• The Journal of the Korea Contents Association
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• v.22 no.3
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• pp.369-379
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• 2022

With the deepening integration of technology and cultural industries, China's digital cultural industry has begun to rise. The digital culture industry has met new demands for cultural consumption and brought new experiences to consumers in the digital economy era. This paper uses the public data of 36 Chinese A-share listed companies in digital culture from 2018 to 2019 to construct a technical innovation efficiency evaluation index system for listed companies in China's digital cultural industry. Through the use of data envelopment analysis (DEA) method, the technical innovation efficiency of 36 listed companies in China's digital cultural industry was evaluated. The research results show that: (1) China's 36 listed companies have low technological innovation efficiency; (2) the allocation of R&D resources of listed companies is unreasonable; (3) there is a large difference in technological innovation efficiency among listed companies. Therefore, it is necessary to increase the efficiency of technology innovation of listed companies in China's digital culture industry by investing more R&D funds, distributing R&D resources, establishing effective dynamic incentive mechanism, promoting government-industrial-academic research.

• Journal of The Korean Society of Integrative Medicine
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• v.10 no.2
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• pp.73-83
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• 2022

Purpose : Low back pain (LBP) is reported as a risk of experiencing musculoskeletal disorders due to muscle stiffness and hypokinetics. The lumbar spine in an unstable state causes imbalance and lumbar instability. Therefore, This study examined the effects of lumbar stabilization exercise and self-complex exercise program on pain, function, psychosocial level, static balance ability, and transverse abdominal muscle (TrA) thickness and contraction ratio in patients with lumbar instability. Methods : The design of this is a randomized controlled trial (RCT). Twenty-six LBP patients participated in this study. Screening tests were performed and assigned to the experimental group (n=13) and control group (n=13) using a random allocation program. Both groups underwent a lumbar stabilization exercise program. In addition, the experimental group implemented the self-complex exercise program. All interventions were applied three times per week for four weeks. The quadruple visual analog (QVAS), the Korean version of the Oswestry disability index (K-ODI), Korean version of fear-avoidance belief questionnaire (FABQ), static balance ability, TrA thickness, and contraction ratio were compared to evaluate the effect on intervention. Statistical significance was set at 𝛼=.05. Results : Both groups showed significant differences before and after the intervention in QVAS, K-ODI, FABQ, static balance ability, and TrA thickness in contraction (p<.05). In addition, significant differences in K-ODI and FABQ were observed between the experimental group and control group (p<.05). Conclusion : A lumbar stabilization exercise and self-complex exercise program resulted in reduced dysfunctions, psychosocial stability in patients with lumbar instability. Therefore, Lumbar stabilization exercise and self-complex exercise program for patients with lumbar instability are effective method with clinical significance in improving the function and psychosocial stability.

• The korean journal of orthodontics
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• v.54 no.1
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• pp.16-25
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• 2024

Objective: To compare the effectiveness of laser-engineered copper-nickel titanium (SmartArch) and superelastic nickel-titanium (SENT) archwires in aligning teeth and inducing root resorption and pain experienced by patients. Methods: Two-arm parallel groups with a 1:1 allocation ratio were used. The participants were patients aged 11.5 years and older with 5-9 mm of mandibular anterior crowding who were indicated for non-extraction treatment. The primary outcome was alignment effectiveness, assessed using Little's irregularity index (LII) over 16 weeks with a single wire (0.016-inch) in the SmartArch group and 2 wires (0.014- and 0.018-inch) in the SENT group (8 weeks each). Secondary outcomes included root resorption evaluated by pre- and post-intervention periapical radiographs and pain levels recorded by the participants during the first week. Results: A total of 40 participants were randomly allocated into 2 groups; 33 completed the study and were analyzed (16 in the SmartArch group and 17 in the SENT group, aged 16.97 ± 4.05 years). The total LII decrease for the SmartArch and SENT groups was 5.63 mm and 5.29 mm, respectively, which was neither statistically nor clinically significant. Root resorption was not significantly different between the groups. The difference in pain levels was not statistically significant for the first 5 days following wire placement; however, there was a significant difference favoring the SENT group in the final 2 days. Conclusions: SmartArch and SENT archwires were similarly effective during the alignment phase of orthodontic treatment. Root resorption should be observed throughout the treatment with either wire. SmartArch wires demonstrated higher pain perception than SENT wires.

