• Therapeutic Science for Rehabilitation
• /
• v.8 no.1
• /
• pp.41-50
• /
• 2019

Objective: The purpose of this study was to investigate whether there is a difference in the brain connectivity in mental practice and physical performance of training bilateral upper extremity function. Method: The subject performed activities involving mental tasks and physical exercise for bilateral upper extremity functioning during each phase of EEG measurements. The subject performed a symmetrical task(lifting a box and placing it back) that involved moving both arms at the same time and an asymmetrical task(opening and closing a bottle cap) in order to perform functional tasks. EEG electrodes were attached to Fp1, Fp2, F3, F4, T3, T4, P3, and P4. Data analysis was performed using Cross-Line Mapping for correlational analyses between EEG electrode pairs. Conclusion: This study found that the brain connectivity patterns of symmetrical and asymmetric upper extremity tasks have similar patterns for the motor and sensory area, and that the correlation of the physical practice is generally higher than that of the mental practice.

• Journal of Oral Medicine and Pain
• /
• v.36 no.3
• /
• pp.169-176
• /
• 2011

Oromandibular dystonia (OMD) is a form of focal dystonia that affects the masticatory, facial and lingual muscles in any variety of combinations, which results in repetitive involuntary and possibly painful jaw opening, closing, deviation or a combination of these movements. This study aimed to investigate clinical features and treatment type of OMD patients. By retrospective chart review, the study was conducted to consecutive OMD patients who visited a department of Oral Medicine and Orofacial Pain Clinic in a university dental hospital during Aug 2007 to Apr 2010. 78 OMD patients were identified with female preponderance (M:F=1:3.6) and a mean age of 72 years. Their mean duration of OMD was about 10 months. The most common chief complaints at the first visit was jaw ache, followed by uncontrolled, repetitive movement of the jaw and/or oral tissues, pain in the oral region(p=0.000). The most common subtype of OMD was lateral jaw-deviation dystonia, followed by combination and jaw-closing dystonia(p=0.001). While no apparent cause was recognized in over 60% of the OMD patients, peripheral trauma including dental treatment such as prosthetic treatment and extraction was the most frequently reported as precipitating factor(p=0.000). Medication was the 1st line therapy for our patients and anxiolytics such as clonazepam was given to most of them. Based on the results of this study, OMD is the disease of the elderly, particularly of women and causes orofacial pain and compromises function of orofacial region. Some patients considered dental treatment a precipitating factor. Dentists, therefore, should have knowledge of symptoms and treatment of OMD.

• Journal of Intelligence and Information Systems
• /
• v.19 no.4
• /
• pp.55-79
• /
• 2013

In this paper, we propose a hybrid genetic algorithm (HGA) approach to effectively solve the reverse logistics network with centralized centers (RLNCC). For the proposed HGA approach, genetic algorithm (GA) is used as a main algorithm. For implementing GA, a new bit-string representation scheme using 0 and 1 values is suggested, which can easily make initial population of GA. As genetic operators, the elitist strategy in enlarged sampling space developed by Gen and Chang (1997), a new two-point crossover operator, and a new random mutation operator are used for selection, crossover and mutation, respectively. For hybrid concept of GA, an iterative hill climbing method (IHCM) developed by Michalewicz (1994) is inserted into HGA search loop. The IHCM is one of local search techniques and precisely explores the space converged by GA search. The RLNCC is composed of collection centers, remanufacturing centers, redistribution centers, and secondary markets in reverse logistics networks. Of the centers and secondary markets, only one collection center, remanufacturing center, redistribution center, and secondary market should be opened in reverse logistics networks. Some assumptions are considered for effectively implementing the RLNCC The RLNCC is represented by a mixed integer programming (MIP) model using indexes, parameters and decision variables. The objective function of the MIP model is to minimize the total cost which is consisted of transportation cost, fixed cost, and handling cost. The transportation cost is obtained by transporting the returned products between each centers and secondary markets. The fixed cost is calculated by opening or closing decision at each center and secondary markets. That is, if there are three collection centers (the opening costs of collection center 1 2, and 3 are 10.5, 12.1, 8.9, respectively), and the collection center 1 is opened and the remainders are all closed, then the fixed cost is 10.5. The handling cost means the cost of treating the products returned from customers at each center and secondary markets which are opened at each RLNCC stage. The RLNCC is solved by the proposed HGA approach. In numerical experiment, the proposed HGA and a conventional competing approach is compared with each other using various measures of performance. For the conventional competing approach, the GA approach by Yun (2013) is used. The GA approach has not any local search technique such as the IHCM proposed the HGA approach. As measures of performance, CPU time, optimal solution, and optimal setting are used. Two types of the RLNCC with different numbers of customers, collection centers, remanufacturing centers, redistribution centers and secondary markets are presented for comparing the performances of the HGA and GA approaches. The MIP models using the two types of the RLNCC are programmed by Visual Basic Version 6.0, and the computer implementing environment is the IBM compatible PC with 3.06Ghz CPU speed and 1GB RAM on Windows XP. The parameters used in the HGA and GA approaches are that the total number of generations is 10,000, population size 20, crossover rate 0.5, mutation rate 0.1, and the search range for the IHCM is 2.0. Total 20 iterations are made for eliminating the randomness of the searches of the HGA and GA approaches. With performance comparisons, network representations by opening/closing decision, and convergence processes using two types of the RLNCCs, the experimental result shows that the HGA has significantly better performance in terms of the optimal solution than the GA, though the GA is slightly quicker than the HGA in terms of the CPU time. Finally, it has been proved that the proposed HGA approach is more efficient than conventional GA approach in two types of the RLNCC since the former has a GA search process as well as a local search process for additional search scheme, while the latter has a GA search process alone. For a future study, much more large-sized RLNCCs will be tested for robustness of our approach.

