Artificial Neural Networks (ANNs) and Machine Learning (ML) Modeling Employee Behavior with Management Towards the Economic Advancement of Workers DOI Open Access
Chulhee Lee

Sustainability, Journal Year: 2024, Volume and Issue: 16(21), P. 9516 - 9516

Published: Nov. 1, 2024

The role of employee behavior in organizations and their interaction with management is crucial advancing the economic progress workers. This study examines impact practices on organizational performance progress, using advanced artificial intelligence techniques to explore complex relationships provide evidence-based strategies for sustainable workforce development. research analyzes critical aspects such as job satisfaction, motivation, participation, communication uncover underlying mechanisms that contribute It recognizes dynamic relationship between employees management, confirming central effective leadership, communication, teamwork achieving positive results. emphasizes harmonious cooperation necessary create a favorable work environment contributes development utilizes an neural network (ANN) better understand interdependencies different parameters effects within framework this ongoing project. results existing body knowledge by providing practical implications seeking optimize employee–employer increase overall productivity. By understanding dynamics practices, can supportive maximizes potential growth. findings demonstrate accuracy over 70%, indicating enhancing satisfaction significantly improve productivity, performance.

Language: Английский

Financing and Management Strategies for Expanding Green Development Projects: A Case Study of Energy Corporation in China’s Renewable Energy Sector Using Machine Learning (ML) Modeling DOI Open Access

Chen Han,

Yang Lu

Sustainability, Journal Year: 2024, Volume and Issue: 16(11), P. 4338 - 4338

Published: May 21, 2024

This study investigates potential financing and management strategies that the Energy Corporation, a Chinese renewable energy company, could adopt in order to expand its green development projects. While China has made significant advancements energy, heavy reliance on fossil fuels necessitates shift towards more sustainable system. To analyze factors driving impeding sustainability, this article provides an overview of China’s sector policies. Through case studies Corporation other prominent companies, showcases range demonstration projects, models, technologies have accelerate growth initiatives. Recommendations from expert interviews are also provided, covering areas such as optimizing investment, monitoring distributed assets, balancing social environmental impacts. The results show can effectively develop wind, solar, efficiency projects nationwide by leveraging partnerships, utilizing bonds, employing big data platforms, engaging stakeholders, while setting sustainability benchmarks. With strategic approach, aims invest USD 1 billion over next five years, targeting capacity 5000 MW 20% reduction CO2 emissions. Achieving these goals would position companies global leaders transition energy. utilized artificial neural network (ANN) impact increasing jobs capacities emission economic growth. indicate effect reducing emissions compared capacities. When increased remained constant, substantial reductions were observed, but was only 1%. However, when there moderate increase alongside four-fold capacities, reached 4%. network’s prediction errors deemed acceptable based linear regression analysis experimental results.

Language: Английский

Citations

6
Machine Learning (ML) Modeling, IoT, and Optimizing Organizational Operations through Integrated Strategies: The Role of Technology and Human Resource Management DOI Open Access
Yixin Sun, Hoe-Kyung Jung

Sustainability, Journal Year: 2024, Volume and Issue: 16(16), P. 6751 - 6751

Published: Aug. 7, 2024

In the dynamic contemporary business environment, efficient optimization of organizational operations is crucial for companies to maintain competitiveness and secure enduring success. To achieve this goal, organizations can leverage a range elements including human resource management, Internet Things (IoT), technology, time employee training, development, customer relationship management. Enhancing through these factors offers numerous benefits such as increased productivity, cost efficiency, better decision-making, work–life balance, heightened satisfaction among employees customers, boosted revenue, improved competitiveness, sustained This research employed blended methodology, encompassing quantitative surveys qualitative interviews, explore effective application in optimizing operations. Additionally, an artificial neural network (ANN) model was utilized deepen understanding relationships between key parameters their impacts on outcomes like competitiveness. The results indicated that technology had most significant impact at 76.28%, underscoring substantial influence new technologies performance. Moreover, training management also played roles study identified various challenges implementation, resistance change employees, lack technical expertise, integration issues with legacy systems, incomplete data, along best practices overcome hurdles regular performance evaluations, robust security measures, personalized experiences. By adopting holistic approach integrates internal external factors, valuable insights seeking improve operations, enhance goals more efficiently. findings emphasize importance multifaceted strategy harnesses technological advancements propel success today’s fast-paced landscape. Further intricate interactions provide additional guidance striving long-term competitive advantages.

Language: Английский

Citations

5
Maximizing the performance of badminton athletes through core strength training: Unlocking their full potential using machine learning (ML) modeling DOI Creative Commons
Shuzhen Ma, Kim Geok Soh,

Salimah Binti Japar

et al.

Heliyon, Journal Year: 2024, Volume and Issue: 10(15), P. e35145 - e35145

Published: July 24, 2024

Language: Английский

Citations

4
A new approach to bioceramics based on tissue reaction of tricalcium phosphate for biomedical and sport applications using machine learning modeling DOI

Zhou Zilin,

Yun Xu,

Sh Baghei

et al.

