• Journal of Intelligence and Information Systems
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• v.17 no.1
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• pp.111-125
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• 2011

Clustering is a process of grouping similar or relevant documents into a cluster and assigning a meaningful concept to the cluster. By this process, clustering facilitates fast and correct search for the relevant documents by narrowing down the range of searching only to the collection of documents belonging to related clusters. For effective clustering, techniques are required for identifying similar documents and grouping them into a cluster, and discovering a concept that is most relevant to the cluster. One of the problems often appearing in this context is the detection of a complex concept that overlaps with several simple concepts at the same hierarchical level. Previous clustering methods were unable to identify and represent a complex concept that belongs to several different clusters at the same level in the concept hierarchy, and also could not validate the semantic hierarchical relationship between a complex concept and each of simple concepts. In order to solve these problems, this paper proposes a new clustering method that identifies and represents complex concepts efficiently. We developed the Hierarchical Overlapping Clustering (HOC) algorithm that modified the traditional Agglomerative Hierarchical Clustering algorithm to allow overlapped clusters at the same level in the concept hierarchy. The HOC algorithm represents the clustering result not by a tree but by a lattice to detect complex concepts. We developed a system that employs the HOC algorithm to carry out the goal of complex concept detection. This system operates in three phases; 1) the preprocessing of documents, 2) the clustering using the HOC algorithm, and 3) the validation of semantic hierarchical relationships among the concepts in the lattice obtained as a result of clustering. The preprocessing phase represents the documents as x-y coordinate values in a 2-dimensional space by considering the weights of terms appearing in the documents. First, it goes through some refinement process by applying stopwords removal and stemming to extract index terms. Then, each index term is assigned a TF-IDF weight value and the x-y coordinate value for each document is determined by combining the TF-IDF values of the terms in it. The clustering phase uses the HOC algorithm in which the similarity between the documents is calculated by applying the Euclidean distance method. Initially, a cluster is generated for each document by grouping those documents that are closest to it. Then, the distance between any two clusters is measured, grouping the closest clusters as a new cluster. This process is repeated until the root cluster is generated. In the validation phase, the feature selection method is applied to validate the appropriateness of the cluster concepts built by the HOC algorithm to see if they have meaningful hierarchical relationships. Feature selection is a method of extracting key features from a document by identifying and assigning weight values to important and representative terms in the document. In order to correctly select key features, a method is needed to determine how each term contributes to the class of the document. Among several methods achieving this goal, this paper adopted the $x^2$�� statistics, which measures the dependency degree of a term t to a class c, and represents the relationship between t and c by a numerical value. To demonstrate the effectiveness of the HOC algorithm, a series of performance evaluation is carried out by using a well-known Reuter-21578 news collection. The result of performance evaluation showed that the HOC algorithm greatly contributes to detecting and producing complex concepts by generating the concept hierarchy in a lattice structure.

• Korean Journal of Remote Sensing
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• v.32 no.6
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• pp.629-637
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• 2016

In this present study, we identified the $SO_2$ effect on $O_3$ retrieval from the Ozone Monitoring Instrument (OMI) measurement over Chinese Industrial region from 2005 through 2007. The Planetary boundary layer (PBL) $SO_2$ data measured by OMI sensor is used in this present study. OMI-Total Ozone Mapping Spectrometer (TOMS) total $O_3$ is compared with OMI-Differential Optical Absorption Spectrometer (DOAS) total $O_3$ in various $SO_2$ condition in PBL. The difference between OMI-TOMS and OMI-DOAS total $O_3$ (T-D) shows dependency on $SO_2$ (R (Correlation coefficient) = 0.36). Since aerosol has been reported to cause uncertainty of both OMI-TOMS and OMI-DOAS total $O_3$ retrieval, the aerosol effect on relationship between PBL $SO_2$ and T-D is investigated with changing Aerosol Optical Depth (AOD). There is negligible aerosol effect on the relationship showing similar slope ($1.83{\leq}slope{\leq}2.36$) between PBL $SO_2$ and T-D in various AOD conditions. We also found that the rate of change in T-D per 1.0 DU change in PBL, middle troposphere (TRM), and upper troposphere and stratosphere (STL) are 1.6 DU, 3.9 DU and 4.9 DU, respectively. It shows that the altitude where $SO_2$ exist can affect the value of T-D, which could be due to reduced absolute radiance sensitivity in the boundary layer at 317.5 nm which is used to retrieve OMI-TOMS ozone in boundary layer.