• Nuclear Engineering and Technology
• /
• v.52 no.7
• /
• pp.1396-1408
• /
• 2020

Filtered containment venting system (FCVS) is one of the severe accident mitigation systems designed to release containment pressurization to maintain its integrity. The thermal-hydraulic behaviors in FCVSs are important since they affect the operation characteristics of the FCVS. In this study, a representative FCVS was modeled by RELAP5/Mod3.3 code, and the Station BlackOut (SBO) was chosen as an accident scenario. The thermal-hydraulic behaviors of an FCVS during long-term operation with two venting strategies (open-and-close strategy, open-and-non-close strategy) and the sensitivity analysis of important parameters were investigated. The results show that the FCVS can operate up to 250 h with a periodic open-and-close strategy during an SBO. Under the combined effects of steam condensation and water evaporation, the solution inventory in the FCVS increases during the venting phase and decreases during the intermission phase, showing a periodic pattern. Under this condition, the appropriate initial water level is 3-4 m; however, it should be adjusted according to the environment temperature. The FCVS can accommodate a decay heat power of 150-260 kW and may need to feed water for a higher decay heat power or drain water for a lower decay heat power during the late phase. The FCVS can function within an opening pressure range from 450 kPa to 500 kPa and a closing pressure range between 250 kPa and 350 kPa. When the open-and-non-close strategy is adopted, the solution inventory increases quickly in the early venting phase due to steam condensation and then decreases gradually due to the evaporation of water; drying-up may occur in the late venting phase. Decreasing the venting pipe diameter and increasing the initial water level can mitigate the evaporation of the scrubbing solution. These results are expected to provide useful references for the design and engineering application of FCVSs.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.18 no.11
• /
• pp.644-652
• /
• 2017

The purpose of this study was to analyze the EEG according to the elderly's tendency to be addicted to smartphone games. We compared the effects of smartphone addiction on mental health such as brain waves, sleep problems and depression through comparative analysis of asymmetry and connectivity in quantitative EEG results. The study participants were two elderly people who were addicted to smartphone game and one elderly person who did not use smartphone (Ed- to confirm: only 3 participants?!). The participant's addiction tendency of smartphone was measured by using the smartphone addiction scale and EEG (QEEG) was used for EEG analysis. The results are as follows. First, the brain waves of elderly people and smartphone non-user elderly who showed symptoms of immersion and smartphone game showed a difference in asymmetry in both opening and closing anisles. Second, there were significant differences in the openness and the anxiety of the elderly who were immersed in the mobile phone and the elderly who did not use the smartphone. Through this, it is also meaningful to explore the relationship between senile cognitive impairment and smartphone use by exploring the effect of smartphone game use on brain cognitive function through comparison of EEG analysis.

