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Analysis of Selective Emitter Formation Technology of n-TOPCon Solar Cell

Transactions of the Korean Institute of Electrical Engineers 2022年第1期71卷 114-120页

作者： Jeong, Sungjin Cha, Yewon Kim, Sungheon Kim, Hongrae Park, Somin Kim, Taeyong Park, Jinjoo Ju, Minkyu Yi, Junsin Dept. of Electrical and Computer Engineering Sungkyunkwan University Korea Republic of Interdisciplinary Program in Photovoltaic System Engineering Sungkyunkwan University Korea Republic of Dept. of Energy Convergence Engineering Division of Energy & Optical Technology Convergence Cheongju University Korea Republic of College of Information and Communication Engineering Sungkyunkwan University Korea Republic of

The main efficiency limiting factors for homogeneous emitter solar cells are resistance loss through metal contact on the front side and recombination loss at the surface. Herein, a selective emitter technology is introduced to solve the above problem, and it is currently commercialized in the mainstream p-PERC (Passivated Emitter Rear Contact) solar cell. The selective emitter boosts efficiency by 0.3-0.4% when compared to a homogeneous emitter, and when applied to the n-TOPCon (Tunnel Oxide Passivated Contact) solar cell, high efficiency of 26% or higher may be predicted. The most widely utilized selective emitter technologies are laser and etch-back. The One-Step Technology, which is suited to the n-TOPCon solar cell process, a laser is suitable for mass manufacturing with high yield. Because selective emitters increase electrical characteristics, which impact cell efficiency, it is required to study and create a technology that is optimal for the n-TOPCon manufacturing process. © 2022 Korean Institute of Electrical Engineers. All rights reserved.

关键词： Efficiency

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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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NFT-Based Hydroponic Automated Control Using Adaptive Network-Based Fuzzy Inference System 2

NFT-Based Hydroponic Automated Control Using Adaptive Networ...

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2nd International Conference on Robotics, Automation and Artificial Intelligence, RAAI 2022

作者： Surantha, Nico Vincentdo, Vito Bina Nusantara University Binus Graduate Program - Computer Science Jakarta11480 Indonesia Tokyo City University Faculty of Scienc and Engineering Department of Electrical Electronics and Communication Engineering Japan

ISBN: (纸本)9781665459440

The rapid population growth and industrial development in developing countries harm the agricultural sector because many agricultural lands are converted into residential or industrial areas. Applying modern agriculture technologies such as hydroponic could help to overcome the problem. However, hydroponics requires special attention in adjusting the pH and nutrient levels to maximize plant growth, so an automated system is needed to manage the process. In this research, a smart hydroponic system is proposed by applying Adaptive Networkbased Fuzzy Inference System (ANFIS) and Internet-of-Things. The IoT system consists of sensor, actuator, and data processing layer is designed to monitor and control the condition of pH and nutrition of the observed plants. Then, the ANFIS algorithm is designed to control the level of pH and nutrition. The experiment results show that the system can automatically adjust the pH and nutrient levels to the expected range for growing plants, and the fuzzy controller made using ANFIS are more accurate and stable than the fuzzy controller made using Sugeno. This study shows that ANFIS has excellent performance when controlling multiple actuators, as long as the data set has great granularity and well defined. © 2022 IEEE.

关键词： Hydroponics

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A Novel Hybrid Framework for Energy-Efficient Clustering and Routing in Heterogeneous IoT-Driven Wireless Sensor Networks 7

A Novel Hybrid Framework for Energy-Efficient Clustering and...

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7th International Conference on Contemporary Computing and Informatics, IC3I 2024

作者： Gupta, Gopal Kumar Jain, Arpit Sharma, Khemraj Ashok Kumar, P.M. Gupta, Shubhi Agarwal, Sheenu Nagpur Campus Pune440008 India Koneru Lakshmaiah Education Foundation Department of Computer Science Engineering AP Vaddeswaram522502 India Nanhua University Program in Management Sciences Department of Business Administration Dalin Chiayi62248 Taiwan Amity University Department of Computer Science and Engineering Uttar Pradesh Greater Noida India Uttarakhand Technical University Department of Electronics and Communication Engineering U.K. Dehradun India

ISBN: (纸本)9798350350067

Smart computing has been particularly notable in the development of wireless sensor networks (WSNs), which have many applications. Battery-powered, self-configuring sensor nodes are the basis of these networks. Energy and resources are limited when it comes to sensors. Unbalanced nodes in the network consume more power, which adversely affects the network's lifespan. An improved energy-efficient cluster-based routing protocol for heterogeneous wireless sensor networks (WSNs) based on the Internet of Things is proposed in this study. Several performance metrics were used to evaluate the proposed model's effectiveness, including energy efficiency, alive nodes, dead nodes, network lifetime, and residual energy. The results of the comparison were compared with existing methodologies, such as LEACH, PSO, and hybrid PSO. The proposed approach outperforms the existing model by a substantial margin in networks with 50 and 100 nodes, according to the simulation results. © 2024 IEEE.

