• Journal of the Korea Academia-Industrial cooperation Society
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• v.18 no.11
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• pp.218-228
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• 2017

This study covers an investigation using meta-analysis of the factors related to the effects of singing activities for children, focusing on the dissertations conducted for master and doctor degrees and the studies published in academic journals over the past 16 years. Ameta-regression analysis was conducted to examine the changes of the factors in each published year. The analysis results were as follows: Both the entire effect size and the groups of singing activity related factors were revealed to have significant effect sizes. While the group of social factors and the group of cultural & artistic factors showed large effect sizes, the group of psychological & emotional factors appeared to have an intermediate effect size. The sub-factors of the group of social factors were shown to have significantly larger effect sizes than the others, except for the factor of capability of recognizing others. Among the sub-factors, naturally friendly behavior showed relatively larger effect size than the others. In the sub-factors of the group of psychological & emotional factors, self-expression capability and self-control capability showed large effect sizes and stress suppression and emotional intelligence showed intermediate effect sizes. Among the sub-factors of the group of cultural & artistic factors, except for creative capability which showed an intermediate effect size, all of the sub-factors showed large effect sizes. According to the results of the analysis of the trend of the effect size changes in each published year, the trends of the entire effect size and the effect size of each factor, such as the groups of social factors, psychological & emotional factors and cultural & artistic factors, showed that the activity effects increase as the publication year comes closer to the most recent year.

• The Journal of Pediatrics of Korean Medicine
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• v.15 no.1
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• pp.77-104
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• 2001

The effects of the oriental herbal medicine Saenghyetang(SHT, 生慧湯), which consists of Rehmanniae Radix (熟地黃 九蒸: was made by 9th steam) 40g, Corni Fructus(山茱黃) 16g, Polygalae Radix(遠志) 8g, Zizyphi Spinosae Semen(酸棗仁) 2g, Biotae Semen(柏子仁 去油: oil ingredient was removed) 20g, Poria Cocos(茯笭) 12g, Ginseng Radix(人蔘) 12g, Acori Graminei Rhizoma(石菖蒲) 2g, Sinapis Semen(白芥子) 8g, on learning ability and memory were investigated. Hot water extract(HWE) and ethanol extract(EE) from SHT were used for the studies. Learning ability and memory are related to modifications of synaptic strength among neurons that interactive. Enhanced synaptic coincidence detection leads to improved learning ability and memory. If the NMDA receptor, a synaptic coincidence detector, acts as a graded switch for memory formations, enhanced signal detection by NMDA receptors should enhance learning ability and memory. It was shown that NR2B was increased in the forebrains of oriental medicine-administrated mice, leading to enhanced activation of NMDA receptors and facilitating synaptic potentiation in response to stimulation at 10-100 Hz. These HWE-SHT treated mice exhibited that superior ability in learning and memory when performing various behavioral tasks, showing that NR2B is enhanced by HWE-SHT treatment and also is critical in gating the age-dependent threshold for plasticity and memory formation. NMDA receptor-dependent modifications, which were mediated in part by HWE administration, of synaptic efficacy, therefore, represent a mechanism for associative learning ability and memory. Results suggest that oriental medical enhancement of NR2B contributes to increase intelligence and memory in mammals On the other hand, to examine the effects of EE-SHT on the learning ability and memory in experimental mice, EE-SHT was tested on passive and active avoidance responses. The EE-SHT ameliorated the memory retrieval deficit induced by ethanol in mice, but not other memory impairments. EE-SHT(10, 20mg/100 g, p.o.) did not affect the passive avoidance responses of normal mice in the step through and step down tests, the conditioned and unconditioned avoidance responses of normal mice in the shuttle box, lever press performance tests and the ambulatory activity of normal mice in a normal condition. However, EE-SHT at 20 mg/kg significantly decrease the spontaneous motor activity during the shuttle box test, and also to extend the sleeping time induced by pentobarbital in mice. These results suggest that SHT has an ameliorating effect on memory retrieval impairments and a weak tranquilizing action.

