• Journal of Intelligence and Information Systems
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• v.26 no.4
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• pp.149-171
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• 2020

The period at university is to make decision about getting an actual job. As our society develops rapidly and highly, jobs are diversified, subdivided, and specialized, and students' job preparation period is also getting longer and longer. This study analyzed the log data of college students to see how the various activities that college students experience inside and outside of school might have influences on employment. For this experiment, students' various activities were systematically classified, recorded as an activity data and were divided into six core competencies (Job reinforcement competency, Leadership & teamwork competency, Globalization competency, Organizational commitment competency, Job exploration competency, and Autonomous implementation competency). The effect of the six competency levels on the employment status (employed group, unemployed group) was analyzed. As a result of the analysis, it was confirmed that the difference in level between the employed group and the unemployed group was significant for all of the six competencies, so it was possible to infer that the activities at the school are significant for employment. Next, in order to analyze the impact of the six competencies on the qualitative performance of employment, we had ANOVA analysis after dividing the each competency level into 2 groups (low and high group), and creating 6 groups by the range of first annual salary. Students with high levels of globalization capability, job search capability, and autonomous implementation capability were also found to belong to a higher annual salary group. The theoretical contributions of this study are as follows. First, it connects the competencies that can be extracted from the school experience with the competencies in the Human Resource Management field and adds job search competencies and autonomous implementation competencies which are required for university students to have their own successful career & life. Second, we have conducted this analysis with the competency data measured form actual activity and result data collected from the interview and research. Third, it analyzed not only quantitative performance (employment rate) but also qualitative performance (annual salary level). The practical use of this study is as follows. First, it can be a guide when establishing career development plans for college students. It is necessary to prepare for a job that can express one's strengths based on an analysis of the world of work and job, rather than having a no-strategy, unbalanced, or accumulating excessive specifications competition. Second, the person in charge of experience design for college students, at an organizations such as schools, businesses, local governments, and governments, can refer to the six competencies suggested in this study to for the user-useful experiences design that may motivate more participation. By doing so, one event may bring mutual benefits for both event designers and students. Third, in the era of digital transformation, the government's policy manager who envisions the balanced development of the country can make a policy in the direction of achieving the curiosity and energy of college students together with the balanced development of the country. A lot of manpower is required to start up novel platform services that have not existed before or to digitize existing analog products, services and corporate culture. The activities of current digital-generation-college-students are not only catalysts in all industries, but also for very benefit and necessary for college students by themselves for their own successful career development.

• Journal of Distribution Research
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• v.15 no.4
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• pp.1-19
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• 2010