关键词： Sensor nodes

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Predicting Microsatellite Instability from Histology Images with Dilated Neighborhood Attention Transformer in Colorectal Cancer 24

Predicting Microsatellite Instability from Histology Images ...

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24th IEEE International Conference on Bioinformatics and Bioengineering, BIBE 2024

作者： Chen, Yun-Chi Chao, Tung Phandita, Wimaya Nitya Sun, Tzu-Yu Wang, Huai-Zhi Hsieh, Yi-Hsien Hsu, Le-Yin Lin, Che Taipei Taiwan College of Bioresources and Agriculture NTU Taipei Taiwan National Taiwan University of Science and Technology Department of Computer Science and Information Engineering Taipei Taiwan Graduate Institute of Communication Engineering NTU Taipei Taiwan NTU Data Science Degree Program Taipei Taiwan NTU Department of Electrical Engineering Taipei Taiwan Center for Advanced Computing and Imaging in Biomedicine NTU Taipei Taiwan NTU Smart Medicine and Health Informatics Program Taipei Taiwan

ISBN: (纸本)9798331518622

Microsatellite instability (MSI) is a pivotal genetic marker influencing the efficacy of immunotherapy in colorectal cancer. Traditional MSI examination often requires additional genetic or immunohistochemical tests, whereas histology images, widely available in colorectal cancer diagnosis, offer a valuable alternative for MSI prediction. Although Transformer-based models have demonstrated promising outcomes in predicting MSI from histology images, they are hampered by traditional local attention mechanisms that struggle to capture long-range interdependencies and establish a comprehensive global receptive field. In this study, we introduce DiNAT-MSI, a novel framework for histology-based MSI prediction that incorporates the Dilated Neighborhood Attention Transformer (DiNAT). This model enhances global context recognition and substantially expands receptive fields, all without additional computational burden. Our results demonstrate that DiNAT-MSI achieves a superior patientwise AUROC compared to ResNet18 and Swin Transformer, along with commendable explainability. Our work not only illustrates a more accessible diagnostic tool for leveraging histological data but also underscores the potential of Transformerbased models with sophisticated attention designs in advancing precision medicine for colorectal cancer patients. © 2024 IEEE.

关键词： Diseases

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Analysis of the mechanism of degradation of p-type silicon solar cell

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Transactions of the Korean Institute of Electrical Engineers 2021年第8期70卷 1181-1187页

作者： Cha, Yewon Jeong, Sungjin Kim, Sungheon Kim, Youngkuk Yi, Junsin Dept. of Electrical and Computer Engineering Sungkyunkwan University Korea Republic of Interdisciplinary Program in Photovoltaic System Engineering Sungkyunkwan University Korea Republic of College of Information and Communication Engineering Sungkyunkwan University Korea Republic of

Two main factors that limiting the efficiency of the p-type solar cells are LID(Light Induced Degradation) and LeTID(Light and elevated temperature induced degradation). The major cause of LID is the formation of boron-oxygen defects in boron doped silicon. The LeTID is similar kinds as LID, but also occurs in the dark condition and by the recombination of metals and impurities or the reaction between the hydrogen and arbitrary substance. An overall 7% of LeTID degradation rate occurs over long-term scales. Unexpectedly, these degradations have been recently found to also arises in high purity materials such as float-zone(Fz-Si) and Czochralski-grown(Cz-Si). The proposed method to reduce these two degradations is to use appropriate firing process and annealing conditions. © 2021 Korean Institute of Electrical Engineers. All rights reserved.

关键词： Degradation

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Quantum Wrapper Networking: Investigating the Noise Impact of Classical Headers on the Quantum Payload

Quantum Wrapper Networking: Investigating the Noise Impact o...

