• International Journal of Precision Engineering and Manufacturing
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• v.2 no.2
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• pp.65-72
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• 2001

The design of multi-stage gear drives is a time-consuming process, since on includes more complicated problems, which are not considered in the design of single-stage gear drives. The designer has th determine the number of reduction stages and the gear ratios of each reduction state. In addition, the design problems include not only the dimensional design but also the configuration design of gear drive elements. There is no definite rule and principle for these types of design problems. Thus the design practices largely depend on the sense and the experiences of the designer , and consequently result in undesirable design solution. We propose a new generalized design algorithm to support the designer at the preliminary design phase of multi-stage gear drives. The proposed design algorithm automates the design process by integrating the dimensional design and the configuration design process. The algorithm consists of four steps. In the first step, a designer determines the number of reduction stage. In the second step. gear ratios se chosen by using the random search method. In the third step, the values of basic design parameter are chosen by using the generate and test method. Then, the values of other dimension, such ad pitch diameter, outer diameter, and face width, are calculated for the configuration design in the final step. The strength and durability of a gear is guaranteed by the bending strength and the pitting resistance rating practices by using the AGMA rating formulas. In the final step, the configuration design is carried out b using the simulated annealing algorithm. The positions of gears and shafts are determined to minimize the geometrical volume(size) of a gearbox, while satisfying spatial constraints between them. These steps are carried out iteratively until a desirable solution is acquired. The propose design algorithm has been applied to the preliminary design of four-stage gear drives in order to validate the availability. The design solution have shown considerably good results in both aspects of the dimensional and the configuration design.

• Journal of KIISE:Computing Practices and Letters
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• v.15 no.2
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• pp.140-144
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• 2009

The efficient test tool is indispensable to the test driven development. The test tool is very helpful to get the advantage of the test driven development. Many traditional automation test tool does not support standard script language and are not suitable to unit test. In traditional unit test tool, a code for the test is added at the source code. Such method makes the complexity of a source code and has a problem which must modify many part of the source code when the test case is changed. In this paper, we present a design technique of a flexible unit testing tool which makes a developer can modify easily the test case by using the standard java script in test driven development. We implement the test tool by this design technique to verify the availability of this technique.

• Journal of the Korean Dietetic Association
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• v.17 no.3
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• pp.302-312
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• 2011

The purpose of this study was to investigate the equipment ratio of sanitary facility/equipment as well as the sanitary management performance level at foodservice of correctional institutions in Korea. For this purpose, a total of 47 questionnaires were distributed to dietitians working at correctional institutions during the period from March 20th to May 18th of 2008. A total of 38 questionnaires (response rate 81%) was analyzed using SPSS (windows ver. 14.0). The majority of the respondents were females (65.8%), 35 years or older (55.3%), with 7 years or longer experiences (65.8%), and with education level of university or higher (60.5%). Among the institutions, 39.5% had less than 500, 28.9% had 501 or more but less than 1,200, and 31.6% had 1,201 or more inmates. The equipment ratio of the sanitary facilities/equipment was 49.7%, which was relatively low. Most dietitians perceived 'limited availability of facilities and equipment' and 'the lack of support from financing department' as the major barriers in implementing a desirable sanitary system. On the other hand, perceived sanitary management performance was rated by the respondents as being between 2.55 to 4.50 (5-point Likert scale)-'Cleaning hands properly as specified' showed the lowest performance, whereas 'Sampling preserved meals by standard methodology' showed the highest. The results of this study suggest that a sanitary education program designed for inmate food handlers is needed for successful sanitary management.

• KIISE Transactions on Computing Practices
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• v.21 no.1
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• pp.46-51
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• 2015

The explosive growth of data and the rapidly changing technical social evolution new analysis paradigm for predicting and reacting the future the past and present ig data. Prescriptive analysis has a fundamental difference because can support specific behaviors and results according to user's goals with defin researchers establish judgments and activities achiev the goals. However research methods not widely implemented and even the terminology, Prescriptive analysis, is still unfamiliar. This paper thus propose an infrastructure in the prescriptive analysis field with key considerations for enhancing capability of researchers through a case study based on InSciTe Advisory developed with scientific big data. InSciTe Advisory system s developed in 2013, and offers a prescriptive analytics report which contains various As-Is analysis results and To-Be analysis results 5W1H methodology. InSciTe Advisory therefore shows possibility strategy aims to reach a target role model group. Through the availability and reliability of the measurement model the evaluation results obtained relative advantage of 118.8% compared to Elsevier SciVal.

