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SSRN 2024年

作者： Ragragio, Titus James Reynon Borres, Rianina D. Persada, Satria Fadil Young, Michael Nayat Ong, Ardvin Kester S. Prasetyo, Yogi Tri Nadlifatin, Reny Zulvia, Ferani Eva School of Industrial Engineering and Engineering Management Mapua University 658 Muralla St. Intramuros Manila1002 Philippines Entrepreneurship Department BINUS Business School Undergraduate Program Bina Nusantara University Malang65154 Indonesia International Bachelor Program in Engineering Yuan Ze University 135 Yuan-Tung Road Chung-Li32003 Taiwan Department of Industrial Engineering and Management Yuan Ze University 135 Yuan-Tung Road Chung-Li32003 Taiwan Department of Information Systems Institut Teknologi Sepuluh Nopember Kampus ITS Sukolilo Surabaya60111 Indonesia National Taiwan University of Science and Technology No.43 Keelung Rd. Sec.4 Da'an Dist. Taipei City106335 Taiwan

This study delves into the perception of homeowners in the Philippines regarding the utilization of Residential Rooftop Solar Photovoltaic Systems (RSPVS), focusing on their intention to adopt this renewable energy technology. The research is driven by the advantageous conditions in the Philippines, including high irradiance levels, supportive solar PV policies, and decreasing system costs. Understanding prosumers' (producers and consumers) perspectives is crucial to accelerating the adoption of RSPVS, which can significantly contribute to decentralizing and greening the electrical production landscape in the country. Building on previous studies, which highlight a keen interest in solar technology among homeowners but cite high installation costs and a lack of understanding as major barriers, this research aims to shed light on the factors influencing prosumers' intentions to use RSPVS. Employing a theoretical framework combining the technology Acceptance Model (TAM), Theory of Planned Behavior (TPB), Unified Theory of Acceptance and Use of technology (UTAUT), and integrating Technophilia and Perceived Risk as supplementary constructs, this study seeks to uncover the drivers and inhibitors of RSPVS adoption. The study employs an online questionnaire distributed in key cities where Residential RSPVS is available, with a sample size of 239 respondents. The data collected are analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM) to examine the relationships between variables and to test the hypothesized model. The results indicate that factors such as Technophilia, Price Value, and Social Influence are significant determinants of prosumers' intent to adopt RSPVS. Notably, Technophilia, reflecting enthusiasm for new technology, emerged as a key factor, suggesting that prosumers are motivated by the allure of solar energy. Additionally, the study found that Perceived Risk was not a significant inhibitor, indicating a high level of confidence and tr

关键词： Solar energy

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Ultrasound-Guided Deep Learning for Regional Nerve Block Anesthesia in Scapular Fracture

Ultrasound-Guided Deep Learning for Regional Nerve Block Ane...

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Distributed Computing and Electrical Circuits and Electronics (ICDCECE), IEEE International Conference on

作者： Upasna Joshi Mohan Raparthi Ramswaroop Reddy Pramod Kumar Praveen Thuniki Mohammad Shabaz Delhi Technical Campus Greater Noida India Software Engineer Alphabet Life Science Dallas Texas USA Yellu Independent Research Richmond VA 23233 University of Texas Austin US Ganga Institute of Technology and Management Haryana India Independent Research Sr Program Analyst Georgia Cumming GA USA Model Institute of Engineering and Technology Jammu J&K India

ISBN: (数字)9798350318609

ISBN: (纸本)9798350318616

This study introduces a novel approach to regional nerve block anesthesia in scapular fractures by integrating ultrasound guidance with deep learning techniques. The proposed method leverages advanced imaging modalities and state-of-the-art deep learning models to achieve precise nerve localization amidst complex fracture patterns. Through extensive experimentation and evaluation, we demonstrate the effectiveness of the proposed method in enhancing surgical planning, intraoperative decision-making, and patient safety. This study represents a significant advancement in the field of orthopedic surgery, offering a promising solution for improving outcomes and quality of life for patients with scapular fractures. The method this study suggests for locating nerves in shoulder fractures advances orthopaedic surgery. We can improve, expedite, and streamline procedures with the use of AI and medical imaging. This will improve the quality of life and outcomes for scapular fractures.

