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6th International Conference on Technology and Vocational Teachers, ICTVT 2020

作者： Salsabila, A. Khairudin, M. Postgraduate Program of Electrical Engineering Education Universitas Negeri Yogyakarta Indonesia Department of Electrical Engineering Educatio Faculty of Engineering Universitas Negeri Yogyakarta Indonesia

Learning media is a means of learning for students that can provide a real picture of real work that has a high risk if it is carried out directly. Learning media has a role in facilitating students to be able to experience it directly with minimal risk from a practicum. Analyzing the need for making learning media is very important for the development of real learning media. This study aims to: (1) Determine the need for the development of learning media for IOT-based smart building installation systems in Vocational High School (VHS);(2) Analyzing the needs used in the development of learning media for IOT-based smart building installation systems in VHS. The results showed that the things needed in developing IOT learning media were seen from the technology used in the form of (1) Software based on media interaction with the internet using a visual studio;(2) Arduino Uno, temperature sensor device, ESP8266, gas sensor and light sensor are needed as hardware to reflect building capabilities;(3) The cloud computing system uses spread sheets to store data;(4) Internet network for uploading and downloading data. In its implementation, a needs analysis for the development of instructional media is needed so that in the later development process the media is developed appropriately and on target. The results of research and development research using the ADDIE method need the development of learning media for IOT-based smart building installation systems in vocational high schools to improve the learning abilities of students. © Published under licence by IOP Publishing Ltd.

关键词： Students

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A Performance Study of Selected Machine Learning Techniques for Predicting Heart Diseases 2nd

A Performance Study of Selected Machine Learning Techniques ...

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2nd International Conference on Security and Information Technologies with AI, Internet Computing and Big-data Applications, SITAIBA 2023

作者： Olorunfemi, Blessing Oluwatobi Ogunde, Adewale Opeoluwa Adeniyi, Abidemi Emmanuel Awotunde, Joseph Bamidele Imoize, Agbotiname Lucky Li, Chun-Ta Faculty of Natural Sciences Department of Computer Science Redeemer’s University Osun Nigeria Department of Computer Science Bowen University Iwo Nigeria Faculty of Information and Communication Sciences Department of Computer Science University of Ilorin Ilorin240003 Nigeria Faculty of Engineering Department of Electrical and Electronics Engineering University of Lagos Lagos Akoka100213 Nigeria Bachelor’s Program of Artificial Intelligence and Information Security Fu Jen Catholic University New Taipei City24206 Taiwan

ISBN: (纸本)9789819777853

Heart Disease remains a leading cause of mortality worldwide. It alarmingly rises at a quick rate, making early heart disease prediction crucial for effective prevention and timely intervention. Heart disease diagnosis is a difficult process that requires technical skills and accuracy to complete. With improvements in technology, computing has lent its voice to simplify the diagnosis of various health problems. Machine learning uses past or existing history to predict future results. Various machine learning techniques have been developed over the years and used in predicting heart diseases with various levels of performance. Identifying the best-suited machine learning technique to use for prediction purposes can be a challenging task. This research work analyses the performance of seven (7) machine learning techniques, comprising AdaBoost Algorithm, KNN, Logistic Regression, Naïve Bayes Classifier, Random Forest, SVM, and XGBoost. The heart disease dataset was downloaded from the UCI repository and analysed using Python programming language in the Jupyter Notebook environment. A comparative analysis of the seven (7) techniques was performed based on Accuracy, Precision, and Recall. From the results obtained, KNN, Random Forest, and XGBoost showed superior performance over the others with an accuracy of 100%, AdaBoost Algorithm followed with an accuracy of 92.2%, SVM followed with an accuracy of 91.71%, Naïve Bayes Classifier followed with an accuracy of 88.29% while Logistic Regression has the least accuracy of 86.34%. KNN, RF, and XGBoost outperformed AdaBoost, SVN, and LR. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Adversarial machine learning

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Achievement of green campus indications based on assessment indicators on H-BAT program Universitas Negeri Semarang 9

Achievement of green campus indications based on assessment ...