As having the movement of developing private brand (PB) goods, domestic big retailers are facing up with new problems. Thus, it is required studies of PB products, and how consumers recognize PB products as a consideration commodity set. Also, it is worthy in order that it gives us the important meaning on the marketing strategy with focusing on evaluating the differences between customers buying PB grocery goods with respect to demographic characteristics and purchasing behaviors. PB has some advantages for customers and retailers. However, according to AC Nielson's report (2005), Asian and emerging market has 1/5 sales relatively to Western countries. But we can assume that the emerging market has the most potential growth through this result. As a result from several other studies, it becomes necessary to not only increase the rate of selling composition of PB product temporarily, but also analyze the characteristics of customers using big retailers and segmenting customer groups to make PB product as a consideration commodity set for them. In addition, it is needed to have a variety of acts of marketing. From studies related to PB, there is a prejudice - cheap products have low quality - but, evaluation by customers who have used those products shows neutral stand, and there is a study representing that it is the most important to accumulate the belief between the retailers selling PB products and consumers using those for the accurate evaluation and intention on purchasing. Also, by the result from analyzing the characteristics of customers buying PB products, we could assume that higher income and higher education level, more preference on PB products. Especially, according to TNS's research, the primary targets of PB product are 30's who seeks value for money and planned spending habits, and 40's who have teenager children, and are interested in encouraging themselves. This paper used Probit model to analyze the characteristics of consumers. This model helps us to analyze with the variables representing the demographic characteristics of consumers (gender, age, educational level, occupation, income level, living area), and variables related to purchasing behavior (visiting frequency on big retailers, the average amount that they pay for goods in there, and check-up which brand made those goods). The method we used in this study is by man to man interview and survey on-line with the rate of 89% and 11% in Seoul and Gyunggi Province, respectively, for about one month from the beginning of February, 2008. As a result of this, under the assumption that people buy PB products more as long as they go shopping more, it was not meaningful for target groups which we pointed out as frequently visiting customers to be. Although, we have expected women buy more PB products than men do, gender doesn't mean anything for the result. And, it has inferred that married people buy more PB goods than singles do. It was also meaningless with variables related to occupation. Because housewives are often exposed to any kind of supermarket than workers are, we could not get any relatives. Moreover, we couldn't proof that younger generation prefer big retailers more than older people who 50~60's. Education levels doesn't affect on the purchase of PB product as well. Related to living area, the result is statistically not similar as we expected whether living in Seoul or not. It shows there is no relationship with the preference on retail brands and PB products, and it is similar with the study researched by TNS(2008) that customers tend to buy PB product impulsively no matter which brand it is and where they are even though their shopping place is the big market where customers are often using. Variables on which we had meaningful results are income level and living place. That is, customers who have 3,000,000~6,000,000 WON every month on average are more willing to buy PB products than other customers whose income is over 6,000,000 WON, and residents not living in Seoul prefer PB goods than those who are living in Seoul. To explain more about what we got, if there is only one condition about customer's visiting frequency on big retails, we could come up with this result that more exposed to PB products, more purchasing frequency. Consequently, it brings the important insight that large retailers have to prepare something to make customers visit them often to increase selling rate of PB products. To demonstrate the result of analyzing more, what is more efficient variables are demographically including marital status, income level, and residential area to buy items that affect the PB products and could include the frequency of visiting large markets by the purchase habits. Specifically, then, married couples rather than singles, middle-income customers than high-income customers, and local residents not living in Seoul than customers in Seoul are more likely to purchase PB goods. In addition, as long as a customer visits two times more, then the purchasing rate of PB products is to increase over 5.3%. Therefore, it seems that retailers are better to make a shopping place as fun and comfortable places. With overwhelming the idea that PB products are just cheap, one-time purchase goods, it is needed to increase the loyalty on those goods like NB products, try to make PB products as a consideration products set, and occur to sustainable sales. Especially, as suggested by this paper, it seems like it strongly needs to identify the characteristics of customers who prefer PB, to segment those customers, and to select the main target, and to do positioning with well-planned marketing strategies. Then, it is able to give us a meaningful point on marketing strategy by developing the field of PB study, identifying the difference of life style and shopping habits of customers.

• Korean Journal of Breeding Science
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• v.43 no.3
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• pp.165-171
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• 2011

A new rice variety 'Jinbo' is a japonica rice (Oryza sativa L.) with good eating quality, lodging tolerance, and resistance to rice stripe virus (RSV) and bacterial blight disease (BB). It was developed by the rice breeding team of Yeongdeog Substation, National Institute of Crop Science (NICS), RDA in 2009. This variety was derived from a cross between 'Yeongdeog26' with good grain quality and wind tolerance and 'Koshihikari' with good eating quality in 1998 summer season. A promising line, YR21324-56-1-1, selected by pedigree breeding method, was designated as the name of 'Yeongdeog45' in 2005. After the local adaptability test was carried out at nine locations from 2006 to 2008, 'Yeongdeog45' was released as the name of 'Jinbo' in 2009. 'Jinbo' has short culm length as 74 cm and medium maturating growth duration. This variety is resistant to $K_1$, $K_2$, and $K_3$ races of bacterial blight and stripe virus and moderately resistant to leaf blast disease with durable resistance, and also it has tolerance to unfavorable environments such as cold and dried wind. 'Jinbo' has translucent and clear milled rice kernel without white core and white belly rice, and good eating quality as a result of panel test. The yield potential of 'Jinbo' in milled rice is about 5.65 MT/ha at ordinary fertilizer level in local adaptability test. This cultivar would be adaptable to middle plain, mid-west costal area, east-south coastal area, and south mid-mountainous area.

