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A Technology-Organization-Environment (TOE) Framework Based on Scientometry for Understanding The Risk Factors in Sustainable Water Resources Management

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Water Resources Management 2023年第15期37卷 5849-5869页

作者： Lin, Chih-Hsien Chen, Wei-Hsiang Institute of Environmental Engineering National Sun Yat-sen University Kaohsiung804 Taiwan Aerosol Science and Research Center National Sun Yat-sen University Kaohsiung804 Taiwan Center for Emerging Contaminants Research National Sun Yat-sen University Kaohsiung804 Taiwan Department of Public Health Kaohsiung Medical University Kaohsiung807 Taiwan Doctoral and Mater Degree Program in Toxicology Kaohsiung Medical University Kaohsiung807 Taiwan

The study of how water can be used sustainably through risk management has become increasingly complex due to the many different aspects involved. This study used a three-step approach to investigate the issue: trend analysis, bibliometric analysis, and the development of a conceptual TOE framework. The trend analysis identified water conservation and water crisis as the most frequently mentioned keywords, suggesting the need to address public concern for these issues. The bibliometric analysis found that 37% of the articles were published in the last three years, and environmental science and technology was the most common field of study. The TOE framework was used to link and group the keywords (risk factors) from the articles into three categories: technology, organization, and environment. This framework provides a way to understand the different factors that contribute to water scarcity and to develop strategies for addressing these risk factors. The three risk factors with the highest scores were statistical analysis (technology), climate change (environment), and uncertainty (environment). In the technology category, statistical analysis, sustainable development, and water quality were the most important risk factors. In the organization category, water management, governance, and water markets were the most important risk factors. In the environment category, climate change, uncertainty, and flood were the most important risk factors. This study is expected to provide valuable insights into the research trends that are important for achieving sustainability in water resource management, both in conventional and academic studies, over the past decade. Graphical Abstract: [Figure not available: see fulltext.]. © 2023, The Author(s), under exclusive licence to Springer Nature B.V.

关键词： Sustainable development

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A Dynamic Model for Pauses in the Synthesized Speech of Mathematical Expressions in MathML 22

A Dynamic Model for Pauses in the Synthesized Speech of Math...

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Proceedings of the 14th International Conference on Education Technology and Computers

作者： Adriana Souza Diamantino Freitas Bahia Federal Institute of Education Science and Technology Brazil and Doctoral Program in Digital Media Faculty of Engineering Faculty of Engineering of University of Porto Portugal Department of Electrical and Computer Engineering Faculty of Engineering of University of Porto Portugal

ISBN: (纸本)9781450397766

Voice synthesizers still present several challenges in the speech of mathematical content, as spoken mathematics has quite peculiar rules. In the synthesized speech, pauses help blind and visually impaired students identify the limits of mathematical operators and subexpressions. However, most studies on pauses define them uniformly or use simple punctuation marks to force the synthesizer to introduce pauses in certain parts of the expression. Speech is a dynamic process and pauses in expressions also need to be dynamic to make the synthetic speech of expressions more natural, as this can help in memorizing this type of content. This work proposed a dynamic model of pauses for mathematical expressions. Collected math expressions spoken by teachers were used to create the model. These expressions were useful for identifying patterns and creating a linear regression model. Blind and visually impaired students evaluated the model. Some improvements were observed when we compared the synthesized mathematical expressions with the model and Audiomath, the parameter tool used in this study.

