Open Access. Powered by Scholars. Published by Universities.®
Physical Sciences and Mathematics Commons™
Open Access. Powered by Scholars. Published by Universities.®
- Keyword
-
- Machine learning (4)
- Algorithms (2)
- Artificial intelligence (2)
- Blockchain (2)
- Cloud computing (2)
-
- Digital triad (2)
- Digital twins (2)
- Forecasting (2)
- Internet of things (2)
- IoT (2)
- Predictive models (2)
- Software (2)
- Stock markets (2)
- Structural equation modeling (2)
- Support vector machines (2)
- AI monitoring (1)
- Affective computing (1)
- Agile software development (1)
- Agile software effort estimation (1)
- Algorithmic trading (1)
- Architecture (1)
- Artificial neural networks (1)
- Axiomatic design theory (1)
- BDA (1)
- Behavioral assessment (1)
- Bertrand model (1)
- Big data (1)
- Big data analytics (1)
- Bug fix (1)
- Bug-fixing effort estimation (1)
Articles 1 - 27 of 27
Full-Text Articles in Physical Sciences and Mathematics
Inventions In The Area Of Nanotechnologies And Nanomaterials. Part I, Leonid A. Ivanov, Li Da Xu, Zhanna V. Pisarenko, Svetlana R. Muminova, Nadezda G. Miloradova
Inventions In The Area Of Nanotechnologies And Nanomaterials. Part I, Leonid A. Ivanov, Li Da Xu, Zhanna V. Pisarenko, Svetlana R. Muminova, Nadezda G. Miloradova
Information Technology & Decision Sciences Faculty Publications
Introduction. Advanced technologies inspire people by demonstrating the latest achievements (materials, methods, systems, technologies, devices etc.) that dramatically change the world. This, first of all, concerns nanotechnological inventions designed by scientists, engineers and specialists from different countries. Main part. The article provides an abstract overview of inventions of scientists, engineers and specialists from different countries: Germany, Russia, China, USA et al. The results of the creative activity of scientists, engineers and specialists, including inventions in the field of nanotechnology and nanomaterials allow, when introduced to industry, achieving a significant effect in construction, housing and communal services, and related sectors of …
Machine-Learning-Based Vulnerability Detection And Classification In Internet Of Things Device Security, Sarah Bin Hulayyil, Shancang Li, Li Da Xu
Machine-Learning-Based Vulnerability Detection And Classification In Internet Of Things Device Security, Sarah Bin Hulayyil, Shancang Li, Li Da Xu
Information Technology & Decision Sciences Faculty Publications
Detecting cyber security vulnerabilities in the Internet of Things (IoT) devices before they are exploited is increasingly challenging and is one of the key technologies to protect IoT devices from cyber attacks. This work conducts a comprehensive survey to investigate the methods and tools used in vulnerability detection in IoT environments utilizing machine learning techniques on various datasets, i.e., IoT23. During this study, the common potential vulnerabilities of IoT architectures are analyzed on each layer and the machine learning workflow is described for detecting IoT vulnerabilities. A vulnerability detection and mitigation framework was proposed for machine learning-based vulnerability detection in …
Assessing Univariate And Multivariate Normality In Pls-Sem, Kathy Qing Ma, Weiyong Zhang
Assessing Univariate And Multivariate Normality In Pls-Sem, Kathy Qing Ma, Weiyong Zhang
Information Technology & Decision Sciences Faculty Publications
Partial least squares structural equation modeling (PLS-SEM) has gained popularity among researchers in part due to its relaxed requirement for multivariate normality. One important step in performing structural equation modeling (SEM) is to test the normality assumption. In this paper, we illustrate how to assess univariate and multivariate normality in PLS-SEM using WarpPLS.
