• Journal of the Korean Geographical Society
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• v.40 no.3 s.108
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• pp.296-309
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• 2005

In this study, we investigated the change of future land-surface and relationships of land-surface change with geo-spatial information, using a Bayesian prediction model based on a likelihood ratio function, for analysing the land-surface change of the Gongju area. We classified the land-surface satellite images, and then extracted the changing area using a way of post classification comparison. land-surface information related to the land-surface change is constructed in a GIS environment, and the map of land-surface change prediction is made using the likelihood ratio function. As the results of this study, the thematic maps which definitely influence land-surface change of rural or urban areas are elevation, water system, population density, roads, population moving, the number of establishments, land price, etc. Also, thematic maps which definitely influence the land-surface change of forests areas are elevation, slope, population density, population moving, land price, etc. As a result of land-surface change analysis, center proliferation of old and new downtown is composed near Gum-river, and the downtown area will spread around the local roads and interchange areas in the urban area. In case of agricultural areas, a small tributary of Gum-river or an area of local roads which are attached with adjacent areas showed the high probability of change. Most of the forest areas are located in southeast and from this result we can guess why the wide chestnut-tree cultivation complex is located in these areas and the capability of forest damage is very high. As a result of validation using a prediction rate curve, a capability of prediction of urban area is $80\%$, agriculture area is $55\%$, forest area is $40\%$ in higher $10\%$ of possibility which the land-surface change would occur. This integration model is unsatisfactory to Predict the forest area in the study area and thus as a future work, it is necessary to apply new thematic maps or prediction models In conclusion, we can expect that this way can be one of the most essential land-surface change studies in a few years.

• Journal of the Korean Institute of Landscape Architecture
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• v.43 no.1
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• pp.16-28
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• 2015

This study is suggested to enlarge the green area and to connect and improve the present green areas by deriving the lines of community greenway using living areas and community spaces close to the life of residence in Nam-gu. The purpose of this paper is to suggest the method of establishing greenway for the formation of community in which the residence can grow the community spirit and love their living space much more. Land-use status, green coverage ratio, and impermeability paving ratio are investigated. The community facilities are classified. The highest is educational facility, which is 7.7%, the green facility is 1.9% and the total area of community facilities which is 21.4%. The total area of Nam-gu is divided into 31 zones in total according to the administrative districts, the mail roads and reserved land of railroad and urban development. The total 20 lines of community greenway lines are chosen and the total length of lines is 18.2km. Finally, the characteristics of community greenway lines are analysed, the characteristics of community greenway lines are overall estimated according to the land-use, the street environment and the community facility. The classification system of community greenway is established on the basis on the function and purpose of greenway, the present status of land-use and the type of community facility. Based on the field investigation, the 6 greenway types are suggested considering the interconnection. The method of establishment of community greenway is suggested according to the principle of function and purpose, the principle of land-use and the principle of use of the facilities. Furthermore, the planting methods suitable to each greenway type are suggested in the building planting case of wall planting, roof planting, veranda planting, etc., and in the complex planting of parks, schools, roads, parking lots and other small areas.

• Journal of the Korean Society of School Health
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• v.17 no.1
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• pp.1-12
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• 2004