关键词： Accessibility Synthesized Speech Mathematics Visual Impairment

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Fucoxanthin induces human melanoma cytotoxicity by thwarting the JAK2/STAT3/BCL-xL signaling axis

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Environmental Toxicology 2024年第6期39卷 3356-3366页

作者： Kuo, Min-Yung Dai, Wen-Chyi Chang, Jie-Li Chang, Jo-Shu Lee, Tse-Min Chang, Chia-Che Pediatric Surgery Division Department of Surgery Tungs' Taichung MetroHarbor Hospital Taichung Taiwan Doctoral Program in Biotechnology Industrial Innovation and Management National Chung Hsing University Taichung Taiwan Taichung Municipal Taichung First Senior High School Taichung Taiwan Department of Chemical and Materials Engineering Research Center for Smart Sustainable Circular Economy Tunghai University Taichung Taiwan Department of Life Sciences National Chung Hsing University Taichung Taiwan Department of Marine Biotechnology and Resources National Sun Yat-sen University Kaohsiung Taiwan Graduate Institute of Biomedical Sciences Master Program in Precision Health Doctoral Program in Translational Medicine Rong Hsing Research Center for Translational Medicine The iEGG and Animal Biotechnology Research Center National Chung Hsing University Taichung Taiwan Department of Medical Laboratory Science and Biotechnology Asia University Taichung Taiwan Department of Medical Research China Medical University Hospital Taichung Taiwan Traditional Herbal Medicine Research Center Taipei Medical University Hospital Taipei Taiwan

Melanoma is the most lethal skin malignancy. Fucoxanthin is a marine carotenoid with significant anticancer activities. Intriguingly, Fucoxanthin's impact on human melanoma remains elusive. Signal Transducer and Activator of Transcription 3 (STAT3) represents a promising target in cancer therapy due to its persistent activation in various cancers, including melanoma. Herein, we revealed that Fucoxanthin is cytotoxic to human melanoma cell lines A2758 and A375 while showing limited cytotoxicity to normal human melanocytes. Apoptosis is a primary reason for Fucoxanthin's melanoma cytotoxicity, as the pan-caspase inhibitor z-VAD-fmk drastically abrogated Fucoxanthin-elicited clonogenicity blockage. Besides, Fucoxanthin downregulated tyrosine 705-phosphorylated STAT3 (p-STAT3 (Y705)), either inherently present in melanoma cells or inducible by interleukin 6 (IL-6) stimulation. Notably, ectopic expression of STAT3-C, a dominant-active STAT3 mutant, abolished Fucoxanthin-elicited melanoma cell apoptosis and clonogenicity inhibition, supporting the pivotal role of STAT3 blockage in Fucoxanthin's melanoma cytotoxicity. Moreover, Fucoxanthin lowered BCL-xL levels by blocking STAT3 activation, while ectopic BCL-xL expression rescued melanoma cells from Fucoxanthin-induced killing. Lastly, Fucoxanthin was found to diminish the levels of JAK2 with dual phosphorylation at tyrosine residues 1007 and 1008 in melanoma cells, suggesting that Fucoxanthin impairs STAT3 signaling by blocking JAK2 activation. Collectively, we present the first evidence that Fucoxanthin is cytotoxic selectively against human melanoma cells while sparing normal melanocytes. Mechanistically, Fucoxanthin targets the JAK2/STAT3/BCL-xL antiapoptotic axis to provoke melanoma cell death. This discovery implicates the potential application of Fucoxanthin as a chemopreventive or therapeutic strategy for melanoma management. © 2024 Wiley Periodicals LLC.

关键词： Carotenoids

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Convolutional Neural Network Approach for Sentiment Analysis of GoFood Services

Convolutional Neural Network Approach for Sentiment Analysis...

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Computer sciences, engineering, and Technology Innovation (ICoCSETI), International Conference on

作者： Zaenal Abidin Adzqi Aulia Ryan Randy Suryono Permata Akmal Junaidi Wamiliana Wamiliana Doctoral Program of Mathematics and Natural Sciences Universitas Lampung Bandarlampung Indonesia Faculty of Engineering and Computer Science Universitas Teknokrat Indonesia Bandarlampung Indonesia Department of Computer Science Universitas Lampung Bandarlampung Indonesia Department of Mathematics Universitas Lampung Bandarlampung Indonesia