Applications Of Blockchain In Business Processes: A Comprehensive Review, Wattana Viriyasitavat, Li Xu, Dusit Niyato, Zhuming Bi, Danupol Hoonsopon
Applications Of Blockchain In Business Processes: A Comprehensive Review, Wattana Viriyasitavat, Li Xu, Dusit Niyato, Zhuming Bi, Danupol Hoonsopon
Information Technology & Decision Sciences Faculty Publications
Blockchain (BC), as an emerging technology, is revolutionizing Business Process Management (BPM) in multiple ways. The main adoption is to serve as a trusted infrastructure to guarantee the trust of collaborations among multiple partners in trustless environments. Especially, BC enables trust of information by using Distributed Ledger Technology (DLT). With the power of smart contracts, BC enforces the obligations of counterparties that transact in a business process (BP) by programming the contracts as transactions. This paper aims to study the state-of-the-art of BC technologies by (1) exploring its applications in BPM with the focus on how BC provides the trust …
Smart Manufacturing—Theories, Methods, And Applications, Zhuming Bi, Lida Xu, Puren Ouyang
Smart Manufacturing—Theories, Methods, And Applications, Zhuming Bi, Lida Xu, Puren Ouyang
Information Technology & Decision Sciences Faculty Publications
(First paragraph) Smart manufacturing (SM) distinguishes itself from other system paradigms by introducing ‘smartness’ as a measure to a manufacturing system; however, researchers in different domains have different expectations of system smartness from their own perspectives. In this Special Issue (SI), SM refers to a system paradigm where digital technologies are deployed to enhance system smartness by (1) empowering physical resources in production, (2) utilizing virtual and dynamic assets over the internet to expand system capabilities, (3) supporting data-driven decision making at all domains and levels of businesses, or (4) reconfiguring systems to adapt changes and uncertainties in dynamic environments. …
Estimating Efforts For Various Activities In Agile Software Development: An Empirical Study, Lan Cao
Estimating Efforts For Various Activities In Agile Software Development: An Empirical Study, Lan Cao
Information Technology & Decision Sciences Faculty Publications
Effort estimation is an important practice in agile software development. The agile community believes that developers’ estimates get more accurate over time due to the cumulative effect of learning from short and frequent feedback. However, there is no empirical evidence of an improvement in estimation accuracy over time, nor have prior studies examined effort estimation in different development activities, which are associated with substantial costs. This study fills the knowledge gap in the field of software estimation in agile software development by investigating estimations across time and different development activities based on data collected from a large agile project. This …
The Effects Of Antecedents And Mediating Factors On Cybersecurity Protection Behavior, Ling Li, Li Xu, Wu He
The Effects Of Antecedents And Mediating Factors On Cybersecurity Protection Behavior, Ling Li, Li Xu, Wu He
Information Technology & Decision Sciences Faculty Publications
This paper identifies opportunities for potential theoretical and practical improvements in employees' awareness of cybersecurity and their motivational behavior to protect themselves and their organizations from cyberattacks using the protection motivation theory. In addition, it contributes to the literature by examining additional variables and mediators besides the core constructs of the Protection Motivation Model (PMT). This article uses empirical data and structural equation modeling to test the antecedents and mediators of employees' cybersecurity motivational behavior. The study offers theoretical and pragmatic guidance for cybersecurity programs. First, the model developed in this study can partially explain how people may change their …
Why Do Family Members Reject Ai In Health Care? Competing Effects Of Emotions, Eun Hee Park, Karl Werder, Lan Cao, Balasubramaniam Ramesh
Why Do Family Members Reject Ai In Health Care? Competing Effects Of Emotions, Eun Hee Park, Karl Werder, Lan Cao, Balasubramaniam Ramesh
Information Technology & Decision Sciences Faculty Publications
Artificial intelligence (AI) enables continuous monitoring of patients’ health, thus improving the quality of their health care. However, prior studies suggest that individuals resist such innovative technology. In contrast to prior studies that investigate individuals’ decisions for themselves, we focus on family members’ rejection of AI monitoring, as family members play a significant role in health care decisions. Our research investigates competing effects of emotions toward the rejection of AI monitoring for health care. Based on two scenario-based experiments, our study reveals that emotions play a decisive role in family members’ decision making on behalf of their parents. We find …
