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Fostering firm innovativeness:Understanding the sequential relationships between human resource practices,psychological empowerment,innovative work behavior,and firm innovative capability

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International Journal of Innovation Studies 2024年第1期8卷 76-91页

作者： Ruba Sami Al Daboub Amro Al-Madadha Ahmad Samed Al-Adwan business administration department Princess Sumaya University for TechnologyAmmanJordan department of business Technology Business SchoolHourani Center for Applied Scientific ResearchAl-Ahliyya Amman UniversityAmmanJordan

This study investigated the relationships between human resource(HR)practices,employee psychological empowerment,employee innovative work behavior,and firm innovation capability in the context of the Information and Communication Technology(ICT)sector in *** the Social Exchange Theory(SET)as a guiding framework,this study explored how employee psychological empowerment and innovative work behavior mediated the influence of HR practices on a firm’s innovative *** on extensive data collected from ICT organizations in Jordan,our analysis had several key findings.A significant positive correlation between HR practices and psychological empowerment was *** design emerged as the most influential factor affecting psychological empowerment,whereas compensation had a weaker ***,we established that psychological empowerment significantly enhanced innovative work behavior,underscoring its role as a catalyst for innovative work behavior within the ***,our study supported the theory that psychological empowerment influenced a firms’innovation capabilities,emphasizing the pivotal role of employee empowerment in driving firm-level innovation in the Jordanian ICT *** findings provide insights for academic and practical audiences,clarifying how HR practices,employee psychological empowerment,and innovative work behavior collectively influenced firm innovation capability within the unique context of the Jordanian ICT sector.

关键词： Human resources practices Psychological empowerment Innovative work behavior Firm innovative capability Social exchange theory Job design

Risk-Averse Two-Stage Distributionally Robust Economic Dispatch Model Under Uncertain Renewable Energy

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CSEE Journal of Power and Energy Systems 2024年第4期10卷 1514-1524页

作者： Ce Yang Weiqing Sun Jiannan Yang Dong Han department of Control Science and Engineering University of Shanghai for Science and TechnologyShanghai 200093China department of Electrical Engineering University of Shanghai for Science and TechnologyShanghai 200093China School of Economics and business administration Chongqing UniversityChongqing 400044China

With the participation of large quantities of renewable energy in power system operations,their volatility and intermittence increases the difficulties and challenges of power system economic *** the uncertainty of renewable energy generation,based on the distributionally robust optimization method,a two-stage economic dispatch model is proposed to minimize the total operation *** this paper,it is assumed that the fluctuating of renewable power generation follows the unknown probability distribution that is restricted in an ambiguity set,which is established by utilizing the first-order moment information of available historical ***,the theory of conditional value-at-risk is introduced to transform the model into a tractable model,which we call robust counterpart *** on the stochastic dual dynamic programming method,an improved iterative algorithm is proposed to solve the robust counterpart ***,the convergence optimum can be obtained by the improved iterative algorithm,which performs a forward pass and backward pass repeatedly in each iterative ***,by comparing with other methods,the results on the modified IEEE 6-bus,118-bus,and 300-bus system show the effectiveness and advantages of the proposed model and method.

关键词： Energy and reserve co-dispatch distributionally robust conditional value-at-risk stochastic dual dynamic programming

The future of competitive advantage in Oman: Integrating green product innovation, Al, and intellectual capital in business strategies

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International Journal of Innovation Studies 2024年第2期8卷 154-171页

作者： Fadi Abdelfattah Mohammed Salah Khalid Dahleez Riyad Darwazeh Hussam Al Halbusi Modern College of business and Science(MCBS) MuscatOman Dean College of business administration A'Sharqiyah UniversityIbraOman Head of Accounting department Business SchoolAl-Ahliya Amman UniversityAmmanJordan Management department Ahmed Bin Mohammed Military College(ABMMC)DohaQatar

This study delves into the dynamics of green product innovation,artificial intelligence(Al)adaption,and intellectual capital,investigating their impact on the competitiveness of firms in *** emphasizes the crucial role of government intervention and R&D investments in this *** on the responses of 214 top managers in Oman,the research employs structural equation modeling to analyze the intricate relationships between these *** findings underscore a significant positive correlation between green innovation,Al implementation,and intellectual capital,with government involvement and R&D investments as vital *** study provides a novel perspective on the synergy of technology,innovation,and intellectual capital in developing *** offers essential insights for business leaders,policymakers,and scholars,highlighting the necessity of integrating advanced technologies and sustainable practices in business strategies to achieve competitive *** research adds to the existing body of knowledge on innovation and *** offers practical implications for enhancing firm performance in Oman and similar emerging markets.

