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Recent Advances and Innovations in engineering (ICRAIE)

作者： Fergyanto E. Gunawan Rahmanda Wulandari Dian Wahyuningtyas Mohammad Asrol Industrial Engineering Department BINUS Graduate Program – Master of Industrial Engineering Bina Nusantara University Jakarta Indonesia Business Engineering Program Industrial Engineering Department BINUS-ASO School of Engineering Bina Nusantara University Jakarta Indonesia

The IEEE Standard 762-1987 introduced a comprehensive set of 25 indices for reporting power plant reliability, availability, and productivity. The sheer number of indices can be impractical, and an univariate indicator is preferable for real-world applications. Developing a single indicator derived from the 25 indices is the work's main theme. This study addresses this issue using machine learning to consolidate these indices, ultimately classifying power plant performance into "performed" and "unperformed." Monthly performance data from 2020 were collected from 570 power plants in the Java-Sumatra interconnected electric system. These data were obtained from the Generation Availability Information System, a proprietary application owned by the Indonesia National Electric Power Company. Using the $k$-means clustering method, we classified the performance of these power plants. The clustering process was supplemented with the opinions of seven experts with extensive experience in the system. The comparison between machine learning classifications and expert opinions is presented.

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Fuzzy Logic for Assessing the Health of a Corn Crop within Family Farming

Fuzzy Logic for Assessing the Health of a Corn Crop within F...

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Latin America Congress on Computational Intelligence (LA-CCI)

作者： Vanessa Mendonça Mikael Santos Daniel M. Muñoz Carlos Humberto Llanos Department of Computer Science Federal Institute of Brasilia Department of Mechanical Engineering Mechatronics Graduate Program Department of Agronomy Federal Institute of Brasilia Faculty of Gama Electronics Engineering Undergraduate Program University of Brasilia Brasilia DF Brazil

ISBN: (数字)9798350374575

ISBN: (纸本)9798350374582

Technological advancements are increasingly evident across various sectors, including automobiles, industry, and healthcare. In precision agriculture, significant progress has been made, with AgroTICs and Smart Agriculture gaining substantial traction in the market. However, a gap remains between cutting-edge technology and family farming, presenting a challenge from both social and applied research perspectives. However, there is still a gap between cutting-edge technology and family farming, which creates a challenge from a social and applied research point of view. In this context, this paper proposes a monitoring model based on Fuzzy Logic and sensor automation applied to estimate the health of a corn crop. The proposed Fuzzy inference system involves calculating an indicator of nutrients as well as the average color and area of corn plants. The nutrient indicator is automatically computed by an ESP32 microcontroller using sensor readings, while the average color and area inputs are manually entered via a mobile application. Additionally, the Fuzzy inference is integrated into the ESP32. The model underwent experimental validation on the health of the plantation, and the results were evaluated in four areas: one was designated for testing, and three were for validation. The model achieved an accuracy of 97.5% in Scenario 3, categorized as ’Very Favorable’, and an accuracy of 65% in Scenarios 2 and 4, categorized as ‘Unfavorable’. The implications of this research contribute to the advancement of AgroTICs among small producers, with the potential to enhance and automate the monitoring of their harvest production.

关键词： Fuzzy logic Accuracy Computational modeling Plantations Crops Production Color Nutrients Monitoring Fuzzy systems

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Correlations between water quality and precipitation in areas with different levels of human occupation

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International Journal of Energy and Water Resources 2021年第1期5卷 25-31页

作者： Rodrigues, Lucas Augusto Pereira Radomski, Fernando Aparecido Dias Godoy, Rodrigo Felipe Bedim Trevisan, Elias Crisigiovanni, Enzo Luigi Department of Environment State University of Maringá Maringá-PR Brazil Graduate Program in Materials Science and Engineering Federal University of Paraná Curitiba-PR Brazil Graduate Program in Forest Sciences Unicentro Guarapuava-PR Brazil