• Journal of Intelligence and Information Systems
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• v.27 no.3
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• pp.75-94
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• 2021

The low birth rate and shortened military service period are causing concerns about selecting excellent military officers. The Republic of Korea entered a low birth rate society in 1984 and an aged society in 2018 respectively, and is expected to be in a super-aged society in 2025. In addition, the troop-oriented military is changed as a state-of-the-art weapons-oriented military, and the reduction of the military service period was implemented in 2018 to ease the burden of military service for young people and play a role in the society early. Some observe that the application rate for military officers is falling due to a decrease of manpower resources and a preference for shortened mandatory military service over military officers. This requires further consideration of the policy of securing excellent military officers. Most of the related studies have used social scientists' methodologies, but this study applies the methodology of text mining suitable for large-scale documents analysis. This study extracts words of discriminative characteristics from the Republic of Korea Air Force Non-Commissioned Officer Applicant cover letters and analyzes the polarity of pass and fail. It consists of three steps in total. First, the application is divided into general and technical fields, and the words characterized in the cover letter are ordered according to the difference in the frequency ratio of each field. The greater the difference in the proportion of each application field, the field character is defined as 'more discriminative'. Based on this, we extract the top 50 words representing discriminative characteristics in general fields and the top 50 words representing discriminative characteristics in technology fields. Second, the number of appropriate topics in the overall cover letter is calculated through the LDA. It uses perplexity score and coherence score. Based on the appropriate number of topics, we then use LDA to generate topic and probability, and estimate which topic words of discriminative characteristic belong to. Subsequently, the keyword indicators of questions used to set the labeling candidate index, and the most appropriate index indicator is set as the label for the topic when considering the topic-specific word distribution. Third, using L-LDA, which sets the cover letter and label as pass and fail, we generate topics and probabilities for each field of pass and fail labels. Furthermore, we extract only words of discriminative characteristics that give labeled topics among generated topics and probabilities by pass and fail labels. Next, we extract the difference between the probability on the pass label and the probability on the fail label by word of the labeled discriminative characteristic. A positive figure can be seen as having the polarity of pass, and a negative figure can be seen as having the polarity of fail. This study is the first research to reflect the characteristics of cover letters of Republic of Korea Air Force non-commissioned officer applicants, not in the private sector. Moreover, these methodologies can apply text mining techniques for multiple documents, rather survey or interview methods, to reduce analysis time and increase reliability for the entire population. For this reason, the methodology proposed in the study is also applicable to other forms of multiple documents in the field of military personnel. This study shows that L-LDA is more suitable than LDA to extract discriminative characteristics of Republic of Korea Air Force Noncommissioned cover letters. Furthermore, this study proposes a methodology that uses a combination of LDA and L-LDA. Therefore, through the analysis of the results of the acquisition of non-commissioned Republic of Korea Air Force officers, we would like to provide information available for acquisition and promotional policies and propose a methodology available for research in the field of military manpower acquisition.

• Proceedings of the Korean Information Science Society Conference
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• 2005.11b
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• pp.46-48
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• 2005

