• Journal of Information Processing Systems
• /
• v.15 no.1
• /
• pp.55-66
• /
• 2019

Storage system often applies erasure codes to protect against disk failure and ensure system reliability and availability. Liberation code that is a type of coding scheme has been widely used in many storage systems because its encoding and modifying operations are efficient. However, it cannot effectively achieve fast recovery from single disk failure in storage systems, and has great influence on recovery performance as well as response time of client requests. To solve this problem, in this paper, we present HRSF, a Hybrid Recovery method for solving Single disk Failure. We present the optimal algorithm to accelerate failure recovery process. Theoretical analysis proves that our scheme consumes approximately 25% less amount of data read than the conventional method. In the evaluation, we perform extensive experiments by setting different number of disks and chunk sizes. The results show that HRSF outperforms conventional method in terms of the amount of data read and failure recovery time.

• Journal of Auto-vehicle Safety Association
• /
• v.13 no.2
• /
• pp.50-56
• /
• 2021

The purpose of this study is to investigate vulnerable parts of tower crane structures by analyzing extensive non-destructive test data. Approximately ten percent of domestically registered tower cranes were inspected by using magnetic particle inspection. The testing was carried out as advised in KS B 0213. The non-destructive results was analyzed with respect to jib types, age and crane size. As a result, the number of crack occurrences were the largest in mast parts, followed by main jib part. Moreover, it was found that turntables were important parts deserved to be noticed at the perspective of safe maintenance.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.16 no.7
• /
• pp.2359-2376
• /
• 2022

With the exponential growth of medical image big data represented by high-resolution CT images(CTI), the high-resolution CTI data is of great importance for clinical research and diagnosis. The paper takes lung CTI as an example to study. Retrieving answer CTIs similar to the input one from the large-scale lung CTI database can effectively assist physicians to diagnose. Compared with the conventional content-based image retrieval(CBIR) methods, the CBIR for lung CTIs demands higher retrieval accuracy in both the contour shape and the internal details of the organ. In traditional supervised deep learning networks, the learning of the network relies on the labeling of CTIs which is a very time-consuming task. To address this issue, the paper proposes a Weakly Supervised Similarity Evaluation Network (WSSENet) for efficiently support similarity analysis of lung CTIs. We conducted extensive experiments to verify the effectiveness of the WSSENet based on which the CBIR is performed.

• International Journal of Computer Science & Network Security
• /
• v.21 no.3
• /
• pp.83-93
• /
• 2021

COVID-19 poses a major risk to global health, highlighting the importance of faster and proper diagnosis. To handle the rise in the number of patients and eliminate redundant tests, healthcare information exchange and medical data are transmitted between healthcare centres. Medical data sharing helps speed up patient treatment; consequently, exchanging healthcare data is the requirement of the present era. Since healthcare professionals share data through the internet, security remains a critical challenge, which needs to be addressed. During the COVID-19 pandemic, computed tomography (CT) and X-ray images play a vital part in the diagnosis process, constituting information that needs to be shared among hospitals. Encryption and image steganography techniques can be employed to achieve secure data transmission of COVID-19 images. This study presents a new encryption with the image steganography model for secure data transmission (EIS-SDT) for COVID-19 diagnosis. The EIS-SDT model uses a multilevel discrete wavelet transform for image decomposition and Manta Ray Foraging Optimization algorithm for optimal pixel selection. The EIS-SDT method uses a double logistic chaotic map (DLCM) is employed for secret image encryption. The application of the DLCM-based encryption procedure provides an additional level of security to the image steganography technique. An extensive simulation results analysis ensures the effective performance of the EIS-SDT model and the results are investigated under several evaluation parameters. The outcome indicates that the EIS-SDT model has outperformed the existing methods considerably.

• International Journal of Internet, Broadcasting and Communication
• /
• v.11 no.4
• /
• pp.65-70
• /
• 2019

We are looking the impact associated with globalization in favor of small and medium enterprises (SMEs) growth and how helped to reduce the obstacle facing SMEs growth. We used empirical analysis in order to examine the relationship underlying the globalization and its impact to SME growth. We employed primarily data from Tanzania SMEs. Further we seeks to explain the negative notion that has been created that globalization is not friendly to SME growths. We employed primary data from Tanzania SMEs. The partial least squares (PLS) was used for analysis. The conclusion has indicated that globalization has a relationship with SMEs growth and has contributed to the reduction of obstacles that inhibit SMEs growth. However study confirmed controversial result on part of availability of managers and manpower with global perspectives to influence SMEs growth. The test accepted that globalization has influenced availability of managers with global perspectives but reject the availability of these managers influences the SMEs growth The results give a clear outlook to help policy maker in policy review process, formulate base for extensive study on issues for manager perspectives and draw intervention.

