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Conference on Power, Energy and Innovations (ICPEI)

作者： Aphirak Thitinaruemit Suchada Sitjongsatapom Sethakarn Prongnuch The Electrical Engineering Graduate Program Faculty of Engineering and Technology Mahanakorn University of Technology Bangkok Thailand Mahanakorn Institute of Innovation (MII) Faculty of Engineering and Technology Mahanakorn University of Technology Bangkok Bangkok Thailand Faculty of Industrial Technology Suan Sunandha Rajabhat University Bangkok Thailand

ISBN: (纸本)9781665402170

This paper present the network design and capacity planning of access point (AP) deployment for indoor positioning system. The estimation of WiFi distance is described briefly how to measure the signal strength of AP. Co-channel interference is a key for network design of access point installation for network capacity. The objective function for network capacity planning of AP deployment is to optimize the number of access point and location for indoor positioning system concerning with the minimized co-channel interference. Simulations are tested to install AP for lecture hall in university. Capacity planning design of wireless AP deployment is proposed for indoor position systems in terms of the received signal strength indications (RSSI). We assume the situation is supported for the crowded conference. The requirement of the results of wireless AP positioning in crowded conference rooms are placing the wireless AP in forms of overlap the signal in order to get the strong signal. Experimental results have been tested their received signal of WiFi APs with the 2.4GHz frequency using the receiver installed in laptops to check the signal. The empirical results shown that the strength of RSSI will be received a signal of -44 dBm at a distance of approximately 20 meters.

关键词： Meters Technological innovation Portable computers Receivers Wireless access points Linear programming Received signal strength indicator

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Social Media Analysis using Sentiment Analysis on COVID-19 from Twitter

Social Media Analysis using Sentiment Analysis on COVID-19 f...

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International Conference on Information Technology, Information Systems and electrical engineering (ICITISEE)

作者： Fairuz Iqbal Maulana Yaya Heryadi Lukas Wayan Suparta Yulyani Arifin Computer Science Department BINUS Graduate Program Doctor of Computer Science Bina Nusantara University Jakarta Indonesia Cognitive Engineering Research Group (CERG) Faculty of Engineering Universitas Katolik Indonesia Atma Jaya Jakarta Indonesia Department of Electrical Engineering Faculty of Industrial Technology Institut Teknologi Nasional Yogyakarta Yogyakarta Indonesia Computer Science Department School of Computer Science Bina Nusantara University Jakarta Indonesia

The development of the internet is getting faster, participating in encouraging the emergence of new and innovative information. In filtering the various information that appears, we need a recommended system to perform well for users in today's internet era. A well-performing recommendation system in question is a reliable recommendation algorithm. This algorithm is fundamental to analyzing various information, such as responses on social media based on user behavior data related to the topic of COVID. This data is crawled from tweets on social media Twitter. The data analysis algorithm obtained uses Python, which is then visualized in the form of a diagram. The processed data is user comments on Twitter, and the text data is analyzed using Python, using more than 60000 data sets taken to form visualizations and conclusions. From sentiment analysis, polarity and subjectivity data are obtained to be analyzed, which are negative, neutral, or positive. The result is show positive tweets with 29.2%, negative tweets is 13%, and 57.8% neutral tweets. Lastly, sentiment analysis can help people effectively infer vast and complex data from social media like Twitter.

关键词： COVID-19 Sentiment analysis Analytical models Data analysis Social networking (online) Blogs Data visualization

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AUTOMATED DRIVING ARCHITECTURE AND OPERATION OF A LIGHT COMMERCIAL VEHICLE

arXiv

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arXiv 2023年

作者： Gözü, Murat Emirler, Mümin Tolga Uygan, Ismail Meriç Can Böke, Tevfik Ali Güvenç, Levent Güvenç, Bilin Aksun Istanbul Okan University Institute of Sciences and Engineering Mechatronics Engineering Program Istanbul Turkey Yildiz Technical University Faculty of Applied Sciences Department of Aviation Electronics Istanbul Turkey Tübitak Bilgem Cyber Security Institute Kocaeli Gebze Turkey Tofaş Research and Development Center Bursa Turkey The Ohio State University Automated Driving Lab ColumbusOH United States The Ohio State University Department of Mechanical and Aerospace Engineering ColumbusOH United States The Ohio State University Department of Electrical and Computer Engineering ColumbusOH United States

This paper is on the automated driving architecture and operation of a light commercial vehicle. Simple longitudinal and lateral dynamic models of the vehicle and a more detailed CarSim model are developed and used in simulations and controller design and evaluation. Experimental validation is used to make sure that the models used represent the actual response of the vehicle as closely as possible. The vehicle is made drive-by-wire by interfacing with the existing throttle-by-wire, by adding an active vacuum booster for brake-by-wire and by adding a steering actuator for steer-by-wire operation. Vehicle localization is achieved by using a GPS sensor integrated with six axes IMU with a built-in INS algorithm and a digital compass for heading information. Front looking radar, lidar and camera are used for environmental sensing. Communication with the road infrastructure and other vehicles is made possible by a vehicle to vehicle communication modem. A dedicated computer under real time Linux is used to collect, process and distribute sensor information. A dSPACE MicroAutoBox is used for drive-by-wire controls. CACC based longitudinal control and path tracking of a map of GPS waypoints are used to present the operation of this automated driving vehicle. © 2023, CC BY-NC-ND.