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9th engineering International Conference, EIC 2020

作者： Prihanto, T. Fathoni, K. Prasetiyo, B. Study Program of Architecture Faculty of Engineering Universitas Negeri Semarang Indonesia Study Program of Electrical Engineering Faculty of Engineering Universitas Negeri Semarang Indonesia Study Program of Informatics Universitas Negeri Semarang Indonesia

Universitas Negeri Semarang (UNNES) has a spirit to become a Conservation and International Reputation University is realized through strategic missions. One of the conservation-oriented implementation programs is H-BAT (Green, Clean and Healthy) program. In its implementation, there is a problem, namely the achievement of H-BAT program has not been maximized during the last 3 years in assessment. The objectives of this research are: (1) to identify of the potential and character of environmental support in the work units;(2) to determine the achievement of the indication of a green campus based on the assessment indicators on H-BAT program. This research was carried out in four stages: (1) Data collection;(2) Spatial data processing;(3) Non Spatial data processing;(4) Analysis (ecological, technical standards);The results achieved in June 2020 are as follows: FT got 87,50%, FE got 85,87%, FMIPA got 81,52%, BUHK got79,49%, FIP got 73,91%, LP3 got 69,23%, LP2M got 63,46%, FIS got 60,33%,PPS got 57,07%, FIK got 56,52%, FH got 52,72%, FBS got 49,46%, TIK got 40,38%, BPB got 34,62%, Library got 30,13%, Archive got 17,31%. From these results, it can be seen that there is a lack of maximum achievement due to, among others, the lack of guidance and technical assistance in the management of the unit. So it is necessary to complete governance guidelines and technical assistance that are more intensive in unit governance to achieve the goals of UNNES as a green campus. © Published under licence by IOP Publishing Ltd.

关键词： Data handling

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An Economically Comparative Study of 12 MWp PV Floating and PV on-Ground Solar Farms in an Industrial Estate in Thailand

An Economically Comparative Study of 12 MWp PV Floating and ...

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Power and Renewable Energy engineering (PREE), International Conference on

作者： Worajak Bamrungsawat Pattarabordee Khaigunha Amnart Suksri Tanakorn Wongwuttanasatian Energy Engineering Program Faculty of Engineering Khon Kaen University Khon Kaen Thailand Department of Computer Engineering Faculty of Engineering Nakhon Phanom University Nakhon Phanom Thailand Department of Electrical Engineering Facuty of Engineering Khon Kaen University Khon Kaen Thailand Department of Mechanical Engineering Faculty of Engineering Khon Kaen University Khon Kaen Thailand

ISBN: (数字)9798350366808

ISBN: (纸本)9798350366815

This study focuses on the economic comparison between 12 MWp PV floating and PV on-ground solar farms in an industrial estate in Thailand. The objective is to evaluate the economic feasibility and electricity-produced efficiency of both systems. This study uses models for both power generation systems and collects data on investment and operational costs over a 20-year project lifespan, using a discount rate of 10% and a Time of Use (TOU) electricity rate for medium-sized businesses with a voltage of 22–33 kV, where the peak period rate is 0.113 USD/kWh and the off-peak period rate is 0.07 USD/kWh [1]. The evaluation uses indicators such as NPV, IRR, Payback Period, B/C Ratio, and sensitivity analysis under two scenarios: 1) the investment cost changes by ±5%, while 2) the electricity selling price changes by ±5% every 5 years during peak periods. The study found that the initial investment for PV floating power plants is 8.77 million USD, while PV on-ground power plants require an initial investment of 9.36 million USD. Economic evaluation reveals that PV floating has an NPV of 1.25 million USD > 0, an IRR of 12% > 10%, a payback period of 7.07 years, and a B/C ratio of 1.14 > 1, whereas PV on-ground has an NPV of 0.36 million USD > 0, an IRR of 11%, a payback period of 7.83 years, and a B/C ratio of 1.04> 1. When conducting sensitivity analysis under both scenarios, PV floating meets all criteria, whereas PV on-ground fails to meet the criteria when variables causing a decrease in net profit are applied. As a result, the study concludes that PV floating solar farms are more economically viable than PV on-ground solar farms in Thailand's industrial estates.

关键词： Economics Hands Renewable energy sources Costs Sensitivity analysis Electricity Solar farms Voltage Power generation Investment

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Impact of Multimedia Sensor Placement to Car Licence Number Detection 2022

Impact of Multimedia Sensor Placement to Car Licence Number ...

