. Artificial intelligence (AI) plays a crucial role in enhancing these systems by enabling precise detection and diagnosis of defects and faults. This paper offers a concise review of the current state of AI applications in monitoring and diagnosing issues within solar photovoltaic (PV) energy systems, focusing on thermal imaging and current-voltage (I-V) curve analytics inspection methods. Integrating AI with solar technologies not only boosts system performance but also reduces maintenance costs and minimizes downtime, thereby significantly enhancing the overall effectiveness of renewable energy solutions.

关键词： Renewable energy sources Fault detection System performance Solar energy Inspection Thermal analysis Solar system Artificial intelligence Photovoltaic systems Climate change Machine learning

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Foot hemodynamics using optical tomography: A potential biomarker of peripheral arterial disease

Foot hemodynamics using optical tomography: A potential biom...

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2023 Advances in Science and engineering Technology International Conferences, ASET 2023

作者： Al Abdi, Rabah M. Zakaria, Amer Al Nashash, Hasan Zalak, Tasnim Goswami, Nandu Jeet, Vishwa Jordan Univ. of Science and Tech. Dept. of Biomedical Engineering Irbid Jordan American University of Sharjah Dept. of Electrical Engineering Sharjah United Arab Emirates American University of Sharjah Master of Science in Biomedical Engineering Program Sharjah United Arab Emirates College of Medicine Mohammed Bin Rashed University of Medicine and Health Sciences Dubai United Arab Emirates

ISBN: (纸本)9781665454742

Peripheral arterial disease (PAD) is the narrowing of the arteries within the lower extremities, which inhibits blood flow to the foot. We present the use of dynamic diffuse optical tomography (DDOT) system to measure blood flow in the foot during venous and arterial occlusions. DDOT is a non-ionizing, contrast-free, and fast imaging modality. The DDOT system consists of 4 sensors, each containing four laser diodes (at wavelengths of 670, 780, 808, and 850 nm) and two silicon photodiodes. We examined 11 healthy subjects with a protocol consisting of five consecutive measurements. Biomarkers were extracted from changes in hemoglobin concentrations during the measurements. The results from a pilot study are presented in this report. The average increase in total hemoglobin was 17.2 ±5.8 μ M during a measurement with 60 mmHg occlusion and 10.4 ± 6.7 μ M during a measurement with 180 mmHg occlusion. The biomarkers can quantify blood perfusion and oxygen consumption in the foot, and they have the potential to detect and monitor PAD. © 2023 IEEE.

关键词： Hemodynamics

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Low-Resolution Face Recognition for CCTV and Edge-Powered Smart Attendance Systems

Low-Resolution Face Recognition for CCTV and Edge-Powered Sm...

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IEEE Annual International Computer Software and Applications Conference (COMPSAC)

作者： Nico Surantha Edward Yose Sani Muhamad Isa Department of Electrical Electronics and Communication Engineering Faculty of Science and Engineering Tokyo City University Tokyo Japan Computer Science Department BINUS Graduate Program-Master of Computer Science Bina Nusantara University Jakarta Indonesia

ISBN: (数字)9798350376968

ISBN: (纸本)9798350376975

Attendance systems have become more modern, and one of the biometric systems without physical contact is face recognition. However, many face-based attendance systems still carry out attendance individually and cannot detect multiple faces simultaneously. In addition, capturing facial data in real-time is still a challenge because the relatively large distance between the camera and the individual reduces the ability to recognize faces. The general solution is to use super-resolution to generate better-quality faces while maintaining the main facial recognition features. One technique still being researched is super-resolution generative adversarial networks (SRGAN). SRGAN can enlarge the resolution of captured images and maintain image quality sufficient for face recognition. The attendance system can be easily integrated into edge devices such as the Jetson Nano. This paper proposes automatic and effective attendance systems with the super-resolution technique to detect and recognize faces in low-resolution input. The experimental results show that using face data capture with a resolution of 40 × 40 pixels and a four-fold magnification results in a resolution of 160 × 160 pixels. Combining Face SRGAN with FaceNet architecture as the basis of face recognition can achieve an accuracy rate of 78.19% and an F1-Score of 81.13% with an average processing time of 1.61 seconds per frame on a PC and 14.55 seconds per frame on a Jetson Nano at an average of face recognition per frame of as many as up to 8 faces simultaneously.

关键词： Support vector machines Image quality Accuracy Face recognition Image edge detection Superresolution Generative adversarial networks

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Development of LED Lighting for Microalgae Propagation with Emission Spectrum Having Broader Emission Peaks

Development of LED Lighting for Microalgae Propagation with ...

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Sustainable Smart Lighting World Conference & Expo (LS18), IEEE

作者： Nobuaki Hosoda Takashi Murata Takayuki Misu Graduate School of Engineering Master's Degree Program in Electrical and Electronic Engineering Kanagawa Institute of Technology Atsugi Kanagawa Japan Department of Applied Chemistry and Bioscience Faculty of Engineering Kanagawa Institute of Technology Atsugi Kanagawa Japan Department of Electrical and Electronic Engineering Faculty of Engineering Kanagawa Institute of Technology Atsugi Kanagawa Japan

ISBN: (数字)9798331540197

ISBN: (纸本)9798331540203

In this study, we aimed to develop LED lighting with an emission spectrum effective for microalgae propagation, and fabricated LED lighting with Phosphor layer RGB, which has peaks in the red, green, and blue wavelength bands, and Phosphor layer RG’B’, which has broader peaks in the red, green, and blue wavelength bands. In order to examine the effect of microalgae propagation, Closterium ehrenbergii samples prepared at different dilution rates were irradiated with LED illumination light of Phosphor layer RG’B’ and Phosphor layer RGB, respectively, for 7 days, and their propagation rates were compared. The results of the experiment showed that Phosphor layer RG’B’ produced a higher propagation rate than Phosphor layer RGB.

关键词： Phosphors Lighting Light emitting diodes

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