• Korean Journal of Breeding Science
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• v.42 no.6
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• pp.638-644
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• 2010

A new rice variety 'Haeoreumi' is a japonica rice (Oryza sativa L.) with lodging tolerance, resistance to rice stripe virus (RSV) and bacterial leaf blight (BLB), and high grain quality. It was developed by the rice breeding team of Yeongdeog Substation, National Institute of Crop Science (NICS), RDA in 2008. This variety was derived from a cross between 'Milyang165' with good grain quality and lodging resistance, and 'Haepyeongbyeo' with wind tolerance in winter season of 2000/2001. A promising line, YR22375-B-B-1, selected by pedigree breeding method, was designated as the name of 'Yeongdeog46' in 2005. 'Yeongdeog46' was released as the name of 'Haeoreumi' in 2008 after the local adaptability test that was carried out at nine locations from 2006 to 2008. 'Haeoreumi' has 74 cm short culm length as and medium maturating growth duration. This variety showed resistance to $K_1,\;K_2$, and $K_3$ races of bacterial blight, and stripe virus and moderate resistant to leaf blast disease with durable resistance, and also has tolerance to unfavorable environment such as cold, dry and cold salty wind. 'Haeoreumi' has translucent and clear milled rice kernel without white core and white belly rice, and good eating quality as a result of panel test. The yield potential of 'Haeoreumi' in milled rice is about 5.58MT/ha at ordinary fertilizer level of local adaptability test. This cultivar would be adaptable to Middle plain, mid-west costal area, and east-south coastal area.

• Journal of Korean Society of Occupational and Environmental Hygiene
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• v.25 no.3
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• pp.380-391
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• 2015

Objectives: The objective of this study is to assess airborne particulate matter pollution and its effect on health of residents living near Ansim Briquette Fuel Complex and its vicinities. Also, this study measured and analyzed the concentration of TSP, $PM_{10}$, $PM_{2.5}$, and heavy metals which influences on the environmental and respiratory disease in Ansim Briquette Fuel Complex, Daegu, Korea. Methods: In this study, we analyzed various environmental pollutants such as particulate matter and heavy metals from Ansim Briquette Fuel Complex that adversely affected local residents's health. In particular, we verified the concentration distribution and characteristics of exposure for TSP, $PM_{10}$, and $PM_{2.5}$ among particulate matters, and heavy metals(Cd, Cr, Cu, Mn, Ni, Pb, Fe, Zn, and Mg). In that regard, the official test method on air pollution in Korea for analysis of particulate matter and heavy metal in atmosphere were conducted. The large capacity air sampling method by the official test method on air pollution in Korea were applied for sampling of heavy metals in atmosphere. In addition, we evaluated the concentration of seasonal environmental pollutants for each point of residence in Ansim Briquette Fuel Complex and surrounding area. The sampling measured periods for air pollutants were from August 11, 2013 to February 21, 2014. Furthermore, we measured and analyzed the seasonal concentrations(summer, autumn and winter). Results: The average concentration for TSP, $PM_{10}$, and $PM_{2.5}$ by direct influence area at Ansim Briquette Fuel Complex were 1.7, 1.4 and 1.9 times higher than reference region. In analysis results of seasonal concentrations for particulate matter in four direct influence and reference area, concentration levels for winter were generally somewhat higher than concentrations for summer and autumn. The average concentrations for Cd, Cr, Mn, Ni, Pb, Fe, and Zn in direct influence area at Ansim Briquette Fuel Complex were $0.0008{\pm}0.0004{\mu}g/Sm^3$, $0.0141{\pm}0.0163{\mu}g/Sm^3$, $0.0248{\pm}0.0059{\mu}g/Sm^3$, $0.0026{\pm}0.0011{\mu}g/Sm^3$, $0.0272{\pm}0.0084{\mu}g/Sm^3$, $0.4855{\pm}0.1862{\mu}g/Sm^3$, and $0.3068{\pm}0.0631{\mu}g/Sm^3$, respectively. In particularly, the average concentrations for Cd, Cr, Mn, Ni, Pb, Fe, and Zn in direct influence area at Ansim Briquette Fuel Complex were 1.9, 3.6, 2.1, 1.9, 1.4, 2.6, and 1.2 times higher than reference area, respectively. The continuous monitoring and management were required for some heavy metals such as Cr and Ni. Moreover, the average concentration in winter for particulate matter in direct influence area at Ansim Briquette Fuel Complex were generally higher than concentrations in summer and autumn. Also, average concentrations for TSP, $PM_{10}$, and $PM_{2.5}$ were from 1.5 to 2.0 times, 1.2 to 1.8 times, and 1.1 to 2.3 times higher than reference area, respectively. In results for seasonal atmospheric environment, TSP, $PM_{10}$, $PM_{2.5}$, and heavy metal concentrations in direct influence area were higher than reference area. Especially, the concentrations in C station were a high level in comparison with other area. Conclusions: In the results, some particulate matters and heavy metals were relatively high concentration, in order to understand the environmental pollution level and health effect in surrounding area at Ansim Briquette Fuel Complex. The concentration of some heavy metals emitted from direct influence area at Ansim Briquette Fuel Complex were relatively higher than reference area. In particular, average concentration for heavy metals in this study were higher than average concentrations in air quality monitoring station for heavy metal for 7 years in Deagu metropolitan region. Especially, the residents near Ansim Briquette Fuel Complex may be exposed to the pollutants(TSP, $PM_{10}$, $PM_{2.5}$, and heavy metals, etc) emitted from the factories in Ansim Briquette Fuel Complex.