关键词： Deep learning Location awareness Ultrasonic imaging Orthopedic surgery Decision making Shoulder Anesthesia

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FincGAN: A Gan Framework of Imbalanced Node Classification on Heterogeneous Graph Neural Network

FincGAN: A Gan Framework of Imbalanced Node Classification o...

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International Conference on Acoustics, Speech, and Signal Processing (ICASSP)

作者： Hung Chun Hsu Ting-Le Lin Bo-Jun Wu Ming-Yi Hong Che Lin Chih-Yu Wang Graduate Program of Data Science National Taiwan University and Academia Sinica Taiwan Department of Accounting and Statistics National ChengChi University Taiwan Department of Risk Management and Insurance National ChengChi University Taiwan Department of Electrical Engineering National Taiwan University Taiwan Graduate Institute of Communication Engineering National Taiwan University Taiwan Research Center for Information Technology Innovation Academia Sinica Taiwan

Graph Neural Networks (GNNs) frequently face class imbalance issues, especially in heterogeneous graphs. Existing GNNs often assume balanced class sizes, which isn’t true in many cases. Applying them directly to imbalanced data can lead to sub-optimal performance. Traditional oversampling methods, while effective, risk overfitting and face difficulties in reintegrating synthetic samples into the original graph. In this study, we introduce Framework of Imbalanced Node Classification on heterogeneous graph neural network with GAN (FincGAN), a new framework that utilizes oversampling techniques to address class imbalance in heterogeneous graphs. Instead of duplicating existing samples, FincGAN employs a Generative Adversarial Network (GAN) to create synthetic samples and uses deep learning-based edge generators to connect them back to the original graph. Our evaluations on spam user detection in the Amazon and Yelp Review datasets show that FincGAN outperforms baseline models in all essential metrics, including F-score and AUC-PRC score, showing its effectiveness in addressing class imbalance.

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Reconstructing suspended sediment concentrations in the Mekong River Basin via semi-supervised-based deep neural networks

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Science of the Total Environment 2024年 955卷 176758页

作者： Nguyen, Thi Thu Ha Vu, Duc Quang Doan, Ngoc Phu Chi, Huynh Thi Khanh Li, Peixin Binh, Doan Van An, Yimeng Dung, Pham Tuan Hoang, Tuan A. Son, Mai Thai Laboratory of Environmental Sciences and Climate Change Institute for Computational Science and Artificial Intelligence Van Lang University Ho Chi Minh City Viet Nam Faculty of Environment School of Technology Van Lang University Ho Chi Minh City Viet Nam Department of Computer Science and Information System Thai Nguyen University of Education Viet Nam School of Electronics Electrical Engineering and Computer Science Queen's University Belfast United Kingdom College of Economics and Management Nanjing University of Aeronautics and Astronautics China Master program in Water Technology Reuse and Management Faculty of Engineering Vietnamese-German University Binh Duong Province Ben Cat City Viet Nam

The Mekong River Basin (MRB) is crucial for the livelihoods of over 60 million people across six Southeast Asian countries. Understanding long-term sediment changes is crucial for management and contingency plans, but the sediment concentration data in the MRB are extremely sporadic, making analysis challenging. This study focuses on reconstructing long-term suspended sediment concentration (SSC) data using a novel semi-supervised machine learning (ML) model. The key idea of this approach is to exploit abundant available hydroclimate data to reduce training overfitting rather than solely relying on sediment concentration data, thus enhancing the accuracy of the employed ML models. Extensive experiments on daily hydroclimate and SSC data obtained from 1979 to 2019 at the three main stations (i.e., Chiang Saen, Nong Khai, and Mukdahan) are conducted to demonstrate the superior performance of the proposed method compared to the state-of-the-art supervised techniques (i.e., Random Forest, XGBoost, CatBoost, MLP, CNN, and LSTM), and surpasses existing semi-supervised methods (i.e., CoReg, ⊓ Model, ICT, and Mean Teacher). This approach is the first semi-supervised method to reconstruct sediment data in the field and has the potential for broader application in other river systems. © 2024 The Author(s)

关键词： Self-supervised learning

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Social Media Engagement as Mediator: Does Content Vividness Predict Purchase Intention?

Social Media Engagement as Mediator: Does Content Vividness ...

