• Asia Pacific Journal of Business Review
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• v.6 no.2
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• pp.27-60
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• 2022

Previous studies stated that low carbon innovation performance could be influenced by government regulations and the green market, which is the new trend of consumer consumption in the present time, mainly focusing on external factors. Before study augured that low carbon innovation performance could be driven by internal and external factors of cooperation such as institutional pressure, stakeholder pressure, and innovation resources. However, the study of green transformational leadership and organizational environmental culture on low carbon innovation performance is rare, especially in Chinese manufacturing, as well as the effect of influencing factors of TPB model: environmental attitude, subjective norm, and perceived behavior capability on low carbon innovation performance. Previous studies mostly used the TPB model for predicting individual behavior. This study established a theoretical model combining the TPB model with green transformational leadership and organizational environmental culture of Chinese automobile manufacturing on low carbon innovation performance. This study consists of two sections of research methodology: section 1 related to questionnaire design and data collection. We established a questionnaire and distributed it online, targeting responses from the managerial level working in Chinese automobile manufacturing. Eventually, 155 valid questionnaires were used for analysis. Section 2 involved data analysis using statistical software. Reliability and data validity was examined by reliability analysis and factor analysis. Correlations and convergent validity analyses were applied, and structural equation modeling was conducted to test the proposed hypotheses. The findings indicated that green transformational leadership, organizational environmental culture, and essential factors of TPB model; environmental attitude, subjective norm and perceived behavior capability positively affect low carbon innovation performance. In addition, the indirect effect of green transformational leadership was tested and found that organizational environmental culture and TPB factors mediated the relationship between transformational leadership and low carbon innovation performance.

• Journal of the Korea Convergence Society
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• v.13 no.2
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• pp.21-29
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• 2022

Based on the importance of dialect research, preservation, and communication, this paper conducted a study on machine translation of Korean dialects for dialect users who may be marginalized. For the dialect data used, AIHUB dialect data distributed based on the highest administrative district was used. We propose a many-to-one dialect machine translation that promotes the efficiency of model distribution and modeling research to improve the performance of the dialect machine translation by applying Copy mechanism. This paper evaluates the performance of the one-to-one model and the many-to-one model as a BLEU score, and analyzes the performance of the many-to-one model in the Korean dialect from a linguistic perspective. The performance improvement of the one-to-one machine translation by applying the methodology proposed in this paper and the significant high performance of the many-to-one machine translation were derived.

• International Journal of Computer Science & Network Security
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• v.22 no.3
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• pp.77-88
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• 2022

In response to the significant COVID-19 outbreak, countries have enforced the use of E-learning systems as an alternative to traditional learning; to contain the virus and minimize the infection rate while maintaining the continuity of the learning experience. However, the effective adoption of E-learning systems requires a well-understanding of critical factors, especially in times of crisis. In this regard, this study intends to assess the success of the E-learning system adoption by Higher Education Institutions (HEIs) during the crisis of COVID-19 by utilizing the Information Systems Success (ISS) model. This study's adopted model consists of nine interdependent dimensions, namely: Technical System Quality, Information Quality, Service Quality, Learner Quality, Perceived Satisfaction, Perceived Usefulness, System Use, Intention to Use, and System Success. An electronic survey was distributed among higher education students from different universities in Saudi Arabia to explore each model's dimension. Structural Equation Modeling (SEM) has been applied via SmartPLS software to test the causal relationships between dimensions. This study's main results revealed that students' Service Quality, Learner Quality, and the Intention to Use by students are essential drives for E-learning System Use during the Covid-19 pandemic. Meanwhile, the Intention to Use the system is significantly influenced by Perceived Satisfaction and Perceived Usefulness dimensions. Further, Perceived Satisfaction, Perceived Usefulness, and System Use are interdependent, and all three have a significant positive impact on E-learning System Success.

• Computers and Concrete
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• v.29 no.6
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• pp.393-405
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• 2022

Lightweight concrete is a superior material due to its light weight and high strength. There however remain significant lacunae in engineering knowledge with regards to shear failure of lightweight fiber reinforced concrete beams. The main aim of the present study is to investigate the optimum usage of steel fibers in lightweight fiber reinforced concrete (LWFRC). Multi-scale finite element model calibrated with experimental results is developed to study the effect of steel fibers on the mechanical properties of LWFRC beams. To decrease the amount of steel fibers, it is preferred to reinforce only the middle section of the LWFRC beams, where the flexural stresses are higher. For numerical simulation, a multi-scale finite element model was developed. The cement matrix was modeled as homogeneous and uniform material and both steel fibers and lightweight coarse aggregates were randomly distributed within the matrix. Considering more realistic assumptions, the bonding between fibers and cement matrix was considered with the Cohesive Zone Model (CZM) and its parameters were determined using the model update method. Furthermore, conformity of Load-Crack Mouth Opening Displacement (CMOD) curves obtained from numerical modeling and experimental test results of notched beams under center-point loading tests were investigated. Validating the finite element model results with experimental tests, the effects of fibers' volume fraction, and the length of the reinforced middle section, on flexural and residual strengths of LWFRC, were studied. Results indicate that using steel fibers in a specified length of the concrete beam with high flexural stresses, and considerable savings can be achieved in using steel fibers. Reducing the length of the reinforced middle section from 50 to 30 cm in specimens containing 10 kg/m3 of steel fibers, resulting in a considerable decrease of the used steel fibers by four times, whereas only a 7% reduction in bearing capacity was observed. Therefore, determining an appropriate length of the reinforced middle section is an essential parameter in reducing fibers, usage leading to more affordable construction costs.