• Journal of the Korea Society of Computer and Information
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• v.26 no.4
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• pp.11-19
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• 2021

An abnormal object refers to a person, an object, or a mechanical device that performs abnormal and unusual behavior and needs observation or supervision. In order to detect this through artificial intelligence algorithm without continuous human intervention, a method of observing the specificity of temporal features using optical flow technique is widely used. In this study, an abnormal situation is identified by learning an algorithm that translates an input image frame to an optical flow image using a Generative Adversarial Network (GAN). In particular, we propose a technique that improves the pre-processing process to exclude unnecessary outliers and the post-processing process to increase the accuracy of identification in the test dataset after learning to improve the performance of the model's abnormal behavior identification. UCSD Pedestrian and UMN Unusual Crowd Activity were used as training datasets to detect abnormal behavior. For the proposed method, the frame-level AUC 0.9450 and EER 0.1317 were shown in the UCSD Ped2 dataset, which shows performance improvement compared to the models in the previous studies.

• Journal of Intelligence and Information Systems
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• v.19 no.4
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• pp.123-132
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• 2013

As the smartphones are equipped with various sensors such as the accelerometer, GPS, gravity sensor, gyros, ambient light sensor, proximity sensor, and so on, there have been many research works on making use of these sensors to create valuable applications. Human activity recognition is one such application that is motivated by various welfare applications such as the support for the elderly, measurement of calorie consumption, analysis of lifestyles, analysis of exercise patterns, and so on. One of the challenges faced when using the smartphone sensors for activity recognition is that the number of sensors used should be minimized to save the battery power. When the number of sensors used are restricted, it is difficult to realize a highly accurate activity recognizer or a classifier because it is hard to distinguish between subtly different activities relying on only limited information. The difficulty gets especially severe when the number of different activity classes to be distinguished is very large. In this paper, we show that a fairly accurate classifier can be built that can distinguish ten different activities by using only a single sensor data, i.e., the smartphone accelerometer data. The approach that we take to dealing with this ten-class problem is to use the ensemble of nested dichotomy (END) method that transforms a multi-class problem into multiple two-class problems. END builds a committee of binary classifiers in a nested fashion using a binary tree. At the root of the binary tree, the set of all the classes are split into two subsets of classes by using a binary classifier. At a child node of the tree, a subset of classes is again split into two smaller subsets by using another binary classifier. Continuing in this way, we can obtain a binary tree where each leaf node contains a single class. This binary tree can be viewed as a nested dichotomy that can make multi-class predictions. Depending on how a set of classes are split into two subsets at each node, the final tree that we obtain can be different. Since there can be some classes that are correlated, a particular tree may perform better than the others. However, we can hardly identify the best tree without deep domain knowledge. The END method copes with this problem by building multiple dichotomy trees randomly during learning, and then combining the predictions made by each tree during classification. The END method is generally known to perform well even when the base learner is unable to model complex decision boundaries As the base classifier at each node of the dichotomy, we have used another ensemble classifier called the random forest. A random forest is built by repeatedly generating a decision tree each time with a different random subset of features using a bootstrap sample. By combining bagging with random feature subset selection, a random forest enjoys the advantage of having more diverse ensemble members than a simple bagging. As an overall result, our ensemble of nested dichotomy can actually be seen as a committee of committees of decision trees that can deal with a multi-class problem with high accuracy. The ten classes of activities that we distinguish in this paper are 'Sitting', 'Standing', 'Walking', 'Running', 'Walking Uphill', 'Walking Downhill', 'Running Uphill', 'Running Downhill', 'Falling', and 'Hobbling'. The features used for classifying these activities include not only the magnitude of acceleration vector at each time point but also the maximum, the minimum, and the standard deviation of vector magnitude within a time window of the last 2 seconds, etc. For experiments to compare the performance of END with those of other methods, the accelerometer data has been collected at every 0.1 second for 2 minutes for each activity from 5 volunteers. Among these 5,900 ($=5{\times}(60{\times}2-2)/0.1$) data collected for each activity (the data for the first 2 seconds are trashed because they do not have time window data), 4,700 have been used for training and the rest for testing. Although 'Walking Uphill' is often confused with some other similar activities, END has been found to classify all of the ten activities with a fairly high accuracy of 98.4%. On the other hand, the accuracies achieved by a decision tree, a k-nearest neighbor, and a one-versus-rest support vector machine have been observed as 97.6%, 96.5%, and 97.6%, respectively.