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International Conference on Business and Industrial Research (ICBIR)

作者： Wachyu Hari Haji Shandy Aditya Afifa Qurrota Ainin Sri Susilawati Islam Management Department BINUS Entrepreneurship Center Bina Nusantara University Jakarta Indonesia Digital Business Study Program Faculty of Economics State University of Jakarta Jakarta Indonesia Faculty of Business Sampoerna University Jakarta Indonesia Faculty of Engineering & Technology Sampoerna University Jakarta Indonesia

This study examines Instagram influencers' social media behavior and providing suggestions for increasing engagement and purchase intentions towards endorsed products via post-effectiveness. Several objectives will be raised in this study: (1) determining the effect of content vividness on social media engagement, (2) determining the impact of social media engagement on purchase intentions, (3) determining the effect of content vividness on purchase intentions. This quantitative study utilizes Partial Least Square (PLS) software as a tool to test validity and reliability and SPSS to test the hypothesis and regression model. With the total of 199 valid respondents participating into this study's survey, the result highlights the positive effects of content vividness in enhancing purchase intentions through mediating variable, namely social media engagement.

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Potential of fungal thermostable alpha amylase enzyme isolated from Hot springs of Central Anatolia(Turkey)in wheat bread quality

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Food Bioscience 2022年第1期45卷 214-222页

作者： Arzu Unal Asiye Seis Subasi Semra Malkoc Ijlal Ocak SElif Korcan Elif Yetilmezer Seyhun Yurdugül Hülya Yaman Turgay Sanal Alaettin Keceli Igdır University Faculty of AgricultureDepartment of Agricultural BiotechnologyI˘gdırTurkey Ministry of Agriculture and Forestry Field Crops Central Research Institute Department of Quality and TechnologyAnkaraTurkey Eskisehir Technical University Faculty of EngineeringDepartment of Environmental EngineeringEskisehirTurkey Afyon Kocatepe University Faculty of EducationDepartment of Mathematics and Science EducationDivision of Science EducationAfyonTurkey Usak University Vocational School of Health ServicesMedical Laboratory Techniques ProgramUsakTurkey Ministry of Agriculture and Forestry Field Crops Central Research Institute Department of BiotechnologyAnkaraTurkey Bolu Abant Izzet Baysal University Faculty of Arts and ScienceDepartment of BiologyBoluTurkey Bolu Abant Izzet Baysal University Vocational School of the Technical Sciences of BoluFood Technology ProgramBoluTurkey Pamukkale University School of Applied SciencesDepartment of Organic Farming Business ManagementDenizliTurkey

Many industrial processes may quickly proceed with biotechnological and enzymatic *** and production facilitator properties of enzymes have provided variable advantages for ***,enzyme utilization has become inevitable for industry and supplied financial advantages in case of the high energy requirement *** the study,the amylase enzymes were isolated from thermal spring sources,and the effect on bread quality was ***,fungal amylases were isolated from thermal spring sources(29-98◦C)in various places around *** determining the functional properties of amylase enzymes,the most active enzyme was used in bread production to examine their effect on bread *** maximum alpha-amylase activity(38.6 U/mg)has been detected in Aspergillus niger G 2-1 *** compared with the commercially available one,native alpha-amylase increased the bread volume.A significant difference(p<0.01)was found in the color properties and size of the bread between microbial produced in this study and commercially produced *** ppm alpha-amylase addition showed the optimum bread properties for dough processing.

关键词： Alpha-amylase Thermal spring Quality of bread Commercial enzymes

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Occurrence and fate of pharmaceutical pollutants in wastewater: Insights on ecotoxicity, health risk, and state–of–the-art removal

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Chemosphere 2024年 354卷 141678页