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11th International Conference on Software and Computer Applications, ICSCA 2022

作者： Amelia, Afritha Zarlis, Muhammad Suherman, Suherman Efendi, Syahril Graduate Program of Computer Science Faculty of Computer Science and Information Technology University of Sumatera Utara Indonesia Computer Science Faculty of Computer Science and Information Technology University of Sumatera Utara Indonesia Electrical Engineering Faculty of Engineering University of Sumatera Utara Indonesia

ISBN: (纸本)9781450385770

A vehicle has a license plate and can be identified by the license number attached to the vehicle plate. For detection and recognition, multimedia sensors can be used so that it requires a vehicle tracking application that has a vehicle monitoring function and has implications for various fields. One of them is a multimedia sensor that requires an optimal design and method in the form of the number of multimedia sensors to be used, the placement of the multimedia sensor positions and solutions in the event of a system failure. To achieve multimedia sensor performance, research on multimedia sensors is carried out using a camera type with Phase Detection Auto Focus (PDAF) technology which is similar to a pair of right and left eyes to see an object. The objects detected were 2 cars, where the car passed the camera sensor at a speed of 10-15 km/hour 20 times. Changes in the distance of the vehicle to the camera affect the disparity value and the object's accuracy value, namely and the object's Accuracy value of the minimum disparity value of 6.20×106 of 16.88×109. © 2022 ACM.

关键词： Disparity Vehicle plate Phase Detection Auto Focus (PDAF) Tracking application Object accuracy

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Dynamic Surrogate Optimization of Vertically Stacked Nanosheet FET Based on Gaussian Process Regression

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IEEE Access 2025年 13卷 95730-95738页

作者： Christofer N. Yalung Doldet Tantraviwat Doctor of Philosophy Program in Nanoscience and Nanotechnology (International Program/Interdisciplinary) Materials Science Research Center Faculty of Science Chiang Mai University Chiang Mai Thailand Department of Electrical Engineering Faculty of Engineering Chiang Mai University Chiang Mai Thailand Center of Excellence in Materials Science and Technology Faculty of Science Chiang Mai University Chiang Mai Thailand

While speed improvements are pivotal for advancing modern transistor technologies and ensuring faster computational performance, the tradeoffs with other critical electrical properties, such as threshold voltage ( $V_{T}$ ) and off-current ( $I_{OFF}$ ), are often overlooked. These tradeoffs can significantly impact the overall device performance. The design of vertically stacked n-type and p-type nanosheet FETs (NSFETs) was applied using a dynamic surrogate optimization-gaussian process regression (DSO-GPR) with batch assessment and halting conditions. A vertically stacked silicon-based system is created and refined. Source extension ( $S_{ext}$ ), drain extension ( $D_{ex\mathrm {t}}$ ), gate length ( $L_{g}$ ), nanosheet height (NSh), nanosheet width (NSw), and number of fin (nfin) make up the input variables. In addition to applying normalization to make the weight assignment to the goal functions easier, a penalty component was incorporated to manage the $V_{T}$ . This study demonstrates the effectiveness of the DSO-GPR framework in optimizing NSFET-based inverter designs by balancing speed, $I_{OFF}$ and $V_{T}$ . Among the three evaluated cases, case 1 achieved the fastest propagation delay (1.05 ps) due to higher $I_{ON}$ and lower $V_{T}$ , albeit with increased $I_{OFF}$ and $V_{T}$ mismatch. Case 2 provided a balanced trade-off, significantly reducing $I_{OFF}$ while maintaining a competitive delay of 1.25 ps and achieving $V_{T}$ matching at 0.11 V for both n-type and p-type NSFETs. The optimum parameters for n-type are ${L} _{g}$ = 5 nm, $N_{Sh} = 9$ nm, $N_{Sw} = 42$ nm, $S_{ext} = 3$ nm and $D_{ext} = 4$ nm, nfin = 5; for p-type, $L_{g} = 7$ nm, $N_{Sh} = 10$ nm, $N_{Sw} = 42$ nm, $S_{ext} = 3$ nm and $D_{ext} = 3$ nm, nfin = 5. Case 3 minimized leakage at the cost of delay, highlighting the trade-off between power and performance. These results validate the framework’s adaptability and automation, with performance-based stopping criteria that balance

关键词： Optimization Logic gates Ions Silicon Performance evaluation Linear programming Gaussian processes Field effect transistors Accuracy Machine learning

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A Reconfigurable Compute-In-Memory Design with Adaptive Bit-Precision and Power Adjustment

A Reconfigurable Compute-In-Memory Design with Adaptive Bit-...