The State Of The Art Of Information Integration In Space Applications, Zhuming Bi, K. L. Yung, Andrew W.H. Ip., Yuk Ming Tang, Chris W.J. Zhang, Li Da Xu
The State Of The Art Of Information Integration In Space Applications, Zhuming Bi, K. L. Yung, Andrew W.H. Ip., Yuk Ming Tang, Chris W.J. Zhang, Li Da Xu
Information Technology & Decision Sciences Faculty Publications
This paper aims to present a comprehensive survey on information integration (II) in space informatics. With an ever-increasing scale and dynamics of complex space systems, II has become essential in dealing with the complexity, changes, dynamics, and uncertainties of space systems. The applications of space II (SII) require addressing some distinctive functional requirements (FRs) of heterogeneity, networking, communication, security, latency, and resilience; while limited works are available to examine recent advances of SII thoroughly. This survey helps to gain the understanding of the state of the art of SII in sense that (1) technical drivers for SII are discussed and …
Image Source Identification Using Convolutional Neural Networks In Iot Environment, Yan Wang, Qindong Sun, Dongzhu Rong, Shancang Li, Li Da Xu
Image Source Identification Using Convolutional Neural Networks In Iot Environment, Yan Wang, Qindong Sun, Dongzhu Rong, Shancang Li, Li Da Xu
Information Technology & Decision Sciences Faculty Publications
Digital image forensics is a key branch of digital forensics that based on forensic analysis of image authenticity and image content. The advances in new techniques, such as smart devices, Internet of Things (IoT), artificial images, and social networks, make forensic image analysis play an increasing role in a wide range of criminal case investigation. This work focuses on image source identification by analysing both the fingerprints of digital devices and images in IoT environment. A new convolutional neural network (CNN) method is proposed to identify the source devices that token an image in social IoT environment. The experimental results …
Stock Trend Prediction Using Candlestick Charting And Ensemble Machine Learning Techniques With A Novelty Feature Engineering Scheme, Yaohu Lin, Shancun Liu, Haijun Yang, Harris Wu
Stock Trend Prediction Using Candlestick Charting And Ensemble Machine Learning Techniques With A Novelty Feature Engineering Scheme, Yaohu Lin, Shancun Liu, Haijun Yang, Harris Wu
Information Technology & Decision Sciences Faculty Publications
Stock market forecasting is a knotty challenging task due to the highly noisy, nonparametric, complex and chaotic nature of the stock price time series. With a simple eight-trigram feature engineering scheme of the inter-day candlestick patterns, we construct a novel ensemble machine learning framework for daily stock pattern prediction, combining traditional candlestick charting with the latest artificial intelligence methods. Several machine learning techniques, including deep learning methods, are applied to stock data to predict the direction of the closing price. This framework can give a suitable machine learning prediction method for each pattern based on the trained results. The investment …
Generic Design Methodology For Smart Manufacturing Systems From A Practical Perspective, Part I—Digital Triad Concept And Its Application As A System Reference Model, Zhuming Bi, Wen-Jun Zhang, Chong Wu, Chaomin Luo, Lida Xu
Generic Design Methodology For Smart Manufacturing Systems From A Practical Perspective, Part I—Digital Triad Concept And Its Application As A System Reference Model, Zhuming Bi, Wen-Jun Zhang, Chong Wu, Chaomin Luo, Lida Xu
Information Technology & Decision Sciences Faculty Publications
Rapidly developed information technologies (IT) have continuously empowered manufacturing systems and accelerated the evolution of manufacturing system paradigms, and smart manufacturing (SM) has become one of the most promising paradigms. The study of SM has attracted a great deal of attention for researchers in academia and practitioners in industry. However, an obvious fact is that people with different backgrounds have different expectations for SM, and this has led to high diversity, ambiguity, and inconsistency in terms of definitions, reference models, performance matrices, and system design methodologies. It has been found that the state of the art SM research is limited …
Promoting Diversity In Teaching Cybersecurity Through Gicl, Yuming He, Wu He, Xiaohong Yuan, Li Yang, Theo Bastiaens (Ed.)
Promoting Diversity In Teaching Cybersecurity Through Gicl, Yuming He, Wu He, Xiaohong Yuan, Li Yang, Theo Bastiaens (Ed.)