作者： Nguyen, Minh-Ky Lin, Chitsan Bui, Xuan-Thanh Rakib, Md. Refat Jahan Nguyen, Hoang-Lam Truong, Quoc-Minh Hoang, Hong-Giang Tran, Huu-Tuan Malafaia, Guilherme Idris, Abubakr M. Faculty of Environment and Natural Resources Nong Lam University Hamlet 6 Linh Trung Ward Thu Duc City Ho Chi Minh City700000 Viet Nam Ph.D. Program in Maritime Science and Technology National Kaohsiung University of Science and Technology Kaohsiung81157 Taiwan Department of Marine Environmental Engineering National Kaohsiung University of Science and Technology Kaohsiung81157 Taiwan Linh Trung Ward Thu Duc City Ho Chi Minh City700000 Viet Nam Ho Chi Minh City700000 Viet Nam Department of Environmental Science and Management North South University Dhaka Bashundhara1229 Bangladesh Department of Civil Engineering McGill University Montreal Canada Faculty of Management Science Thu Dau Mot University Binh Duong 75000 Viet Nam Faculty of Medicine Dong Nai Technology University Dong Nai Bien Hoa76100 Viet Nam Laboratory of Ecology and Environmental Management Science and Technology Advanced Institute Van Lang University Ho Chi Minh City700000 Viet Nam Faculty of Applied Technology School of Engineering and Technology Van Lang University Ho Chi Minh City700000 Viet Nam Post-Graduation Program in Ecology Conservation and Biodiversity Federal University of Uberlândia MG Uberlândia Brazil Post-Graduation Program in Biotechnology and Biodiversity Federal University of Goiás GO Goiânia Brazil Post-Graduation Program in Conservation of Cerrado Natural Resources Goiano Federal Institute GO Urutaí Brazil Department of Chemistry College of Science King Khalid University Abha62529 Saudi Arabia King Khalid University Abha62529 Saudi Arabia

Pharmaceutical active compound (PhAC) residues are considered an emerging micropollutant that enters the aquatic environment and causes harmful ecotoxicity. The significant sources of PhACs in the environment include the pharmaceutical industry, hospital streams, and agricultural wastes (animal husbandry). Recent investigations demonstrated that wastewater treatment plants (WWTPs) are an important source of PhACs discharging ecosystems. Several commonly reported that PhACs are detected in a range level from ng L−1 to μg L−1 concentration in WWTP effluents. These compounds can have acute and chronic adverse impacts on natural wildlife, including flora and fauna. The approaches for PhAC removals in WWTPs include bioremediation, adsorption (e.g., biochar, chitosan, and graphene), and advanced oxidation processes (AOPs). Overall, adsorption and AOPs can effectively remove PhACs from wastewater aided by oxidizing radicals. Heterogeneous photocatalysis has also proved to be a sustainable solution. Bioremediation approaches such as membrane bioreactors (MBRs), constructed wetlands (CWs), and microalgal-based systems were applied to minimize pharmaceutical pollution. Noteworthy, applying MBRs has illustrated high removal efficiencies of up to 99%, promising prospective future. However, WWTPs should be combined with advanced solutions, e.g., AOPs/photodegradation, microalgae–bacteria consortia, etc., to treat and minimize their accumulation. More effective and novel technologies (e.g., new generation bioremediation) for PhAC degradation must be investigated and specially designed for a low-cost and full-scale. Investigating green and eco-friendly PhACs with advantages, e.g., low persistence, no bioaccumulation, less or non-toxicity, and environmentally friendly, is also necessary. © 2024 Elsevier Ltd

关键词： Microalgae

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Multimodal Sentiment Analysis using Kernel Based Support Vector Machine

Multimodal Sentiment Analysis using Kernel Based Support Vec...

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Advanced Technologies in Intelligent Control, Environment, Computing & Communication engineering (ICATIECE), International Conference on

作者： V Sunil Kumar Piyush Kumar Pareek Victor Hugo Costa De Albuquerque Ashish Khanna Deepak Gupta Madhumala R B Department Artificial Intelligence & Machine Learning Nitte Meenakshi Institute of Technology Bengaluru Graduate Program in Telecommunication Engineering Federal Institute of Education Science and Technology of Ceará Fortaleza Brazil Department of Teleinformatics Engineering Federal University of Ceará Brazil CSE Dept Maharaja Agrasen Institute of Technology GGSIPU Department of ISE Dayananda Sagar Academy of Technology and Management Bangalore

ISBN: (纸本)9781665493970

There has been a steady expansion in the number of social websites, electronic media outlets, and blogging services, all of which contribute a large number of user messages such as comments, reviews, and opinions from customers. The quantity of these signals, which are used to evaluate the quality of a wide variety of goods and services, is rather substantial. As a result, it is challenging to monitor and identify the feelings of customers. As a result, a method known as Sentiment Analysis (SA), also known as Opinion Mining (OM), was developed. This method gathers data from the internet by using Natural Language Processing (NLP) strategies and then analyses people's thoughts. It does this by extracting subjective information from the words, assessing opinions, and quantifying positive and negative evaluations. The end result is a conclusion about the specific entity, which may be an organisation, the public, or a product. The NLP first gathers the views, and then those opinions are sorted into positive, neutral, and negative categories. Both the marketing promotion and the customer's ability to choose the most appropriate product for their needs may be improved by doing an analysis. The purpose of this study is to evaluate the use of different machine learning and swarm intelligence optimization methods to perform sentiment analysis on data derived from movie reviews. This study helps many businesses increase their profits while simultaneously lowering the number of problems caused by a certain product. Within the scope of this investigation, three distinct models of sentiment analysis were investigated. An effective method for doing sentiment analysis known as a Hybrid Kernel based Support Vector Machine (HKSVM) has been presented. The preprocessing that is described here is meant to cut down on the data inconsistencies and get rid of the data that isn't needed. After that, the Expectation Maximization (EM) technique is used in order to identify an outlier. After t