关键词： Green product innovation R&D investments AI adoption Intellectual capital Government involvement Knowledge-driven culture Oman

Application of Pomegranate Rind Extract for Improvement of Functional Properties of Various Materials—A Critical Review

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Open Journal of Composite Materials 2024年第2期14卷 71-90页

作者： Habeebunissa Nooman Narayanan Gokarneshan Murugan Umamaheswari Muthumani Dhiliphan Kumar Usha Kumari Ratna Jayagopal Lavanya Senthamarai Kannan Umamageshwari Sona Mohandas Anton Zahurudeen Shahanaz Venkatesan Sathya David Piriadarshani Chokkanathan Kayalvizhi department of Knitwear Design National Institute of Fashion Technology Chennai India department of Textile Chemistry SSM College of Engineering Komarapallayam India department of Management Studies Dr. SNS Rajalakshmi College of Arts and Science Coimbatore India department of business administration Kalasalingam Business School Kalasalingam Academy of Research and Education Srivilliputhur India department of Textiles and Clothing Avinashi Lingam Institute for Home Science and Higher Education for Women Coimbatore India department of fashion Design SRM Institute of Science and Technology (Kattankalathur) Chennai India department of fashion Design Hindustan Institute of Technology and Science Chennai India department of fashion Design SRM Institute of Science and Technology (Ramapuram) Chennai India department of Mathematics Hindustan Institute of Technology and Science Chennai India department of Textile Technology Jaya Engineering College Tiruninravur India

Pomegranate rind is abundantly available as a waste material. Pomegranate Rind Extract (PRE) can be applied to cotton fabrics for its natural colours, as a mordanting agent and also for imparting certain functional properties such as fire retardancy and antimicrobial properties. This paper reviews the feasibility of Pomegranate Rind Extract to improve the functional properties of cellulosic fabrics. Studies show that varying concentrations and higher temperatures that were used to apply the extract on the fabric, resulted in enhanced functional properties. At a particular concentration, the treated fabric showed a 15 times lower burning rate in comparison with the control fabric. Also, antimicrobial efficacy has been observed against Gram-positive and Gram-negative bacteria. Due to the natural colouring material, it can be used as a natural dye on cotton material. The fire retardancy of pomegranate rind extract was tested on jute material under varying alkalinity. Research has indicated that pomegranate rind extract could be used to dye polyamide as well. The rubbing and wash fastness of the finished fabrics is good. The light fastness was fair, and its antibacterial efficiency against tested bacteria was good.

关键词： Natural Polymers Synthetic Polymers Pomegranate Rind Extract (PRE) Dyeing Functional Property

Improving Supply Chain Strategies towards Mitigating the Effect of Crude Oil Theft and Pipeline Vandalism in the Nigerian Oil and Gas Industry: A Case Study of the Nigerian National Petroleum Corporation (NNPC)

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Open Journal of Yangtze Oil and Gas 2024年第3期9卷 75-93页

作者： Ruth Agwom Panle department of business administration Faculty of Management Sciences University of Jos Jos Nigeria.

Generically, SCM may be said to include all activities carried out to ensure proper functioning of the supply chain. The activities included in proper management of a supply chain broadly include logistics activities, planning and control of the flow of information and materials in a firm, management of relationships with other organizations and government intervention, However, crude oil theft and pipeline vandalism are established products supply chain disruptors in Nigeria which are rendering the task of running an efficient petroleum supply chain onerous. This paper aims to establish the importance of effective supply chain strategies for companies in the oil and gas industry with special focus on the Nigerian oil and gas sector and the strategies by which the state oil and gas corporation in this sector may mitigate disruptions to its supply chain. This study investigates the enhancement of supply chain strategies towards meeting the challenge of crude oil theft and pipeline vandalism, using the Nigerian National Corporation (NNPC) as a case study. Based on this study, data were collected from two sources: A summary of incident reports obtained from NNPC and an interview with personnel in the PPMC department. Incident report refers to a report produced when accidents such as equipment failure, injury, loss of life, or fire occur at the work site. Content analysis is utilized to evaluate data obtained from interview responses, CBN financial stability reports, NDIC annual reports, circulars, banking supervision reports and implementation guidelines. The study found out that NNPC should endeavor to sustain its value chain and ward of pipeline vandals and crude oil thieves by engaging in community partnership, detailing security outfits to ensure its pipelines’ right of way and bridging. Concluded that the oil supply chain of the Nigerian National Petroleum Corporation has been plagued by disruptions in the form of crude oil theft and pipeline vandalism which has h