Riverine water is largely used for human consumption and it is well known that its quality is correlated to many external factors. Because of that, this study evaluated linear correlations between precipitation and several water quality parameters using data collected from Antas’ river (Paraná, Brazil) at locations with different levels of human occupation aiming to identify water quality irregularities related to these important external factors, especially at a point surrounded by preserved vegetation. The statistical analyses were made using Pearson’s linear correlation coefficient (r) and the open source programming software, R. The results showed that precipitation has moderate to strong correlation with turbidity, true color, total coliforms and E. coli (0.99 ≥ r ≥ 0.44), and also has weak to moderate correlations with pH (− 0.39 ≥ r ≥ − 0.58) and biochemical oxygen demand (0.48 ≥ r ≥ 0.36), regardless of the level of human occupation nearby. The high correlations observed for E. coli and total coliforms in an area protected by native vegetation, probably due to adjacent rural activities, represents a novel and major finding. Dissolved oxygen and temperature showed no significant correlations with rainfall volume (0.26 ≥ r ≥ − 0.19). Since Brazilian law ensures that water quality parameters must be measured and considered in projects of water resources management, the proposed methodology seems to be promising for government policies applications, since it comprises only simple analyzes and a free software for simulations. © Islamic Azad University (IAU) 2021.

关键词： Hydrology R software Rainfall Spatial data Statistical analysis

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Microscopic Investigation on Interfacial Transition Zone in Fly Ash Cement Hydrates Using Roof-Tile Waste Aggregate 2nd

Microscopic Investigation on Interfacial Transition Zone in ...

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2nd International Conference on Sustainable Civil engineering and Architecture, ICSCEA 2021

作者： Okamoto, Kazuma Huynh, Phat Tan Ogawa, Yuko Kawai, Kenji Civil and Environmental Engineering Program Graduate School of Advanced Science and Engineering Hiroshima University 1-4-1 Kaganiyama Higashihiroshima Japan Depertment of Civil and Environmental Engineering Graduate School of Engineering Hiroshima University 1-4-1 Kaganiyama Higashihiroshima Japan 268 Ly Thuong Kiet Street District 10 Ho Chi Minh Viet Nam Vietnam National University Ho Chi Minh City Linh Trung Ward Thu Duc District Ho Chi Minh Viet Nam

ISBN: (纸本)9789811933028

Previous studies reported that the strength reduction in fly ash concrete (FAC) can be improved by internal curing with roof-tile waste aggregate (RWA). However, how much the internal curing by RWA improved the compressive strength of FAC was different, and there was no clear explanation on it. The purpose of this study is to clarify the effect of the internal curing in the FAC by examining the range of the internal curing effect with RWA in the interfacial transition zone (ITZ) around coarse aggregate. Paste and concrete specimens in which part of cement was replaced with fly ash were prepared. For paste specimens, one aggregate particle was placed in the center of the specimen. Vickers hardness around the aggregate in the paste specimen and the compressive strength of the concrete specimen were investigated. As a result, the range of Vickers hardness improvement around RWA changed depending on the replacement ratio of fly ash. This indicates that the internal curing effect differs depending on the mixture proportion of paste matrix such as the replacement ratio of fly ash. Furthermore, it was observed that the compressive strength of concrete increased as the thickness of ITZ around RWA decreased. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Compressive strength

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On Efficient Processing of Queries for Live Multi-Streaming Soiree Organization

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IEEE Transactions on Services Computing 2023年第4期16卷 2812-2826页

作者： Kankeu Fotsing, C.P. Shen, Chih-Ya Huang, Liang-Hao Chen, Yi-Shin Lee, Wang-Chien Yang, De-Nian International Graduate Program Academia Sinica Social Networks and Human-Centered Computing Program Taipei115 Taiwan National Tsing Hua University Institute of Information Systems and Applications Hsinchu300 Taiwan National Tsing Hua University Department of Computer Science Hsinchu300 Taiwan Academia Sinica Institute of Information Science Taipei115 Taiwan Pennsylvania State University Department of Computer Science and Engineering State CollegePA16801 United States

