Calls for Papers (special): Journal of Organizational and End User Computing (JOEUC)


Special Issue On: Secure Smart Solutions for Organizational and End User Computing

Submission Due Date
12/31/2021

Guest Editors
Dr. Sang-Bing Tsai, School of Business, Wuyi University
sangbing@hotmail.com
Dr. Xiaochun Cheng, Middlesex University, UK
xiaochun.cheng@gmail.com
Dr. Yu-Hsi Yuan, Chinese Culture University, Taiwan
yuanyh@gm.ypu.edu.tw

Introduction
Journal of Organizational and End User Computing” attracts the state of art in organizational computing and end user computing. Due to epidemic spreading of COVID-19, many companies have to stop old fashioned face to face team working and face to face service to clients. While each employee is working remotely from home, or the client is served through a networked computer or mobile device, secure smart solutions for organizational data or for end user data processing are important for data driven business decision making, which can avoid epidemic spreading of the contagious virus, save some travel and traffic, hence reduce usage of petrol and air pollution; which is important for sustainable development of environment and economy in the long run.

Objective
The main goal of the proposed special issue is to attract the most recent innovative secure smart solutions for organizational computing and end user computing in Covid-19 epidemic environment, to support remote working team members and clients being connected through available cabled or wireless networks. The focus on security is to meet the need to keep the organizational secrets and to protect the individual privacy for such emerging decentralized working and service modality. We want to best support diverse needs, personalized requirements, different organizational and users constraints with available limited communication and computing facilities, hence a range of smart solutions can be applied to optimize the infrastructural communication and computing services, to most effectively support distributed co-workers and clients.

Recommended Topics
• Secure Smart Organizational or End User Computing Solutions for Medical Healthcare
• Secure Smart Organizational or End User Computing Solutions for Crowd Sourcing
• Secure Smart Organizational or End User Computing Solutions for Mobile Shopping
• Secure Smart Organizational or End User Computing Solutions for Delivery Transportation
• Secure Smart Organizational or End User Computing Solutions for E-government
• Secure Smart Organizational or End User Computing Solutions for Finance Service
• Secure Smart Organizational or End User Computing Solutions for Fighting Crimes / Frauds
• Secure Smart Organizational or End User Computing Solutions for Emergency Response
• Secure Smart Organizational or End User Computing Solutions for Education
• Secure Smart Computing Solutions for Geoscience and Earth Science
• Secure Smart Computing Solutions for Environment Protection
• Secure Smart Computing Solutions for Weather Forecast

Submission Procedure
Researchers and practitioners are invited to submit papers for this special theme issue on Secure Smart Solutions for Organizational and End User Computing on or before December 31, 2021. All submissions must be original and may not be under review by another publication. INTERESTED AUTHORS SHOULD CONSULT THE JOURNAL’S GUIDELINES FOR MANUSCRIPT SUBMISSIONS at http://www.igi-global.com/publish/contributor-resources/before-you-write/. All submitted papers will be reviewed on a double-blind, peer review basis. Papers must follow APA style for reference citations.

All inquiries should be directed to the attention of:
Dr. Xiaochun Cheng
Guest Editor
Journal of Organizational and End User Computing
xiaochun.cheng@gmail.com

Special Issue On: Human Capital and Technology Application Interaction by Practical Data Mining: Theory, Application, and Management

Submission Due Date
5/31/2022

Guest Editors
Yu-Hsi Yuan, Department of Labor and Human Resources, Chinese Culture University, Taiwan
Jie Zhou, College of Tourism and Service Management, Nankai University, China
Ching-Wen Pai, Department of Labor and Human Resources, Chinese Culture University, Taiwan
Wei Liu, University of Sydney, Australia
Chia-Hui Liu, Department of Applied Mathematics, Chinese Culture University, Taiwan

Introduction
Relay on the society growth, technology such as Artificial Intelligence, Internet of Things, Big Data, Block-chain, and Cloud Computing is developing accordingly. However, technology development dependents on the talents' cultivation. The strength of technology is the ability of data collection, data management, data process, and data analysis. The feature of big data is high volume, high velocity, and/or high variety. Therefore, it needs a whole new methodology to deal with. Meanwhile, the big data was changing dynamically, thus, it required advantage technology and specified technique or integrated them to discover the multiple, comprehensive, and huge contents of the data. Therefore, the current challenge of the global issue to be identified into three dimensions as industrial structure, human resource transform, and learning model. It focused on the vary challenging issues which involved environmental changes and emerging technologies. That will change the human’s thoughts, lifestyle, and behavior patterns. Hence, the international society must face those challenges directly. And people should develop cross-field integrated solutions by aware of the future changing trends in all perspective levels. On the other hand, the industry needs the assistance of humanities talents to contribute their through, value, belief, and responsibility to enhance human capital in the technology era. Under the demands of the new economic style trend to the talents, it is necessary to prepare and upgrade the human capital by cultivating the professional and humanity talents to promote technology development. In this situation, it is required cross-field cooperation to balance the development between technology, society, and humanity in problem identification, technology development feature and main strain, and social needs. The government shall provide a foresight, cross-field, integrate, apply, practice, and good comprehensive judgment technology development and talent cultivation plan for next generation. Furthermore, it is argued that artificial intelligence is creating job opportunities or seize it was still debating by encomiasts and technicians. Further, the education system should be well prepared for future talents’ cultivation and reform the curriculum, teacher, teaching method, material, and assessment of learning outcome to comply with emerging technology development. Besides, during the COVID-19 pandemic, however, technology plays an essential role in social work and economic operation. Thus, as e-learning, e-commerce, share economics, social media platform, and e-marketing are rising by information and communication technology.