• Information Systems Review
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• v.16 no.3
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• pp.161-177
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• 2014

Corporate credit rating assessment consists of complicated processes in which various factors describing a company are taken into consideration. Such assessment is known to be very expensive since domain experts should be employed to assess the ratings. As a result, the data-driven corporate credit rating prediction using statistical and artificial intelligence (AI) techniques has received considerable attention from researchers and practitioners. In particular, statistical methods such as multiple discriminant analysis (MDA) and multinomial logistic regression analysis (MLOGIT), and AI methods including case-based reasoning (CBR), artificial neural network (ANN), and multiclass support vector machine (MSVM) have been applied to corporate credit rating.2) Among them, MSVM has recently become popular because of its robustness and high prediction accuracy. In this study, we propose a novel optimized MSVM model, and appy it to corporate credit rating prediction in order to enhance the accuracy. Our model, named 'GAMSVM (Genetic Algorithm-optimized Multiclass Support Vector Machine),' is designed to simultaneously optimize the kernel parameters and the feature subset selection. Prior studies like Lorena and de Carvalho (2008), and Chatterjee (2013) show that proper kernel parameters may improve the performance of MSVMs. Also, the results from the studies such as Shieh and Yang (2008) and Chatterjee (2013) imply that appropriate feature selection may lead to higher prediction accuracy. Based on these prior studies, we propose to apply GAMSVM to corporate credit rating prediction. As a tool for optimizing the kernel parameters and the feature subset selection, we suggest genetic algorithm (GA). GA is known as an efficient and effective search method that attempts to simulate the biological evolution phenomenon. By applying genetic operations such as selection, crossover, and mutation, it is designed to gradually improve the search results. Especially, mutation operator prevents GA from falling into the local optima, thus we can find the globally optimal or near-optimal solution using it. GA has popularly been applied to search optimal parameters or feature subset selections of AI techniques including MSVM. With these reasons, we also adopt GA as an optimization tool. To empirically validate the usefulness of GAMSVM, we applied it to a real-world case of credit rating in Korea. Our application is in bond rating, which is the most frequently studied area of credit rating for specific debt issues or other financial obligations. The experimental dataset was collected from a large credit rating company in South Korea. It contained 39 financial ratios of 1,295 companies in the manufacturing industry, and their credit ratings. Using various statistical methods including the one-way ANOVA and the stepwise MDA, we selected 14 financial ratios as the candidate independent variables. The dependent variable, i.e. credit rating, was labeled as four classes: 1(A1); 2(A2); 3(A3); 4(B and C). 80 percent of total data for each class was used for training, and remaining 20 percent was used for validation. And, to overcome small sample size, we applied five-fold cross validation to our dataset. In order to examine the competitiveness of the proposed model, we also experimented several comparative models including MDA, MLOGIT, CBR, ANN and MSVM. In case of MSVM, we adopted One-Against-One (OAO) and DAGSVM (Directed Acyclic Graph SVM) approaches because they are known to be the most accurate approaches among various MSVM approaches. GAMSVM was implemented using LIBSVM-an open-source software, and Evolver 5.5-a commercial software enables GA. Other comparative models were experimented using various statistical and AI packages such as SPSS for Windows, Neuroshell, and Microsoft Excel VBA (Visual Basic for Applications). Experimental results showed that the proposed model-GAMSVM-outperformed all the competitive models. In addition, the model was found to use less independent variables, but to show higher accuracy. In our experiments, five variables such as X7 (total debt), X9 (sales per employee), X13 (years after founded), X15 (accumulated earning to total asset), and X39 (the index related to the cash flows from operating activity) were found to be the most important factors in predicting the corporate credit ratings. However, the values of the finally selected kernel parameters were found to be almost same among the data subsets. To examine whether the predictive performance of GAMSVM was significantly greater than those of other models, we used the McNemar test. As a result, we found that GAMSVM was better than MDA, MLOGIT, CBR, and ANN at the 1% significance level, and better than OAO and DAGSVM at the 5% significance level.