Purpose : this study purposed to investigate school nursing phenomena in Korea by applying ICNP, the international standard nursing classification system developed by ICN, and to compare school nursing phenomena at elementary, middle and high schools. Method : The subjects of this study are 110 nursing teachers from 82 elementary schools, 16 middle schools, and 12 high schools. In the survey, subjects were asked to score the degree to which phenomena and characteristics of Korean school nursing, identified in previous research, on a 5 point scale. Questionnaires were distributed and recovered by mail and email. The period of data collection was 6 months from July to December 2003. The general characteristics of schools and nursing teachers were represented with frequencies and percentages, the phenomena and characteristics of school nursing with the mean score of the questions, and the phenomena school nursing by school grade with ANOVA and Duncan's posterior analysis. Results : 1) As for the characteristics of schools according to school nursing phenomena related to human behavior, the mean score of questions on inadequate stress management was highest at 3.24 points followed by the score on inadequate weight control (3.23), inadequate eating habits (3.22), the risk of spine disorders (2.68), inadequate emergency management (2.62), inadequate response to sex -related problems (2.19), and smoking and drug use (1.85). 2) As for the characteristics of schools according to school nursing phenomena related to human function, the mean score of questions on oral health management was highest at 3.11 points followed by the score on the risk of digestive system disorder (2.87), improper eyesight management (2.81), the risk of respiratory system disorders (2.75), lack of sexual identity (2.52), and inadequate contagious disease control (2.12). 3) As for the mean score according to school nursing phenomena related to environment, the score of the risk of accidents in classroom was highest as 2.68 points followed by the score of the risk of accidents around the school (2.65), maladjustment to school (2.62), the risk of accidents outside the classroom (2.43), inadequate learning environment (1.83), the risk of exposure to socially and physically harmful environment factors (1.82), and inadequate waste disposal (1.77). 4) This study tested the mean scores of questions corresponding to each school nursing phenomenon in order to see if there is a difference in the school nursing phenomenon among elementary, middle and high schools, and performed Duncan's posterior comparison for school nursing phenomena. A significant difference was found at p<.1. According to the results, school nursing phenomena found to be significantly different among elementary, middle and high schools was smoking and drug use (p<.05), which appeared more problematic in high school than in elementary school. phenomena such as inadequate eating habits, inadequate weight control, inadequate response to sex-related problems and inadequate waste disposal were also found to be statistically different at p<.1; however, according to the result of Duncan's posterior comparison, no difference was found among groups in improper eating habits and improper response to sex-related problems, and a significant difference was found between middle and high schools in inadequate weight control and inadequate waste disposal. Conclusion: Based on the results of this study, it is necessary to plan school health projects focused on the characteristic school nursing phenomena that had high scores and to develop and execute school healthe projects in accordance with the characteristics of elementary, middle and high schools. Considering that the scores of school nursing phenomena related to human behavior are high, it is necessary to introduce school health promotion projects in a systematic way.

• Journal of Intelligence and Information Systems
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• v.26 no.1
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• pp.119-133
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• 2020

Fama asserted that in an efficient market, we can't make a trading rule that consistently outperforms the average stock market returns. This study aims to suggest a machine learning algorithm to improve the trading performance of an intraday short volatility strategy applying asymmetric volatility spillover effect, and analyze its trading performance improvement. Generally stock market volatility has a negative relation with stock market return and the Korean stock market volatility is influenced by the US stock market volatility. This volatility spillover effect is asymmetric. The asymmetric volatility spillover effect refers to the phenomenon that the US stock market volatility up and down differently influence the next day's volatility of the Korean stock market. We collected the S&P 500 index, VIX, KOSPI 200 index, and V-KOSPI 200 from 2008 to 2018. We found the negative relation between the S&P 500 and VIX, and the KOSPI 200 and V-KOSPI 200. We also documented the strong volatility spillover effect from the VIX to the V-KOSPI 200. Interestingly, the asymmetric volatility spillover was also found. Whereas the VIX up is fully reflected in the opening volatility of the V-KOSPI 200, the VIX down influences partially in the opening volatility and its influence lasts to the Korean market close. If the stock market is efficient, there is no reason why there exists the asymmetric volatility spillover effect. It is a counter example of the efficient market hypothesis. To utilize this type of anomalous volatility spillover pattern, we analyzed the intraday volatility selling strategy. This strategy sells short the Korean volatility market in the morning after the US stock market volatility closes down and takes no position in the volatility market after the VIX closes up. It produced profit every year between 2008 and 2018 and the percent profitable is 68%. The trading performance showed the higher average annual return of 129% relative to the benchmark average annual return of 33%. The maximum draw down, MDD, is -41%, which is lower than that of benchmark -101%. The Sharpe ratio 0.32 of SVS strategy is much greater than the Sharpe ratio 0.08 of the Benchmark strategy. The Sharpe ratio simultaneously considers return and risk and is calculated as return divided by risk. Therefore, high Sharpe ratio means high performance when comparing different strategies with different risk and return structure. Real world trading gives rise to the trading costs including brokerage cost and slippage cost. When the trading cost is considered, the performance difference between 76% and -10% average annual returns becomes clear. To improve the performance of the suggested volatility trading strategy, we used the well-known SVM algorithm. Input variables include the VIX close to close return at day t-1, the VIX open to close return at day t-1, the VK open return at day t, and output is the up and down classification of the VK open to close return at day t. The training period is from 2008 to 2014 and the testing period is from 2015 to 2018. The kernel functions are linear function, radial basis function, and polynomial function. We suggested the modified-short volatility strategy that sells the VK in the morning when the SVM output is Down and takes no position when the SVM output is Up. The trading performance was remarkably improved. The 5-year testing period trading results of the m-SVS strategy showed very high profit and low risk relative to the benchmark SVS strategy. The annual return of the m-SVS strategy is 123% and it is higher than that of SVS strategy. The risk factor, MDD, was also significantly improved from -41% to -29%.