Tissue and Cell, Journal Year: 2025, Volume and Issue: unknown, P. 102899 - 102899

Published: April 1, 2025

Language: Английский

Citations

0
Beyond algorithms: The human touch machine-generated titles for enhancing click-through rates on social media DOI Creative Commons
Wenyu Yang

PLoS ONE, Journal Year: 2024, Volume and Issue: 19(7), P. e0306639 - e0306639

Published: July 12, 2024

Artificial intelligence (AI) has the potential to revolutionize various domains by automating language-driven tasks. This study evaluates effectiveness of an AI-assisted methodology, called "POP Title AI Five-Step Optimization Method," in optimizing content titles on RED social media platform. By leveraging advancements natural language generation, this methodology aims enhance impact incorporating emotional sophistication and cultural proficiency, addressing existing gaps capabilities. The entails training generative models using human-authored examples that align with aspirations target audience. popular keywords derived from user searches, relevance discoverability are enhanced. Audience-centric filtering is subsequently employed further refine generated outputs. Furthermore, human oversight introduced provide essential intuition systems alone may lack. A total one thousand titles, AI, underwent linguistic engagement analyses. Qualitatively, 65% exhibited intrigue conveyed meaning comparable those humans. However, attaining full remained a challenge. Quantitatively, emphasizing curiosity contrast demonstrated positive correlations interactions, thus validating efficacy these techniques. Consequently, machine-generated achieved coherence par human-generated signifying significant progress for refinement. Nevertheless, achieving socio-cultural awareness vital match understanding across diverse contexts, presenting critical avenue future improvement methodology. Continuous can adaptability reduce subjectivity promoting flexibility instead relying solely manual reviews. As gains deeper humanity, opportunities its application industries through experiential reasoning abilities emerge. case exemplifies nurturing AI’s refining skills evolutionary process.

Language: Английский

Citations

3
Adaptive Mechanisms of Dental Pulp Stem Cells (DPSCs) in Response to Oral Disease: Evaluating Chitosan-Calcium Zirconium Nanoparticle Biomaterials for Tissue Engineering DOI

Xiao Sun,

Yu Zhang, Satoshi Fukumoto

et al.

Materials Chemistry and Physics, Journal Year: 2024, Volume and Issue: 323, P. 129610 - 129610

Published: June 13, 2024

Language: Английский

Citations

2
Investigating the impact of the internet on managing green financial innovation and improving agricultural conditions in water-scarce Asian regions using ANN modeling DOI Creative Commons

Xiaohan Sheng,

Guangmin Liu

Scientific Reports, Journal Year: 2024, Volume and Issue: 14(1)

Published: Sept. 27, 2024

Language: Английский

Citations

1
Transforming Health and Wellness: Exploring the Captivating Convergence of Rehabilitation, Exercise, and Cutting-Edge Health Gadgets in the Rapidly Evolving Tech-Driven World DOI
Yadong Chen, Wei Li,

Albę Słabi Hussam

et al.

Technology in Society, Journal Year: 2024, Volume and Issue: unknown, P. 102808 - 102808

Published: Dec. 1, 2024

Language: Английский

Citations

1
Navigating the innovation policy dilemma: How subnational governments balance expenditure competition pressures and long-term innovation goals DOI Creative Commons
Wenjuan Song, Kai Zhao

Heliyon, Journal Year: 2024, Volume and Issue: 10(15), P. e34787 - e34787

Published: July 18, 2024

In the pursuit of economic growth, role innovation has become increasingly important, posing dilemmas for subnational governments as they navigate balance between expenditure competition and long-term investments in innovation. This study aimed to investigate intricate relationship fiscal pressures goals faced by regional authorities. To achieve this, a systematic literature review was conducted, synthesizing more than 150 studies published within past 15 years. Keyword searches were conducted across multiple databases, additional scholarly articles incorporated through citation tracking. Rigorous qualitative analysis techniques, including inductive coding thematic analysis, employed distill conceptual insights from literature. The performed this reveals extensive discussions regarding influence on outcomes, encompassing wide range perspectives. potential advantages localization are emphasized some viewpoints, while others caution against risks inadequate investment. effective coordination policies levels governance maximize synergies national systems emerges complex yet crucial challenge. It is observed that collaborative networks, which facilitate knowledge exchange industrial clustering public-private linkages, play significant leveraging assets. Strategic approaches successfully with capacity development have been demonstrated leading jurisdictions. These findings highlight significance tailored policy frameworks account unique contexts each region, providing opportunities harness competitive motivations sustaining Ongoing essential strike responsiveness coherence diverse territories. offers practical guidance academic strategies align decentralized imperatives, aiming optimize prosperity creation evolving multi-level systems. By shedding light these strategies, research contributes both understandings how effectively capitalize dynamics such

Language: Английский

Citations

1
Enhancing target detection accuracy through cross-modal spatial perception and dual-modality fusion DOI Creative Commons
Ning Zhang,

Wenqing Zhu

Frontiers in Physics, Journal Year: 2024, Volume and Issue: 12

Published: June 6, 2024

The disparity between human and machine perception of spatial information presents a challenge for machines to accurately sense their surroundings improve target detection performance. Cross-modal data fusion emerges as potential solution enhance the perceptual capabilities systems. This article introduces novel method that integrates dual-modality feature coupled attention mechanisms validate improvement in performance through cross-modal fusion. proposed approach incorporates extraction multi-scale structure employing dual-flow architecture. Additionally, transformer is integrated fusion, while system optimized utilization linear combination loss functions. Experimental results demonstrate superiority our algorithm over single-modality using visible images, exhibiting an average accuracy 30.4%. Furthermore, outperforms infrared image by 3.0% comparative multimodal algorithms 3.5%. These effectiveness fusing dual-band features, significantly enhancing accuracy. adaptability robustness are showcased these results.

Language: Английский

Citations

0