• Journal of the Korean Society of Food Culture
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• v.32 no.5
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• pp.383-393
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• 2017

This study was conducted to analyze the dietary lifestyle of local Chinese consumers and to classify dietary characteristics according to their dietary lifestyle factors and dietary behaviors. This investigation was conducted for 1 month from 1 January 2017 targeting 300 adult males and females living in China using the online survey company surveymonkey. Four factors relating to dietary lifestyle were identified, gourmet factor, healthy factor, convenience factor and economic factor, and these were grouped into 4 clusters according to their dietary lifestyle factor scores. Group 1, the gourmet economy group, showed a high percentage of living alone and a high frequency of eating out, but a relatively low percentage of three regular meals per day. Their dietary lifestyle was sensitive to gourmet factors and economic factors, but less sensitive to health and convenience factors. Group 2, the wide interest group, contained a high percentage of individuals in their 30s, as well as more highly educated individuals and a higher income than other groups. Because their dietary lifestyle scores tended to be higher than those of other groups, they sought a variety of new foods and gourmet meals for enjoyment of dining and life, as well as well-being food materials and foods related to health. Group 3, the health economic group, constituted a family-type consumer group with lower income level than the other groups. Members of this group were seeking health food and natural food in their dietary lifestyle and tended to pursue a high economic profit ratio when purchasing food. Finally, group 4 showed a relatively higher percentage of women over 30 and individuals with a college level or higher education than the other groups. This group was more interested in health and taste than price and convenience, and showed the highest LOHAS orientation among middle aged Chinese women. Moreover, members of this group directly utilized their knowledge regarding nutrition in real life.

• Radiation Oncology Journal
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• v.17 no.3
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• pp.195-202
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• 1999

Purpose : We peformed this study to evaluate the prognostic factors and the effect of induction chemotherapy in locally advanced non-small cell lung cancer (NSCLC). Materials and Methods : A retrospective analysis was done for 130 patients with locally advanced NSCLC treated with curative radiotherapy alone or induction chemo-radiotherapy from January 1986 to October 1996. Eighty-five patients were treated with radiotherapy alone, forty-five with induction chemotherapy and radiotherapy. Age, sex, performance status, histopathologic type, and stage were evenly distributed in both groups. The patients were treated with 6 MV or 10 MV X-ray. Conventional fractionation with daily fraction size 1$.8\~2.0$ Gy was done. Of the patients, 129 patients received total dose above 59.6 Gy ($56\~66$ Gy, median 60 Gy). Induction chemotherapy regimen were CAP (Cyclo-phosphamide, Adriamycin, Cisplatin) in 6 patients, MVP (Mitomycin, Vinblastine, Cisplatin) in 9 patients, MIC (Mitomycin, Ifosfamide Cisplatin) in 13 patients, and EP (Etoposide, Cisplatin) in 17 patients. Chemotherapy was done in $2\~5$ cycles (median 2). Results : Overall 1-, 2-, and 3-year survival rate (YSR) for all patients were $41.5\%,{\;}13.7\%,{\;}and{\;}7\%$, respectively (median survival time 11 months). According to treatment modality, median survival time, overall 1-, 2-, and 3-YSR were 9 months, $32.9\%,{\;}10.\5%,{\;}6\%$ for radiotherapy alone group, and 14 months, $57.8\%,{\;}20\%,{\;}7.6\%$ for induction chemotherapy group, respectively (f=0.0005). Complete response (CR) to overall treatments was $25\%$ (21/84) in radiotherapy alone and $40.5\%$ (17/42) in induction chemotherapy group (p=0.09). The Prognostic factors affecting overall survival were hemoglobin level (p=0.04), NSE (neuron-specific enolase) level (p=0.004), and respense to overall treatment(p=0.004). According to treatment modalities, NSE (neuron-specific enolase) (p=0.006) and response to overall treatment (p=0.003) were associated with overall survival in radiotherapy alone group, and response to overall treatment (p=0.007) in induction chemotherapy group. The failure Pattern analysis revealed no significant difference between treatment modalities. But, in patients with CR to overall treatment, distant metastasis were found in 11/19 patients with radiotherapy alone, and 3/13 patients with induction chemotherapy and radiotherapy (p=0.07). Locoregional failure patterns were not different between two groups (10/19 vs 6/13). Conclusion : Induction chemotherapy and radiotherapy achieved increased 2YSR compared to radiotherapy alone, At least in CR patients, there was decreased tendency in distant metastasis with induction chemotherapy. But, locoregional failures and long-term survival were not improved. Thus, there is need of more effort to increasing local control and further decreasing distant metastasis.