• The Southeast Asian review
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• v.27 no.1
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• pp.163-191
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• 2017

This article aims to review the recent, especially focusing on the year of 2016, situations and prospects of the Vietnamese politics, economy, and international relations. Politically, Vietnam completed the election of members for the National Assembly and organized new leadership at the 12th National Congress of the Vietnamese Communist Party in 2016. One characteristic of the new leadership is that the politicians, especially the members of politburo, from the North continue to occupy the position of majority. The other one is that the new leadership promised to carry out the restructuring of economy toward industries producing higher value-added commodities even though Vietnam industries admittedly need to accelerate present industrialization and modernization as a developing country under the seemingly contradictory slogan of "the development of market economy for socialism." The declared goals of the new leadership in Vietnam are inevitable in a sense since the development of Vietnamese economy has been heavily dependent upon Foreign Direct Investment(FDI) taking advantage of Vietnamese cheap labor and simultaneously it is evident that its future is unsecure if it maintains status quo. In fact, the Vietnamese economy has impressively showed high growth rate by the help of foreign capitals since 1990s despite the repetitive recessions of global economy but its growth is not likely to be sustainable anymore if it will not reduce foreign dependency and social economic inequality in a long term. In a short run, global economic recession, the financial and monetary policies of global powers, and recent protectionism and uncertainty of trade agreements will be three crucial variables to affect Vietnamese economy. In terms of international relations, Vietnam is continuously expected to practise the policy of checks and balances among the powerful countries. Vietnam has seriously disputed with China on islands sovereignty in the South China Sea and attempted to maintain close relationship with other powerful countries including especially America. However, mainly due to the new protectionism by the regime of American president Donald Trump, the Vietnamese government also need to keep close relationship with China increasingly for both economic and diplomatic security. Under the circumstances, Vietnam is expected to maintain more practical and balanced international relations.

• Korean Journal of Psychosomatic Medicine
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• v.4 no.2
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• pp.269-276
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• 1996

A theroretical study was made on the psychodynamism of somatoform disorder. Somatoform disorder is caused by a defense mechanism of somatization. Somatization is the tendency to react to stimuli(drives, defenses, and conflict between them) physically rather than psychically(Moore, 1990). Ford(1983) said it is a way of life, and Dunbar(1954) said it is the shift of psychic energy toward expression in somatic symptoms. As used by Max Shur(1955), somatization links symptom formation to the regression that may occur in response to acute and chronic conflict. In the neurotic individual psychic conflict often provokes regressive phenomena that may include somatic manifestations characteristic of an earlier developmental phase. Schur calls this resomatization. Pain is the most common example of a somatization reaction to conflict. The pain has an unconscious significance derived from childhood experiences. It is used to win love, to punish misdeeds, as well as a means to amend. Among all pains, chest pain has a special meaning. Generally speaking, 'I have pain in my chest' is about the same as 'I have pain in my mind'. The chest represent the mind, and the mind reminds us about the heart. So we have a high tendency to recognize mental pain as cardiac pain. Kellner(1990) said rage and hostility, especially repressed hostility, are important factors in somatization. In 'Psychoanalytic Observation on Cardiac Pain', psychoanalyst Bacon(1953) presented clinical cases of patients who complained of cardiac pain in a psychoanalytic session that spread from the left side of their chests down their left arms. The pain was from rage and fear which came after their desire to be loved was frustrated by the analyet. She said desires related to cardiac pain were dependency needs and aggressions. Empatic relationship and therapeutic alliances are indispensable to psychotherapy in somatoform disorder. The beginning of therapy is to discover a precipitating event from the time their symptoms have started and to help the patient understand a relation between the symptom and precipitating event. Its remedial process is to find and interpret a intrapsychic conflict shown through the symptoms of the patient. Three cases of somatoform disorder patients treated based on this therapeutic method were introduced. The firt patient, Mr. H, had been suffering from hysterical aphasia with repressed rage as ie psychodynamic cause. An interpretation related to the precipitating event was given by written communication, and he recovered from his aphasia after 3 days of the session. The second patient was a dentist in a cardiac neurosis with agitation and hypochondriasis, whose psychodynamism was caused by a fear that he might lose his father's love. His symptom was also interpreted in relation to the precipitating event. It showed the patient a child-within afraid of losing his father's love. His condition improved after getting a didactic interpretation which told him, to be master of himself, The third patient was a lady transferred from the deparment of internal medicine. She had a frequent and violent fit of chest pains, whose psychodynamic cause was separation anxiety and a rage due to the frustration of dependency needs. Her symptom vanished dramatically when she wore a holler EKG monitor and did not occur during monitoring. By this experience she found her symptom was a psychogenic one, and a therapeutic alliance was formed. later in reguar psychotherapy sessions, she was told the relaton between symptoms and precipitating events. Through this she understood that her separation anxiety was connected to the symptom and she became less terrifide when it occurred. Now she can travel abroad and take well part in social activities.