Real-time social interactions and multi-streaming are two critical features of live streaming services. In this paper, we formulate a new fundamental service query, Social-aware Diverse and Preferred Organization Query (SDSQ), that jointly selects a set of diverse and preferred live streaming channels and a group of socially tight viewers for organization of a live multi-streaming soiree. We prove that SDSQ is NP-hard and inapproximable within any factor, and design SDSSel, a 2-approximation algorithm with a guaranteed error bound. Moreover, we study SDSQ-T, a special case of SDSQ, where the social graph is a threshold graph, and propose TDSSel, a 2-approximation algorithm without any error to SDSQ-T. We propose two pruning strategies, PCP and CDP to boost SDSSel and TDSSel. We further propose a more challenging but practical service query, Generalized Social-aware Maximum Preferred and Diverse Query (GSPQ), a generalization of SDSQ. We design GPDSel, a 4-approximation algorithm for GSPQ with a guaranteed error bound. We propose a strategy to improve the approximation ratios of the proposed algorithms. A user study on Twitch validates SDSQ, and the large-scale experiments on real datasets demonstrate the superiority of the proposed algorithms over several baselines for live-streaming services. © 2008-2012 IEEE.

关键词： Approximation algorithms

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An Optimized VLSI Exponential Unit Design Exploring Efficient Arithmetic Operation Strategies

An Optimized VLSI Exponential Unit Design Exploring Efficien...

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IEEE International Conference on Electronics, Circuits and Systems (ICECS)

作者： Patrícia Da Costa Morgana Da Rosa Rafael Soares Eduardo Da Costa Sergio Bampi Graduate Program on Microelectronics Federal University of Rio Grande do Sul Porto Alegre Brazil Graduate Program on Computing Federal University of Pelotas (UFPel) Pelotas Brazil Graduate Program on Electronic Engineering and Computing Catholic University of Pelotas (UCPel) Pelotas Brazil Graduate Program on Microelectronics (PGMICRO) Federal University of Rio Grande do Sul (UFRGS) Porto Alegre Brazil

This work presents an optimized exponential function VLSI hardware design by Taylor series expansion. The proposed architecture implements the exponential by approximating the logic design of a 4 th -order Taylor series and explores efficient CMOS arithmetic operation strategies. It implements a shift-based divider and explores an efficient 4-2 adder compressor in the adder tree. The proposal with a −7 to 11 input values range shows an output error of around 2% of MRED with a reduced energy consumption of 3.63 pJ/operation for 32-bit output. For a 64-bit output, the energy per operation of the VLSI exponential unit is 14.97pJ/op, being able to process a more comprehensive input range (i.e., −14 to 22) for a negligible mean output error of around 1.7% of MRED.

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Optical OFDM transmission based on phase modulation and fiber bragg grating

Optical OFDM transmission based on phase modulation and fibe...

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IEEE/LEOS International Conference on Optical MEMS

作者： Paulo de Tarso Neves Junior Luis Carlos Vieira Alexandre de Almeida Prado Pohl Graduate Program in Electrical and Computer Engineering (CPGEI) Federal University of Technology - Paraná (UTFPR) Curitiba Brazil

In this work, we propose an optical OFDM system using phase modulation followed by optical filtering and direct detection. A fiber Bragg grating is used as an optical filter for phase to amplitude conversion. The performance of the proposed system is investigated for both 16 QAM- and 64 QAM-OFDM signals considering different numbers of training signals for frequency-domain channel estimation. With adequate choice of the training sequence length, BER results below 10 −4 are reported for the 16 QAM based signal.

