• Journal of the Korean Society for Precision Engineering
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• v.21 no.6
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• pp.188-196
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• 2004

The objective of this paper is to propose a new technology of the orthopaedic surgery using the combination of reverse engineering (RE) based on CT data and rapid prototyping (RP). The proposed technology utilizes symmetrical characteristics of the human body and capability of the combination of RE and RP, which rapidly manufactures three-dimensional parts from CT data. The original .stl data of injured extents are generated from the mirror transformation of .stl file fur uninjured extents. The physical shape before injuring is manufactured from RP using the original .stl data. Subsequently, pre-operative planning, such as a selection of proper implants, preforming of the implant, a decision of fixation locations and an insert position for the implant, an estimation of the invasive size, and pre-education of operators are performed using the physical shape. In order to examine the applicability and the efficiency of the proposed surgical technology, various case studies, such as a distal tibia commented fracture, a proximal tibia plateau fracture and an iliac wing fracture of pelvis, are carried out. From the results of case studies, it has been shown that the proposed technology is an effective surgical tool of the orthopaedic surgery reducing the operational time, the operational cost, the radiation exposure of the patient and operators, and morbidity. In addition, the proposed technology could improve the accuracy of operation and the speed of rehabilitation.

• Journal of Mechanical Science and Technology
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• v.18 no.7
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• pp.1121-1130
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• 2004

The Genetic Algorithm (GA), an optimization technique based on the theory of natural selection, has proven to be a relatively robust means of searching for global optimum. It converges to the global optimum point without auxiliary information such as differentiation of function. In the case of a complex problem, the GA involves a large population number and requires a lot of computing time. To improve the process, this research used parallel processing with several personal computers. Parallel process technique is classified into two methods according to subpopulation's size and number. One is the fine-grained method (FGM), and the other is the coarse-grained method (CGM). This study selected the CGM as a parallel process technique because the load is equally divided among several computers. The given design domain should be reduced according to the degree of feasibility, because mechanical system problems have constraints. The reduced domain is used as an initial design domain. It is consistent with the feasible domain and the infeasible domain around feasible domain boundary. This parallel process used the Message Passing Interface library.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.18 no.11
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• pp.1118-1127
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• 2008

The position and size of holes in the partition of a double cavity are known to strongly affect the eigenfrequency of the longitudinal eigenmodes of the double cavity. To maximize or minimize the eigenfrequency of the hole-partitioned double cavity, two acoustical topology optimization problems are formulated and solved. While two sub-cavities are filled with air, a partition between them is assumed to consist of sub-partitions of variable acoustical properties. One design variable is assigned to each sub-partition, whose material properties are interpolated as those of an intermediate material between air and a rigid body. The penalty parameter of the used interpolation function is adjusted to obtain a distinct air and rigid body distribution at the converged stage in each acoustical topology optimization problem. A special attention is paid to the selection of initial values of design variables to obtain solutions as close to global optimum and symmetric as possible. To show numerical characteristics of these optimization problems, the formulated problems are first solved for the one-dimensional partition design domain and then for the two-dimensional partition design domain.

• Journal of Information Processing Systems
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• v.15 no.4
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• pp.833-852
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• 2019

In real time applications, due to their effective cost and small size, wireless networks play an important role in receiving particular data and transmitting it to a base station for analysis, a process that can be easily deployed. Due to various internal and external factors, networks can change dynamically, which impacts the localisation of nodes, delays, routing mechanisms, geographical coverage, cross-layer design, the quality of links, fault detection, and quality of service, among others. Conventional methods were programmed, for static networks which made it difficult for networks to respond dynamically. Here, machine learning strategies can be applied for dynamic networks effecting self-learning and developing tools to react quickly and efficiently, with less human intervention and reprogramming. In this paper, we present a wireless networks survey based on different machine learning algorithms and network lifetime parameters, and include the advantages and drawbacks of such a system. Furthermore, we present learning algorithms and techniques for congestion, synchronisation, energy harvesting, and for scheduling mobile sinks. Finally, we present a statistical evaluation of the survey, the motive for choosing specific techniques to deal with wireless network problems, and a brief discussion on the challenges inherent in this area of research.

• Journal of Distribution Science
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• v.20 no.12
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• pp.13-22
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• 2022

Purpose: The paper contributes to the existing literature on Vietnamese corporate governance and firm performance with a focus on listed family firms and the use of a more suitable econometric framework to analyze firm performance. The study investigates how family firm performance is affected by corporate governance under the standpoint of stewardship theory in Vietnam. Research design, data and methodology: With the use of different measures for firm performance (Tobin's Q, ROA, and ROE), regression models were estimated using Generalized Least Square (GLS) method on a panel data of a total of 113 listed companies during the five-year period from 2015 to 2019. Results: We found that family ownership as the main characteristic of the stewardship theory affects family firms positively. In addition, several other characteristics in corporate governance as board composition (board independence, board audits, and board committees), CEO (age and tenure) and firm characteristics (size, age, expansion, and annual sales) showed significant impacts on firm performance. Our findings also suggest that family firm performance can be either positively or negatively affected based on the characteristics of corporate governance. The findings can help companies evaluate the significance of corporate governance through deciding board structure and the selection of CEOs to match family firm characteristics. It also gives insights for investors, rating agencies, and policymakers for relevant purposes.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.3
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• pp.1047-1062
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• 2022