• Journal of Intelligence and Information Systems
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• v.25 no.4
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• pp.141-154
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• 2019

Rapid growth of internet technology and social media is progressing. Data mining technology has evolved to enable unstructured document representations in a variety of applications. Sentiment analysis is an important technology that can distinguish poor or high-quality content through text data of products, and it has proliferated during text mining. Sentiment analysis mainly analyzes people's opinions in text data by assigning predefined data categories as positive and negative. This has been studied in various directions in terms of accuracy from simple rule-based to dictionary-based approaches using predefined labels. In fact, sentiment analysis is one of the most active researches in natural language processing and is widely studied in text mining. When real online reviews aren't available for others, it's not only easy to openly collect information, but it also affects your business. In marketing, real-world information from customers is gathered on websites, not surveys. Depending on whether the website's posts are positive or negative, the customer response is reflected in the sales and tries to identify the information. However, many reviews on a website are not always good, and difficult to identify. The earlier studies in this research area used the reviews data of the Amazon.com shopping mal, but the research data used in the recent studies uses the data for stock market trends, blogs, news articles, weather forecasts, IMDB, and facebook etc. However, the lack of accuracy is recognized because sentiment calculations are changed according to the subject, paragraph, sentiment lexicon direction, and sentence strength. This study aims to classify the polarity analysis of sentiment analysis into positive and negative categories and increase the prediction accuracy of the polarity analysis using the pretrained IMDB review data set. First, the text classification algorithm related to sentiment analysis adopts the popular machine learning algorithms such as NB (naive bayes), SVM (support vector machines), XGboost, RF (random forests), and Gradient Boost as comparative models. Second, deep learning has demonstrated discriminative features that can extract complex features of data. Representative algorithms are CNN (convolution neural networks), RNN (recurrent neural networks), LSTM (long-short term memory). CNN can be used similarly to BoW when processing a sentence in vector format, but does not consider sequential data attributes. RNN can handle well in order because it takes into account the time information of the data, but there is a long-term dependency on memory. To solve the problem of long-term dependence, LSTM is used. For the comparison, CNN and LSTM were chosen as simple deep learning models. In addition to classical machine learning algorithms, CNN, LSTM, and the integrated models were analyzed. Although there are many parameters for the algorithms, we examined the relationship between numerical value and precision to find the optimal combination. And, we tried to figure out how the models work well for sentiment analysis and how these models work. This study proposes integrated CNN and LSTM algorithms to extract the positive and negative features of text analysis. The reasons for mixing these two algorithms are as follows. CNN can extract features for the classification automatically by applying convolution layer and massively parallel processing. LSTM is not capable of highly parallel processing. Like faucets, the LSTM has input, output, and forget gates that can be moved and controlled at a desired time. These gates have the advantage of placing memory blocks on hidden nodes. The memory block of the LSTM may not store all the data, but it can solve the CNN's long-term dependency problem. Furthermore, when LSTM is used in CNN's pooling layer, it has an end-to-end structure, so that spatial and temporal features can be designed simultaneously. In combination with CNN-LSTM, 90.33% accuracy was measured. This is slower than CNN, but faster than LSTM. The presented model was more accurate than other models. In addition, each word embedding layer can be improved when training the kernel step by step. CNN-LSTM can improve the weakness of each model, and there is an advantage of improving the learning by layer using the end-to-end structure of LSTM. Based on these reasons, this study tries to enhance the classification accuracy of movie reviews using the integrated CNN-LSTM model.

• Proceedings of the Korean Institute Of Construction Engineering and Management
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• autumn
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• pp.99-106
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• 2002

