• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.11 no.3
• /
• pp.1722-1741
• /
• 2017

Intrusion detection techniques based on virtual machine introspection (VMI) provide high temper-resistance in comparison with traditional in-host anti-virus tools. However, the presence of semantic gap also leads to the performance and compatibility problems. In order to map raw bits of hardware to meaningful information of virtual machine, detailed knowledge of different guest OS is required. In this work, we present VDSM, a lightweight and general approach based on driver separation mechanism: divide semantic view reconstruction into online driver of view generation and offline driver of semantics extraction. We have developed a prototype of VDSM and used it to do intrusion detection on 13 operation systems. The evaluation results show VDSM is effective and practical with a small performance overhead.

• Journal of Biosystems Engineering
• /
• v.24 no.1
• /
• pp.1-8
• /
• 1999

In this study, the physical properties of live garlic at the harvesting season were measured and analyzed as a fundamental study for developing a garlic harvester. A universal testing machine and a machine vision system were used to obtain mechanical and morphological properties of live garlic, respectively. The moisture content of live garlic at the harvesting season was 50% higher than that of dried garlic. The root of live garlic elongated greatly with respect to the applied tensile force. The relationship between the projected area and the weight of a bulb of live garlic was linear. Such a feature would be applied to develop an effective garlic harvester or garlic quality grader. Other useful physical properties of live garlic at the harvesting season were represented in the study.

• Physical Therapy Korea
• /
• v.28 no.3
• /
• pp.177-185
• /
• 2021

Background: Muscle undergoes change continuously with aging. Sarcopenia, in which muscle mass decrease with aging, is associated with various diseases, the risk of falling, and the deterioration of quality of life. Obesity and sarcopenia also have a synergy effect on the disease of the older adults. Objects: This study examined the risk factors for sarcopenia, sarcopenic obesity, and sarcopenia without obesity and developed prediction models. Methods: This machine-learning study used the 2008-2011 Korea National Health and Nutrition Examination Surveys in the analysis. After data curation, 5,563 older participants were selected, of whom 1,169 had sarcopenia, 538 had sarcopenic obesity, and 631 had sarcopenia without obesity; the remaining 4,394 were normal. Decision tree and random forest models were used to identify risk factors. Results: The risk factors for sarcopenia chosen by both methods were body mass index (BMI) and duration of moderate physical activity; those for sarcopenic obesity were sex, BMI, and duration of moderate physical activity; and those for sarcopenia without obesity were BMI and sex. The areas under the receiver operating characteristic curves of all prediction models exceeded 0.75. BMI could predict sarcopenia-related disease. Conclusion: Risk factors for sarcopenia-related diseases should be identified and programs for sarcopenia-related disease prevention should be developed. Data-mining research using population data should be conducted to enhance the effectiveness of early treatment for people with sarcopenia-related diseases through predictive models.

• Journal of the Korean Society for Precision Engineering
• /
• v.23 no.1 s.178
• /
• pp.193-200
• /
• 2006

To perform the finish grinding process of ferrules which are widely used as fiber optic connectors, a high-precision centerless grinding machine is necessary. The high-precision centerless grinding machine is consisted of the hydrostatic GW and RW spindle systems, hydrostatic RW feeding mechanism, RW swivel mechanism, on-machine GW and RW dressers, and concrete-filled steel bed. In this study, the thermal characteristics of the high-precision centerless grinding machine such as the temperature distribution, temperature rise and thermal deformation, are estimated based on the virtual prototype of the grinding machine and the heat generation rates of heat sources related to the machine operation conditions. The reliability of the predicted results is demonstrated by the temperature characteristics measured from the physical prototype. Especially, the predicted and measured results show the fact that the high-precision centerless grinding machine has very stable thermal characteristics.

• Journal of the Korean Society of Fisheries and Ocean Technology
• /
• v.51 no.1
• /
• pp.94-101
• /
• 2015

The heat treatment machine based on immersion was developed to reduce temperature difference during netting process and appraised it performance compared current heat treatment machine using high pressure. It was also reviewed the optimum heat treatment procedures for PBSAT monofilament net in accordance with the immersion time and temperature. The procedure was based on physical measurement such as breaking load, elongation and angle of the mesh for PBSAT monofilament. The water temperature gap of the treatment machine based on immersion was less than $1^{\circ}C$. and the energy consumption was also increased in high temperature condition. It was identified that the optimum temperature was $75^{\circ}C$ and its optimum processing time was between 15 minutes and 20 minutes to get qualified physical properties.

