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engineering & Computing Technologies (ICECT), International Conference on

作者： Inbasat Fiza Fizza Khurshid Manahil Fatima Umara Noor Zahid Rashid Department of Software Engineering Faculty of Computing and Information Technology International Islamic University Islamabad Pakistan Technology Management Economics and Policy Program College of Engineering Seoul National University Seoul South Korea

ISBN: (数字)9798350349719

ISBN: (纸本)9798350349726

The ATT&CK MITRE framework serves as an expansive repository of adversary tactics, techniques, and procedures. Given the sheer volume of these intricate attack patterns, the conventional manual navigation method proves to be time-intensive and less efficient for security analysts. As a remedy, there arises a compelling necessity to present the rich content encapsulated within the ATT&CK MITRE repository through interactive visualizations. In this paper ATT&CKViz an interactive web-based cyber-attack patterns visualization tool is presented that aims to empower security analysts with the ability to effortlessly explore the repository from diverse angles, which facilitates deep insights into cyber threats. The aim is to understand cyber threat efficiently with a timely response. The empirical evaluations depict that effectiveness and user-friendliness of ATT&CKViz.

关键词： Computers Navigation Visual analytics Manuals Cyberattack

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Unitig-centered pan-genome machine learning approach for predicting antibiotic resistance and discovering novel resistance genes in bacterial strains

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Computational and Structural Biotechnology Journal 2024年 23卷 1864-1876页

作者： Do, Duyen Thi Yang, Ming-Ren Vo, Tran Nam Son Le, Nguyen Quoc Khanh Wu, Yu-Wei Graduate Institute of Biomedical Informatics College of Medical Science and Technology Taipei Medical University Taipei Taiwan Department of Electrical Engineering National Taiwan University of Science and Technology Taipei Taiwan Department of Business Administration College of Management Lunghwa University of Science and Technology Taoyuan City Taiwan Professional Master Program in Artificial Intelligence in Medicine College of Medicine Taipei Medical University Taipei Taiwan Clinical Big Data Research Center Taipei Medical University Hospital Taipei Taiwan TMU Research Center for Digestive Medicine Taipei Medical University Taipei Taiwan

In current genomic research, the widely used methods for predicting antimicrobial resistance (AMR) often rely on prior knowledge of known AMR genes or reference genomes. However, these methods have limitations, potentially resulting in imprecise predictions owing to incomplete coverage of AMR mechanisms and genetic variations. To overcome these limitations, we propose a pan-genome-based machine learning approach to advance our understanding of AMR gene repertoires and uncover possible feature sets for precise AMR classification. By building compacted de Brujin graphs (cDBGs) from thousands of genomes and collecting the presence/absence patterns of unique sequences (unitigs) for Pseudomonas aeruginosa, we determined that using machine learning models on unitig-centered pan-genomes showed significant promise for accurately predicting the antibiotic resistance or susceptibility of microbial strains. Applying a feature-selection-based machine learning algorithm led to satisfactory predictive performance for the training dataset (with an area under the receiver operating characteristic curve (AUC) of > 0.929) and an independent validation dataset (AUC, approximately 0.77). Furthermore, the selected unitigs revealed previously unidentified resistance genes, allowing for the expansion of the resistance gene repertoire to those that have not previously been described in the literature on antibiotic resistance. These results demonstrate that our proposed unitig-based pan-genome feature set was effective in constructing machine learning predictors that could accurately identify AMR pathogens. Gene sets extracted using this approach may offer valuable insights into expanding known AMR genes and forming new hypotheses to uncover the underlying mechanisms of bacterial AMR. © 2024 The Authors

关键词： Genes

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Enhanced Dye Adsorption and Bacterial Removal of Magnetic Nanoparticle-Functionalized Bacterial Cellulose Acetate Membranes

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Journal of Renewable Materials 2024年第9期12卷 1605-1624页

作者： Heru Suryanto Daimon Syukri Fredy Kurniawan Uun Yanuhar Joseph Selvi Binoj Sahrul Efendi Fajar Nusantara Jibril Maulana Nico Rahman Caesar Komarudin Komarudin Centre of Advanced Material for Renewable Energy(CAMRY) Universitas Negeri MalangMalang65145Indonesia Department of Mechanical and Industrial Engineering Universitas Negeri MalangMalang65145Indonesia Department of Food and Agricultural Product Technology Faculty of Agricultural TechnologyAndalas UniversityPadang25163Indonesia Department of Chemistry Institut Teknologi Sepuluh NopemberSurabaya60111Indonesia Study Program of Aquatic Resources Management Faculty of Fisheries and Marine ScienceBrawijaya UniversityMalang65145Indonesia Institute of Mechanical Engineering Saveetha School of EngineeringSaveetha Institute of Medical and Technical Sciences(SIMATS)Saveetha UniversityChennai602105India Faculty of Vocational Universitas Negeri MalangMalang65145Indonesia