• Journal of Intelligence and Information Systems
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• v.16 no.4
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• pp.85-97
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• 2010

Internet communities are a typical space for knowledge creation and use on the Internet as people discuss their common interests within the internet communities. When we define 'Knowledge Communities' as internet communities that are related to knowledge creation and use, they are categorized into 4 different types such as 'Search Engine,' 'Open Communities,' 'Specialty Communities,' and 'Activity Communities.' Each type of knowledge community does not remain the same, for example. Rather, it changes with time and is also affected by the external business environment. Therefore, it is critical to develop processes for practical use of such changeable knowledge communities. Yet there is little research regarding a strategic framework for knowledge communities as a source of knowledge creation and use. The purposes of this study are (1) to find factors that can affect knowledge creation and use for each type of knowledge community and (2) to develop a strategic framework for practical use of the knowledge communities. Based on previous research, we found 7 factors that have considerable impacts on knowledge creation and use. They were 'Fitness,' 'Reliability,' 'Systemicity,' 'Richness,' 'Similarity,' 'Feedback,' and 'Understanding.' We created 30 different questions from each type of knowledge community. The questions included common sense, IT, business and hobbies, and were uniformly selected from various knowledge communities. Instead of using survey, we used these questions to ask users of the 4 representative web sites such as Google from Search Engine, NAVER Knowledge iN from Open Communities, SLRClub from Specialty Communities, and Wikipedia from Activity Communities. These 4 representative web sites were selected based on popularity (i.e., the 4 most popular sites in Korea). They were also among the 4 most frequently mentioned sitesin previous research. The answers of the 30 knowledge questions were collected and evaluated by the 11 IT experts who have been working for IT companies more than 3 years. When evaluating, the 11 experts used the above 7 knowledge factors as criteria. Using a stepwise linear regression for the evaluation of the 7 knowledge factors, we found that each factors affects differently knowledge creation and use for each type of knowledge community. The results of the stepwise linear regression analysis showed the relationship between 'Understanding' and other knowledge factors. The relationship was different regarding the type of knowledge community. The results indicated that 'Understanding' was significantly related to 'Reliability' at 'Search Engine type', to 'Fitness' at 'Open Community type', to 'Reliability' and 'Similarity' at 'Specialty Community type', and to 'Richness' and 'Similarity' at 'Activity Community type'. A strategic framework was created from the results of this study and such framework can be useful for knowledge communities that are not stable with time. For the success of knowledge community, the results of this study suggest that it is essential to ensure there are factors that can influence knowledge communities. It is also vital to reinforce each factor has its unique influence on related knowledge community. Thus, these changeable knowledge communities should be transformed into an adequate type with proper business strategies and objectives. They also should be progressed into a type that covers varioustypes of knowledge communities. For example, DCInside started from a small specialty community focusing on digital camera hardware and camerawork and then was transformed to an open community focusing on social issues through well-known photo galleries. NAVER started from a typical search engine and now covers an open community and a special community through additional web services such as NAVER knowledge iN, NAVER Cafe, and NAVER Blog. NAVER is currently competing withan activity community such as Wikipedia through the NAVER encyclopedia that provides similar services with NAVER encyclopedia's users as Wikipedia does. Finally, the results of this study provide meaningfully practical guidance for practitioners in that which type of knowledge community is most appropriate to the fluctuated business environment as knowledge community itself evolves with time.