• Journal of the Korean Institute of Landscape Architecture
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• v.42 no.4
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• pp.10-20
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• 2014

This study was carried out for the purpose of analysis correlations between street furniture design elements and preference of street furniture. This research analyzed the various street furniture set on Ilsan new town street, which are rest, hygiene, light, information, sale, traffic, and landscape. This study has processed by analysing street furniture literature investigation and consideration of theory. First, for analysed effect of street furniture element, has been appear as element 'relaxation facilities', 'information facilities', landscape facilities' mainly effect on street. Specially, 'rest', 'landscape', 'information' in order had a major influence on scenery. Each kind of 'chair elements' in rest facilities, 'sign board' in information facilities, 'sculpture', 'fountain' in 'landscape facilities' has analyzed as the main elements in the landscape affinity property affecting factor. Second, the results of analyzed landscape elements (shape, colour, texture, scale) affect to the affinity of street furniture. chair which are included in rest facilities affect "texture", "form", "scale", "color" in the order of preference of the molding design elements that influence landscape. Particularly, showed statistically significant on 'colour' element affecting the landscape preference than the other three elements. It means as the chair element which is rest facilities mainly affect on preferences, rather than texture, form, scale, colour. Monument in the landscape associated with a preference 'colour', 'shape', 'texture' 'scale' and appears to be in order of impact so we could get the consequence like chair and rest facilities show different aspects of the respectively. It means, visual element which are colour and shape significantly impact on landscape preferences. Third, information facilities such as signboard formative elements of landscape design preferences and correlation with negative showed that the correlation. That mean if the sign board is very negative influence on landscape preferences and the correlations of the design formative elements appear in order of 'scale', 'colour', 'texture'. It also means that the 'scale' namely the size of advertising material and colour are adversely affected in terms of landscape. As these results, when design street furniture as the street scenery, facilities according to the kind of the shape element and need to focus on relative shape element according to the kind of facilities difference. Finally, so far as to clarify the street furniture, mainly 'function' and 'system' classification shows undesirable in outdoor scape. Thus, performed studies in relationship with landscape, classify 'kind of facilities' is more desirable than 'system'.

• Journal of Distribution Science
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• v.9 no.2
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• pp.83-95
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• 2011

Conventional markets in Korea have played a pivotal role in the vitalization of local communities and economies along with the distribution of products. Although many people believe the markets to be disorderly, they are lively and provide local people with things to enjoy, watch and buy. However, superstores have undergone a mushrooming proliferation since Korea opened its gates to multinational superstores in 1996. This phenomenon has caused a crisis for Korea's conventional markets. They have lost their competitiveness because of this environmental change, inefficient management, and their outmoded facilities. Government efforts to revitalize the markets have centered on redevelopment of the facilities, a perspective that has caused not only the fall of the old business districts but also the decline of the distribution function. Under these conditions, the traditional market has re-entered into competition. The Korean government enacted a special law to revitalize the conventional markets and has been implementing many policies to support them since 2003. In 2009, the government amended the law and adopted the Business Improvement District System. The government also changed the official term from 'old markets' to 'Conventional markets'. Despite this legal amendment, though, we still need to re-establish the concept of the Conventional market. Historically, markets grew up spontaneously to dispose of surplus products. Some manmade markets were established through urban planning or as public facilities. Their businesses transactions have always been based on mutual trust between consumers and trades people, the traditional way of commercial dealing. Conventional markets can be defined, then, as creatures of societal necessity where transactions for services and products are based on mutual trust. Problematically, unlisted markets are left out of government support. Although unlisted markets have performed almost the same functions as listed markets, they exist only as a statistic as far as the special law is concerned. In some areas, there are more unlisted markets than unlisted ones. Therefore, it is necessary to establish systematic management methods for the unlisted markets. Some unlisted markets received support in the form of facility improvement from local governments' budgets in the early stage of the special law's enforcement. The current government also assists with safety issues involving unlisted markets; however, the current special law provides no legal framework for unlisted markets. Moreover, consumers cannot tell the difference between unlisted markets and listed ones. Finding a solution to this problemrequires new standards and a wider scope of support by which the efficiency of the market improvement support system might be enhanced.