Recommended Topics
  • Technology talent cultivation
  • Technology education
  • Technology toward enterprises’ cost
  • Technology management
  • Industry-changing
  • Technology application


Submission Procedure
Researchers and practitioners are invited to submit papers for this special theme issue on Human Capital and Technology Application Interaction by Practical Data Mining: Theory, Application, and Management on or before May 31st, 2022. All submissions must be original and may not be under review by another publication. INTERESTED AUTHORS SHOULD CONSULT THE JOURNAL’S GUIDELINES FOR MANUSCRIPT SUBMISSIONS at http://www.igi-global.com/publish/contributor-resources/before-you-write/. All submitted papers will be reviewed on a double-blind, peer review basis. Papers must follow APA style for reference citations.

All inquiries should be directed to the attention of:
Yu-Hsi Yuan
Jie Zhou
Ching-Wen Pai
Wei Liu
Chia-Hui Liu
Guest Editors
Journal of Organization End User Computing (JOEUC)
Email: yuanyh@gm.ypu.edu.tw; zhouj@nankai.edu.cn; bjw@faculty.pccu.edu.tw; wei.liu2@sydney.edu.au; ljh34@ulive.pccu.edu.tw

Special Issue On: DEEP UNSUPERVISED LEARNING FOR DISTRIBUTED NEURAL END USER COMPUTING

Submission Due Date
7/10/2022

Guest Editors
Dr. Nagaraj Balakrishnan, Rathinam Technical Campus, India.
Dr. Raffaele Mascella, University of Teramo, Italy.
Dr. Yong Deng, University of Electronic Science and Technology of China, China.

Introduction
Data science systems are used in extracting knowledge and information that gives insight to the core of structured and unstructured data (which is collected in massive quantity). It uses scientific methods and algorithms to analyze and provide deep insights into the data. The rapid growth of fields such as industry, business, and medical, requires more such insights for further development of the situation created by COVID19 pandemic needs the most. Data science needs to be involved with techniques such as data mining, big data, and Distributed Neural Systems to get such in-depth knowledge of the fields mentioned above. In this research, the optimal usage strategy of learning algorithms, along with the clustering methodologies, is addressed for unsupervised data classification applications. Data classification is the process of categorizing the given dataset or a feature for applications like computer vision, medical diagnosis, etc. The data classification is analyzed, and the decisions are made based on the assessment of the data. The techniques such as SVM (Support Vector Machine), linear regression, feature vectors are used for the application of data classification. During the past decade, the Distributed Neural algorithm plays a significant role in data science development. The Distributed Systems technique generates a non-linear logic to suit real-time problems and applications by considering their uncertainty. The Distributed Systems algorithm can be broadly classified into various types, such as Supervised Learning, Unsupervised Learning, Reinforcement Learning. ANN (Artificial Neural Network) is a field of study in Distributed Systems and artificial intelligence, follows the supervised learning methodology, which is widely used in many applications. ANN algorithms are capable of scientifically learn and understand the situation with the iterative learning process organized with the help of previously generated/ collected data. On the other hand, the data mining algorithm is a field of study in Distributed Systems which follows the unsupervised learning methodology(Deep Embedded Clustering).

Objective
This special issue seeks to bring forward the research opportunities that focus on enhancing the behavior and nature of deep learning methods with the clustering neural algorithm's nature. So, that Deep Unsupervised Learning methodology based on Intelligent End user computing can be implemented and could make the system more self-analysis basis and make decisions on its own in the organizational platform.