• Journal of The Korean Society of Inherited Metabolic disease
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• v.24 no.1
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• pp.26-36
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• 2024

Lesch-Nyhan syndrome (LNS) is an Clinical symptoms can range from mild to severe depending on residual enzyme activity and genetic mutations. In Korea, 27 cases of LNS have been reported. We report the results of an 11-year comparative follow-up of two cases of children who visited because of pink diapers, one who died from LNS with no residual enzymes and one case with partial residual enzymes. Case 1: During follow-up, seizures, developmental delay, and regression were observed. The boy experienced insomnia and severe constipation. He exhibited self-mutilating behavior, a grand mal seizure, scoliosis with severe spasticity, truncal hypotonia, choreoathetoid movement, and ataxia. After prolonged emaciation, staghorn calculi, and recurrent pneumonia, the patient died suddenly at the age of 11 years. Genetic testing revealed a hemizygous HPRT1 variant (c.151C>T (p.Arg51Ter)). Uric acid level was 10.5 mg/dL (normal range: ~3.5-7.9) and HPRT activity 0.02 nmol/hr/spot (10-23.8 nmol/hr/spot). Case 2: During follow-up, the patient remained underweight. He has normal intelligence attending primary school. Self-mutilation symptoms were not observed. Regular renal ultrasonography did not reveal urolithiasis. The patient had a hemizygous HPRT1 variant (c.35A>C (p.Asp12Ala)). Uric acid level and HPRT activity were 11 mg/dL and 0.56 nmol/hr/spot. Pink diapers after the neonatal period and severe protein aversion, neurological problems, and kidney stones, differentiation for LNS is necessary. When suspected, serum uric acid levels, HPRT enzyme activity, and molecular biological tests may be helpful in predicting the prognosis of LNS.

• Journal of Intelligence and Information Systems
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• v.20 no.1
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• pp.149-161
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• 2014

The export of domestic public services to overseas markets contains many potential obstacles, stemming from different export procedures, the target services, and socio-economic environments. In order to alleviate these problems, the business incubation platform as an open business ecosystem can be a powerful instrument to support the decisions taken by participants and stakeholders. In this paper, we propose an ontology model and its implementation processes for the business incubation platform with an open and pervasive architecture to support public service exports. For the conceptual model of platform ontology, export case studies are used for requirements analysis. The conceptual model shows the basic structure, with vocabulary and its meaning, the relationship between ontologies, and key attributes. For the implementation and test of the ontology model, the logical structure is edited using Prot$\acute{e}$g$\acute{e}$ editor. The core engine of the business incubation platform is the simulator module, where the various contexts of export businesses should be captured, defined, and shared with other modules through ontologies. It is well-known that an ontology, with which concepts and their relationships are represented using a shared vocabulary, is an efficient and effective tool for organizing meta-information to develop structural frameworks in a particular domain. The proposed model consists of five ontologies derived from a requirements survey of major stakeholders and their operational scenarios: service, requirements, environment, enterprise, and county. The service ontology contains several components that can find and categorize public services through a case analysis of the public service export. Key attributes of the service ontology are composed of categories including objective, requirements, activity, and service. The objective category, which has sub-attributes including operational body (organization) and user, acts as a reference to search and classify public services. The requirements category relates to the functional needs at a particular phase of system (service) design or operation. Sub-attributes of requirements are user, application, platform, architecture, and social overhead. The activity category represents business processes during the operation and maintenance phase. The activity category also has sub-attributes including facility, software, and project unit. The service category, with sub-attributes such as target, time, and place, acts as a reference to sort and classify the public services. The requirements ontology is derived from the basic and common components of public services and target countries. The key attributes of the requirements ontology are business, technology, and constraints. Business requirements represent the needs of processes and activities for public service export; technology represents the technological requirements for the operation of public services; and constraints represent the business law, regulations, or cultural characteristics of the target country. The environment ontology is derived from case studies of target countries for public service operation. Key attributes of the environment ontology are user, requirements, and activity. A user includes stakeholders in public services, from citizens to operators and managers; the requirements attribute represents the managerial and physical needs during operation; the activity attribute represents business processes in detail. The enterprise ontology is introduced from a previous study, and its attributes are activity, organization, strategy, marketing, and time. The country ontology is derived from the demographic and geopolitical analysis of the target country, and its key attributes are economy, social infrastructure, law, regulation, customs, population, location, and development strategies. The priority list for target services for a certain country and/or the priority list for target countries for a certain public services are generated by a matching algorithm. These lists are used as input seeds to simulate the consortium partners, and government's policies and programs. In the simulation, the environmental differences between Korea and the target country can be customized through a gap analysis and work-flow optimization process. When the process gap between Korea and the target country is too large for a single corporation to cover, a consortium is considered an alternative choice, and various alternatives are derived from the capability index of enterprises. For financial packages, a mix of various foreign aid funds can be simulated during this stage. It is expected that the proposed ontology model and the business incubation platform can be used by various participants in the public service export market. It could be especially beneficial to small and medium businesses that have relatively fewer resources and experience with public service export. We also expect that the open and pervasive service architecture in a digital business ecosystem will help stakeholders find new opportunities through information sharing and collaboration on business processes.