关键词： Supply Chain Strategies Management Production Crude Oil Theft Pipeline Vandalism Information Technology Operations

A Dimensional Reduction Approach Based on Essential Constraints in Linear Programming

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American Journal of Operations Research 2024年第1期14卷 1-31页

作者： Eirini I. Nikolopoulou George S. Androulakis department of Mathematics University of Patras Patras Greece department of business administration University of Patras Patras Greece

This paper presents a new dimension reduction strategy for medium and large-scale linear programming problems. The proposed method uses a subset of the original constraints and combines two algorithms: the weighted average and the cosine simplex algorithm. The first approach identifies binding constraints by using the weighted average of each constraint, whereas the second algorithm is based on the cosine similarity between the vector of the objective function and the constraints. These two approaches are complementary, and when used together, they locate the essential subset of initial constraints required for solving medium and large-scale linear programming problems. After reducing the dimension of the linear programming problem using the subset of the essential constraints, the solution method can be chosen from any suitable method for linear programming. The proposed approach was applied to a set of well-known benchmarks as well as more than 2000 random medium and large-scale linear programming problems. The results are promising, indicating that the new approach contributes to the reduction of both the size of the problems and the total number of iterations required. A tree-based classification model also confirmed the need for combining the two approaches. A detailed numerical example, the general numerical results, and the statistical analysis for the decision tree procedure are presented.

关键词： Linear Programming Binding Constraints Dimension Reduction Cosine Similarity Decision Analysis Decision Trees

LSTM Based Neural Network Model for Anomaly Event Detection in Care-Independent Smart Homes

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Computer Modeling in Engineering & Sciences 2024年第9期140卷 2689-2706页

作者： Brij B.Gupta Akshat Gaurav Razaz Waheeb Attar Varsha Arya Ahmed Alhomoud Kwok Tai Chui department of Computer Science and Information Engineering Asia UniversityTaichung413Taiwan Symbiosis Centre for Information Technology(SCIT) Symbiosis International UniversityPune411057India Center for Interdisciplinary Research University of Petroleum and Energy Studies(UPES)Dehradun248007India Computer Engineering Ronin InstituteMontclairNJ 07043USA Management department College of Business AdministrationPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia department of business administration Asia UniversityTaichung413Taiwan department of Electrical and Computer Engineering Lebanese American UniversityBeirut1102Lebanon department of Computer Sciences Faculty of Computing and Information TechnologyNorthern Border UniversityRafha91911Saudi Arabia School of Science and Technology Hong Kong Metropolitan University(HKMU)Hong Kong

This study introduces a long-short-term memory(LSTM)-based neural network model developed for detecting anomaly events in care-independent smart homes,focusing on the critical application of elderly fall *** balances the dataset using the Synthetic Minority Over-sampling Technique(SMOTE),effectively neutralizing bias to address the challenge of unbalanced datasets prevalent in time-series classification *** proposed LSTM model is trained on the enriched dataset,capturing the temporal dependencies essential for anomaly *** model demonstrated a significant improvement in anomaly detection,with an accuracy of 84%.The results,detailed in the comprehensive classification and confusion matrices,showed the model’s proficiency in distinguishing between normal activities and *** study contributes to the advancement of smart home safety,presenting a robust framework for real-time anomaly monitoring.