ISBN: (数字)9798331508616

ISBN: (纸本)9798331508623

In the age of swift digital advancement, social media has emerged as a vital and readily available information source for users. Individuals utilize social media to communicate, articulate thoughts, and disseminate their viewpoints, both textually and visually. Twitter is a social media platform that people extensively utilize to disseminate both favorable and unfavorable information regarding GoFood services. This study intends to apply the Convolutional Neural Network (CNN) algorithm within the GoFood service on Twitter. This research also seeks to assess the accuracy of the CNN algorithm in relation to GoFood services. Employing deep learning techniques, particularly the convolutional neural network algorithm, to analyze Twitter user sentiment can enhance the efficiency, accuracy, and simplicity of classifying answers to GoFood services. The findings indicated that the Convolutional Neural Network technique was effectively employed to classify positive, negative, and neutral feelings. The optimal accuracy rate was attained through preprocessing with Stemming, yielding 51% accuracy for multiclass classification and 72% for binary class classification. The accuracy percentage for classification without stemming was 49% for multiclass classification and 70% for binary classification. This research holds possible consequences for Gojek firms and can serve as evaluative and assessment material for GoFood services, enabling them to implement necessary corrective measures.

关键词： Sentiment analysis Accuracy Social networking (online) Convolution Blogs Text categorization Feature extraction Classification algorithms Convolutional neural networks Testing

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Bibliometric Analysis of Trends and Directions in Machine Learning Applied to FinTech

Bibliometric Analysis of Trends and Directions in Machine Le...

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Electronic and Electrical engineering and Intelligent System (ICE3IS), International Conference on

作者： Erman Arif Suherman Suherman Aris Puji Widodo Doctoral Program of Information System School of Postgraduate Studies Diponegoro University Semarang Indonesia Department of Chemical Engineering Faculty of Engineering Diponegoro University Semarang Indonesia Department of Informatics Faculty of Science and Mathematics Diponegoro University Semarang Indonesia

ISBN: (数字)9798350378368

ISBN: (纸本)9798350378375

Our article presents a comprehensive analysis of trends and directions in the application of machine learning in the FinTech sector. By utilizing data from academic databases such as Scopus, our objective is to showcase the advancements in this interdisciplinary research area. The study identifies key trends, influential authors, leading journals, and significant collaborative networks that shape the field. The methodology employed involves quantitative bibliometric analysis to evaluate publications from the past five years. The results indicate a substantial increase in the number of studies during this period, highlighting the importance of machine learning in addressing critical financial challenges, including fraud detection, algorithmic trading, credit scoring, and risk management. Additionally, we delve into the main themes, countries, and institutions that dominate the current research agenda. This analysis provides valuable insights into the present state and future direction of machine learning in FinTech, serving as a resource for researchers and practitioners seeking to comprehend and contribute to this dynamic and rapidly evolving field. We also discuss implications for future research, emphasizing the necessity for continuous innovation and interdisciplinary collaboration to maximize the potential of machine learning in transforming financial services.

关键词： Symbiosis Technological innovation Machine learning algorithms Bibliometrics Collaboration Machine learning Market research Dynamic scheduling Fraud Risk management

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Initial Exploration and Understanding of Parameters for Successful Enterprise Architecture Implementation

Initial Exploration and Understanding of Parameters for Succ...

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International Conference on ICT For Smart Society (ICISS)

作者： Dyna Marisa Khairina Purwanto Purwanto Dinar Mutiara Kusumo Nugraheni Doctoral Program in Information Systems School of Postgraduate Studies Universitas Diponegoro Semarang Indonesia Department of Chemical Engineering Faculty of Engineering Universitas Diponegoro Semarang Indonesia Department of Informatics Faculty of Science and Mathematics Universitas Diponegoro Semarang Indonesia