• Perspectives in Nursing Science
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• v.5 no.1
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• pp.33-43
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• 2008

Objective: This study explored the reuse of data captured into an electronic nursing record system using the International Classification for Nursing Practice to support nursing research of inpatient's falls. Methods: Risk factors relevant to inpatients falls ;n an acute setting were identified from the literature review. Four risk assessment tools and two risk identification studies were selected. To examine the availability of coded data in an electronic nursing record system for the identified fall fisk factors, we reviewed 11.319 hospital-day records of 118 patients who were reported by the self-report system. Results: We identified 24 fall risk factors of five categories from the literature review, which were used to identify the standard nursing statements addressing fall risks. One hundred thirty five nursing statements were searched from the hospital's nursing data dictionary of statements and were matched with 14 fall fisk factors. Using the 135 statements. we found that mental status, catheter of drip in situ, abnormal gait, insomnia, surgical procedure. and dizziness/vertigo appeared frequently in the nursing records of inpatients with fall s. Also we found 6 risk factors more through the record review. Conclusion: The electronic records would be a good research source for inpatients' falls. Specifically international classification for nursing practice based nursing record system has the potential for promoting clinical researches.

• Korean Journal of Community Nutrition
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• v.13 no.4
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• pp.520-530
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• 2008

The purpose of this study was to investigate the characteristics of the foodservice management practices, the equipment ratio of sanitary facility/equipment, and dietitians' perceptions of (i) the barriers to sanitary management and (ii) the sanitary management performance level in the welfare institutions for the disabled in Korea. The survey was conducted during the period from September 7 to October 15, 2006. A total of 91 institutions(response rate 74.6%) were analyzed by using SPSS(windows ver. 14.0). The average number of meals served per day per an institution was 379. The majority(93.4%) of dietitians made decisions in procurement. The major part of the purchase was made through private contract. The factors affecting menu planning were nutrition, food preference, and cost, in the order of importance. Among the food items, fruits were infrequently served, while protein source foods and green leaf vegetables were almost daily served. The equipment ratio of sanitary facilities/equipment was 45%, which was relatively low. Most dietitians perceived 'limited availability of facilities and equipment' and 'the lack of support from financing department' as the major barriers in implementing a desirable sanitary system. Sanitary management performance in 'the food ingredient' was perceived as the lowest, while that in 'the uniform' showed the highest. The results of this study suggest that a proper supporting program on securing the facility/equipment and adequately trained employees are needed for successful sanitary management. Also, a more frequent supply of fruits for the disabled is recommended.

• Journal of Microbiology and Biotechnology
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• v.32 no.6
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• pp.776-782
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• 2022

Corn-soybean meal diets are commonly used in the pork industry as a primary source of energy and protein. However, such a diet generally contains non-starch polysaccharides (NSPs) which present a challenge in finding ways to improve their availability and digestibility. Dietary multi-carbohydrases (MCs) have been proposed as an efficient approach to utilize NSPs, and can result in improved growth performance and host intestinal fitness. In this study, we evaluated the effects of MC in lactation diets on gut microbiota composition of lactating sows and their litters. The experimental design contained two dietary treatments, a diet based on corn-soybean meal (CON), and CON supplemented with 0.01% multigrain carbohydrases (MCs). Sow and piglet fecal samples were collected on days 7 and 28 after farrowing. Based on the results from 16S rRNA gene amplicon sequencing, MC led to changes in species diversity and altered the microbial compositions in lactating sows and their piglets. Specifically, the MC treatment induced an increase in the proportions of Lactobacillus in piglets. Clostridium and Spirochaetaceae showed a significantly reduced proportion in MC-treated sows at day 28. Our results support the beneficial effects of dietary carbohydrases and their link with improved production due to better host fitness outcomes and gut microbiota composition.