• Journal of the Korean Society of Manufacturing Technology Engineers
• /
• v.25 no.1
• /
• pp.54-61
• /
• 2016

Washing machine manufacturers typically advise consumers to maintain the relative humidity in the drum less than 80% for three days after the termination of a washing cycle in order to prevent bacteria proliferation. A vent installed in the back of a washing machine is used to release moisture to satisfy this condition. Up to now, the design and installation of the vent have been based on experiments without understanding its roles and physical phenomena. In this study, various CFD results are presented in order to explain the physical mechanism of moisture release in a washing machine. Two methods of moisture release (diffusion and convection) were studied; diffusion was found to be the dominant process in removing moisture. Experiments were also performed to validate this behavior. In addition, this study will aid in the efficient design of vents to keep the relative humidity low inside the drum.

• Korean Journal of Soil Science and Fertilizer
• /
• v.48 no.5
• /
• pp.564-569
• /
• 2015

In highland crop fields, saprolite is piled up approximately every three years as deep much as 20 to 30 cm because farmers expect that adding new materials may improve productivity and mitigate hazards by continuous cultivation of a single crop. Piling saprolite, however, has been reported to induce poor soil drainage. Effects of deep ploughing with a spading machine and an excavator were studied in sites located in Daekwanryeong-myeon, Pyeongchang in which soil physical properties were deteriorated by piled saprolite. The soil made of parent material of Samgag series was piled up over surface soil of Haggog series naturally developed in the area. Carrot was cultivated in the field. Productivity and growth factors of carrot were compared among control and deep ploughing by a spading machine and an excavator. Effective soil depth extended to 60 cm or greater by 60 cm deep ploughing by an excavator or 50 cm deep ploughing by a spading machine. On the other hand, effective soil depth was within 50 cm at control plot. Productivity of carrot responded to amelioration of soil physical properties. The productivity was greater in deep ploughing treatments than that of control or 30 cm ploughing. It suggested that increased productivity by deep ploughing was mainly related to breaking plough pan which inhibited extension of rooting zone.

• Journal of The Korean Society of Integrative Medicine
• /
• v.12 no.2
• /
• pp.155-166
• /
• 2024

Purpose : This study aims to identify key factors for predicting dropout risk at the university level and to provide a foundation for policy development aimed at dropout prevention. This study explores the optimal machine learning algorithm by comparing the performance of various algorithms using data on college students' dropout risks. Methods : We collected data on factors influencing dropout risk and propensity were collected from N University. The collected data were applied to several machine learning algorithms, including random forest, decision tree, artificial neural network, logistic regression, support vector machine (SVM), k-nearest neighbor (k-NN) classification, and Naive Bayes. The performance of these models was compared and evaluated, with a focus on predictive validity and the identification of significant dropout factors through the information gain index of machine learning. Results : The binary logistic regression analysis showed that the year of the program, department, grades, and year of entry had a statistically significant effect on the dropout risk. The performance of each machine learning algorithm showed that random forest performed the best. The results showed that the relative importance of the predictor variables was highest for department, age, grade, and residence, in the order of whether or not they matched the school location. Conclusion : Machine learning-based prediction of dropout risk focuses on the early identification of students at risk. The types and causes of dropout crises vary significantly among students. It is important to identify the types and causes of dropout crises so that appropriate actions and support can be taken to remove risk factors and increase protective factors. The relative importance of the factors affecting dropout risk found in this study will help guide educational prescriptions for preventing college student dropout.

• Transactions of the Korean Society of Mechanical Engineers A
• /
• v.26 no.8
• /
• pp.1461-1471
• /
• 2002

Linear motor has a lot of advantages in comparison with conventional feed mechanisms: high velocity, high acceleration, good positioning accuracy and a long lifetime. An important disadvantage of linear motor is its high power loss and heating up of motor and neighboring machine components in operation. For the application of the linear motors to precision machine tools an effective cooling method and thermal optimizing measures are required. In this paper Finite-Element-Method for the thermal behavior of synchronous linear motor is introduced, which is useful for the design and manufacturing of linear motors. By modeling the linear motor the orthotropic physical properties of the sheet metal and windings were considered and convective coefficient in the water cooler and to the surroundings was defined by analytical and experimental method. The calculated isothermal lines could analyze the heat flow in the linear motor.

• Journal of Biosystems Engineering
• /
• v.34 no.4
• /
• pp.211-219
• /
• 2009

In the process of oyster mushroom production, loading work of culture medium needs the most intensive labor power and cost. Therefore, the development of culture medium loading machine causes to reduce the manpower and cost. The main objectives of this study are identify cultivating environment, physical properties of culture medium and to make an element design of culture medium loading machine. The results are summarized as follows: 1. The moisture content and density of popularly used culture medium were 70%(w.b), $26\;kg/m^3$, respectively. 2. Pressure of the blower increased as the impeller speed increased, and the opening ratio of pressure controller decreased. 3. Recommendable c1earance(${\delta}$) between an impeller plate and a blower case was 25 mm at an impeller speed of 3183 rpm 4. Discharge device of type B with a hopper and suit was better than type A with a hopper.