• Journal of Aerospace System Engineering
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• v.17 no.4
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• pp.28-33
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• 2023

In this study, computational fluid dynamics was used to analyze the flow bias generated as air supplied by a fan passes through ducts, piping, and a coal separation screen. The flow bias of the air flow is mostly caused by the spatial characteristics of the fan volute and duct, and the internal baffle and the coal separation screen at the outlet cause strong pressure losses that dampen the flow bias. ANSYS CFX was used for computational fluid dynamics, and since the baffle and the coal separation screen are shaped like perforated plates with many small holes uniformly distributed, actual modeling for analysis was not possible. Therefore, the Porous Loss Model was applied. The evaluation of the flow bias was analyzed based on the velocity distribution of the Porous Loss Model at the outlet surface of the coal separation screen obtained from the computational fluid dynamics results.

• Journal of the Korea Society for Simulation
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• v.18 no.3
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• pp.139-146
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• 2009

Recently, software industry regarding national defense increases system development of distributed simulation system of M&S based to overcome limit of resource and expense. It is one of key technologies for offering of mutual validation among objects and reuse of objects which are discussed for developing these systems. RTI, implementation of HLA interface specification as software providing these technologies uses Federation Object Model for exchanging information with joined federates in the federation and each federate has a characteristic that is supposed to have identical FOM in the federation. This paper presents a characteristic of Base Object Model, SISO standardization for improving reuse and interoperability of Federation Object Model applied simulation network manager based HLA/RTI and suggests method of designing the structure of simulation network manager through the modularity of Federation Object Model.

• Journal of the Korea Society for Simulation
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• v.18 no.2
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• pp.1-8
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• 2009

Enterprise security management system proposed to properly manage heterogeneous security products is the security management infrastructure designed to avoid needless duplications of management tasks and inter-operate those security products effectively. In this paper, we defined the security policies using Z-Notation and the detection algorithm of policy conflict for managing heterogeneous firewall systems. It is designed to help security management build invulnerable security policies that can unify various existing management infrastructures of security policies. Its goal is not only to improve security strength and increase the management efficiency and convenience but also to make it possible to include different security management infrastructures while building security policies. With the process of the detection and resolution for policy conflict, it is possible to integrate heterogeneous security policies and guarantee the integrity of them by avoiding conflicts or duplications among security policies. And further, it provides convenience to manage many security products existing in large networks.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.3
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• pp.958-979
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• 2023

Due to laws, regulations, privacy, etc., between 70-90 percent of providers do not share medical data, forming a "data island". It is essential to collaborate across multiple institutions without sharing patient data. Most existing methods adopt distributed learning and centralized federal architecture to solve this problem, but there are problems of resource heterogeneity and data heterogeneity in the practical application process. This paper proposes a collaborative deep learning modelling method based on the blockchain network. The training process uses encryption parameters to replace the original remote source data transmission to protect privacy. Hyperledger Fabric blockchain is adopted to realize that the parties are not restricted by the third-party authoritative verification end. To a certain extent, the distrust and single point of failure caused by the centralized system are avoided. The aggregation algorithm uses the FedProx algorithm to solve the problem of device heterogeneity and data heterogeneity. The experiments show that the maximum improvement of segmentation accuracy in the collaborative training mode proposed in this paper is 11.179% compared to local training. In the sequential training mode, the average accuracy improvement is greater than 7%. In the parallel training mode, the average accuracy improvement is greater than 8%. The experimental results show that the model proposed in this paper can solve the current problem of centralized modelling of multicenter data. In particular, it provides ideas to solve privacy protection and break "data silos", and protects all data.

• Journal of Internet Computing and Services
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• v.24 no.5
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• pp.51-66
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• 2023

In this paper, we propose a new type of process discovery framework, which is named as control-path-driven process group discovery framework, to be used for process mining and process reengineering in supporting life-cycle management of business process models. In addition, we develop a process mining system based on the proposed framework and perform experimental verification through it. The process execution event logs applied to the experimental effectiveness and verification are specially defined as Process BIG-Logs, and we use it as the input datasets for the proposed discovery framework. As an eventual goal of this paper, we design and implement a control path-driven process group discovery algorithm and framework that is improved from the ρ-algorithm, and we try to verify the functional correctness of the proposed algorithm and framework by using the implemented system with a BIG-Log dataset. Note that all the process mining algorithm, framework, and system developed in this paper are based on the structural information control net process modeling methodology.

• International Journal of Computer Science & Network Security
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• v.24 no.6
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• pp.207-215
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• 2024

Cloud computing is now used by most companies, business centres and academic institutions to embrace new computer technology. Cloud Service Providers (CSPs) are limited to certain services, missing some of the assets requested by their customers, it means that different clouds need to interconnect to share resources and interoperate between them. The clouds may be interconnected in different characteristics and systems, and the network may be vulnerable to volatility or interference. While information technology and cloud computing are also advancing to accommodate the growing worldwide application, criminals use cyberspace to perform cybercrimes. Cloud services deployment is becoming highly prone to threats and intrusions. The unauthorised access or destruction of records yields significant catastrophic losses to organisations or agencies. Human intervention and Physical devices are not enough for protection and monitoring of cloud services; therefore, there is a need for more efficient design for cyber defence that is adaptable, flexible, robust and able to detect dangerous cybercrime such as a Denial of Service (DOS) and Distributed Denial of Service (DDOS) in heterogeneous cloud computing platforms and make essential real-time decisions for forensic investigation. This paper aims to develop a framework for digital forensic for the detection of cybercrime in a joined heterogeneous cloud setup. We developed a Digital Forensics model in this paper that can function in heterogeneous joint clouds. We used Unified Modeling Language (UML) specifically activity diagram in designing the proposed framework, then for deployment, we used an architectural modelling system in developing a framework. We developed an activity diagram that can accommodate the variability and complexities of the clouds when handling inter-cloud resources.