• Journal of Acupuncture Research
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• v.17 no.2
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• pp.187-208
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• 2000

By the activation of ovary hormone, many morphological changes occur in the epithelial cell lines and muscle cells in rat uterus. These two cells in uterus are important to the implantation of embryo, maintaining pregnancy and starting parturition. One important change associated with the morphological change of these two cells in uterus is the change on prostaglandin(PG) metabolism. Its presence and synthesis in endometriurn and myometrium in uterus affects estrous cycle and the start of embryo implantation in uterus. It also performs as an important modulator in parturition. So the abnormally weak expression of PG causes difficulty during labor and over-expression causes pre-term labor. PG biosynthesis starts from either free or liberated arachidonic acids from membrane phospholipid by phospholipase. Such arachidonic acids are converted into PG catalyzed by Cyclooxygenase. Under normal physiological condition, Cyclooxygenase-1(COX-1) having 602 units of amino acids controls the synthesis of PG. It acts as a local hormone regulating vasomodulation of blood flow, flexible muscle movement, increasing the blood permeability and contributing the protective role in preserving integrity of the stomach lining and Cyclooxygenase-2 (COX-2) is induced by the inflammation, pregnancy and increased its expression until parturition. Lipid metabolite like PG is located in uterine and expression of COX-2 increased with pregnancy. Increased expression of COX proteins in epithelial cells and myometrial cells are told to increase the muscle contractility in uterus but decreased right after the labor in rat. It is a good sign indicating that COX proteins are deeply related to the start of labor. Currently, Several studies report the use of PG and COX-2 inhibitor as medication for controlled abortion or to prevent pre-term labor but they entail various side-effects. Our study proposed to suggest use of acupuncture as an another mediator to control abortion or pre-term labor without causing unnecessary side-effects by those medicines. Two acupuncture sites, LI-4 & SP-6 were selected due to their known efficacy. From the immunohistochemical staining of COX-2, normal expression of COX-2 protein in nonpregnant SD rat's uterus revealed that COX-2 protein was primarily detected in the lumina epithelial lining and in the epithelial cell lining contacting the stromal cells. High resolution optical microscopic scanning revealed distinguishable staining in the myometrial mucosa. LI-4 acupuncture administered nonpregnant rat's uterus showed strong expression for COX-2 in endometrium contacted with lumina epithelial lining of rat uterus and in myometrial mucosa. Stromal cells showed more staining than untreated nonpregnant rat's uterus and stronger staining in stromal cells contacting myometrial layer compared to untreated nonpregnant rat's uterus. SP-6 acupuncture administered nonpregnant rat's uterus showed weak expression for COX-2 in myometrial layers and stromal cells but no staining was visible in lumina epitheliai and glandular epithelial cells. Few stromal cells and myometrial mucosa were positively stained for COX-2. Pregnant SD rat's uterus was also immunostained for COX-2 expression after 18 days of pregnancy. Unlike to untreated nonpregnant rat's uterus, luminal epithelial cells were not positively stained for COX-2 but stronger staining for COX-2 was revealed in stromal cells. LI-4 acupunctured SD rat's uterus had very strong expression of COX-2 in luminal epithelial lining. Few stromal cells showed stronger positive COX-2 staining and myometrial layers also showed more expression than untreated pregnant rat. SP-6 acupuncture administered pregnant SD rat's uterus showed positive expression of COX-2 in epithelial cells of luminal mucosa layer but weaker than that of LI-4 acupuncture treatment's case. However, strong positive staining was revealed in stromal mucosa and myometrial layers. Virgin SD rat's uterus motility index during LI-4 acupuncture was 66.52 % (Prob〉T = 0.0197) compared to its motility before the acupuncture treatment but the motility index was slighdy elevated up to 79.58 % (Prob〉T = 0.1175) after the acupuncture. During the SP-6 acupuncture treatment for 30 minutes, uterus motility index was 90.52 % (Prob〉T = 0.1832) showing lesser decrement but consequently reached similar motility index decreasal to 79.95 % (Prob〉T = 0.0215) after the acupuncture treatment as LI-4 showed. LI-4 acupuncture tend to be a quick treatment to reducing the uterus motility in a virgin rat but eventually both two acupuncture administration created very similar reduction of uterus motility seeing the index after the both acupunctures. The uterus movement monitored during the LI-4 acupuncture administered for 30 minutes, Pregnant SD rat showed decreased motility down to 77.90 % (Prob〉 T = 0.0076) compared to uterus motility before the acupuncture and it continuously decreased down to 71.81 %(Prob〉T = 0.0214) after the removal of needle. The statistical analysis using paired t-test showed significance difference for both two motility indexs at =0.05. SP-6 acupuncture administered to pregnant SD rat also had similar pattern of decreasing uterus motility index down to 74.70 % (Prob〉T = 0.1730) during the initial 30 minutes acupuncture administration and it was continuously lowered to 71.52 % (Prob〉T = 0.0155) after the acupuncture. The paired t-test resuit for SP-6 suggest prompt response of uterus motility index to the SP-6 acupuncture treatment but consequently reached same level of inducing the motility reduction as LI-4 at =0.05 level.

