• Nuclear Engineering and Technology
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• v.54 no.3
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• pp.896-908
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• 2022

As a part of probabilistic risk (or safety) assessment (PRA or PSA) of nuclear power plants (NPPs), the primary role of human reliability analysis (HRA) is to provide credible estimations of the human error probabilities (HEPs) of safety-critical tasks. In this regard, it is vital to provide credible HEPs based on firm technical underpinnings including (but not limited to): (1) how to collect HRA data from available sources of information, and (2) how to inform HRA practitioners with the collected HRA data. Because of these necessities, the U.S. Nuclear Regulatory Commission and the Korea Atomic Energy Research Institute independently developed two dedicated HRA data collection systems, SACADA (Scenario Authoring, Characterization, And Debriefing Application) and HuREX (Human Reliability data EXtraction), respectively. These systems provide unique frameworks that can be used to secure HRA data from full-scope training simulators of NPPs (i.e., simulator data). In order to investigate the applicability of these two systems, two papers have been prepared with distinct purposes. The first paper, entitled "SACADA and HuREX: Part 1. The Use of SACADA and HuREX Systems to Collect Human Reliability Data", deals with technical issues pertaining to the collection of HRA data. This second paper explains how the two systems are able to inform HRA practitioners. To this end, the process of estimating HEPs is demonstrated based on feed-and-bleed operations using HRA data from the two systems.

• Nuclear Engineering and Technology
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• v.53 no.4
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• pp.1304-1310
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• 2021

Two-phase flow, especially gas-liquid two-phase flow, has a wide application in industrial field. The diagnosis of two-phase flow parameters, which directly determine the flow and heat transfer characteristics, plays an important role in providing the design reference and ensuring the security of online operation of two-phase flow system. Computer tomography (CT) is a good way to diagnose such parameters with imaging method. This paper has proposed a novel image reconstruction method for thermal neutron CT of two-phase flow with improved simulated annealing (ISA) algorithm, which makes full use of the prior information of two-phase flow and the advantage of stochastic searching algorithm. The reconstruction results demonstrate that its reconstruction accuracy is much higher than that of the reconstruction algorithm based on weighted total difference minimization with soft-threshold filtering (WTDM-STF). The proposed method can also be applied to other types of two-phase flow CT modalities (such as X(𝛄)-ray, capacitance, resistance and ultrasound).

• Journal of Veterinary Science
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• v.22 no.6
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• pp.74.1-74.13
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• 2021

Tissue engineering has been extensively investigated and proffered to be a potential platform for novel tissue regeneration. The utilization of mesenchymal stem cells (MSCs) from various sources has been widely explored and compared. In this regard, MSCs derived from bone marrow have been proposed and described as a promising cell resource due to their high yield of isolated cells with colony-forming potential, self-renewal capacity, MSC surface marker expression, and multi-lineage differentiation capacities in vitro. However, there is evidence for bone marrow MSCs (BM-MSCs) both in vitro and in vivo from different species presenting identical and distinct potential stemness characteristics. In this review, the fundamental knowledge of the growth kinetics and stemness properties of BM-MSCs in different animal species and humans are compared and summarized. Finally, to provide a full perspective, this review will procure results of current information studies focusing on the use of BM-MSCs in clinical practice.

• International Journal of Computer Science & Network Security
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• v.22 no.5
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• pp.215-219
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• 2022

Bankruptcy is one of the major areas that have attracted the interest of many researchers in the American system, particularly in terms of the laws that oversee it. It provides a plan of reorganization that enables the debtor or the proprietor to discharge liabilities to the creditors through dividing the assets to settle debts. This activity is carried out under supervision to fairly protect the interests of the creditors. Bankruptcy protection systems are dynamic and complex in nature, in line with the economic sector, ensuring the protection of affected individuals from falling into huge losses. Some bankruptcy procedures give the debtor the opportunity to stay in operation or business activity and benefit from revenues until the debt is settled. This law allows some debtors to be relived from any financial burden after the distribution of assets, even if the debt is not paid in full. In light of the above information, this research paper seeks to explore the nature of the complexity of bankruptcy protection laws, their characteristics, and the justice system that regulate them. It also sheds more light on the decision-making powers on bankruptcy cases. There are specialized courts that cover bankruptcy cases located in district courts in every state.

• Structural Monitoring and Maintenance
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• v.9 no.2
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• pp.179-200
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• 2022

This paper proposes a data-driven methodology for online early damage identification under changing environmental conditions. The proposed method relies on two data analysis methods: feature-based method and hybrid principal component analysis (PCA) and kernel PCA to separate damage from environmental influences. First, spectral sub-band features, namely, spectral sub-band centroids (SSCs) and log spectral sub-band energies (LSSEs), are proposed as damage-sensitive features to extract damage information from measured structural responses. Second, hybrid modeling by integrating PCA and kernel PCA is performed on the spectral sub-band feature matrix for data normalization to extract both linear and nonlinear features for nonlinear procedure monitoring. After feature normalization, suppressing environmental effects, the control charts (Hotelling T² and SPE statistics) is implemented to novelty detection and distinguish damage in structures. The hybrid PCA-KPCA technique is compared to KPCA by applying support vector machine (SVM) to evaluate the effectiveness of its performance in detecting damage. The proposed method is verified through numerical and full-scale studies (a Bridge Health Monitoring (BHM) Benchmark Problem and a cable-stayed bridge in China). The results demonstrate that the proposed method can detect the structural damage accurately and reduce false alarms by suppressing the effects and interference of environmental variations.