Recommended Topics
  • Architectures for Neural Real-time sensing and intelligent preprocessing
  • Real-time Neural Signal processing based on Deep Embedded Clustering
  • Parallel and distributed Neural algorithm design and implementation
  • Neural Analytics for multi-dimension data for Cybernetics
  • The selection of suitable unsupervised learning methodologies
  • The selection of suitable and efficient Neural deep learning methodology
  • The selection of diverse datasets and problems to test and validate the research outcomes
  • The exploration of the optimal deep learning methodology for Neural data classifications
  • Traditional data generated in the past decades seeks the requirement for the modern algorithms and process segment/classification
  • An optimized strategy to implement Neural intelligent automation in analyzing data
  • The requirement of high computational power like GPU (Graphical Processing Unit)
  • Neural Adequate parameter selection to avoid overfitting or underfitting


Submission Procedure
Researchers and practitioners are invited to submit papers for this special theme issue on DEEP UNSUPERVISED LEARNING FOR DISTRIBUTED NEURAL END USER COMPUTING on or before July 20th, 2022. All submissions must be original and may not be under review by another publication. INTERESTED AUTHORS SHOULD CONSULT THE JOURNAL’S GUIDELINES FOR MANUSCRIPT SUBMISSIONS at http://www.igi-global.com/publish/contributor-resources/before-you-write/. All submitted papers will be reviewed on a double-blind, peer review basis. Papers must follow APA style for reference citations.

All inquiries should be directed to the attention of:
Dr. Nagaraj Balakrishnan.
Dr. Raffaele Mascella.
Dr. Yong Deng.
Guest Editors
Journal of Organizational and End User Computing (JOEUC)
Emails: dean.sa@rathinam.in; rmascella@unite.it; dengentropy@uestc.edu.cn

Special Issue On: Digital Information Technologies and Computing on Industrial Applications

Submission Due Date
11/30/2022

Guest Editors
Dr. Yang Gao, Dalian University of Technology, China.
Dr. Xinchun Wang, West Virginia University, United States.

Introduction
New technologies, such as big data analytics, cloud computing, network platform, and human-computer interaction, strongly influence organizational and industrial applications. These digital information and computing technologies continuously push the industrial boundaries and offer opportunities for firms to develop competitive advantage in various industrial environments. Enhanced by the digital information and computing technologies, organizations can significantly improve their intra-firm cooperation among departments and the efficiency of knowledge and resources management. For example, big data analytics provide opportunities for firms to reconfigure their customer relationship management (CRM) systems by utilizing large-scale data and thus understanding customer needs both quicker and better. The new CRM with data analytic function also improves knowledge and resources transformation within an organization. In addition, the application of artificial intelligence (AI) and machine learning enables firms to develop better learning capabilities and thus enhance their innovation performances. With the advancement of information technologies, user computing management is becoming increasingly intelligent and more efficient. As a result, organizations enjoy more flexible strategic decision-making and benefit from innovation activities across industries. Finally, the application of information technologies also enhances inter-organizational cooperation and the efficiency of supply chain management, which facilitates customer participation in various supplier activities.
Though digital information technologies and computing are becoming more important than ever before, managers still face a few critical challenges. For example, digital information technologies and computing not only provide opportunities for firms to develop competitive advantage, but also result in more uncertainties and intensified competition among firms. Moreover, recent research reports that the risk of breaking user privacy and cybersecurity significantly hinder firms’ willingness and abilities to adopt advanced information technologies.

Objective
This special issue is aimed to develop a better understanding of digital information technologies and computing, and their applications in a dynamic environment. In this special issue, we seek high quality work on the roles of digital information technologies and computing in organizations and industries. Any unpublished review articles, theoretical framework, empirical research, and other high-quality research related to the topic are welcomed.

Recommended Topics
  • The process and modes of digital information management in different industries.
  • End user computing management in different industries driven by new technologies.
  • The digital information management capability and its impact on resource management in different industries.
  • The synergy between knowledge and traditional resources enabled by digital information technologies and computing in different industries.
  • The impacts of digital information technologies and computing on innovation in different industries.
  • The users’ participation and its impact on knowledge and resource management in different industries.
  • The individual and organizational learning driven by digital information technologies and computing such as big data analytics, network platform in different industries.
  • Digital information technologies risk management in different industries.
  • The risk management of computing private and security.


Submission Procedure
Researchers and practitioners are invited to submit papers for this special theme issue on Digital Information Technologies and Computing on Industrial Applications on or before November 30, 2022. All submissions must be original and may not be under review by another publication. INTERESTED AUTHORS SHOULD CONSULT THE JOURNAL’S GUIDELINES FOR MANUSCRIPT SUBMISSIONS at http://www.igi-global.com/publish/contributor-resources/before-you-write/. All submitted papers will be reviewed on a double-blind, peer review basis. Papers must follow APA style for reference citations.

All inquiries should be directed to the attention of:
Dr. Yang Gao,
Dr. Xinchun Wang.

Guest Editors
Journal of Organizational and End User Computing (JOEUC)
Emails: gzm@dlut.edu.cn; xinchun.wang@mail.wvu.edu