• Journal of Intelligence and Information Systems
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• v.24 no.3
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• pp.89-117
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• 2018

The Korean companies are intensifying competition with not only domestic companies but also foreign companies in globalization. In this environment, it is essential activities not only for large companies but also Small and Medium Enterprises (SMEs) to get and develop the core competency. Particularly, SMEs that are inferior to resources of various aspects, such as financial resources etc., can make innovation through effective R&D investment. And then, SMEs can occupy a competency and can be survive at the environment. Conventionally, the method of "self-development" by using only the internal resources of the company has been dominant. Recently, however, R&D method through cooperation, also called "Open Innovation", is emerging. Especially SMEs are relatively short of available internal resources. Therefore, it is necessary to utilize technology and resources through cooperation with external companies(such as joint development or contract development etc.) rather than self-development R&D. In this context, we confirmed the effect of SMEs' factors on sales in Korea. Specifically, the factors that SMEs hold are classified as 'Technical characteristic', 'Company competency', and 'R&D activity' and analyzed how they influence the sales achieved as a result of R&D. The analysis was based on a two-year statistical survey conducted by the Korean government. In addition, we confirmed the influence of the factors on the sales according to the R&D method(Self-Development vs. Open Innovation), and also observed the influence change in 29 industrial categories. The results of the study are summarized as follows: First, regression analysis shows that twelve factors of SMEs have a significant effect on sales. Specifically, 15 factors included in the analysis, 12 factors excluding 3 factors were found to have significant influence. In the technical characteristic, 'imitation period' and 'product life cycle' of the technology were confirmed. In the company competency, 'R&D led person', 'researcher number', 'intellectual property registration status', 'number of R&D attempts', and 'ratio of success to trial' were confirmed. The R&D activity was found to have a significant impact on all included factors. Second, the influence of factors on the R&D method was confirmed, and the change was confirmed in four factors. In addition, these factors were found that have different effects on sales according to the R&D method. Specifically, 'researcher number', 'number of R&D attempts', 'performance compensation system', and 'R&D investment' were found to have significant moderate effects. In other words, the moderating effect of open innovation was confirmed for four factors. Third, on the industrial classification, it is confirmed that different factors have a significant influence on each industrial classification. At this point, it was confirmed that at least one factor, up to nine factors had a significant effect on the sales according to the industrial classification. Furthermore, different moderate effects have been confirmed in the industrial classification and R&D method. In the moderate effect, up to eight significant moderate effects were confirmed according to the industrial classification. In particular, 'R&D investment' and 'performance compensation system' were confirmed to be the most common moderating effect by each 12 times and 11 times in all industrial classification. This study provides the following suggestions: First, it is necessary for SMEs to determine the R&D method in consideration of the characteristics of the technology to be R&D as well as the enterprise competency and the R&D activity. In addition, there is a need to identify and concentrate on the factors that increase sales in R&D decisions, which are mainly affected by the industry classification to which the company belongs. Second, governments that support SMEs' R&D need to provide guidelines that are fit to their situation. It is necessary to differentiate the support for the company considering various factors such as technology and R&D purpose for their effective budget execution. Finally, based on the results of this study, we urge the need to reconsider the effectiveness of existing SME support policies.