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SCENE TEXT RECOGNITION MODELS EXPLAINABILITY USING LOCAL FEATURES

arXiv

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arXiv 2023年

作者： Ty, Mark Vincent Atienza, Rowel Electrical and Electronics Engineering Institute University of the Philippines Philippines AI Graduate Program University of the Philippines Philippines

Explainable AI (XAI) is the study on how humans can be able to understand the cause of a model's prediction. In this work, the problem of interest is Scene Text Recognition (STR) Ex-plainability, using XAI to understand the cause of an STR model's prediction. Recent XAI literatures on STR only provide a simple analysis and do not fully explore other XAI methods. In this study, we specifically work on data explainability frameworks, called attribution-based methods, that explain the important parts of an input data in deep learning models. However, integrating them into STR produces inconsistent and ineffective explanations, because they only explain the model in the global context. To solve this problem, we propose a new method, STRExp, to take into consideration the local explanations, i.e. the individual character prediction explanations. This is then benchmarked across different attribution-based methods on different STR datasets and evaluated across different STR models. © 2023, CC BY-SA.

关键词： Forecasting

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Development of Detection Lung Disease Stand Alone System Based on Convolutional Neural Network (CNN)

Development of Detection Lung Disease Stand Alone System Bas...

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International Conference of Computer and Informatics engineering (IC2IE)

作者： Edgar Caesar Liewarnata Yosica Mariana Sofyan Tan Suryadiputra Liawatimena Winda Astuti Automotive and Robotics Program Computer Engineering Department BINUS ASO School of Engineering Bina Nusantara University Jakarta Indonesia Product Design Program Industrial Engineering Department BINUS ASO School of Engineering Bina Nusantara University Jakarta Indonesia Automotive & Robotics Program Computer Engineering Department BINUS ASO School of Engineering Computer Science Department BINUS Graduate Program – Master of Computer Science Bina Nusantara University Jakarta Indonesia

ISBN: (数字)9798331505530

ISBN: (纸本)9798331505547

Lung disease, especially Tuberculosis (TBC), placed the highest death rate in Indonesia. Tuberculosis (TB) in Indonesia is ranked second after India. Therefore, it is important to reduce or early detection of the lung disease, to prevent this disease and speed up handling. The system can recognize the disease lung identification, and the system applied as standalone system. In this work, the Convolutional Neural Network (CNN) approach for identifying diseases lung identification is proposed. The Mel Frequency Cepstral Coefficient (MFCC) applied to process the stethoscope sounds which will used as input to the CNN. The performance of the proposed system has been investigated and resulted. The accuracy of 99% and 98%, for training and testing accuracy respectively. Furthermore, the system accurately detects lung diseases identification.

关键词： Training Accuracy Tuberculosis Pulmonary diseases Lungs Stethoscope Recording Convolutional neural networks Mel frequency cepstral coefficient Testing

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Capacitance Estimation Algorithm for Condition Monitoring of Electrolytic DC-Link Capacitors Using Artificial Neural Network in Front-End Diode Rectifier Three-Phase Motor Drive Systems

Capacitance Estimation Algorithm for Condition Monitoring of...

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IEEE Annual Southern Power Electronics Conference (SPEC)

作者： Mateus Abreu de Andrade Rodolfo César Costa Flesch Graduate Program in Automation and Systems Engineering Universidade Federal de Santa Catarina Florianópolis Brazil

A factor that must be taken into account in the modern design of power electronics converters is the reliability of dc-link capacitors, but traditional condition monitoring methods require extra hardware that increase the overall cost. This work proposes and experimentally evaluates a condition monitoring method for electrolytic dc-link capacitors in three-phase front-end diode rectifier motor drives which does not require hardware modifications. The presented method uses an artificial neural network (ANN) to predict the capacitance value of the dc-link capacitor bank. Based on time-domain parameters, the ANN is trained and evaluated using an error analysis to determine the effectiveness of the proposed method with a printed circuit board capacitor jig and aged samples. The proposed method is evaluated in several operating conditions and the results show that the prediction errors are less than 2.4% and that the method is able to monitor the degradation level of the dc-link capacitor bank.

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