Researches on integration of design and construction information from earlier era focused on the conceptual data models. Development and prevalent use of commercial database management system led many researchers to design database schemas for enlightening of relationship between non-graphic data items. Although these researches became the foundation fur the proceeding researches. they did not utilize the graphic data providable from CAD system which is already widely used. 4D CAD concept suggests a way of integrating graphic data with schedule data. Although this integration provided a new possibility for integration, there exists a limitation in data dependency on a specific application. This research suggests a new approach on integration for design and construction information, 'Product Model Centered Integration Methodology'. This methodology achieves integration by preliminary research on existing methodology using 4D CAD concept. and by development and application of new integration methodology, 'Product Model Centered Integration Methodology'. 'Design Component' can be converted into digital format by object based CAD system. 'Unified Object-based Graphic Modeling' shows how to model graphic product model using CAD system. Possibility of reusing design information in latter stage depends on the ways of creating CAD model, so modeling guidelines and specifications are suggested. Then prototype system for integration management, and exchange are presented, using 'Product Frameworker', and 'Product Database' which also supports multiple-viewpoints. 'Product Data Model' is designed, and main data workflows are represented using 'Activity Diagram', one of UML diagrams. These can be used for writing programming codes and developing prototype in order to automatically create activity items in actual schedule management system. Through validation processes, 'Product Model Centered Integration Methodology' is suggested as the new approach for integration of design and construction information.

• Journal of the Korean Society for Library and Information Science
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• v.15
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• pp.225-266
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• 1988

Various theories and techniques for the subject catalog have been developed since Charles Ammi Cutter first tried to formulate rules for the construction of subject headings in 1876. However, they do not seem to be appropriate to Korean language because the syntax and semantics of Korean language are different from those of English and other European languages. This study therefore attempts to develop a new Korean subject indexing system, namely Korean String Indexing System(KOSIS), in order to increase the use of subject catalogs. For this purpose, advantages and disadvantages between the classed subject catalog nd the alphabetical subject catalog, which are typical subject ca-alogs in libraries, are investigated, and most of remarkable subject indexing systems, in particular the PRECIS developed by the British National Bibliography, are reviewed and analysed. KOSIS is a string indexing based on purely the syntax and semantics of Korean language, even though considerable principles of PRECIS are applied to it. The outlines of KOSIS are as follows: 1) KOSIS is based on the fundamentals of natural language and an ingenious conjunction of human indexing skills and computer capabilities. 2) KOSIS is. 3 string indexing based on the 'principle of context-dependency.' A string of terms organized accoding to his principle shows remarkable affinity with certain patterns of words in ordinary discourse. From that point onward, natural language rather than classificatory terms become the basic model for indexing schemes. 3) KOSIS uses 24 role operators. One or more operators should be allocated to the index string, which is organized manually by the indexer's intellectual work, in order to establish the most explicit syntactic relationship of index terms. 4) Traditionally, a single -line entry format is used in which a subject heading or index entry is presented as a single sequence of words, consisting of the entry terms, plus, in some cases, an extra qualifying term or phrase. But KOSIS employs a two-line entry format which contains three basic positions for the production of index entries. The 'lead' serves as the user's access point, the 'display' contains those terms which are themselves context dependent on the lead, 'qualifier' sets the lead term into its wider context. 5) Each of the KOSIS entries is co-extensive with the initial subject statement prepared by the indexer, since it displays all the subject specificities. Compound terms are always presented in their natural language order. Inverted headings are not produced in KOSIS. Consequently, the precision ratio of information retrieval can be increased. 6) KOSIS uses 5 relational codes for the system of references among semantically related terms. Semantically related terms are handled by a different set of routines, leading to the production of 'See' and 'See also' references. 7) KOSIS was riginally developed for a classified catalog system which requires a subject index, that is an index -which 'trans-lates' subject index, that is, an index which 'translates' subjects expressed in natural language into the appropriate classification numbers. However, KOSIS can also be us d for a dictionary catalog system. Accordingly, KOSIS strings can be manipulated to produce either appropriate subject indexes for a classified catalog system, or acceptable subject headings for a dictionary catalog system. 8) KOSIS is able to maintain a constistency of index entries and cross references by means of a routine identification of the established index strings and reference system. For this purpose, an individual Subject Indicator Number and Reference Indicator Number is allocated to each new index strings and new index terms, respectively. can produce all the index entries, cross references, and authority cards by means of either manual or mechanical methods. Thus, detailed algorithms for the machine-production of various outputs are provided for the institutions which can use computer facilities.

• Management & Information Systems Review
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• v.37 no.1
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• pp.103-122
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• 2018

