• Journal of the Korea Convergence Society
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• v.9 no.4
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• pp.341-349
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• 2018

In this study, the effect of chronic pain on the lives of elderly people in long-term care service was analyzed based on the mediated effect of depression. The research data was sampled from elderly people in long-term care services, 204 people participated. From mediated regression analysis, depression was the most relevant factor on the quality of life, followed by chronic pain. With chronic pain and depression as independent variables and quality of life as a dependent variable, depression was proved to have had a fully mediated effect on quality of life. The result of this study suggested that convergence of various support systems should be implemented for the elderly in long-term care services.

• Geomechanics and Engineering
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• v.37 no.3
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• pp.213-222
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• 2024

Determination of jointed rock mass properties plays a significant role in the design and construction of underground structures such as tunneling and mining. Rock mass classification systems such as Rock Mass Rating (RMR), Rock Mass Index (RMi), Rock Mass Quality (Q), and deformation modulus (Em) are determined from the jointed rock masses. However, parameters of jointed rock masses can be affected by the tunnel depth below the surface due to the effect of the in situ stresses. In addition, the geomechanical properties of rocks change due to the effect of metamorphism. Therefore, the main objective of this study is to apply correlation analysis to investigate the relationships between rock mass properties and some parameters related to the depth of the tunnel studied. For this purpose, the field work consisted of determining rock mass parameters in a tunnel alignment (~7.1 km) at varying depths from 21 m to 431 m below ground surface. At the same excavation depths, thirty-seven rock types were also sampled and tested in the laboratory. Correlations were made between vertical stress and depth, horizontal/vertical stress ratio (k) and depth, k and Em, k and RMi, k and point load index (PLI), k and Brazilian tensile strength (BTS), Em and uniaxial compressive strength (UCS), UCS and PLI, UCS and BTS. Relationships were significant (significance level=0.000) at the confidence interval of 95% (r = 0.77-0.88) between the data pairs for the rocks taken from depths greater than 166 m where the ratio of horizontal to vertical stress is between 0.6 and 1.2. The in-situ stress parameters affected rock mass properties as well as metamorphism which affected the geomechanical properties of rock materials by affecting the behavior of minerals and textures within rocks. This study revealed that in-situ stress parameters and metamorphism should be reviewed when tunnel studies are carried out.

• Quality Improvement in Health Care
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• v.7 no.1
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• pp.72-89
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• 2000

Background : Various types of protective footwear have been used to minimize bacterial contamination in operating rooms. In recent years, debate has arisen concerning the need for use of such protective footwear. This study was designed to provide useful data about choosing shoes most suitable for the surgical environment. Methods : Between November, 1999 and January, 2000, we performed this experimental study by comparing effect of three types of shoes (i.e., disposable shoescover, operating room-restricted shoes, and ordinary shoes) on bacterial contamination of operating rooms equipped with two different ventilation systems (i.e., high air-change, low air-change) respectively. Data were collected during two- hour sham operations in which subjects and their activities were strictly standardized. Bacterial flora were sampled from the study area floor and air colony counts were measured. Results : In experiments involving high air-change ventilation system, there was a significant difference of floor contamination between three types of shoes, but no difference of air contamination. Under low air-change system, there was a significant difference of both floor and air contamination between three types of shoes. Conclusion : The results show that protective footwear would be unnecessary in the operating room with high air-change ventilation system, but it is important to choose suitable shoes carefully under low air-change system. Therefore, the use of outdoor shoes can be considered under high air-change system, but it would seem sensible to apply their first use in less bloody operations at the day surgery center or out-patient department to prevent transfer of body fluid into the outside environment.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.11 no.2
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• pp.265-272
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• 2007

This proposed gamma (${\gamma}$) correction system is developed to reduce the difference between non-linear gamma curve produced by a typical formula and result produced by the proposed algorithm. In order to reduce the difference, the proposed system is using the Least Squares Polynomial which is calculating the best fitting polynomial through a set of points which is sampled. Each system is consisting of continuous several kinds of equations and having their own overlap sections to get more precise. Based on the algorithm verified by MATLAB, the proposed systems are implemented by using Verilog-HDL. This paper will compare the previous algorithm of gamma system such as Existing system with Seed Table with the latest that such as Proposed system. The former and the latter system have 1, 2 clock latency; each 1 result per clock. Because each of the error range (LSB) is $1{\sim}+1,\;0{\sim}+36$, we can how that Proposed system is improved. Under the condition of SAMSUNG STD90 0.35 worst case, each gate count is 2,063, 2,564 gates and each maximum data arrival time is 29.05[ns], 17.52[ns], respectively.