ISBN: (数字)9798350389654

ISBN: (纸本)9798350389661

This study provides an initial exploration and further understanding of the factors that are parameters in evaluating the success of Enterprise Architecture (EA) implementation. An evaluation process is needed to ensure that the EA project implementation provides effectiveness, efficiency, and feasibility of the EA information system as well as assessing previous project experience to avoid future EA project risks. The research aims to present a Systematic Literature Review based on the stages of identification, screening, eligibility, and inclusion so that 14 main articles are selected for review with strong actual relevance. The study results provide insights and references that can be used to further explore key factors in evaluating the success of EA implementation in the future. It was found that there were ten factors that most influenced the evaluation of the success of EA implementation and it was concluded that two potential factors were the most influential and required further exploration in evaluating the success of EA implementation which could be applied in various sectors/dimensions. This study contributes as an initial reference for overcoming problems in investigating and exploring the factors that influence the success of EA implementation as an effort to assess the success of achieving future organizational goals.

关键词： Bibliographies Testing Information systems

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Optional Hyperparameter Tuning of Convolutional Neural Network for ECG Classification

Optional Hyperparameter Tuning of Convolutional Neural Netwo...

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International Conference on Informatics, Multimedia, Cyber and Information System (ICIMCIS)

作者： Muhamad Akbar Siti Nurmaini Radiyati Umi Partan Doctoral Program of Engineering Science Fakulty of Engineering Universitas Sriwijaya Palembang Indonesia Intelligent System Research Group Universitas Sriwijaya Palembang Indonesia Faculty of Medicine Universitas Sriwijaya Palembang Indonesia

Although deep learning has resulted in tremendous success for image classification processing, speech processing, and video detection processing applications in recent years, most of the training uses sub-optimal hyperparameters, requiring unnecessarily long training time. The Setting hyperparameters remains a black box which requires considerable experience to acquire. This study proposes several efficient ways to adjust hyperparameters that significantly reduce training time and improve model performance. Hyperparameters are used for the classification of arrhythmias. Classification is used for 16 classes that get an accuracy value 98.88%. Apart from tuning learning rate and batch size, this research also tried several scenarios of optimizer, ratio training set, validation set, and testing set; where the ratio 70 : 10 : 20 makes a significant contribution to the accuracy value.

关键词：

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Renewable Energy Generation Forecasting on Smart Home Micro Grid using Deep Neural Network

Renewable Energy Generation Forecasting on Smart Home Micro ...

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2021 International Conference on Artificial Intelligence and Mechatronics Systems, AIMS 2021

作者： Purwanto Hermawan Suherman Widodo, Djoko Adi Iksan, Nur School of Postgraduates Studies Universitas Diponegoro Doctoral Program of Environmental Science Faculty of Engineering Department of Chemical Engineering Semarang Indonesia Universitas Negeri Semarang Faculty of Engineering Department of Electrical Engineering Semarang Indonesia

ISBN: (纸本)9781665424820

The implementation of smart grid on a micro scale in this study was for household electricity fulfillment needs. The use of renewable energy sources such as solar power will be integrated through a smart grid so that households can become independent in providing electricity and not depend on state electricity. Besides, it can also reduce monthly electricity costs when integrated with the state electricity network. Smart Micro Grid also enables the availability of energy management services such as monitoring, prediction, forecasting, scheduling and decision-making that was supported by some technologies such as artificial intelligent, smart sensors so that consumer use of electricity was more efficient. In this research, the forecasting method developed using the Deep Neural Network (DNN) and the Gate Recurrent Unit (GRU) as the architectural model. The GRU model was chosen because it has better performance compared to other models, namely LSTM, Auto-LSTM, Auto-GRU with MAE and MSE values of 0.0342 and 0.00245. © 2021 IEEE.

关键词： Forecasting

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Hand-Woven Fabric Motif Recognition Methods: A Systematic Literature Review 3

Hand-Woven Fabric Motif Recognition Methods: A Systematic Li...