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2024 Frontiers in Optics, FiO 2024

作者： Gül, Gamze On, Mehmet Berkay Tan, Shannon G. Proietti, Roberto Kanter, Gregory S. Yoo, S.J. Ben Kumar, Prem Graduate Program in Applied Physics Northwestern University 2145 Sheridan Road EvanstonIL60208 United States Department of Electrical and Computer Engineering University of California Davis DavisCA95616 United States Center for Photonic Communication and Computing Dept. of Electrical and Computer Eng. Northwestern University EvanstonIL60208 United States Department of Electronics and Telecommunications Engineering Politecnico di Torino Italy

We study the impact in time and frequency domains of classical headers on quantum payloads in quantum wrapper networking. We identify and characterize in-fiber scattering processes that produce noise photons degrading...

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The Contribution of Pancasila Education and Civic Education on Value Education for The Students During COVID 19 Pandemic in Digital Era

The Contribution of Pancasila Education and Civic Education ...

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2022 IEEE International Conference on Electrical, computer, and Energy Technologies, ICECET 2022

作者： Benawa, Arcadius Lusia, Erma Alwino, Alfensius Irawan, Iwan Witono, Petrus Hepi Faculty of Economics and Communication Bina Nusantara University Character Building Development Center Mass Communication Program Communication Department Jakarta Indonesia Faculty of Economics and Communication Bina Nusantara University Tourism Department Jakarta Indonesia Bina Nusantara University School of Computer Science Character Building Development Center Computer Science Department Jakarta Indonesia Bina Nusantara University School of Industrial Engineering Industrial Engineering Department Jakarta Indonesia

ISBN: (数字)9781665470872

ISBN: (纸本)9781665470872

When all nations including Indonesia are hit by COVID-19 pandemic in era digital, we are compelled to conduct research with the main purpose, namely how much the contribution or influence of Pancasila Education and Civic Education on Value Education for students during the Covid-19 pandemic. The method used in this research is a quantitative method. The data was obtained by asking the students who were respondents to fill out a questionnaire. 150 students who have attended Pancasila and Citizenship courses were chosen by random sampling. Then the data obtained from the responses of the respondents were processed by the SPSS 22 program, and analyzed by path analysis. From the data processing and path analysis, the results of the research are obtained which prove that Pancasila Education has a significant contribution or influence on Value Education. Civic Education has no significant contribution or influence on Value Education. Based on these findings from this research, it is necessary to increase more intensive and serious efforts in delivering Pancasila Education, especially Civic Education in order to increase the contribution of both education to value education for the students, so that the students as the younger generation do not only have an understanding about Pancasila Education and Civic, but also be able to live the values, especially SPIRIT (Striving for the excellence, Perseverance, Integrity, Respect, Innovation, and Team Work) which are the core values at Bina Nusantara University. © 2022 IEEE.

关键词： Students

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Robust Audio Watermarking Based on Empirical Mode Decomposition and Group Differential Relations

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AES: Journal of the Audio engineering Society 2023年第3期71卷 100-117页

作者： Lai, Wen-Hsing Chou, Tsung-Yuan Chou, Meng-Chen Schuller, Björn W. Department of Computer and Communication Engineering National Kaohsiung University of Science and Technology No. 1 University Rd. Yanchao Dist. Kaohsiung City82445 Taiwan ZD.B Chair of Embedded Intelligence for Health Care and Wellbeing University of Augsburg Germany Ph.D. Program in Engineering Science and Technology College of Engineering National Kaohsiung University of Science and Technology Taiwan GLAM – Group on Language Audio & Music Imperial College London United Kingdom

An audio watermarking technique using Complementary Ensemble Empirical Mode Decomposition and group differential relations of average absolute amplitudes of the last Intrinsic Mode Function (IMF) is proposed. By using group differential relations, the relationship with neighboring samples in the last IMF is well preserved, and near-imperceptibility can be achieved. Placing a watermark on low-frequency components, the last IMF, which is perceptually significant, therefore makes the watermark difficult to be removed. The embedding watermark, which is a logo image in our experiment, is processed by Arnold transformation, secret key encryption, and Bose–Chaudhuri–Hocquenghem coding to enhance robustness and security. Experimental results of the signal-to-noise ratio fit the recommendations of imperceptibility of the International Federation of the Phonographic Industry. The average Objective Difference Grade (an objective measure that correlates very well with subjective assessment) and subjective quality assessment were performed to evaluate the imperceptibility. Furthermore, our method accomplishes robustness under 13 different categories of attacks, including noise corruption, amplitude scaling, echo addition, resampling, re-quantization, low-pass filtering, MPEG-1 Audio Layer III compression, Digital-to-Analog/Analog-to-Digital conversion, cropping, time shift, zero thresholding, jittering, and combined attacks. © 2023 Authors. All rights reserved.

关键词： Intrinsic mode functions

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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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