Differential power analysis (DPA) is disturbed by ghost peaks. There is a phenomenon that the mean absolute difference (MAD) value of the wrong key is higher than the correct key. We propose a compressed key guessing space (CKGS) scheme to solve this problem and analyze the AES algorithm. The DPA based on this scheme is named CKGS-DPA. Unlike traditional DPA, the CKGS-DPA uses two power leakage points for a combined attack. The first power leakage point is used to determine the key candidate interval, and the second is used for the final attack. First, we study the law of MAD values distribution when the attack point is AddRoundKey and explain why this point is not suitable for DPA. According to this law, we modify the selection function to change the distribution of MAD values. Then a key-related value screening algorithm is proposed to obtain key information. Finally, we construct two key candidate intervals of size 16 and reduce the key guessing space of the SubBytes attack from 256 to 32. Simulation experimental results show that CKGS-DPA reduces the power traces demand by 25% compared with DPA. Experiments performed on the ASCAD dataset show that CKGS-DPA reduces the power traces demand by at least 41% compared with DPA.

• Journal of Dairy Science and Biotechnology
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• v.41 no.4
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• pp.163-178
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• 2023

The market size of functional health foods has experienced substantial growth driven by increasing consumer interest. In particular, the application of functional probiotics in various food products has resulted in consistent and progressive growth. One promising category is the application of probiotics in the manufacturing of cheese, which aligns with the rising demand for functional foods among consumers. The inherent advantages of cheese and probiotics provide consumers with a broad selection of functional foods. Therefore, it is crucial to identify functional probiotics that can withstand the cheese manufacturing process and exert significant effects on the flavor and taste of cheese. In this review, we discuss several strategies aimed at developing probiotic-supplemented cheeses for future dairy food markets.

• Journal of the Korean Society of Safety
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• v.39 no.1
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• pp.27-32
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• 2024

This study analyzed cases of hydrogen (H₂) and natural gas (CH₄) leakage from a hydrogen-blended natural gas pipeline to determine a range of leakage characteristics, including leakage type, pipe material, pipe diameter, pressure, and damage size. Based on the results of this analysis, five hydrogen-blended natural gas leakage scenarios were selected. The national vision for a carbon-neutral society by 2050 is a very important strategic objective and promotes environmentally sustainable economic development in the age of the climate crisis. Accordingly, zero-carbon and low-carbon policies are being promoted in various fields, including energy production, consumption, and industrial processes. Hydrogen-blended natural gas is eco-friendly and is considered an important step towards carbon neutrality, with various countries including the United States and several European countries conducting empirical research to further investigate its potential. In Korea, a national research project commenced in April 2023 to verify and demonstrate the life cycle safety of blending hydrogen into the natural gas network. The results of this study will provide important data for the analysis of the damage impacts caused by the leakage of hydrogen-blended natural gas, such as the diffusion of gas clouds, fires, and gas explosions.

• International Journal of Computer Science & Network Security
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• v.24 no.7
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• pp.79-86
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• 2024

This research is conducted in order to analyze the student's academic performance at the secondary school level in Sindh province of Pakistan. The study was focused on the students who have passed the Matriculation level recently. The sample of size equal to 1097 secondary level students was randomly selected in a way that from each college roughly up to 150 students took part in the survey. The sample selection was further divided on gender (Male=448, Female=649) and Locale (Urban=456, Rural=641). A survey questionnaire was circulated for data collection. The statistical analysis based on Pearson's Chi-Square and Correlation models were carried out using the collected data. The conclusion was drawn from results that strongly revealed that the student's academic achievement at high school level was highly associated to their parent's educational level and socio-economic background. Therefore, it is strongly recommended that the financial condition of the population must be enhanced by taking suitable measures. The affected students should be awarded adequate financial assistance or scholarships to face such hardships of their learning career. Free laptops, learning materials, books, and stationery should also be provided.

• The Transactions of the Korea Information Processing Society
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• v.4 no.6
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• pp.1418-1432
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• 1997

Most general content_based image retrieval techniques use color and texture as retrieval indices. In color techniques, color histogram and color pair based color retrieval techniques suffer from a lack of spatial information and text. And This paper describes the design and implementation of content_based image retrieval system using color space and keywords. The preprocessor for image retrieval has used the coordinate system of the existing HSI(Hue, Saturation, Intensity) and preformed to split One image into chromatic region and achromatic region respectively, It is necessary to normalize the size of image for 200*N or N*200 and to convert true colors into 256 color. Two color histograms for background and object are used in order to decide on color selection in the color space. Spatial information is obtained using a maximum entropy discretization. It is possible to choose the class, color, shape, location and size of image by using keyword. An input color is limited by 15 kinds keyword of chromatic and achromatic colors of the Korea Industrial Standards. Image retrieval method is used as the key of retrieval properties in the similarity. The weight values of color space ${\alpha}(%)and\;keyword\;{\beta}(%)$ can be chosen by the user in inputting the query words, controlling the values according to the properties of image_contents. The result of retrieval in the test using extracted feature such as color space and keyword to the query image are lower that those of weight value. In the case of weight value, the average of te measuring parameters shows approximate Precision(0.858), Recall(0.936), RT(1), MT(0). The above results have proved higher retrieval effects than the content_based image retrieval by using color space of keywords.