Utilizing biomass waste as a potential resource for cellulose production holds promise in mitigating environmental *** current study aims to utilize pineapple biowaste extract in producing bacterial cellulose acetate-based membranes with magnetic nanoparticles(Fe_(3)O_(4)nanoparticles)through the fermentation and esterification process and explore its *** bacterial cellulose fibrillation used a high-pressure homogenization procedure,and membranes were developed incorporating 0.25,0.50,0.75,and 1.0 wt.%of Fe3O4 nanoparticles as magnetic nanoparticle for *** membrane characteristics were measured in terms of Scanning Electron Microscope,X-ray diffraction,Fourier Transform Infrared,Vibrating Sample Magnetometer,antibacterial activity,bacterial adhesion and dye adsorption *** results indicated that the surface morphology of membrane changes where the bacterial cellulose acetate surface looks *** crystallinity index of membrane increased from 54.34%to 68.33%,and the functional groups analysis revealed that multiple peak shifts indicated alterations in membrane functional ***,adding Fe_(3)O_(4)-NPs into membrane exhibits paramagnetic behavior,increases tensile strength to 73%,enhances activity against *** and ***,and is successful in removing bacteria from wastewater of the river to 67.4%and increases adsorption for anionic dyes like Congo Red and Acid Orange.

关键词： Bacterial cellulose dye adsorption Fe_(3)O_(4)nanoparticles membrane pineapple waste

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Factors that Influence E-Satisfaction and Their Impact on Online Purchase Intention of Telemedicine Applications 9

Factors that Influence E-Satisfaction and Their Impact on On...

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9th IEEE International Conference on Computing, engineering and Design, ICCED 2023

作者： Gui, Anderes So, Idris Gautama Novantia, Dea Princes, Elfindah Sianipar, Nesti Fronika Haron, Hasnah Bina Nusantara University Information System Program School of Information Systems Jakarta Indonesia Bina Nusantara University Binus Business School Management Department Jakarta Indonesia Bina Nusantara University Binus Graduate Program-Master of Information Systems Management Information Systems Management Department Jakarta Indonesia Bina Nusantara University Faculty of Engineering Food Technology Department Jakarta Indonesia Universiti Sains Islam Malaysia Faculty of Economics and Muamalat Nilai Malaysia

ISBN: (纸本)9798350370126

This study embarked on a rigorous examination of the factors driving user satisfaction and usage behavior in the context of telehealth applications. Utilizing a well- structured Google Form survey, distributed through an array of social media platforms, including WhatsApp, Discord, Instagram, and Line, the research gathered 251 responses. The purposive sampling technique was employed to ensure that the data captured the experiences of individuals who had actively engaged with telehealth services. One hypothesis, relating to the influence of Online Reviews, was found to be unsupported. This surprising result suggests that, contrary to expectations, the opinions and reviews shared online do not significantly affect users' satisfaction or their behavioral decisions in the context of telehealth applications. This finding highlights the need for a more nuanced understanding of the factors influencing user preferences and choices in this rapidly evolving sector. Conversely, other hypotheses examining factors such as Social Influence, Facilitating Conditions, Perceived Reliability, Price Value, and Purchase Intention were substantiated. The positive influence of these factors on customer usage behavior underscores their significance in shaping user experiences and satisfaction within the telehealth ecosystem. Furthermore, the study posits that facilitating conditions should be closely aligned with technological advancements, as this alignment is conducive to the development of enhanced application features. This insight suggests that telehealth providers should continuously innovate and integrate advanced technologies to ensure that the facilitating conditions meet the ever-evolving needs and expectations of users. © 2023 IEEE.

关键词： Sales

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Mental Status Identification for Infertile Patients Using Artificial Intelligence Models 14th

Mental Status Identification for Infertile Patients Using Ar...

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14th International Conference on Frontier Computing, FC 2024

作者： Hsu, Hao-Siang Wang, Jong-Yi Chiou, Hai-Chi Wu, Fu-Hsing Lin, Chuen-Horng Chan, Yung‑Kuan Department of Computer Science and Information Engineering National Taichung University of Science and Technology Taichung404336 Taiwan Department of Health Services Administration China Medical University Taichung406040 Taiwan Bachelor Degree Program of Artificial Intelligence National Taichung University of Science and Technology Taichung404336 Taiwan Department of Management Information Systems National Chung-Hsing University Taichung402202 Taiwan