• Asia-Pacific Journal of Business
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• v.12 no.4
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• pp.13-40
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• 2021

Purpose - The purpose of this study is to predict corporate corruption in emerging markets such as Brazil, Russia, India, and China (BRIC) using different machine learning techniques. Since corruption is a significant problem that can affect corporate performance, particularly in emerging markets, it is important to correctly identify whether a company engages in corrupt practices. Design/methodology/approach - In order to address the research question, we employ predictive analytic techniques (machine learning methods). Using the World Bank Enterprise Survey Data, this study evaluates various predictive models generated by seven supervised learning algorithms: k-Nearest Neighbour (k-NN), Naïve Bayes (NB), Decision Tree (DT), Decision Rules (DR), Logistic Regression (LR), Support Vector Machines (SVM), and Artificial Neural Network (ANN). Findings - We find that DT, DR, SVM and ANN create highly accurate models (over 90% of accuracy). Among various factors, firm age is the most significant, while several other determinants such as source of working capital, top manager experience, and the number of permanent full-time employees also contribute to company corruption. Research implications or Originality - This research successfully demonstrates how machine learning can be applied to predict corporate corruption and also identifies the major causes of corporate corruption.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 1998.10a
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• pp.263-269
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• 1998

The forecasting of container cargo volumes should be estimated correctly because it has a key roles on the establishment of port development planning, and the decision of port operating system. Container cargo volumes have a dynamic characteristics which was changed by effect of competitive ports. Accordingly forecasting was needed overall approach about competitive port's development, alternation and information. But, until now, traffic forecasting was not executed according to competitive situation, and that was accomplished at the point of unit port. Generally, considering the competition situation, simulation method was desirable at forecasting because system's scale was increased, and the influence power was intensified. In this paper, considering this situation, the objectives can be outlined as follows. 1) Structural model constructs by System dynamics method. 2) Structural simulation model develops according to modelling of competitive situation by expended SD method which included HEP(Hierarchical Fuzzy Process) And actually, effectiveness was verified according to proposed model to major port in northeast asia.

• Geomechanics and Engineering
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• v.31 no.5
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• pp.489-503
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• 2022

A 1257-m-long irregular deep foundation pit located in the central of Nanjing, China was constructed using the combined full-width and half-width top-down method. Based on the long-term field monitoring data, this study analyzed the evolution characteristics of the vertical movement of the columns, internal force of the struts, and axial force of the structural beam and slab. The relevance of the three mentioned above and their relationship with the excavation process, structural system, and geological conditions were also investigated. The results showed that the column uplift was within the range of 0.08% to 0.22% of the excavation depth, and the embedded depth ratio of the diaphragm wall and the bottom heave affected significantly on the column uplift. The differential settlement between the column and diaphragm wall remained unchanged after the base slab was cast. The final settlement of the diaphragm wall was twice the column uplift. The internal force of the struts did not varied monotonically but was related to numerous factors such as the excavation depth, number of struts, and environmental conditions. Additionally, the dynamic force and deformation of the columns, beams, and slabs were analyzed to investigate the inherent relationship and variation patterns of the responses of different parts of the structure.

• Journal of Distribution Science
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• v.21 no.6
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• pp.1-11
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• 2023

Purpose: As a modern distribution channel, the growth of e-commerce has brought more competitive pressures on e-marketplace, making trust and loyalty become top priority. As one of many sources of trust and loyalty issues, understanding the effect of careless marketing communications on consumers' perception is critical. This study examines the effect of careless marketing communications (e.g. misspellings, incomplete information) in website on consumers' trust toward and confidence in purchasing a product from an e-commerce. Research design and methodology: An experimental research design (with two experimental studies) was used in to test the hypotheses. Study 1 employs a single-factor design and study 2 employs a 2x2, full-factorial, between-subjects design. Results: Results of the two experimental studies (Study 1, n = 60; Study 2, n = 140) demonstrate that simple mistakes significantly decrease consumers' trust toward an e-commerce and their confidence to purchase from the e-commerce. The effect is found to be significant in the case of high-involvement products; whereas no effect is found in low-involvement products. Conclusions: E-commerce relies heavily on carefully crafted marketing communications to establish consumers' trust and confidence. These studies confirm the equal importance of distribution and communication in maintaining consumers' trust and sustainability of the business.

• Journal of the Korean Society for Precision Engineering
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• v.14 no.1
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• pp.174-184
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• 1997

This paper presents a robust force tracking control of a smart flexible gripper featured by a piezoceramic actuator characterizing its durability and quick response time. A mathematical governing equation for the proposed gripper structure is derived by employing Hamilton's principle and a state space control model is subsequently obtained through model analysis. Uncertain system parameters such as frequency variation are included in the control model. A sliding mode control theory which has inherent robustness to the sys- tem uncertainties is adopted to design a force tracking controller for the piezoceramic actuator. Using out- put information from the tip force sensor, a full-order observer is constructed to estimate state variables of the system. Force tracking performances for desired trajectories represented by sinusoidal and step func- tions are evaluated by undertaking both simulation and experimental works. In addition, in order to illustrate practical feasibility of the proposed method, a two-fingered gripper is constructed and its performance is demonstrated by showing a capability of holding an object.