Information Technology & Decision Sciences Faculty Publications
In summary, it is necessary to develop a diverse group of K-12 students’ interest and skills in cybersecurity as cyber threats continue to grow. Evidence shows that educating the next generation of cyber workers is a crucial job that should begin in elementary school. To ensure the effectiveness of cybersecurity education and equity at the K-12 level, teachers must create thoughtful plans for considering communities’ interests and needs, and to continually reconsider what’s working and how to adjust our strategies, approaches, design, and research plan to meet their specific needs, challenges, and strengths, particularly with students from under-served and underrepresented …
Improving Stock Trading Decisions Based On Pattern Recognition Using Machine Learning Technology, Yaohu Lin, Shancun Liu, Haijun Yang, Harris Wu, Bingbing Jiang
Improving Stock Trading Decisions Based On Pattern Recognition Using Machine Learning Technology, Yaohu Lin, Shancun Liu, Haijun Yang, Harris Wu, Bingbing Jiang
Information Technology & Decision Sciences Faculty Publications
PRML, a novel candlestick pattern recognition model using machine learning methods, is proposed to improve stock trading decisions. Four popular machine learning methods and 11 different features types are applied to all possible combinations of daily patterns to start the pattern recognition schedule. Different time windows from one to ten days are used to detect the prediction effect at different periods. An investment strategy is constructed according to the identified candlestick patterns and suitable time window. We deploy PRML for the forecast of all Chinese market stocks from Jan 1, 2000 until Oct 30, 2020. Among them, the data from …
Exploring Cybersecurity Education At The K-12 Level, Weiru Chen, Yuming He, Xin Tian, Wu He, E. Langran (Ed.), D. Rutledge (Ed.)
Exploring Cybersecurity Education At The K-12 Level, Weiru Chen, Yuming He, Xin Tian, Wu He, E. Langran (Ed.), D. Rutledge (Ed.)
Information Technology & Decision Sciences Faculty Publications
K-12 cybersecurity education is receiving growing attention with the growing number of cyberattacks and a shortage of cybersecurity professionals. However, there are many barriers for teachers to implement effective cybersecurity education in formal classroom environments. This study conducts a systematic literature review to examine the current state-of-the-art on K-12 cybersecurity education. Through the systematic literature review, we identified 20 closely relevant papers and recognized that a well-designed curriculum in cybersecurity education at the K-12 level is strongly needed to motivate students to pursue cybersecurity pathways and careers. The challenge and suggestions of curriculum design, teaching strategy, and learning assessment are …
A Literature Review Of Quantum Education In K-12 Level, Yuming He, Shenghua Zha, Wu He, Theo Bastiaens (Ed.)
A Literature Review Of Quantum Education In K-12 Level, Yuming He, Shenghua Zha, Wu He, Theo Bastiaens (Ed.)
Information Technology & Decision Sciences Faculty Publications
Quantum computing is an emerging technology paradigm of computing and has the potential to solve computational problems intractable using today’s classical computers or digital technology. Quantum computing is expected to be disruptive for many industries. The power of quantum computing technologies is based on the fundamentals of quantum mechanics, such as quantum superposition, quantum entanglement, or the no-cloning theorem. To build a highly trained and skilled quantum workforce that meets future industry needs, there is a need to introduce quantum concepts early on in K-12 schools since the learning of quantum is a lengthy process. As fundamental quantum concepts derive …
Effect Of User Involvement In Supply Chain Cloud Innovation: A Game Theoretical Model And Analysis, Yun Chen, Lian Duan, Weiyong Zhang
Effect Of User Involvement In Supply Chain Cloud Innovation: A Game Theoretical Model And Analysis, Yun Chen, Lian Duan, Weiyong Zhang
Information Technology & Decision Sciences Faculty Publications
Cloud innovation has become increasingly important to supply chain innovation and performance. User involvement is a crucial part of cloud innovation. However, the effect of user involvement in supply chain cloud innovation has not been thoroughly studied, particularly its effect on product cost and optimal price. In this paper, the authors attempted to bridge this major gap in the literature. The authors reviewed the relevant literature to define cloud innovation and user involvement in supply chain cloud innovation. Then the authors developed a game model based on the Bertrand model. Analysis of the model showed that user involvement affects product …
