Lee Tae Kyung;Jon E. Grant;Kim, Suck Won;Oh Dong Yul
Journal of The Korean Society of Clinical Toxicology
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v.1
no.1
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pp.21-26
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2003
Methamphetamine (MA) is a major drug of abuse in Korea. Currently preliminary evidence suggests that MA dependence may cause long-term neural damage in human. Repeated exposure to psychostimulants such as methamphetamine results in behavioral sensitization, a paradigm thought to be relevant to drug craving and addiction in human. Sensitization alters neural circuitry involved in normal processes of incentrive, motivation, and reward. However the precise mechanism of this behavioral sensitization has not yet been fully elucidated. Repeated use of high dose MA causes neurotoxicity which is characterized by a long-lasting depletion of striatal dopamine (DA) and tyrosin hydroxylase activity of DA, DA-transporter binding sites in the striatum. The loss of DA transporters correlates with memory problems and lack of motor coordination. DA fuels motivation and pleasure, but it' s also crucial for learning and movement. This selective review provides a summary of studies that assess the neurobiological mechanisms of MA.
This paper proposes a method for evaluating the work of manufacturing workers using MediaPipe as a risk factor for musculoskeletal diseases. Recently, musculoskeletal disorders (MSDs) caused by repeated working attitudes in industrial sites have emerged as one of the biggest problems in the industrial health field while increasing public interest. The Korea Occupational Safety and Health Agency presents tools such as NIOSH Lifting Equations (NIOSH), OWAS (Ovako Working-posture Analysis System), Rapid Upper Limb Assessment (RULA), and Rapid Entertainment Assessment (REBA) as ways to quantitatively calculate the risk of musculoskeletal diseases that can occur due to workers' repeated working attitudes. To compensate for these shortcomings, the system proposed in this study obtains the position of the joint by estimating the posture of the worker using the posture estimation learning model of MediaPipe. The position of the joint is calculated using inverse kinetics to obtain an angle and substitute it into the REBA equation to calculate the load level of the working posture. The calculated result was compared to the expert's image-based REBA evaluation result, and if there was a result with a large error, feedback was conducted with the expert again.
The aim of this study was to estimate the benefit from repeated examinations in the diagnosis of enterobiasis in nursery school groups, and to test the effectiveness of individual-based risk predictions using different methods. A total of 604 children were examined using double, and 96 using triple, anal swab examinations. The questionnaires for parents, structured observations, and interviews with supervisors were used to identify factors of possible infection risk. In order to model the risk of enterobiasis at individual level, a similarity-based machine learning and prediction software Constud was compared with data mining methods in the Statistica 8 Data Miner software package. Prevalence according to a single examination was 22.5%; the increase as a result of double examinations was 8.2%. Single swabs resulted in an estimated prevalence of 20.1% among children examined 3 times; double swabs increased this by 10.1%, and triple swabs by 7.3%. Random forest classification, boosting classification trees, and Constud correctly predicted about 2/3 of the results of the second examination. Constud estimated a mean prevalence of 31.5% in groups. Constud was able to yield the highest overall fit of individual-based predictions while boosting classification tree and random forest models were more effective in recognizing Enterobius positive persons. As a rule, the actual prevalence of enterobiasis is higher than indicated by a single examination. We suggest using either the values of the mean increase in prevalence after double examinations compared to single examinations or group estimations deduced from individual-level modelled risk predictions.
Topic extraction is a technology that automatically extracts a set of topics from a set of documents, and this has been a major research topic in the area of natural language processing. Representative topic extraction methods include Latent Dirichlet Allocation (LDA) and word clustering-based methods. However, there are problems with these methods, such as repeated topics and mixed topics. The problem of repeated topics is one in which a specific topic is extracted as several topics, while the problem of mixed topic is one in which several topics are mixed in a single extracted topic. To solve these problems, this study proposes a method to extract topics using an LDA that is robust against the problem of repeated topic, going through the steps of separating and merging the topics using the similarity between words to correct the extracted topics. As a result of the experiment, the proposed method showed better performance than the conventional LDA method.
The purpose of this thesis is that the students understand the sentence stated math problems closely related to the real life and adapted the right solving strategies try to find the solution to a problem. The following research problem were proposed. 1. How repeated thinking lessons develop the understanding of problems and influence the usage of correct problem solving strategies and extensions of problem solving. 2. There are how much differences of achievement for each type of sentence stated problems by using comparative analysis of upper class, intermediate class, and lower class for each level between the experimental and comparative classes. In order to conduct this research the classes were divided into three different level - upper class, intermediate class and lower class. Each level include an experimental class and a comparative class. The two classes (experimental class and comparative class) of the same level were tested on the basis of class division record with the experimental class repeated learning papers for two weeks were used to guide the fixed thinking algorism for each sentence stated math problems. Eight common problems were chosen from a variety of textbooks : number calculation problems, velocity-distance-time problems, the density of a mixture, benefit problems, distribution problems, problems about working, ratio problems, the length of a figure problems. After conducting this research experiment The differences in achievement level between the experimental class and comparative class, were compared and analyzed through achievement tests made from the achievement test papers with seven problems, which were worth seventy points (total score). The conclusions of this thesis are as follows: Firstly, leaning activities through the usage of repeated learning papers for each level class produce an even development of achievement level especially in the case of the upper class learners, they have particular differences (between experimental class and comparative class) compared to the intermediate level and lower classes. Secondly, according to the analysis about achievement development each problems, learners easily accept the strategies of solution through the formula setting up to the problem of velocity -distance-time, and to the density of the mixture they adapted the picture drawing strategies interestingly, However each situation requires a variety of appropriate solution strategies. Teachers will have to employ other interesting solution strategies which relate to real life.