关键词： Support vector machines Sentiment analysis Analytical models Sensitivity Veins Tagging Probabilistic logic

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Experimental investigation on the effect of laser powder bed fusion process variables on dimensional accuracy, surface roughness and cylindricity of the AlSi10Mg alloy component

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Proceedings of the Institution of Mechanical Engineers, Part E: Journal of Process Mechanical engineering 2021年

作者： Maurya, Nagendra K Srivastava, Ashish K Saxena, Ambuj Dwivedi, Shashi P Ashraf Ali, Mashood Mustafa, Jiyaul Department of Mechanical Engineering G.L Bajaj Institute of Technology & Management India Department of Mechanical Engineering Industrial Engineering Program College of Engineering Prince Sattam bin Abdulaziz University Saudi Arabia India

The present study deals with the influence of laser powder bed fusion process parameters on the selected linear dimension, surface roughness and cylindricity of AlSi10Mg alloy for manufacturing of a prototype connecting rod. The process variables used in this investigation are laser power, laser velocity, layer thickness and scanning speed. Response surface methodology is used to perform experiments and data analysis. The levels of process parameters are same that is, five for all the selected input process variables. An automotive component connecting rod is used as a component to analyze the effect of process variables on selected response variables. The optimum sating of process variables are different for dimensional accuracy, surface roughness and cylindricity. Minitab 14 software is used for the data analysis. The international tolerance grades of confirmation experiments are calculated as per the ISO standard UNI EN 20286-I and DIN 16901. A quadratic regression models are developed to estimate the response variables in terms of process parameters. The model is adequate within the experimental domain. X-chart of confirmation experiments is plotted. The deviation in the linear dimension is within the limit of ±3 sigma (σ). The lowest values of response variables at the best level of process parameters are obtained, that is, percentage error in dimensional accuracy of 2.65%, surface roughness of 2.57 µm and cylindricity of 0.09 mm. The novelty of this work lies in the fact that only a few studies have been conducted related to the form errors in the archival literature. © IMechE 2021.

关键词： Surface roughness

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Social media-based online entrepreneurship approach on millennials: A measurement of job pursuit intention on multi-level marketing

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Procedia Computer Science 2022年 197卷 110-117页

作者： Reny Nadlifatin Satria Fadil Persada Mutiara Clarinda Gogor Arif Handiwibowo Rr Ratih Laksitowati Yogi Tri Prasetyo Anak Agung Ngurah Perwira Redi Department of Information System Institut Teknologi Sepuluh Nopember Campus ITS Sukolilo Surabaya 60111 Indonesia Department of Business Management Institut Teknologi Sepuluh Nopember Campus ITS Sukolilo Surabaya 60111 Indonesia Department of Technology Management Institut Teknologi Sepuluh Nopember Campus ITS Sukolilo Surabaya 60264 Indonesia School of Industrial Engineering and Engineering Management Mapúa University 658 Muralla St. Intramuros Manila 1002 Philippines Industrial Engineering Department BINUS Graduate Program-Master of Industrial Engineering Bina Nusantara University Jakarta 11480 Indonesia

The present research explores the behavioral perspective of the millennial generation on job pursuit intention on Multi-Level Marketing companies through social media. Theory of Planned Behavior (TPB) and technology Acceptance Model (TAM) are used to assess the job pursuit intention. The data were analyzed by Structural Equation Model (SEM). Analysis reveals the strong influence of attitude on job pursuit intention. The result in this research can be used as the theoretical basis that can be very beneficial for MLM companies, investors, and academicians in marketing. Further theoretical and practical suggestions are discussed.

关键词： Millennial MLM social media TPB TAM

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