Experimental Investigation On The Effects Of Website Aesthetics On User Performance In Different Virtual Tasks, Meinald T. Thielsch, Russell Haines, Leonie Flacke
Experimental Investigation On The Effects Of Website Aesthetics On User Performance In Different Virtual Tasks, Meinald T. Thielsch, Russell Haines, Leonie Flacke
Information Technology & Decision Sciences Faculty Publications
In Human-Computer Interaction research, the positive effect of aesthetics on users' subjective impressions and reactions is well-accepted. However, results regarding the influence of interface aesthetics on a user's individual performance as an objective outcome are very mixed, yet of urgent interest due to the proceeding of digitalization. In this web-based experiment (N = 331), the effect of interface aesthetics on individual performance considering three different types of tasks (search, creative, and transfer tasks) is investigated. The tasks were presented on an either aesthetic or unaesthetic website, which differed significantly in subjective aesthetics. Goal orientation (learning versus performance goals) was included …
Automated Trading Systems Statistical And Machine Learning Methods And Hardware Implementation: A Survey, Boming Huang, Yuziang Huan, Li Da Xu, Lirong Zheng, Zhuo Zou
Automated Trading Systems Statistical And Machine Learning Methods And Hardware Implementation: A Survey, Boming Huang, Yuziang Huan, Li Da Xu, Lirong Zheng, Zhuo Zou
Information Technology & Decision Sciences Faculty Publications
Automated trading, which is also known as algorithmic trading, is a method of using a predesigned computer program to submit a large number of trading orders to an exchange. It is substantially a real-time decision-making system which is under the scope of Enterprise Information System (EIS). With the rapid development of telecommunication and computer technology, the mechanisms underlying automated trading systems have become increasingly diversified. Considerable effort has been exerted by both academia and trading firms towards mining potential factors that may generate significantly higher profits. In this paper, we review studies on trading systems built using various methods and …
Advances In Processing, Mining, And Learning Complex Data: From Foundations To Real-World Applications, Jia Wu, Shirui Pan, Chuan Zhou, Gang Li, Wu He, Chengqi Zhang
Advances In Processing, Mining, And Learning Complex Data: From Foundations To Real-World Applications, Jia Wu, Shirui Pan, Chuan Zhou, Gang Li, Wu He, Chengqi Zhang
Information Technology & Decision Sciences Faculty Publications
Processing, mining, and learning complex data refer to an advanced study area of data mining and knowledge discovery concerning the development and analysis of approaches for discovering patterns and learning models from data with a complex structure (e.g., multirelational data, XML data, text data, image data, time series, sequences, graphs, streaming data, and trees) [1–5]. These kinds of data are commonly encountered in many social, economic, scientific, and engineering applications. Complex data pose new challenges for current research in data mining and knowledge discovery as they require new methods for processing, mining, and learning them. Traditional …
Gender Difference And Employees' Cybersecurity Behaviors, Mohd Anwar, Wu He, Ivan Ash, Xiaohong Yuan, Ling Li, Li Xu
Gender Difference And Employees' Cybersecurity Behaviors, Mohd Anwar, Wu He, Ivan Ash, Xiaohong Yuan, Ling Li, Li Xu
Information Technology & Decision Sciences Faculty Publications
Security breaches are prevalent in organizations and many of the breaches are attributed to human errors. As a result, the organizations need to increase their employees' security awareness and their capabilities to engage in safe cybersecurity behaviors. Many different psychological and social factors affect employees' cybersecurity behaviors. An important research question to explore is to what extent gender plays a role in mediating the factors that affect cybersecurity beliefs and behaviors of employees. In this vein, we conducted a cross-sectional survey study among employees of diverse organizations. We used structural equation modelling to assess the effect of gender as a …
Industrial Wireless Sensor Networks 2016, Qindong Sun, Schancang Li, Shanshan Zhao, Hongjian Sun, Li Xu, Arumugam Nallamathan
Industrial Wireless Sensor Networks 2016, Qindong Sun, Schancang Li, Shanshan Zhao, Hongjian Sun, Li Xu, Arumugam Nallamathan
Information Technology & Decision Sciences Faculty Publications
The industrial wireless sensor network (IWSN) is the next frontier in the Industrial Internet of Things (IIoT), which is able to help industrial organizations to gain competitive advantages in industrial manufacturing markets by increasing productivity, reducing the costs, developing new products and services, and deploying new business models.