• The Journal of Society for e-Business Studies
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• v.26 no.3
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• pp.1-20
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• 2021

As the Great Reset is discussed at the World Economic Forum due to the COVID-19 pandemic, artificial intelligence, the driving force of the 4th industrial revolution, is also in the spotlight. However, corporate research in the field of artificial intelligence is still scarce. Since 2000, related research has focused on how to create value by applying artificial intelligence to existing companies, and research on how startups seize opportunities and enter among existing businesses to create new value can hardly be found. Therefore, this study analyzed the cases of startups using the comprehensive framework of the multi-level perspective with the research question of how artificial intelligence based startups, a sub-industry of software, have different innovation patterns from the existing software industry. The target firms are gazelle firms that have been certified as venture firms in South Korea, as start-ups within 7 years of age, specializing in machine learning modeling purposively sampled in the medical, finance, marketing/advertising, e-commerce, and manufacturing fields. As a result of the analysis, existing software companies have achieved process innovation from an enterprise-wide integration perspective, in contrast machine learning technology based startups identified unit processes that were difficult to automate or create value by dismantling existing processes, and automate and optimize those processes based on data. The contribution of this study is to analyse the birth of artificial intelligence-based startups and their innovation patterns while validating the framework of an integrated multi-level perspective. In addition, since innovation is driven based on data, the ability to respond to data-related regulations is emphasized even for start-ups, and the government needs to eliminate the uncertainty in related systems to create a predictable and flexible business environment.

• Journal of Biosystems Engineering
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• v.26 no.5
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• pp.461-468
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• 2001

Impact between fruits and other materials is a major cause of product damage in harvesting and handling systems. The oriental pears are more susceptible to bruising than other fruits such as European pears and apples, and are required more careful handling. The interest in the handling of the pears for the processing systems has raised the question of the allowable drop height to which pears can be dropped without causing objectionable damage. Drop tests on pears were conducted using an impact device developed by authors to estimate the allowable drop height without bruising. The impact device was constructed to hold in a selected orientation and to release a fruit by vacuum for dropping on to a force transducer. The drop height was adjustable for zero to 60 cm to achieve the desired distance between the bottom of the fruits and the top of the impact force transducer. The transducer was secured to 150 kg$\sub$f/ concrete block. The transducer signal was sampled every 0.17 ms with a strain gage measurement board in the micro computer where it was digitaly stored for later analysis. The selected sample fruit was Niitaka cultivar of pears which is one of the most promising fruit for export in Korea. The pears were harvested during the 1998 harvest season from an orchard in Daejeon. The sample fruit was selected from two groups which were stored for 3 months and 5 months respectively by the method of current commercial practice. The pears were allowed to stabilize at environmental condition(18$^{\circ}C$, 65% rh) of the experimental room. One hundred fifty six pears were tested from the heights of 5, 7.5. 10 and 12.5 cm while measurement were made of impact peak force, contact time, time to peak force, dwell time, pear diameter and mass. The bioyield strength and modulus of elasticity were measured using UTM immediately after each drop test. The allowable drop height was estimated on the base of bioyield strength of the pears in two ways. One was assumed the peak force during impact test increasing linearly with time, and the other was based on the actual drop test results. The computer program was developed for measuring the impact characteristics of the pears and analyzing the data obtained in the study. The peak force increased while contact times decreased with increasing drop height and contact times of the sample from the hard tissue group. The allowable drop height increased with increasing bioyield strength and contact times, and also varied with Poisson\`s ratio, mass and equilibrium radius of the pears. The allowable drop height calculated by a theoretical method was in the range from 1 to 4 cm, meanwhile, the estimated drop height considering the result of the impact test was in the range from 1 to 6 cm. Since the physical properties of fruits affected significantly the allowable drop height, the physical properties of the fruits should be considered when estimating the allowable drop height.