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Consumer Technology (ICCT-Pacific), International Conference on

作者： I-Chieh Hsu Chun-Fu Chen Dao-Long Huang Yun-Kai Yeh Wei-Chieh Lee Qi-Hua Lin Jinjia Zhou I-Chyn Wey Electrical Engineering Department College of Engineering Chang-Gung University Taiwan School of Electrical Engineering National Taiwan University of Science and Technology Taiwan Master Program in Nano-Electronic Engineering and Design Chang Gung University Taiwan Department of Applied Informatics Faculty of Science and Engineering Hosei University Japan

ISBN: (数字)9798331504120

ISBN: (纸本)9798331504137

With the successful development of artificial intelligence (AI), Convolutional Neural Networks (CNNs) occupy a large amount of computing time and power consumption in the entire AI computing process. However, in traditional von Neumann architectures, the separation of the computing element and memory leads to the memory-wall problem of memory data transmission bandwidth from memory to processing element when executing multiply-accumulate-based CNN operations. The data transmission time and power consumption all are much higher than the CNN computing part. Therefore, this paper proposes a memory-in-computation design that can flexibly adjust energy usage, achieve high energy efficiency, and support multiple operation frequencies. By controlling the switches of each memory row, unnecessary energy consumption is avoided, leading to a reduction in total power consumption by 15% to 60%. Additionally, by adjusting the pulse width, the charging power consumption of capacitors is reduced by 65% per charge cycle.

关键词： Energy consumption Power demand Capacitors Bandwidth In-memory computing Control systems Energy efficiency Convolutional neural networks Data communication Artificial intelligence

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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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The Study of Materials for Electric Field Protection of Power Transformer Testing

The Study of Materials for Electric Field Protection of Powe...

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International Conference on engineering, Applied Sciences, and Technology (ICEAST)

作者： Peerawat Meesuk Prajak Bunpakdee Sirirat Sorn-In Electrical Engineering and Automation Control System Program Faculty of Engineering and Industrial Technology Bansomdejchaopraya Rajabhat Univrtsity Bangkok Thailand

This paper proposes the analysis of the material can be protected from transformer testing and presents a mathematical model of the power transformer. In this research, transformers were study in four protective materials, wood, rubber, glass and acrylic that are used in between the electric field measurement and the transformer. By simulating the test results of a transformer with a voltage of 230 kV. Computer-based simulation utilizing the finite element method (FEM) is exploited as a tool for visualizing electric fields distribution volume a power transformer. The simulation results showed that the material with the best protection against the electric field was wood insulation and the best installation location was a distance of 5 m from the transformer.

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Electrocardiogram Detection System of Autistic Children Based on AD8232 for Healthcare

Electrocardiogram Detection System of Autistic Children Base...

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Computer System, Information Technology, and electrical engineering (COSITE), International Conference on

作者： Cut Nanda Nurbadriani Melinda Melinda Yunidar Yunidar Fitri Arnia Graduate program of Electrical Engineering Faculty of Engineering Universitas Syiah Kuala Banda Aceh Indonesia dept. Electrical Engineering Universitas Syiah Kuala Banda Aceh Indonesia

This study is to design and test an early detection tool based on the AD8232 sensor as an ECG detection system. This system is applied to autistic children. Potentially hyperactive autistic children may increase their heart rate suddenly compared to normal children. Through a system that can detect heart conditions can help experts who deal with ECG problems in autistic children. This system is applied to autistic children by using components that are arranged in such a way as to be easy to use for autistic children. With the help of three electrodes attached to the child’s body, namely on the hands and chest, in a test period of 2500 ms. Utilization of the AD8232 sensor and other components can produce heartbeat waves of autistic children. Based on testing by filtering and segmenting, the signal recording results when the electrodes are attached to the hand there is interference from excessive movement. Whereas when the electrode is attached to the chest, it produces a stable signal because the movements made do not affect the electrode during the test. Thus, the use of electrodes on the chest is more appropriate because the sensor can record signals properly.

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