关键词： Controllers

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Probabilistic Genotype-Phenotype Maps Reveal Mutational Robustness of RNA Folding, Spin Glasses, and Quantum Circuits

arXiv

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arXiv 2023年

作者： Sappington, Anna Mohanty, Vaibhav Department of Electrical Engineering and Computer Science Massachusetts Institute of Technology CambridgeMA02139 United States Program for Health Sciences and Technology Harvard Medical School BostonMA02115 United States Massachusetts Institute of Technology CambridgeMA02139 United States Harvard/MIT MD-PhD Program Harvard Medical School BostonMA02115 United States Department of Chemistry and Chemical Biology Harvard University CambridgeMA02138 United States

Recent studies of genotype-phenotype (GP) maps have reported universally enhanced phenotypic robustness to genotype mutations, a feature essential to evolution. Virtually all of these studies make a simplifying assumption that each genotype—represented as a sequence—maps deterministically to a single phenotype, such as a discrete structure. Here, we introduce probabilistic genotype-phenotype (PrGP) maps, where each genotype maps to a vector of phenotype probabilities, as a more realistic and universal language for investigating robustness in a variety of physical, biological, and computational systems. We study three model systems to show that PrGP maps offer a generalized framework which can handle uncertainty emerging from various physical sources: (1) thermal fluctuation in RNA folding, (2) external field disorder in spin glass ground state finding, and (3) superposition and entanglement in quantum circuits, which are realized experimentally on IBM quantum computers. In all three cases, we observe a novel biphasic robustness scaling which is enhanced relative to random expectation for more frequent phenotypes and approaches random expectation for less frequent phenotypes. We derive an analytical theory for the behavior of PrGP robustness, and we demonstrate that the theory is highly predictive of empirical robustness. © 2023, CC BY.

关键词： Quantum computers

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Guava Trees Disease Monitoring Using the Integration of Machine Learning and Predictive Analytics 3

Guava Trees Disease Monitoring Using the Integration of Mach...

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3rd Novel Intelligent and Leading Emerging Sciences Conference, NILES 2021

作者： Elsayed, Mahmoud Hassan, Nourhan Maher, Marina Waleed, Nouran Reda, Rehab Eldin, Haitham Sharaf Mostafa, Hassan The American University of Cairo Mechatronics Department Egypt Nile University Giza12677 Egypt Communication Engineering Alexandria University Egypt Biomedical Engineering Cairo University Egypt Tanta University Egypt Cairo University Faculty of Science Biophysics Department Egypt Cairo University Electronics and Electrical Communications Engineering Department Giza Egypt University of Science and technology Nanotechnology and Nanoelectronics Program Zewail City of Science and Technology October Gardens 6th of October Giza12578 Egypt

ISBN: (纸本)9781665421577

The increase in population, food demand, and the pollution levels of the environment are considered major problems of this era. For these reasons, the traditional ways of farming are no longer suitable for early and accurate detection of biotic stress. Recently, precision agriculture has been extensively used as a potential solution for the aforementioned problems using high resolution optical sensors and data analysis methods that are able to cope with the resolution, size and complexity of the signals from these sensors. In this paper, several methods of machine learning have been utilized in order to study pests, their types, population, and agricultural conditions in terms of soil and climate for some crops such as potatoes, guava, and cotton, which are among the main Egyptian crops. In the process of obtaining a suitable estimate of insects population affecting each of the aforementioned crops, a hardware model control, based on the results provided by the predictive analysis, an estimate of the electromagnetic force is applied to the cultivated areas to get rid of the pests as well as giving a background to farmers about the possibility of infecting a crop such as Potato with Late Blight, according to climatic conditions. © 2021 IEEE.

关键词： Model predictive control

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The effect of koh activator concentration upon the characteristics of biomass-derived water hyacinth process on lithium-ion capacitor 16th

The effect of koh activator concentration upon the character...

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16th International Conference on Quality in Research, QiR 2019

作者： Luthfi, Muhammad Paduraksa, Jagad Verdianto, Ariono Pambudi, Yoyok Dwi Setyo Priyono, Bambang Syahrial, Anne Zulfia Lee, Joong Kee Hudaya, Chairul Department of Electrical Engineering Faculty of Engineering Universitas Indonesia Depok16424 Indonesia Energy System Engineering Study Program Faculty of Engineering Universitas Indonesia Depok16424 Indonesia Department of Metallurgy and Materials Engineering Faculty of Engineering Universitas Indonesia Depok16424 Indonesia Center for Nuclear Reactor Technology and Safety BATAN Puspiptek Area SerpongTangerang Selatan15310 Indonesia Hwarang-ro 14-gil 5 Seongbuk-gu Seoul02792 Korea Republic of

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Analog Behavioral Model of Underdamped Free Oscillation of Cantilever Beams

Analog Behavioral Model of Underdamped Free Oscillation of C...