이동 컴퓨팅 환경에서 다수의 이동 클라이언트들에게 데이터를 전달할 때는 클라이언트들의 동시 데이터 접근을 지원하는 브로드캐스트 기법을 사용하면 무선 채널 대역폭의 협소함과 클라이언트 측의 에너지 제약과 같은 단점을 해결할 수 있다. 기존 기법들은 클라이언트의 데이터에 대한 접근빈도(access frequencies)와 클라이언트의 에너지 효율(energy efficiency)을 동시에 고려하지 않았다. 따라서 원하는 데이터가 올 때까지 계속해서 채널을 들어야 함으로 인해 에너지 소비를 많이 하거나, 데이터를 얻을 때까지 추가한 많은 양의 정보에 따른 지연이 발생하는 단점이 있다. 본 논문에서는 클라이언트의 에너지 절약을 위한 tuning time을 최소화하고 실제 데이터를 얻을 때까지 소요되는 access time의 효율을 높이기 위해 데이터의 접근빈도와 에너지 효율을 동시에 고려하는 HIDAF: Hybrid Index considering Data Access Frequencies 기법을 제한한다. 제안하는 기법은 트리기반 기법과 해싱기반 기법을 함께 적용하여 구성한 인덱스를 브로드캐스트 주기에 배치한다. HIDAF 기법은 데이터 접근빈도를 고려한 트리기반 인덱스를 배치함으로써 데이터를 얻기 위한 클라이언트들의 평균 access time을 줄일 수 있고, 이러한 인덱스에 해싱기반 기법을 추가함으로써 클라이언트의 에너지 효율을 최소화하는 새로운 브로드캐스팅 기법이다. HIDAF 기법은 브로드캐스트 추기에 데이터의 접근빈도를 고려한 인덱스를 교차로 추가하여 핫 데이터에 대한 클라이언트들의 access time을 줄임으로써 전체 사용자에 대한 평균 access time을 최소화하는 동시에 클라이언트들의 제한된 에너지 소비를 최소화하는데 목적이 있다. 제안기법에 대한 평가는 수학적 분석을 통해 HIDAF 기법과 기존의 브로드캐스트 기법의 성능을 비교 분석한다.하였으나 사료효율은 증진시켰으며, 후자(사양, 사료)와의 상호작용은 나타나지 않았다. 이상의 결과는 거세비육돈에서 1) androgen과 estrogen은 공히 자발적인 사료섭취와 등지방 침적을 억제하고 IGF-I 분비를 증가시키며, 2) 성선스테로이드호르몬의 이 같은 성장에 미치는 효과의 일부는 IGF-I을 통해 매개될 수도 있을을 시사한다. 약 $70 {\~} 90\%$의 phenoxyethanol이 유상에 존재하였다. 또한, 미생물에 대한 항균력도 phenoxyethanol이 수상에 많이 존재할수록 증가하는 경향을 나타내었다. 따라서, 제형 내 oil tomposition을 변화시킴으로써 phenoxyethanol의 사용량을 줄일 수 있을 뿐만 아니라, 피부 투과를 감소시켜 보다 피부 자극이 적은 저자극 방부시스템 개발이 가능하리라 보여 진다. 첨가하여 제조한 curd yoghurt는 저장성과 관능적인 면에서 우수한 상품적 가치가 인정되는 새로운 기능성 신제품의 개발에 기여할 수 있을 것으로 사료되었다. 여자의 경우 0.8이상이 되어서 심혈관계 질환의 위험 범위에 속하는 수준이었다. 삼두근의 두겹 두께는 남녀 각각 $20.2\pm8.58cm,\;22.2\pm4.40mm$으로 남녀간에 유의한 차이는 없었다. 조사대상자의 식습관 상태는 전체 대상자의 $84.4\%$가 대부분이 하루 세끼 식사를 규칙적으로 하고 있었으며 식사속도는 허겁지겁 빨리 섭취하는 경우가 남자는 $31.0\%$, 여자는 $21.4\%$로 나타났고 이들을 제외한 나머지 사람들은 보통 속도 혹은 충분한 시간을 가지고 식사를 하였다. 평소 식사량은 조금 적게 혹은 적당하게 섭취하는 사람이 대부분이었으며 남자가 여자보다는 배부르게 먹는 경 향이 유의적으로 높았다(p<0.05). 식사는 혼자 하는 경우가 남자

• Proceedings of the Korea Water Resources Association Conference
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• 2019.05a
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• pp.164-175
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• 2019

The Tor Tong Daeng Irrigation Project with the irrigation area of 61,400 hectares is located in the Ping Basin of the Upper Central Plain of Thailand where farmers depended on both surface water and groundwater. In the drought year, water storage in the Bhumipol Dam is inadequate to allocate water for agriculture, and caused water deficit in many irrigation projects. Farmers need to find extra sources of water such as water from farm pond or groundwater as a supplement. The operation of Bhumipol Dam and irrigation demand estimation are vital for irrigation water allocation to help solve water shortage issue in the irrigation project. The study aims to determine the smart dam operation system to mitigate water shortage in this irrigation project via introduction of machine learning to improve dam operation and irrigation demand estimation via soil moisture estimation from satellite images. Via ANN technique application, the inflows to the dam are generated from the upstream rain gauge stations using past 10 years daily rainfall data. The input vectors for ANN model are identified base on regression and principal component analysis. The structure of ANN (length of training data, the type of activation functions, the number of hidden nodes and training methods) is determined from the statistics performance between measurements and ANN outputs. On the other hands, the irrigation demand will be estimated by using satellite images, LANDSAT. The Enhanced Vegetation Index (EVI) and Temperature Vegetation Dryness Index (TVDI) values are estimated from the plant growth stage and soil moisture. The values are calibrated and verified with the field plant growth stages and soil moisture data in the year 2017-2018. The irrigation demand in the irrigation project is then estimated from the plant growth stage and soil moisture in the area. With the estimated dam inflow and irrigation demand, the dam operation will manage the water release in the better manner compared with the past operational data. The results show how smart system concept was applied and improve dam operation by using inflow estimation from ANN technique combining with irrigation demand estimation from satellite images when compared with the past operation data which is an initial step to develop the smart dam operation system in Thailand.

• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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• v.9 no.5
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• pp.781-791
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• 2019

The purpose of this study was to evaluate the evaluation of long - term care institutions (evaluation rating, evaluation rating, suitability of evaluation index), quality of service of caregivers, Quality satisfaction, life satisfaction, and facility choice. After receiving the IRB, in January and February of 2018, the survey was completed for 79 long-term care institution managers, 381 nursing care workers, and 381 elderly people. The survey carried out an allocation sample reflecting the 2015 long - term care (facility benefit) evaluation results. The results of this study are as follows. First, it is found that the institutional evaluation (evaluation level, change of evaluation level, recognition of suitability of the index) has a greater impact on the quality of life of the elderly, appear. However, the intention of reselecting the facility after discharge was more influenced by the quality of services of caregivers. Therefore, except for the intention to reschedule the facility, it can be said that the evaluation of the National Health Insurance Corporation was partially validated.

• The Korean Journal of Applied Statistics
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• v.34 no.5
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• pp.795-806
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• 2021

Recently, as text data through online channels have become vast, there is a growing interest in research that summarizes and analyzes them. One of the fundamental analyses of text data is to extract potential topics. Although the researcher may read all the data and summarize the contents one by one, it is not easy to deal with large amounts of data. Blei and Lafferty (2007) and Blei et al. (2003) proposed topic modeling methods for extracting topics using a statistical model. Since the text data is generally collected over time, it is worthwhile to monitor the topic's changes. In this study, we propose a topic index based on the results of the topic model. In addition, a control chart, a representative tool for statistical process management, is applied to monitor the topic index over time. As a practical example, we use text data collected from Blue House National Petition boards between March 5, 2018, and March 5, 2020.

• Journal of Intelligence and Information Systems
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• v.23 no.4
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• pp.127-146
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• 2017

Services using artificial intelligence have begun to emerge in daily life. Artificial intelligence is applied to products in consumer electronics and communications such as artificial intelligence refrigerators and speakers. In the financial sector, using Kensho's artificial intelligence technology, the process of the stock trading system in Goldman Sachs was improved. For example, two stock traders could handle the work of 600 stock traders and the analytical work for 15 people for 4weeks could be processed in 5 minutes. Especially, big data analysis through machine learning among artificial intelligence fields is actively applied throughout the financial industry. The stock market analysis and investment modeling through machine learning theory are also actively studied. The limits of linearity problem existing in financial time series studies are overcome by using machine learning theory such as artificial intelligence prediction model. The study of quantitative financial data based on the past stock market-related numerical data is widely performed using artificial intelligence to forecast future movements of stock price or indices. Various other studies have been conducted to predict the future direction of the market or the stock price of companies by learning based on a large amount of text data such as various news and comments related to the stock market. Investing on commodity asset, one of alternative assets, is usually used for enhancing the stability and safety of traditional stock and bond asset portfolio. There are relatively few researches on the investment model about commodity asset than mainstream assets like equity and bond. Recently machine learning techniques are widely applied on financial world, especially on stock and bond investment model and it makes better trading model on this field and makes the change on the whole financial area. In this study we made investment model using Support Vector Machine among the machine learning models. There are some researches on commodity asset focusing on the price prediction of the specific commodity but it is hard to find the researches about investment model of commodity as asset allocation using machine learning model. We propose a method of forecasting four major commodity indices, portfolio made of commodity futures, and individual commodity futures, using SVM model. The four major commodity indices are Goldman Sachs Commodity Index(GSCI), Dow Jones UBS Commodity Index(DJUI), Thomson Reuters/Core Commodity CRB Index(TRCI), and Rogers International Commodity Index(RI). We selected each two individual futures among three sectors as energy, agriculture, and metals that are actively traded on CME market and have enough liquidity. They are Crude Oil, Natural Gas, Corn, Wheat, Gold and Silver Futures. We made the equally weighted portfolio with six commodity futures for comparing with other commodity indices. We set the 19 macroeconomic indicators including stock market indices, exports & imports trade data, labor market data, and composite leading indicators as the input data of the model because commodity asset is very closely related with the macroeconomic activities. They are 14 US economic indicators, two Chinese economic indicators and two Korean economic indicators. Data period is from January 1990 to May 2017. We set the former 195 monthly data as training data and the latter 125 monthly data as test data. In this study, we verified that the performance of the equally weighted commodity futures portfolio rebalanced by the SVM model is better than that of other commodity indices. The prediction accuracy of the model for the commodity indices does not exceed 50% regardless of the SVM kernel function. On the other hand, the prediction accuracy of equally weighted commodity futures portfolio is 53%. The prediction accuracy of the individual commodity futures model is better than that of commodity indices model especially in agriculture and metal sectors. The individual commodity futures portfolio excluding the energy sector has outperformed the three sectors covered by individual commodity futures portfolio. In order to verify the validity of the model, it is judged that the analysis results should be similar despite variations in data period. So we also examined the odd numbered year data as training data and the even numbered year data as test data and we confirmed that the analysis results are similar. As a result, when we allocate commodity assets to traditional portfolio composed of stock, bond, and cash, we can get more effective investment performance not by investing commodity indices but by investing commodity futures. Especially we can get better performance by rebalanced commodity futures portfolio designed by SVM model.