• Progress in Medical Physics
• /
• v.19 no.3
• /
• pp.178-185
• /
• 2008

Living donor liver transplantation is increasingly performed as an alternative to cadaveric transplantation. Preoperative screening of the donor candidates is very important. The quality, size, and vascular and biliary anatomy of the liver are best assessed with magnetic resonance (MR) imaging or computed tomography (CT). In particular, the volume of the potential graft must be measured to ensure sufficient liver function after surgery. Preoperative liver segmentation has proved useful for measuring the graft volume before living donor liver transplantations in previous studies. In these studies, the liver segments were manually delineated on each image section. The delineated areas were multiplied by the section thickness to obtain volumes and summed to obtain the total volume of the liver segments. This process is tedious and time consuming. To compensate for this problem, automatic segmentation techniques have been proposed with multiplanar CT images. These methods involve the use of sequences of thresholding, morphologic operations (ie, mathematic operations, such as image dilation, erosion, opening, and closing, that are based on shape), and 3D region growing methods. These techniques are complex but require a few computation times. We made a phantom for volume measurement with pig and evaluated actual volume of spleen and liver of phantom. The results represent that our semiautomatic volume measurement algorithm shows a good accuracy and repeatability with actual volume of phantom and possibility for clinical use to assist physician as a measuring tool.

• Journal of Intelligence and Information Systems
• /
• v.18 no.2
• /
• pp.143-156
• /
• 2012

People easily believe that news and stock index are closely related. They think that securing news before anyone else can help them forecast the stock prices and enjoy great profit, or perhaps capture the investment opportunity. However, it is no easy feat to determine to what extent the two are related, come up with the investment decision based on news, or find out such investment information is valid. If the significance of news and its impact on the stock market are analyzed, it will be possible to extract the information that can assist the investment decisions. The reality however is that the world is inundated with a massive wave of news in real time. And news is not patterned text. This study suggests the stock-index invest model based on "News Big Data" opinion mining that systematically collects, categorizes and analyzes the news and creates investment information. To verify the validity of the model, the relationship between the result of news opinion mining and stock-index was empirically analyzed by using statistics. Steps in the mining that converts news into information for investment decision making, are as follows. First, it is indexing information of news after getting a supply of news from news provider that collects news on real-time basis. Not only contents of news but also various information such as media, time, and news type and so on are collected and classified, and then are reworked as variable from which investment decision making can be inferred. Next step is to derive word that can judge polarity by separating text of news contents into morpheme, and to tag positive/negative polarity of each word by comparing this with sentimental dictionary. Third, positive/negative polarity of news is judged by using indexed classification information and scoring rule, and then final investment decision making information is derived according to daily scoring criteria. For this study, KOSPI index and its fluctuation range has been collected for 63 days that stock market was open during 3 months from July 2011 to September in Korea Exchange, and news data was collected by parsing 766 articles of economic news media M company on web page among article carried on stock information>news>main news of portal site Naver.com. In change of the price index of stocks during 3 months, it rose on 33 days and fell on 30 days, and news contents included 197 news articles before opening of stock market, 385 news articles during the session, 184 news articles after closing of market. Results of mining of collected news contents and of comparison with stock price showed that positive/negative opinion of news contents had significant relation with stock price, and change of the price index of stocks could be better explained in case of applying news opinion by deriving in positive/negative ratio instead of judging between simplified positive and negative opinion. And in order to check whether news had an effect on fluctuation of stock price, or at least went ahead of fluctuation of stock price, in the results that change of stock price was compared only with news happening before opening of stock market, it was verified to be statistically significant as well. In addition, because news contained various type and information such as social, economic, and overseas news, and corporate earnings, the present condition of type of industry, market outlook, the present condition of market and so on, it was expected that influence on stock market or significance of the relation would be different according to the type of news, and therefore each type of news was compared with fluctuation of stock price, and the results showed that market condition, outlook, and overseas news was the most useful to explain fluctuation of news. On the contrary, news about individual company was not statistically significant, but opinion mining value showed tendency opposite to stock price, and the reason can be thought to be the appearance of promotional and planned news for preventing stock price from falling. Finally, multiple regression analysis and logistic regression analysis was carried out in order to derive function of investment decision making on the basis of relation between positive/negative opinion of news and stock price, and the results showed that regression equation using variable of market conditions, outlook, and overseas news before opening of stock market was statistically significant, and classification accuracy of logistic regression accuracy results was shown to be 70.0% in rise of stock price, 78.8% in fall of stock price, and 74.6% on average. This study first analyzed relation between news and stock price through analyzing and quantifying sensitivity of atypical news contents by using opinion mining among big data analysis techniques, and furthermore, proposed and verified smart investment decision making model that could systematically carry out opinion mining and derive and support investment information. This shows that news can be used as variable to predict the price index of stocks for investment, and it is expected the model can be used as real investment support system if it is implemented as system and verified in the future.