• Journal of Intelligence and Information Systems
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• v.25 no.1
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• pp.163-177
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• 2019

As smartphones are getting widely used, human activity recognition (HAR) tasks for recognizing personal activities of smartphone users with multimodal data have been actively studied recently. The research area is expanding from the recognition of the simple body movement of an individual user to the recognition of low-level behavior and high-level behavior. However, HAR tasks for recognizing interaction behavior with other people, such as whether the user is accompanying or communicating with someone else, have gotten less attention so far. And previous research for recognizing interaction behavior has usually depended on audio, Bluetooth, and Wi-Fi sensors, which are vulnerable to privacy issues and require much time to collect enough data. Whereas physical sensors including accelerometer, magnetic field and gyroscope sensors are less vulnerable to privacy issues and can collect a large amount of data within a short time. In this paper, a method for detecting accompanying status based on deep learning model by only using multimodal physical sensor data, such as an accelerometer, magnetic field and gyroscope, was proposed. The accompanying status was defined as a redefinition of a part of the user interaction behavior, including whether the user is accompanying with an acquaintance at a close distance and the user is actively communicating with the acquaintance. A framework based on convolutional neural networks (CNN) and long short-term memory (LSTM) recurrent networks for classifying accompanying and conversation was proposed. First, a data preprocessing method which consists of time synchronization of multimodal data from different physical sensors, data normalization and sequence data generation was introduced. We applied the nearest interpolation to synchronize the time of collected data from different sensors. Normalization was performed for each x, y, z axis value of the sensor data, and the sequence data was generated according to the sliding window method. Then, the sequence data became the input for CNN, where feature maps representing local dependencies of the original sequence are extracted. The CNN consisted of 3 convolutional layers and did not have a pooling layer to maintain the temporal information of the sequence data. Next, LSTM recurrent networks received the feature maps, learned long-term dependencies from them and extracted features. The LSTM recurrent networks consisted of two layers, each with 128 cells. Finally, the extracted features were used for classification by softmax classifier. The loss function of the model was cross entropy function and the weights of the model were randomly initialized on a normal distribution with an average of 0 and a standard deviation of 0.1. The model was trained using adaptive moment estimation (ADAM) optimization algorithm and the mini batch size was set to 128. We applied dropout to input values of the LSTM recurrent networks to prevent overfitting. The initial learning rate was set to 0.001, and it decreased exponentially by 0.99 at the end of each epoch training. An Android smartphone application was developed and released to collect data. We collected smartphone data for a total of 18 subjects. Using the data, the model classified accompanying and conversation by 98.74% and 98.83% accuracy each. Both the F1 score and accuracy of the model were higher than the F1 score and accuracy of the majority vote classifier, support vector machine, and deep recurrent neural network. In the future research, we will focus on more rigorous multimodal sensor data synchronization methods that minimize the time stamp differences. In addition, we will further study transfer learning method that enables transfer of trained models tailored to the training data to the evaluation data that follows a different distribution. It is expected that a model capable of exhibiting robust recognition performance against changes in data that is not considered in the model learning stage will be obtained.