• Journal of Environmental Impact Assessment
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• v.32 no.1
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• pp.15-28
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• 2023

In the Republic of Korea, the target project scope of the small-scale EIA is stipulated as the plan area above around 5,000~60,000m² depending on a type of project and classification of land use. Whereas, the lower limit of the corresponding local government EIA project is generally located above the small-scale EIA's limits, and overlapping ranges exist. This situation has been enlarged since road construction and district unit planning were included as the target projects for small-scale EIA in the "Enforcement Decree of the Environmental Impact Assessment Act", which was partially revised in November 2016, and the current consultation system needed discussion in that small-scale EIA is allowed to be done without gathering review opinions at the local level. In fact, projects subjected to local government EIA but consulted as small-scale EIAs may seem insignificant because of a small number of total cases; however, it is worth paying attention to the fact that a local government may not add a target project due to the small-scale EIA. This study suggested the three policy measures for improving small-scale EIA to enhance the effectiveness of local government EIA: supplementing the institutional arrangements to incorporate the review opinion from the local region in small-scale EIA, giving priority to local EIA for conducing the projects in overlapping ranges with partial amendments on EIA law regarding exceptions to local government EIA, including small target projects (not to be small-scale EIA targets) to the ordinance that are deemed necessary to be conducted as local government EIA. Even though a positive function of small-scale EIA has been confirmed, efforts should be made to improve the situation in which many projects within local governments are consulted without review from the region.

• The Korean Journal of Archival Studies
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• no.22
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• pp.157-199
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• 2009

The organization for managing records and archives did not emerge together with the founding of the Chinese Communist Party. Such management became active with the establishment of the Department of Documents (文書科) and its affiliated offices overseeing reading and safekeeping of official papers, after the formation of the Central Secretariat(中央秘書處) in 1926. Improving the work of the Secretariat's organization became the focus of critical discussions in the early 1930s. The main criticism was that the Secretariat had failed to be cognizant of its political role and degenerated into a mere "functional organization." The solution to this was the "politicization of the Secretariat's work." Moreover, influenced by the "Rectification Movement" in the 1940s, the party emphasized the responsibility of the Resources Department (材料科) that extended beyond managing documents to collecting, organizing and providing various kinds of important information data. In the mean time, maintaining security with regard to composing documents continued to be emphasized through such methods as using different names for figures and organizations or employing special inks for document production. In addition, communications between the central political organs and regional offices were emphasized through regular reports on work activities and situations of the local areas. The General Secretary not only composed the drafts of the major official documents but also handled the reading and examination of all documents, and thus played a central role in record processing. The records, called archives after undergoing document processing, were placed in safekeeping. This function was handled by the "Document Safekeeping Office(文件保管處)" of the Central Secretariat's Department of Documents. Although the Document Safekeeping Office, also called the "Central Repository(中央文庫)", could no longer accept, beginning in the early 1930s, additional archive transfers, the Resources Department continued to strengthen throughout the 1940s its role of safekeeping and providing documents and publication materials. In particular, collections of materials for research and study were carried out, and with the recovery of regions which had been under the Japanese rule, massive amounts of archive and document materials were collected. After being stipulated by rules in 1931, the archive classification and cataloguing methods became actively systematized, especially in the 1940s. Basically, "subject" classification methods and fundamental cataloguing techniques were adopted. The principle of assuming "importance" and "confidentiality" as the criteria of management emerged from a relatively early period, but the concept or process of evaluation that differentiated preservation and discarding of documents was not clear. While implementing a system of secure management and restricted access for confidential information, the critical view on providing use of archive materials was very strong, as can be seen in the slogan, "the unification of preservation and use." Even during the revolutionary movement and wars, the Chinese Communist Party continued their efforts to strengthen management and preservation of records & archives. The results were not always desirable nor were there any reasons for such experiences to lead to stable development. The historical conditions in which the Chinese Communist Party found itself probably made it inevitable. The most pronounced characteristics of this process can be found in the fact that they not only pursued efficiency of records & archives management at the functional level but, while strengthening their self-awareness of the political significance impacting the Chinese Communist Party's revolution movement, they also paid attention to the value possessed by archive materials as actual evidence for revolutionary policy research and as historical evidence of the Chinese Communist Party.