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2019 International Conference on Sustainable engineering and Creative Computing, ICSECC 2019

作者： Tarigan, Hendra J. Sitompul, Erwin President University Study Program of Electrical Engineering Faculty of Engineering Bekasi Indonesia

ISBN: (纸本)9781728151922

A physical model representing an underdamped free oscillation of a cantilever beam is constructed. The model is incorporated into a pSPICE Analog Behavioral Model (ABM) in order to construct a circuit schematic that generates a model-based waveform representing that of the experiment. A strain gage is employed to sense the change in strain in the oscillating cantilever beam. The frequency and damping ratio of oscillation of the cantilever are determined by means of curve fitting. Experiment and pSPICE ABM results show an excellent agreement. © 2019 IEEE.

关键词： Strain gages

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System Modelling Using Neural Networks with External Recurrence and Exponential Quadratic Cost Function

System Modelling Using Neural Networks with External Recurre...

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2019 International Conference on Sustainable engineering and Creative Computing, ICSECC 2019

作者： Sitompul, Erwin President University Study Program of Electrical Engineering Faculty of Engineering Bekasi Indonesia

ISBN: (纸本)9781728151922

A novel cost function to improve the performance of neural networks in system modelling is proposed in this paper, the exponential quadratic cost function. This cost function combines the strength of penalizing errors exponentially and the feasibility of quadratic function in finding global minima. By applying the exponential quadratic cost function, the learning algorithm is expected to have an improved ability to minimize the difference between system output and model output. Simulations by using a test system with strong nonlinear dynamics were conducted to prove the effectiveness of the proposed cost function. The results show that the network trained using the exponential quadratic cost function performs better in emulating the test system in transient region. © 2019 IEEE.

关键词： Cost functions

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Energy conservation opportunities in coal-fired power plant through detailed energy audit

引用

AIP Conference Proceedings 2023年第1期2683卷

作者： Suriyan Wibowo Berkah Kiono Jaka Windarta Magister Program of Energy School of Postgraduate Studies Diponegoro University Semarang Indonesia Department of Mechanical Engineering Faculty of Engineering Diponegoro University Semarang Indonesia Department of Electrical Engineering Faculty of Engineering Diponegoro University Semarang Indonesia

As the dominant primary energy user until 2050 in. Indonesia, coal-fired power plant energy conservation effortsneed to be increased through a detailed energy audit. Power plant energy performance indicator expressed by Net Plant Heat Rate (NPHR) as the energy required to produce one kWh of net electricity. Energy audits are conducted by comparing NPHR value between actual conditions against commissioning at 61 MW gross loads through performance tests based onASME PTC standards. Actual NPHR increase due to several factors that have been identified by comparing operating parameters and central equipment performance between actual against commissioning value. Furthermore, the deviation of each parameter with different units converted into heat rate unit using references from manufacture NPHR correction factor and Southern Company heat rate handbook. The results show that actual NPHR increased by 510.21 kcal/kWh or 16.93% compared to commissioning value and potentially increased fuel costs to 1,270,147 USD per year. Significant factors that cause NPHR increase are condenser pressure increase, isentropic turbine efficiency decrease, two LPH out of service, primary and secondary air preheater effectiveness decrease, primary and secondary air preheater leakage increase. The study suggests several recommendations to reduce those losses through operation control and equipment repair.

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Immersive Modeling Framework for Training Applications

Immersive Modeling Framework for Training Applications

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International Conference on Advanced Learning Technologies (ICALT)

作者： Vinicius Chrisosthemos Teixeira Carlo Smaniotto Mantovani Alexandre Cardoso Carlos Alexandre dos Santos Márcio Sarroglia Pinho Computer Science Graduate Program School of Technology Pontifical Catholic University of Rio Grande do Sul Porto Alegre Brazil Faculty of Electrical Engineering Federal University of Uberlândia Uberlândia Brazil School of Technology Pontifical Catholic University of Rio Grande do Sul Porto Alegre Brazil

This article describes a framework for modeling and executing training in augmented and virtual reality environments. The framework was designed based on characteristics observed in existing training applications for complex tasks, such as the use of tools, control panels and the need for step-by-step instructions. Unlike other frameworks, in the proposed system, it is possible to create the training entirely within the virtual/augmented environment, avoiding constant switching between 2D and 3D environments. The framework allows for the definition of steps in a training program, each of which includes textual instructions, videos, and 3D objects, static or animated, anchored in the real world. To demonstrate the capabilities of the framework, a training program for operating a Universal Testing Machine was created as a case study. Overall, the proposed framework allows for the creation of effective and efficient AR training programs for a variety of tasks and industries.

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