ISBN: (纸本)9789819623945

Infertile patients may be a high-risk group of mental disorder. The precise identification of the mental status of infertile patients can provide decision support to healthcare professionals and may be helpful in providing preventive measures accordingly. Rare studies focused on the mental status identification using artificial intelligence (AI) models for infertile people. This study aimed to precisely identify the mental status (anxiety and depression) of infertile patients using three AI models, the XGBoost, decision tree, and stacking models. The dataset, retrieved from a structured questionnaire survey in 2011, which included 400 infertility outpatients seeking reproductive treatments at three teaching hospitals in Taiwan was adopted for training and testing AI models. Aforementioned AI models were designed and reached identification performances of accuracy, precision, recall and area under ROC curve (AUC) equaling 0.75–0.82, 0.70–0.80, 0.64–0.72, and 0.64–0.72, respectively. The XGBoost model (accuracy = 0.82, precision = 0.80, recall = 0.72, and AUC = 0.72) outperformed or equaled the decision tree and stacking models in terms of accuracy, precision, recall, and AUC values. Designed AI models for mental status identification can be integrated into the clinical decision support system (CDSS) to provide the anxiety and depression group automatically. Accordingly, the worsening of infertility-related anxiety and depression can be prevented. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： artificial intelligence infertile patients Mental status identification stacking model XGBoost

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Usability Evaluation of Communication Tools Used as Remote Support in Machine Service Industry: A Comparison between Microsoft Teams and Skype 23

Usability Evaluation of Communication Tools Used as Remote S...

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6th International Conference on Computers in management and Business, ICCMB 2023

作者： Flame, Roland Ross F. Prasetyo, Yogi Tri Nadlifatin, Reny Ayuwati, Irene Dyah Persada, Satria Fadil Chuenyindee, Thanatorn School of Industrial Engineering and Engineering Management Mapúa University Manila Philippines International Bachelor Program in Engineering Yuan Ze University 135 Yuan-Tung Rd. Chung-Li32003 Taiwan Department of Information Systems Institut Teknologi Sepuluh Nopember Surabaya Indonesia Faculty of Business and Information Technology Institut Teknologi Telkom Surabaya Surabaya Indonesia Entrepreneurship Department Binus Business School Undergraduate Program Bina Nusantara University Indonesia Department of Industrial Engineering and Aviation Management Navaminda Kasatriyadhiraj Royal Air Force Academy Bangkok10220 Thailand

ISBN: (纸本)9781450398046

Due to pandemic Covid-19, there is an increase and rough transition into remote work. Communication tools/platforms are softwares used by industries to facilitate different functionalities like remote technical support and communication. Especially for service industries, coordinators and engineers adapted on using these tools to support internal and external communications. For a certain machine service company, Skype and Microsoft Teams are the main communication tools used. The objective of this study is to determine the usability/user experience of these tools of engineers and coordinators on their daily activities. System Usability Scale were used to evaluate their user experience. As interpreted using the Curved Grading Scale, only the use of Microsoft Teams of Coordinators is graded as D, and the rest are graded as F. Based on the results on the user experience of coordinators and engineers using platforms Microsoft Teams and Skype, the low scores show that they are struggling with the usability of these tools due to drastic change and adaptability and limitation of activities that these tools can only perform. © 2023 ACM.

关键词： Engineers

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Graph Convolution-Based Recurrent Encoder-Decoder for Anomaly Diagnoses in Multivariate Time-Series Data

SSRN

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SSRN 2024年

作者： Kim, Yejin Lee, Taek-Ho Jeon, Daeseong Park, HyeRim Lee, Changyong Kim, Suhyeon Lee, Junghye Department of Industrial Engineering Ulsan National Institute of Science and Technology Ulsan44919 Korea Republic of Technology Management Economics and Policy Program Institute of Engineering Research Seoul National University Seoul08826 Korea Republic of Department of Management Engineering Ulsan National Institute of Science and Technology Ulsan44919 Korea Republic of Technology Management Economics and Policy Program Seoul National University Seoul08826 Korea Republic of Department of Public Administraion Korea University Seoul02841 Korea Republic of Graduate school of Data Science Kyungpook National University Daegu41566 Korea Republic of Technology Management Economics and Policy Program & Graduate School of Engineering Practice Seoul National University Seoul08826 Korea Republic of

Detecting anomalies in multivariate time-series data is an important task in various real-world industries, but doing so is non-trivial because both the temporal dependency within the time series and correlations between multiple time series must be considered. Previous studies have only addressed one issue, resulting in limited performance. To address this, we propose a graph convolution-based recurrent encoder-decoder, called GC-RED. The model incorporates intra-dependencies and inter-correlations using a graph-construction process and an encoding-decoding process that encodes the graph with an attention-enhanced graph convolutional LSTM and then restores it. Anomaly detection and root cause identification are performed based on the reconstruction error. Considering that anomalies with various durations can occur in actual situations, the model includes a vanilla model reflecting single scales and a model reflecting multiple scales. The feasibility and usefulness of GC-RED are demonstrated by intensive experiments on several benchmark and real-world datasets with comparisons to other competitive methods. © 2024, The Authors. All rights reserved.