关键词： LSTM neural networks anomaly detection smart home health-care elderly fall prevention

Phishing Attacks Detection Using EnsembleMachine Learning Algorithms

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Computers, Materials & Continua 2024年第7期80卷 1325-1345页

作者： Nisreen Innab Ahmed Abdelgader Fadol Osman Mohammed Awad Mohammed Ataelfadiel Marwan Abu-Zanona Bassam Mohammad Elzaghmouri Farah H.Zawaideh Mouiad Fadeil Alawneh department of Computer Science and Information Systems College of Applied SciencesAlmaarefa UniversityDiriyahRiyadh13713Saudi Arabia Applied College King Faisal UniversityAl-Ahsa31982Saudi Arabia department of Management Information Systems College of Business AdministrationKing Faisal UniversityAl-Ahsa31982Saudi Arabia department of Computer Science Faculty of Computer Science and Information TechnologyJerash UniversityJerash26110Jordan department of business Intelligence and Data Analysis Faculty of Financial Sciences and BusinessIrbid National UniversityIrbid21110Jordan Faculty of Information Technology Ajloun National UniversityAjloun26767Jordan

Phishing,an Internet fraudwhere individuals are deceived into revealing critical personal and account information,poses a significant risk to both consumers and web-based *** indicates a persistent rise in phishing ***,these fraudulent schemes are progressively becoming more intricate,thereby rendering them more challenging to ***,it is imperative to utilize sophisticated algorithms to address this *** learning is a highly effective approach for identifying and uncovering these harmful *** learning(ML)approaches can identify common characteristics in most phishing *** this paper,we propose an ensemble approach and compare it with six machine learning techniques to determine the type of website and whether it is normal or not based on two phishing *** that,we used the normalization technique on the dataset to transform the range of all the features into the same *** findings of this paper for all algorithms are as follows in the first dataset based on accuracy,precision,recall,and F1-score,respectively:Decision Tree(DT)(0.964,0.961,0.976,0.968),Random Forest(RF)(0.970,0.964,0.984,0.974),Gradient Boosting(GB)(0.960,0.959,0.971,0.965),XGBoost(XGB)(0.973,0.976,0.976,0.976),AdaBoost(0.934,0.934,0.950,0.942),Multi Layer Perceptron(MLP)(0.970,0.971,0.976,0.974)and Voting(0.978,0.975,0.987,0.981).So,the Voting classifier gave the best *** in the second dataset,all the algorithms gave the same results in four evaluation metrics,which indicates that each of them can effectively accomplish the prediction ***,this approach outperformed the previous work in detecting phishing websites with high accuracy,a lower false negative rate,a shorter prediction time,and a lower false positive rate.

关键词： Social engineering attacks phishing attacks machine learning security artificial intelligence

Posture Detection of Heart Disease Using Multi-Head Attention Vision Hybrid(MHAVH)Model

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Computers, Materials & Continua 2024年第5期79卷 2673-2696页

作者： Hina Naz Zuping Zhang Mohammed Al-Habib Fuad A.Awwad Emad A.A.Ismail Zaid Ali Khan School of Computer Science and Engineering Central South UniversityChangsha410003China department of Quantitative analysis College of Business AdministrationKing Saud UniversityP.O.Box 71115Riyadh11587Saudi Arabia Electrical and Computer Engineering University of VictoriaVictoriaV9A1B8Canada

Cardiovascular disease is the leading cause of death *** disease causes loss of heart muscles and is also responsible for the death of heart cells,sometimes damaging their functionality.A person’s life may depend on receiving timely assistance as soon as ***,minimizing the death ratio can be achieved by early detection of heart attack(HA)*** the United States alone,an estimated 610,000 people die fromheart attacks each year,accounting for one in every four ***,by identifying and reporting heart attack symptoms early on,it is possible to reduce damage and save many lives *** objective is to devise an algorithm aimed at helping individuals,particularly elderly individuals living independently,to safeguard their *** address these challenges,we employ deep learning *** have utilized a vision transformer(ViT)to address this ***,it has a significant overhead cost due to its memory consumption and computational complexity because of scaling dot-product ***,since transformer performance typically relies on large-scale or adequate data,adapting ViT for smaller datasets is more *** response,we propose a three-in-one steam model,theMulti-Head Attention Vision Hybrid(MHAVH).Thismodel integrates a real-time posture recognition framework to identify chest pain postures indicative of heart attacks using transfer learning techniques,such as ResNet-50 and VGG-16,renowned for their robust feature extraction *** incorporatingmultiple heads into the vision transformer to generate additional metrics and enhance heart-detection capabilities,we leverage a 2019 posture-based dataset comprising RGB images,a novel creation by the author that marks the first dataset tailored for posture-based heart attack *** the limited online data availability,we segmented this dataset into gender categories(male and female)and conducted testing on both segmented and original dat

关键词： Image analysis posture of heart attack(PHA)detection hybrid features VGG-16 ResNet-50 vision transformer advance multi-head attention layer