• Journal of Intelligence and Information Systems
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• v.19 no.3
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• pp.127-139
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• 2013

With an advent of recent knowledge-based society, the interest in intellectual property has increased. Firms have tired to result in productive outcomes through continuous innovative activity. Especially, ICT firms which lead high-tech industry have tried to manage intellectual property more systematically. Firm's interest in the patent has increased in order to manage the innovative activity and Knowledge property. The patent involves not only simple information but also important values as information of technology, management and right. Moreover, as the patent has the detailed contents regarding technology development activity, it is regarded as valuable data. The patent which reflects technology spread and research outcomes and business performances are closely interrelated as the patent is considered as a significant the level of firm's innovation. As the patent information which represents companies' intellectual capital is accumulated continuously, it has become possible to do quantitative analysis. The advantages of patent in the related industry information and it's standardize information can be easily obtained. Through the patent, the flow of knowledge can be determined. The patent information can analyze in various levels from patent to nation. The patent information is used to analyze technical status and the effects on performance. The patent which has a high frequency of citation refers to having high technological values. Analyzing the patent information contains both citation index analysis using the number of citation and network analysis using citation relationship. Network analysis can provide the information on the flows of knowledge and technological changes, and it can show future research direction. Studies using the patent citation analysis vary academically and practically. For the citation index research, studies to analyze influential big patent has been conducted, and for the network analysis research, studies to find out the flows of technology in a certain industry has been conducted. Social network analysis is applied not only in the sociology, but also in a field of management consulting and company's knowledge management. Research of how the company's network position has an impact on business performances has been conducted from various aspects in a field of network analysis. Social network analysis can be based on the visual forms. Network indicators are available through the quantitative analysis. Social network analysis is used when analyzing outcomes in terms of the position of network. Social network analysis focuses largely on centrality and structural holes. Centrality indicates that actors having central positions among other actors have an advantage to exert stronger influence for exchange relationship. Degree centrality, betweenness centrality and closeness centrality are used for centrality analysis. Structural holes refer to an empty place in social structure and are defined as efficiency and constraints. This study stresses and analyzes firms' network in terms of the patent and how network characteristics have an influence on business performances. For the purpose of doing this, seventy-four ICT companies listed in S&P500 are chosen for the sample. UCINET6 is used to analyze the network structural characteristics such as outdegree centrality, betweenness centrality and efficiency. Then, regression analysis test is conducted to find out how these network characteristics are related to business performance. It is found that each network index has significant impacts on net income, i.e. business performance. However, it is found that efficiency is negatively associated with business performance. As the efficiency increases, net income decreases and it has a negative impact on business performances. Furthermore, it is shown that betweenness centrality solely has statistically significance for the multiple regression analysis with three network indexes. The patent citation network analysis shows the flows of knowledge between firms, and it can be expected to contribute to company's management strategies by analyzing company's network structural positions.

• Korean Journal of Psychosomatic Medicine
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• v.19 no.2
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• pp.74-82
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• 2011

Objective:The aim of this study was to evaluate the relationship between sustained attention deficits in Attention-Deficit/Hyperactivity Disorder(ADHD) children and short-term Heart Rate Variability(HRV) parameters. In addition, we evaluate the relationship between The ADHD rating scale(ARS), the computerized ADHD diagnostic system(ADS) and Parenting stress index- short form(PSI-SF). Methods:This study was performed in the department of children and Adolescent psychiatry, Korea university Guro hospital from august 2008 to January 2009. We evaluated HRV parameters by short-term recordings of 5 minutes. K-ARS and ADS are used for screening and identifying ADHD children. Intelligence was measured using Korean educational Developmental Institute-wechsler Intelligence Scale for Children. The caregivers Complete Parenting Stress Index scale for evaluation parent stress. Results:The low frequency(LF) was significantly correlated with response variability of ADS. However, the other variables of ARS and ADS were not significantly correlated with LF. Hyperactivity subscale of ARS was significantly correlated with parental distress subscale and difficult child subscale of PSI-SF and inattention subscale of ARS was also significantly correlated with dysfunctional interaction and difficult child subscale of PSI-SF. Conclusion:The LF, 0.10-Hz component of HRV is known to measure effort allocation. This study shows that the LF component of HRV is significantly correlated with the response variability of ADS. This means that more severe symptoms of ADHD were correlated with the increase in the LF that means decreased effort allocation. These results also support the clinical usability of HRV in the assessment of ADHD. Furthermore, PSI-SF is correlated with hyperactivity and inattention variables of ARS.