• International Journal of Computer Science & Network Security
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• v.22 no.12
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• pp.37-50
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• 2022

Modern supply chains include multiple activities from collecting raw materials to transferring final products. These activities involve many parties who share a huge amount of valuable data, which makes managing supply chain systems a challenging task. Current supply chain management (SCM) systems adopt digital technologies such as the Internet of Things (IoT) and blockchain for optimization purposes. Although these technologies can significantly enhance SCM systems, they have their own limitations that directly affect SCM systems. Security, performance, and scalability are essential components of SCM systems. Yet, confidentiality and scalability are one of blockchain's main limitations. Moreover, IoT devices are lightweight and have limited power and storage. These limitations should be considered when developing blockchain-based IoT-SCM systems. In this paper, the requirements of efficient supply chain systems are analyzed and the role of both IoT and blockchain technologies in providing each requirement are discussed. The limitations of blockchain and the challenges of IoT integration are investigated. The limitations of current literature in the same field are identified, and a secure and scalable blockchain-based IoT-SCM system is proposed. The proposed solution employs a Hyperledger fabric blockchain platform and tackles confidentiality by implementing private data collection to achieve confidentiality without decreasing performance. Moreover, the proposed framework integrates IoT data to stream live data without consuming its limited resources and implements a dualstorge model to support supply chain scalability. The proposed framework is evaluated in terms of security, throughput, and latency. The results demonstrate that the proposed framework maintains confidentiality, integrity, and availability of on-chain and off-chain supply chain data. It achieved better performance through 31.2% and 18% increases in read operation throughput and write operation throughput, respectively. Furthermore, it decreased the write operation latency by 83.3%.

• Journal of the Korean institute of surface engineering
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• v.56 no.6
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• pp.437-442
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• 2023

This research aims to enhance the efficiency of Pt/C catalysts due to the limited availability and high cost of platinum in contemporary fuel cell catalysts. Nano-sized platinum particles were distributed onto a carbon-based support via the polyol process, utilizing the metal precursor H₂PtCl₆·6H₂O. Key parameters such as pH, temperature, and RPM were carefully regulated. The findings revealed variations in the particle size, distribution, and dispersion of nano-sized Pt particles, influenced by temperature and pH. Following sodium hydroxide treatment, heat treatment procedures were systematically executed at diverse temperatures, specifically 120, 140, and 160 ℃. Notably, the thermal treatment at 140 ℃ facilitated the production of Pt/C catalysts characterized by the smallest platinum particle size, measuring at 1.49 nm. Comparative evaluations between the commercially available Pt/C catalysts and those synthesized in this study were meticulously conducted through cyclic voltammetry, X-ray diffraction (XRD), and field-emission scanning electron microscopy-energy dispersive X-ray spectroscopy (FE-SEM EDS) methodologies. The catalyst synthesized at 160 ℃ demonstrated superior electrochemical performance; however, it is imperative to underscore the necessity for further optimization studies to refine its efficacy.

• Computers and Concrete
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• v.33 no.2
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• pp.175-193
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• 2024

Researchers have embarked on an active investigation into the feasibility of adopting alternative materials as a solution to the mounting environmental and economic challenges associated with traditional concrete-based construction materials, such as reinforced concrete. The examination of concrete's mechanical properties using laboratory methods is a complex, time-consuming, and costly endeavor. Consequently, the need for models that can overcome these drawbacks is urgent. Fortunately, the ever-increasing availability of data has paved the way for the utilization of machine learning methods, which can provide powerful, efficient, and cost-effective models. This study aims to explore the potential of twelve machine learning algorithms in predicting the tensile strength of geopolymer concrete (GPC) under various curing conditions. To fulfill this objective, 221 datasets, comprising tensile strength test results of GPC with diverse mix ratios and curing conditions, were employed. Additionally, a number of unseen datasets were used to assess the overall performance of the machine learning models. Through a comprehensive analysis of statistical indices and a comparison of the models' behavior with laboratory tests, it was determined that nearly all the models exhibited satisfactory potential in estimating the tensile strength of GPC. Nevertheless, the artificial neural networks and support vector regression models demonstrated the highest robustness. Both the laboratory tests and machine learning outcomes revealed that GPC composed of 30% fly ash and 70% ground granulated blast slag, mixed with 14 mol of NaOH, and cured in an oven at 300°F for 28 days exhibited superior tensile strength.