• Communications for Statistical Applications and Methods
• /
• v.29 no.5
• /
• pp.591-601
• /
• 2022

In gene set analysis with microarray expression data, a group of genes such as a gene regulatory pathway and a signaling pathway is often tested if there exists either differentially expressed (DE) or differentially co-expressed (DC) genes between two biological conditions. Recently, a statistical test based on covariance estimation have been proposed in order to identify DC genes. In particular, covariance regularization by hard thresholding indeed improved the power of the test when the proportion of DC genes within a biological pathway is relatively small. In this article, we compare covariance thresholding methods using four different regularization penalties such as lasso, hard, smoothly clipped absolute deviation (SCAD), and minimax concave plus (MCP) penalties. In our extensive simulation studies, we found that both SCAD and MCP thresholding methods can outperform the hard thresholding method when the proportion of DC genes is extremely small and the number of genes in a biological pathway is much greater than a sample size. We also applied four thresholding methods to 3 different microarray gene expression data sets related with mutant p53 transcriptional activity, and epithelium and stroma breast cancer to compare genetic pathways identified by each method.

• The Journal of Asian Finance, Economics and Business
• /
• v.10 no.2
• /
• pp.123-133
• /
• 2023

The COVID-19 pandemic has impacted the restaurant business adversely. The restaurant business is essential for Thailand's economy as it generates high income and a high employment rate. This study aimed to determine the relationships between restaurant businesses. Furthermore, it examined the problems encountered during COVID-19 and measures already implemented and planned. The research is intended to resolve these issues. We collected data from 136 people who worked in restaurants in Bangkok, Thailand, via telephone interviews. The data was analyzed by descriptive statistics and correspondence analysis using SPSS. The findings of this analysis indicate that all restaurants, irrespective of their size, face problems, though their planned and remedial actions are different. One finding was that medium restaurants face more financial problems and increased costs than others. They are countering this challenge through measures such as applying for loans and transitioning into a "non-restaurant" business. Nevertheless, typical medium restaurants have not engaged in extensive planning for the future. Based on a fact-finding survey, we considered appropriate short- and long-term measures suitable for micro, small and medium restaurants. In addition, our study's findings will help policymakers and practitioners identify strategies for responding to the COVID-19 outbreak and other future crises.

• Journal of Research and Publication Ethics
• /
• v.5 no.2
• /
• pp.1-6
• /
• 2024

Purpose: PBM is emerging as a major management system for securing corporate productivity and enhancing competitiveness, and various studies are being conducted. The purpose of this study is to analyze research trends published in KCI-listed journals and papers since 1999 to understand the current status of research and provide basic data for more extensive research and development of performance management in the future. Research design, data and methodology: A detailed examination of research trends was conducted through the analysis of abstracts from 154 research papers on PBM. To facilitate a comprehensive analysis of these trends, LDA topic modelling was employed. Results: First, it should be noted that research on PBM is not limited to the area of HRM. Instead, PBM research is expanding to encompass comprehensive personnel systems. Second, the results of topic modeling analysis show that although the initial focus of research was on human resource management, there is now a growing interest in fairness and organizational culture in the entire organization. Conclusions: PBM is becoming a dominant paradigm as it shifts from HR systems to organizational fairness and culture. This suggests that future research should consider both quantitative and qualitative aspects of PBM to improve corporate performance while prioritizing organizational fairness and culture.

• The KIPS Transactions:PartD
• /
• v.10D no.3
• /
• pp.417-426
• /
• 2003

The problem of finding clusters in high dimensional data is well known in the field of data mining for its importance, because cluster analysis has been widely used in numerous applications, including pattern recognition, data analysis, and market analysis. Recently, a new framework, projected clustering, to solve the problem was suggested, which first select subdimensions of each candidate cluster and then each input point is assigned to the nearest cluster according to a distance function based on the chosen subdimensions of the clusters. We propose a new algorithm for subdimensional clustering of high dimensional data, each of the three major steps of which partitions the input points into several candidate clutters with proper numbers of points, filters the clusters that can not be useful in the next steps, and then merges the remaining clusters into the predefined number of clusters using a closeness function, respectively. The result of extensive experiments shows that the proposed algorithm exhibits better performance than the other existent clustering algorithms.

• Journal of the Korea Society of Computer and Information
• /
• v.19 no.12
• /
• pp.101-109
• /
• 2014

Medical technology development and increase the income level of a "Long and healthy Life=Wellness," with the growing interest in actively promoting and maintaining health and wellness has become enlarged. In addition, the demand for personalized health care services is growing and extensive medical moves of big data, disease prevention, too. In this paper, the main interest in the market, highlighting wellness in order to support big data-driven healthcare quality through patient-centered medical services purposes. Patients with drug dependence treatment is not to diet but to improve disease prevention and treatment based on analysis of big data. Analysing your Tweets-daily information and wellness disease prevention and treatment, based on the purpose of the dictionary. Efficient big data analysis for node while increasing processing time experiment. Test result case of total access time efficient 26% of one node to three nodes and case of data storage is 63%, case of data aggregate is 18% efficient of one node to three nodes.