• Journal of Intelligence and Information Systems
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• v.16 no.3
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• pp.121-145
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• 2010

University timetabling depending on the educational environments of universities is an NP-hard problem that the amount of computation required to find solutions increases exponentially with the problem size. For many years, there have been lots of studies on university timetabling from the necessity of automatic timetable generation for students' convenience and effective lesson, and for the effective allocation of subjects, lecturers, and classrooms. Timetables are classified into a course timetable and an examination timetable. This study focuses on the former. In general, a course timetable for liberal arts is scheduled by the office of academic affairs and a course timetable for major subjects is scheduled by each department of a university. We found several problems from the analysis of current course timetabling in departments. First, it is time-consuming and inefficient for each department to do the routine and repetitive timetabling work manually. Second, many classes are concentrated into several time slots in a timetable. This tendency decreases the effectiveness of students' classes. Third, several major subjects might overlap some required subjects in liberal arts at the same time slots in the timetable. In this case, it is required that students should choose only one from the overlapped subjects. Fourth, many subjects are lectured by same lecturers every year and most of lecturers prefer the same time slots for the subjects compared with last year. This means that it will be helpful if departments reuse the previous timetables. To solve such problems and support the effective course timetabling in each department, this study proposes a university timetabling support system based on two phases. In the first phase, each department generates a timetable template from the most similar timetable case, which is based on case-based reasoning. In the second phase, the department schedules a timetable with the help of interactive user interface under the timetabling criteria, which is based on rule-based approach. This study provides the illustrations of Hanshin University. We classified timetabling criteria into intrinsic and extrinsic criteria. In intrinsic criteria, there are three criteria related to lecturer, class, and classroom which are all hard constraints. In extrinsic criteria, there are four criteria related to 'the numbers of lesson hours' by the lecturer, 'prohibition of lecture allocation to specific day-hours' for committee members, 'the number of subjects in the same day-hour,' and 'the use of common classrooms.' In 'the numbers of lesson hours' by the lecturer, there are three kinds of criteria : 'minimum number of lesson hours per week,' 'maximum number of lesson hours per week,' 'maximum number of lesson hours per day.' Extrinsic criteria are also all hard constraints except for 'minimum number of lesson hours per week' considered as a soft constraint. In addition, we proposed two indices for measuring similarities between subjects of current semester and subjects of the previous timetables, and for evaluating distribution degrees of a scheduled timetable. Similarity is measured by comparison of two attributes-subject name and its lecturer-between current semester and a previous semester. The index of distribution degree, based on information entropy, indicates a distribution of subjects in the timetable. To show this study's viability, we implemented a prototype system and performed experiments with the real data of Hanshin University. Average similarity from the most similar cases of all departments was estimated as 41.72%. It means that a timetable template generated from the most similar case will be helpful. Through sensitivity analysis, the result shows that distribution degree will increase if we set 'the number of subjects in the same day-hour' to more than 90%.