• Journal of Intelligence and Information Systems
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• v.18 no.4
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• pp.117-127
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• 2012

Due to the recent expansion of the Web 2.0 -based services, along with the widespread of smartphones, online social network services are being popularized among users. Online social network services are the online community services which enable users to communicate each other, share information and expand human relationships. In the social network services, each relation between users is represented by a graph consisting of nodes and links. As the users of online social network services are increasing rapidly, the SNS are actively utilized in enterprise marketing, analysis of social phenomenon and so on. Social Network Analysis (SNA) is the systematic way to analyze social relationships among the members of the social network using the network theory. In general social network theory consists of nodes and arcs, and it is often depicted in a social network diagram. In a social network diagram, nodes represent individual actors within the network and arcs represent relationships between the nodes. With SNA, we can measure relationships among the people such as degree of intimacy, intensity of connection and classification of the groups. Ever since Social Networking Services (SNS) have drawn increasing attention from millions of users, numerous researches have made to analyze their user relationships and messages. There are typical representative SNA methods: degree centrality, betweenness centrality and closeness centrality. In the degree of centrality analysis, the shortest path between nodes is not considered. However, it is used as a crucial factor in betweenness centrality, closeness centrality and other SNA methods. In previous researches in SNA, the computation time was not too expensive since the size of social network was small. Unfortunately, most SNA methods require significant time to process relevant data, and it makes difficult to apply the ever increasing SNS data in social network studies. For instance, if the number of nodes in online social network is n, the maximum number of link in social network is n(n-1)/2. It means that it is too expensive to analyze the social network, for example, if the number of nodes is 10,000 the number of links is 49,995,000. Therefore, we propose a heuristic-based method for finding the shortest path among users in the SNS user graph. Through the shortest path finding method, we will show how efficient our proposed approach may be by conducting betweenness centrality analysis and closeness centrality analysis, both of which are widely used in social network studies. Moreover, we devised an enhanced method with addition of best-first-search method and preprocessing step for the reduction of computation time and rapid search of the shortest paths in a huge size of online social network. Best-first-search method finds the shortest path heuristically, which generalizes human experiences. As large number of links is shared by only a few nodes in online social networks, most nods have relatively few connections. As a result, a node with multiple connections functions as a hub node. When searching for a particular node, looking for users with numerous links instead of searching all users indiscriminately has a better chance of finding the desired node more quickly. In this paper, we employ the degree of user node vn as heuristic evaluation function in a graph G = (N, E), where N is a set of vertices, and E is a set of links between two different nodes. As the heuristic evaluation function is used, the worst case could happen when the target node is situated in the bottom of skewed tree. In order to remove such a target node, the preprocessing step is conducted. Next, we find the shortest path between two nodes in social network efficiently and then analyze the social network. For the verification of the proposed method, we crawled 160,000 people from online and then constructed social network. Then we compared with previous methods, which are best-first-search and breath-first-search, in time for searching and analyzing. The suggested method takes 240 seconds to search nodes where breath-first-search based method takes 1,781 seconds (7.4 times faster). Moreover, for social network analysis, the suggested method is 6.8 times and 1.8 times faster than betweenness centrality analysis and closeness centrality analysis, respectively. The proposed method in this paper shows the possibility to analyze a large size of social network with the better performance in time. As a result, our method would improve the efficiency of social network analysis, making it particularly useful in studying social trends or phenomena.

• 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.