Semantic Inference On Clinical Documents: Combining Machine Learning Algorithms With An Inference Engine For Effective Clinical Diagnosis And Treatment, Shuo Yang, Ran Wei, Jingzhi Guo, Lida Xu
Semantic Inference On Clinical Documents: Combining Machine Learning Algorithms With An Inference Engine For Effective Clinical Diagnosis And Treatment, Shuo Yang, Ran Wei, Jingzhi Guo, Lida Xu
Information Technology & Decision Sciences Faculty Publications
Clinical practice calls for reliable diagnosis and optimized treatment. However, human errors in health care remain a severe issue even in industrialized countries. The application of clinical decision support systems (CDSS) casts light on this problem. However, given the great improvement in CDSS over the past several years, challenges to their wide-scale application are still present, including: 1) decision making of CDSS is complicated by the complexity of the data regarding human physiology and pathology, which could render the whole process more time-consuming by loading big data related to patients; and 2) information incompatibility among different health information systems (HIS) …
Qos Recommendation In Cloud Services, Xianrong Zheng, Li Da Xu, Sheng Chai
Qos Recommendation In Cloud Services, Xianrong Zheng, Li Da Xu, Sheng Chai
Information Technology & Decision Sciences Faculty Publications
As cloud computing becomes increasingly popular, cloud providers compete to offer the same or similar services over the Internet. Quality of service (QoS), which describes how well a service is performed, is an important differentiator among functionally equivalent services. It can help a firm to satisfy and win its customers. As a result, how to assist cloud providers to promote their services and cloud consumers to identify services that meet their QoS requirements becomes an important problem. In this paper, we argue for QoS-based cloud service recommendation, and propose a collaborative filtering approach using the Spearman coefficient to recommend cloud …
A Distributed Consensus Algorithm For Decision Making In Service-Oriented Internet Of Things, Shancang Li, George Oikonomou, Theo Tryfonas, Thomas M. Chen, Li Da Xu
A Distributed Consensus Algorithm For Decision Making In Service-Oriented Internet Of Things, Shancang Li, George Oikonomou, Theo Tryfonas, Thomas M. Chen, Li Da Xu
Information Technology & Decision Sciences Faculty Publications
In a service-oriented Internet of things (IoT) deployment, it is difficult to make consensus decisions for services at different IoT edge nodes where available information might be insufficient or overloaded. Existing statistical methods attempt to resolve the inconsistency, which requires adequate information to make decisions. Distributed consensus decision making (CDM) methods can provide an efficient and reliable means of synthesizing information by using a wider range of information than existing statistical methods. In this paper, we first discuss service composition for the IoT by minimizing the multi-parameter dependent matching value. Subsequently, a cluster-based distributed algorithm is proposed, whereby consensuses are …
Industrial Wireless Sensor Networks, Shancang Li, Hongjian Sun, Arumugam Nallanathan, Li Xu, Shanshan Zhao, Qindong Sun
Industrial Wireless Sensor Networks, Shancang Li, Hongjian Sun, Arumugam Nallanathan, Li Xu, Shanshan Zhao, Qindong Sun
Information Technology & Decision Sciences Faculty Publications
(First Paragraph) Industrial wireless sensor networks (IWSNs) incorporate wireless sensor networks with intelligent industrial systems providing many advantages over existing industrial applications, such as wireless communication, low cost, rapid deployment, self-organization, intelligent controlling, and processing capability. With the proliferation of wireless sensor networks in industrial applications, IWSNs technologies promise to play a significant role in developing more reliable, efficient, stable, flexible, and application-centric industrial systems.
Semantic Inference On Heterogeneous E-Marketplace Activities, Jingzhi Guo, Lida Xu, Zhiguo Gong, Chin-Pang Che, Sohail S. Chaudry
Semantic Inference On Heterogeneous E-Marketplace Activities, Jingzhi Guo, Lida Xu, Zhiguo Gong, Chin-Pang Che, Sohail S. Chaudry
Information Technology & Decision Sciences Faculty Publications
An electronic marketplace (e-marketplace) is a common business information space populated with many entities of different system types. Each of them has its own context of how to process activities. This leads to heterogeneous e-marketplace activities, which are difficult to make interoperable and inferred from one entity to another. This study solves this problem by proposing a concept of separation strategy and implementing it through providing a semantic inference engine with a novel inference algorithm. The solution, called the RuleXPM approach, enables one to semantically infer a next e-marketplace activity across multiple contexts/domains. Experiments show that the cross-context/cross-domain semantic inference …