This paper expands the results of previous studies indicating that manager's ability positively affects business performance to analyze whether the degree to which the role of manager's ability improves business performance appears differently according to the characteristics of enterprises. As for the characteristics of enterprises, whether enterprises correspond to enterprises with high levels of funding constraints or late movers in the market is considered. Enterprises with high levels of funding constraints greatly require managers' roles not only for efficient use of funds but also for smooth financing. Late movers require more judgments of professional managers to overcome insufficient resources held and low profitability. In the case of enterprises with corporate characteristics with high dependency on the manager, the business performance is expected to greatly vary with the ability of the manager. The empirical analysis was conducted with listed companies from 2010 to 2014, manager's ability was measured by first measuring the efficiency of the entire enterprise through data envelopment analysis (DEA) using the methodology of Demerjian et al.(2012) and removing enterprise characteristics factors thereafter. Business performance was measured by the return on industrial fixed assets. The results of the empirical analysis indicated that the degree to which manager's ability improves business performance was higher in managerial competence enhances managerial performance in enterprises with high levels of funding constraints and late movers. Business performance is considered to have been improved further in cases where manager's ability is high because investments were made more efficiently through smooth funding. In addition, in the case of late movers in relatively poor environments, business performance was improved further because high manager's ability induced efficient decision making. In this paper, we extend the precedent study that the manager's ability improves the management performance, and confirm that the manager's ability to improve the managerial performance can be different according to the situation of the company. In addition, it is meaningful to analyze empirically whether a company's managerial ability is more important. This paper expanded the results of previous studies indicating that manager's ability improves performance to identify that the degree to which manager's ability improves business performance may appear differently according to situations in which enterprises are placed. In addition, this paper is meaningful in that it empirically analyzed what enterprises require manager's ability more importantly.

• Journal of Korean Society of Environmental Engineers
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• v.32 no.9
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• pp.840-850
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• 2010

The present study was attempted to find the effects of structural properties of phosphorus on the water quality of Gyehwa reservoir in Saemangeum. Relationship of phosphorus fractions between water and sediment properties was closely examined, and a few types of phosphorus were found from the sample sediment as : Saloid-P, Al-P, Fe-P, Ca-P, Red-P and Occd-P. Saloid-P (1.4%), Al-P (0.5%), Fe-P (39.8%), Ca-P (56.6%), Red-P (0.4%), Occd-P (1.3%) were extracted in a mass basis from the sediment of Gyehwa reservoir. Approximately more than 97% of phosphorus were calcium related phosphorus (Ca-P, 56%) and iron bound phosphorus (Fe-P, 39.8%). The Fe-P closely relates with water quality of T-N (r=0.761, p<0.05), $NO_3$-N (r=0.754, p<0.05), $NH_4$-N (r=0.728, p<0.05), T-P (r=0.774, p<0.05) and $PO_4$-P (r=0.767, p<0.05) while the Ca-P did not show any consistent dependency on the water quality. On the other hand, the correlation of Ca-P with $P_2O_5$ was high with r=0.783 (p<0.05) in the sediment. The Fe-P was affected significantly on the Ignition Loss (r=0.569, p<0.05), T-N (r=0.715, p<0.05) and T-P (r=0.983, p<0.01). In the research of correlation between phosphorus fraction and heavy metals in the sediment, Ca-P did not show any specific relationships with heavy metals. The Fe-P showed a significant correlation with As (r=0.817, p<0.01), Cu (r=0.793, p<0.05), Cd (r=0.786, p<0.05), Zn (r=0.738, p<0.05), so that it can be stated that the presence of Fe-P may implicate the volume of various metallic elements.

• Journal of Science and Technology Studies
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• v.19 no.2
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• pp.169-206
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• 2019

This article seeks to explore new relationships and ethics of human and technology by analyzing a cultural imaginary produced by artificial intelligence. Drawing on theoretical reflections of the Feminist Scientific and Technological Studies which understand science and technology as the matter of care(Puig de la Bellacas, 2011), this paper focuses on the fact that artificial intelligence and robots materialize cultural imaginary such as autonomy. This autonomy, defined as the capacity to adapt to a new environment through self-learning, is accepted as a way to conceptualize an authentic human or an ideal subject. However, this article argues that artificial intelligence is mediated by and dependent on invisible human labor and complex material devices, suggesting that such autonomy is close to fiction. The recent growth of the so-called 'assistant technology' shows that it is differentially visualizing the care work of both machines and humans. Technology and its cultural imaginary hide the care work of human workers and actively visualize the one of the machine. And they make autonomy and agency ideal humanness, leaving disabled bodies and dependency as unworthy. Artificial intelligence and its cultural imaginary negate the value of disabled bodies while idealizing abled-bodies, and result in eliminating the real relationship between man and technology as mutually dependent beings. In conclusion, the author argues that the technology we need is not the one to exclude the non-typical bodies and care work of others, but the one to include them as they are. This technology responsibly empathizes marginalized beings and encourages solidarity between fragile beings. Inspired by an art performance of artist Sue Austin, the author finally comes up with and suggests 'artificial intelligence in wheelchair' as an alternative figuration for the currently dominant 'autonomous artificial intelligence'.