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3rd International Conference on Informatics, Multimedia, Cyber, and Information System, ICIMCIS 2021

作者： Noprisson, Handrie Ermatita, Ermatita Abdiansah, Abdiansah Ayumi, Vina Purba, Mariana Utami, Marissa Universitas Sriwijaya Doctoral Program in Engineering Palembang Indonesia Universitas Sriwijaya Faculty of Computer Science Palembang Indonesia Program of Informatics Management Politeknik Anika Palembang Indonesia Muhammadiyah University of Bengkulu Faculty of Engineering Bengkulu Indonesia

ISBN: (纸本)9781665427333

Knowledge of hand-woven motif recognition is only owned by the older generation, which has not been passed down to the younger generation. Moreover, computer technology can be used to support the recognition of traditional woven fabric motifs. The aim of this research is to conduct a literature review on hand-woven fabric motif recognition, with an emphasis on performance accuracy, techniques, and datasets utilized. This research included three distinct stages of systematic literature review (SLR): planning, execution, and reporting of findings. We found several datasets between 924,845 data and the number of classes between 3-25 class. Based on research result, we obtained several methods for hand-woven fabric motif recognition focused on performance examination. We recommended image pre-processing method, including Adaptive Filtering Denoising, Adaptive Wiener Filtering, Histogram Equalization, Gradient Pyramid (GP) Decomposition. Moreover, we suggested five feature extraction methods, including Radon Transform, Wavelet Transform, Locally Rotation Invariance Measure (LBP-ROR), Transform Invariant Low-Rank Textures (TILT) and Histogram of Oriented Gradients (HOG). For learning method, we recommend Fuzzy C-Mean (FCM), Convolutional neural network (CNN), Deep Neural Network (DNN), MobileNets, Inception-v3 and ResNet-50. © 2021 IEEE.

关键词： Weaving

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Examining the Usability and Security Features of Smart Farm IoT Systems

Examining the Usability and Security Features of Smart Farm ...

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2023 International Conference on Power Energy, Environment and Intelligent Control, PEEIC 2023

作者： Khawale, Vijay R. Fidvi, Huzaifa A. Shamout, Mohamed Dawood Nama, Gigih Forda Anute, Nilesh Limbore, Nilesh Yeshwantrao Chavan College of Engineering Mechanical Department Nagpur India Anjuman College of Engineering and Technology Mechanical Engineering Sadar Maharashtra Nagpur India College of Business Administration University of Sharjah Department of Management Sharjah United Arab Emirates University of Lampung Department of Informatics Doctoral Program of Environtmental Science Bandar Lampung Indonesia ASM's Institute of Business Management and Research Pune India Sharadchandra Pawar Institute of Management and Research Pune India

ISBN: (纸本)9798350357769

Using the net of factors (IoT) technology has led to a resurgence in improving intelligent farms. The capacity to music and reveal crops, animals, and different farm activities has advanced the performance of farming operations. Clever farms enjoy the blessings of connectivity, allowing farmers to be more informed and higher prepared for any ability issues. This increased connectivity has also opened the door for new security problems. This paper looks at intelligent farm IoT structures' usability and safety features. The paper investigates the overall protection levels of the systems and the various security measures that may be implemented as an excellent way to discover and guard in opposition to ability threats. It also evaluates the usability of the structures and assesses the extent of convenience it offers for agriculture employees. The paper also evaluates the present-day enterprise tendencies in IoT protection, value, and potential future trends. Ultimately, the paper gives insights into modern and future security and usability measures that may be taken to ensure the protection and effectiveness of clever farm IoT systems. The paper examines the usability and protection capabilities of innovative Farm Internet of Things (IoT) structures, which provide farmers with the potential to monitor, manipulate, and control various farm elements remotely. Usability functions consisting of user interfaces, device connectivity, and communication protocols are analyzed to evaluate how user-friendly the device is. Additionally, safety functions consisting of authentication, authorization, encryption, and getting entry to manage are tested to decide how the gadget can defend the statistics and assets of the farm. Moreover, this paper touches upon the contemporary and destiny-demanding situations related to those structures, including scalability, cost, and privacy. ultimately, the paper concludes with a comprehensive assessment of the usability and security functions and

关键词： ability implemented increased intelligent opposition

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