关键词： Anomaly detection

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Flood modeling in the Ba River basin using a coupled hydrodynamic model—MIKE FLOOD

River

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River 2024年第2期3卷 199-207页

作者： Luc Anh Tuan Can Thu Van Doan Van Binh Sameh AKantoush Tetsuya Sumi Le Van Quyen Ta Thi Huong Master Program in Water Technology Reuse&Management(with TU DarmstadtGermany)Faculty of EngineeringVietnamese–German UniversityBen Cat TownVietnam Ho Chi Minh City University of Natural Resources and Environment Ho Chi Minh CityVietnam Water Resources Research Center Disaster Prevention Research InstituteKyoto UniversityKyotoJapan VNU School of Interdisciplinary Study and Arts Cau GiayVietnam

The problem of flooding in Central Vietnam in general and the lower Ba River in particular is one of the natural disasters that frequently threatens people's lives and socioeconomic development in the ***,climate change is becoming ever more prominent and hotter,making extreme natural disasters more unusual and *** this research,MIKE-FLOOD—a model that connects a 1-dimensional(1-D)MIKE 11 Hydrodynamics(HD)model with a 2-dimensional(2-D)MIKE 21 HD model—was used to set *** model was calculated for three floods:(1)flood in October 1993,(2)flood in November 2003,and(3)flood in November 2007;these are floods with high frequency and relatively large *** results show that the 1993 flood rose and receded *** flood peak inundated an area of 22,600 ha,accounting for 52%of the natural *** flooded areas deeper than 1,2,3,4,and 5m were 16500,11,000,7000,4200,and 2200 ha,*** the center of Tuy Hoa city,the flooded area at the time of maximum water level was almost 100%.

关键词： Ba River basin coupled hydrodynamic model flooding MikeFlood model

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Determining the Significance of Two Consecutive Fiscal Years of Non-Conformance Cost Data Set in Project Execution of Smart Grid 23

Determining the Significance of Two Consecutive Fiscal Years...

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6th International Conference on Computers in management and Business, ICCMB 2023

作者： Narvas, Miller F. Prasetyo, Yogi Tri Nadlifatin, Reny Ayuwati, Irene Dyah Persada, Satria Fadil School of Industrial Engineering and Engineering Management Mapúa University Manila Philippines International Bachelor Program in Engineering Yuan Ze University 135 Yuan-Tung Rd. Chung-Li32003 Taiwan Department of Information Systems Institut Teknologi Sepuluh Nopember Surabaya Indonesia Faculty of Business and Information Technology Institut Teknologi Telkom Surabaya Surabaya Indonesia Entrepreneurship Department Binus Business School Undergraduate Program Bina Nusantara University Indonesia

ISBN: (纸本)9781450398046

Non-conformance cost is one of the key performance indicators in determining the success of executing a project. This study will substantiate the significance of two consecutive fiscal years of non-conformance cost data set in project execution of smart grid. A two-Sample T-Test was used to compare the means of two consecutive years' data sets. All the results of both fiscal years' data set were insignificant. Since it is insignificant, the best recommendation is to thoroughly review the lessons learned from the previous projects and implementation of preventive actions to mitigate or even prevent the occurrence/ reoccurrence of non-conformance and non-conformance costs. A continuous improvement in preventing failures will assure success and increase the profitability margin of the project. © 2023 ACM.

关键词： Smart power grids

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Assessment and Decision Making for Grid Connection of Photovoltaic Systems in Residential Projects in Iraq

SSRN

引用

SSRN 2023年

作者： Al-Lami, Ammar Zaidan Khalaf Koo, Yoonmo Technology Management Economics and Policy Program Graduate School of Engineering Practice Seoul National University Seoul Korea Republic of

Urban growth leads to continuous demand for energy hence a negative impact on sustainability. Energy transition plays a role in mitigating the impacts of increasing the share of renewable energy and improving energy systems. As solar energy is growing fast, this study focused on the factors that contribute to its growth in developing countries. Grid connection is a crucial in achieving the maximum benefit from the outputs of photovoltaic systems (PVs) in residential projects. This study attempts to address this gap. Iraq’s government initiatives to expand solar energy and establish new residential cities represent a promising opportunity to achieve stability in energy systems. A hybrid decision-making model, TES-AHP, was developed to select the grid connection type to accommodate the PV energy produced in residential projects depending on technical, economic, and social dimensions. The results indicate that distributed energy systems are the best option, and that social acceptance and experience of the technical staff are the most significant factors in this decision. Taking into consideration that all factors investigated in this study contribute to the success of the reforms in the energy sector, this study recommends that policymakers should initiate the expansion of solar energy installation by exploiting residential projects. © 2023, The Authors. All rights reserved.

关键词： Solar energy

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