• Journal of Intelligence and Information Systems
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• v.19 no.2
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• pp.125-140
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• 2013

We call a data set in which the number of records belonging to a certain class far outnumbers the number of records belonging to the other class, 'imbalanced data set'. Most of the classification techniques perform poorly on imbalanced data sets. When we evaluate the performance of a certain classification technique, we need to measure not only 'accuracy' but also 'sensitivity' and 'specificity'. In a customer churn prediction problem, 'retention' records account for the majority class, and 'churn' records account for the minority class. Sensitivity measures the proportion of actual retentions which are correctly identified as such. Specificity measures the proportion of churns which are correctly identified as such. The poor performance of the classification techniques on imbalanced data sets is due to the low value of specificity. Many previous researches on imbalanced data sets employed 'oversampling' technique where members of the minority class are sampled more than those of the majority class in order to make a relatively balanced data set. When a classification model is constructed using this oversampled balanced data set, specificity can be improved but sensitivity will be decreased. In this research, we developed a hybrid model of support vector machine (SVM), artificial neural network (ANN) and decision tree, that improves specificity while maintaining sensitivity. We named this hybrid model 'hybrid SVM model.' The process of construction and prediction of our hybrid SVM model is as follows. By oversampling from the original imbalanced data set, a balanced data set is prepared. SVM_I model and ANN_I model are constructed using the imbalanced data set, and SVM_B model is constructed using the balanced data set. SVM_I model is superior in sensitivity and SVM_B model is superior in specificity. For a record on which both SVM_I model and SVM_B model make the same prediction, that prediction becomes the final solution. If they make different prediction, the final solution is determined by the discrimination rules obtained by ANN and decision tree. For a record on which SVM_I model and SVM_B model make different predictions, a decision tree model is constructed using ANN_I output value as input and actual retention or churn as target. We obtained the following two discrimination rules: 'IF ANN_I output value <0.285, THEN Final Solution = Retention' and 'IF ANN_I output value ${\geq}0.285$, THEN Final Solution = Churn.' The threshold 0.285 is the value optimized for the data used in this research. The result we present in this research is the structure or framework of our hybrid SVM model, not a specific threshold value such as 0.285. Therefore, the threshold value in the above discrimination rules can be changed to any value depending on the data. In order to evaluate the performance of our hybrid SVM model, we used the 'churn data set' in UCI Machine Learning Repository, that consists of 85% retention customers and 15% churn customers. Accuracy of the hybrid SVM model is 91.08% that is better than that of SVM_I model or SVM_B model. The points worth noticing here are its sensitivity, 95.02%, and specificity, 69.24%. The sensitivity of SVM_I model is 94.65%, and the specificity of SVM_B model is 67.00%. Therefore the hybrid SVM model developed in this research improves the specificity of SVM_B model while maintaining the sensitivity of SVM_I model.

• Journal of Korea Society of Industrial Information Systems
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• v.24 no.4
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• pp.65-77
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• 2019

Adolescents reach the game-use states of adaptive and maladaptive by the absorption to computer game. Authors claimed that the two states are commonly related with the time of game-use, and the degree of them are distinctive according to adolescent individuals, specifically their self-control propensity. Authors proposed a conceptual research model that Big Five personality types predict their self-control which moderates the relationships from game use-time to the maladaptive and adaptive states. The data to test its validity and reliability had been sampled 999 Korean students in elementary school, middle school, and high school. Resultingly, the openness and conscientiousness of the adolescents affected positively on the self-control, which moderated negatively the relationship from the game use time to the maladaptive use state, but the positive moderation on the relationships from game use time to adpative state was not significant. These results mean that we could apply teenager's Big Five personality type and their self-control traits as a tool for preventing teens from the overuse state like addiction.

• Asian-Australasian Journal of Animal Sciences
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• v.21 no.4
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• pp.523-531
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• 2008

Buffalo are a major source of milk production, contributing 12.1% in the World and 38.0% in Asia. The buffaloes are kept under peri-urban farming systems to produce milk for urban populations. Breeding is delayed in these herds to get more economic benefit because farmers believe that the pregnancy decreases milk production. The lactation milk value has been studied in this paper as an economic indicator. Complete milk yield records of 3,304 buffaloes was collected from a group of state farms. Economic traits including lactation yield, lactation length, calving interval (CI), dry period and milk yield per day of calving interval (MYPDCI) were derived from the data. The animals were grouped according to parity number (1-3), service period (G1 to G4, conceiving during <150, 150-200, 200-300 and >300 days post calving) and yield levels (HMY>2,500; MMY 2,001-2,500; and LMY 1,500-2,000 liters/ lactation). To study the effect of pregnancy on milk composition a research trial was conducted at a medium size private dairy farm, using forty lactating buffaloes of three yield levels and four service period groups, as described already. Milk was sampled on alternate weeks and analyzed for fat and protein contents (%). For quantifying the value of milk produced during a lactation period, the value corrected milk (VCM) was determined and converted to lactation milk value (LMV). Group means were compared for varicous parameters. Highest milk yield ($2,836.50{\pm}15.68$ liters/lactation) was recorded in the HMY animals of G4 group while lowest milk yield of $1,657.04{\pm}8.34$ liters/lactation was found in LMY of G1. Lactation was significantly increased with the extending of service period. The shortest dry period was recorded in HMY, parity 1, G1 animals and the longest in parity 2, MMY, G4.The CI was shortest in HMY, parity 1, and G1 animals and longest in LMY, parity 3, G4 buffaloes. The HMY, parity 2, G1 buffaloes showed the highest MYPDCI and the lowest value was recorded ($6.53{\pm}0.17$ vs. $2.76{\pm}0.04$ liter/day) for LMY, parity 1, G4 buffaloes. The VCM decreased with the delayed conception. This decreasing trend was higher in respect of the total yield but decrease in the VCM was smaller due to the increasing levels of fat and protein in the milk. The gap between the various production classes was reduced based on the VCM as compared with the yield per day of CI. LMV showed a consistent decline with extending service period in all three production groups. The study suggests that CI increased with delayed conception, showing a consistent trend in the low, moderate and high yielding buffaloes. There was a coherent declining pattern of milk yield with delaying conception, associated with prolonged CI. An animal conceiving at a later stage of lactation showed a decline in financial returns of 24 to 27% compared with those conceiving earlier.

• Journal of Intelligence and Information Systems
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• v.22 no.4
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• pp.69-85
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• 2016

Successful relationship with loving partners is one of the most important factors in life. In psychology, there have been some previous researches studying the factors influencing romantic relationships. However, most of these researches were performed based on statistical analysis; thus they have limitations in analyzing complex non-linear relationships or rules based reasoning. This research analyzes commitment and persistence in heterosexual involvement according to styles of loving using a datamining technique as well as statistical methods. In this research, we consider six different styles of loving - 'eros', 'ludus', 'stroge', 'pragma', 'mania' and 'agape' which influence romantic relationships between lovers, besides the factors suggested by the previous researches. These six types of love are defined by Lee (1977) as follows: 'eros' is romantic, passionate love; 'ludus' is a game-playing or uncommitted love; 'storge' is a slow developing, friendship-based love; 'pragma' is a pragmatic, practical, mutually beneficial relationship; 'mania' is an obsessive or possessive love and, lastly, 'agape' is a gentle, caring, giving type of love, brotherly love, not concerned with the self. In order to do this research, data from 105 heterosexual couples were collected. Using the data, a linear regression method was first performed to find out the important factors associated with a commitment to partners. The result shows that 'satisfaction', 'eros' and 'agape' are significant factors associated with the commitment level for both male and female. Interestingly, in male cases, 'agape' has a greater effect on commitment than 'eros'. On the other hand, in female cases, 'eros' is a more significant factor than 'agape' to commitment. In addition to that, 'investment' of the male is also crucial factor for male commitment. Next, decision tree analysis was performed to find out the characteristics of high commitment couples and low commitment couples. In order to build decision tree models in this experiment, 'decision tree' operator in the datamining tool, Rapid Miner was used. The experimental result shows that males having a high satisfaction level in relationship show a high commitment level. However, even though a male may not have a high satisfaction level, if he has made a lot of financial or mental investment in relationship, and his partner shows him a certain amount of 'agape', then he also shows a high commitment level to the female. In the case of female, a women having a high 'eros' and 'satisfaction' level shows a high commitment level. Otherwise, even though a female may not have a high satisfaction level, if her partner shows a certain amount of 'mania' then the female also shows a high commitment level. Finally, this research built a prediction model to establish whether the relationship will persist or break up using a decision tree. The result shows that the most important factor influencing to the break up is a 'narcissistic tendency' of the male. In addition to that, 'satisfaction', 'investment' and 'mania' of both male and female also affect a break up. Interestingly, while the 'mania' level of a male works positively to maintain the relationship, that of a female has a negative influence. The contribution of this research is adopting a new technique of analysis using a datamining method for psychology. In addition, the results of this research can provide useful advice to couples for building a harmonious relationship with each other. This research has several limitations. First, the experimental data was sampled based on oversampling technique to balance the size of each classes. Thus, it has a limitation of evaluating performances of the predictive models objectively. Second, the result data, whether the relationship persists of not, was collected relatively in short periods - 6 months after the initial data collection. Lastly, most of the respondents of the survey is in their 20's. In order to get more general results, we would like to extend this research to general populations.