Objective: The purpose of the this study was to test the effect of the alcohol preventive educational program for elementary school students through developing the web-based learning instruments. It will prevent the serious alcohol problem for adolescents and be the opening-learning according to learner's needs beyond the traditional classroom learning which has limitation of space and time. Method: This research designed based on web-based instructional system design by In-sung Jong(1997). This study was performed on the elementary school students who are the six grade in M city. The number of experimental group was 72 and control group's number was 72, totaled 144. Data were collected from September, 30th, 2004 to November, 5th, 2004, totaled 37days. The pretest and the posttest for web-based alcohol preventive education program were tested about knowledge and attitudes toward drinking. After the performance, the posttest was also tested the effect of this program under items by the interest of web-based learning, satisfaction, adequateness of material and so on. The data analysis was done using SPSS/Win 11.0 program. Result: The results of this study are as follows: 1) Compared with control group, experimental group which was educated the web-based alcohol preventive educational program for elementary school students was improved the knowledge on drinking, thin there was no significant difference. However, it showed significant difference between two groups after education. It was, therefore, partially supported. 2) Compared with control group, the experimental group which was educated the web-based alcohol preventive educational program for elementary school students showed significant difference in attitudes toward drinking. After education, it showed no significant difference attitudes. toward drinking between experimental group and control group. It was, therefore, partially supported. 3) The degree of learning motivation was an average.595 of 1 after learning applied to by the web-based alcohol preventive educational program for elementary school students. Then, it is relatively more higher than the result of existing studies. So, it showed that the motivation was done well. 4) Correlation among study variables It showed that there was the significantly positive correlation between knowledge and attitudes toward drinking of pretest experimental group. Also, there was the significantly positive correlation between attitudes toward drinking and learning motivation of pretest and posttest experimental group. Conclusion: I found that the web-based educational program helps the elarning process for the health education in the school field which the instructional materials lack. As a result, the web-based education motivates the learner's pleasure and promotes the learners interest. Also, it is possible for students to learn according to their own learning pace, repeated learning and active learning participation in the necessary parts. Therefore, I think the web-based educational program is worth as a intervention to get positive influence for the health education.
The purpose of this study was to design the coaching strategies for the problem based learning and examine 'the problem situation' to analyze the process of learning as it applies to the students' perception on problem based learning. The steps of this model were as follows: 1) presentation of the problem situation 2) confrontation of the problem 3) know/ need to know 4) definition of the problem statement 5) collection and sharing of information 6)generation of possible solutions 7) assessment of the best fit of solutions 8) presentation of the solution. Problem-based learning steps and coaching strategies were designed and implemented to 2nd grade high school students for the environment teaching unit. The results demonstrated that group discussion in the know/need to know step was most helpful for students to review what they know and generate solutions. At first students tend to state problems widely but through repeated group discussions they gradually clarified the problems. In the students' personal reflection notes and perception questionnaire of problem-based learning, many students especially showed difficulties in defining the problem statement. In contrast they participated actively in the learning process and express their opinions enthusiastically. Therefore, this study suggests that developing problem situation based on real context is of great importance for implementing a problem based teaming model continuously.
This paper presents an internet-based self-learning educational system which can be enhancing efficiency in the learning process of Java language. The proposed self-learning educational system is called Java Web Player(JWP), which is a Java application program and is executable through Java Web Start technologies. Also, three important sequential learning processes : concept learning process, programming practice process and assessment process are integrated in the proposed JWP using Java Web Start technologies. This JWP enables the learners to achieve efficient and interesting self-learning since the learning process is designed to enhance the multimedia capabilities on the basis of various educational technologies. Furthermore, internet-based on-line voice presentation and its related texts together with moving images are synchronized for efficient language learning process. Also, a simple and useful Java compiler is included in the JWP for providing language practice environment such as coding, editing, executing and debugging Java source files. Finally, repeated practice can make the learners to understand easily the key concepts of Java language. Simple multiple choices are given suddenly to the learners while they are studying through the JWP and the test results are displayed on the message box. This assessment process is very essential to increase the learner's academic capability.
Journal of Korean Tunnelling and Underground Space Association
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v.21
no.3
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pp.419-432
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2019
Most of deep learning model training was proceeded by supervised learning, which is to train labeling data composed by inputs and corresponding outputs. Labeling data was directly generated manually, so labeling accuracy of data is relatively high. However, it requires heavy efforts in securing data because of cost and time. Additionally, the main goal of supervised learning is to improve detection performance for 'True Positive' data but not to reduce occurrence of 'False Positive' data. In this paper, the occurrence of unpredictable 'False Positive' appears by trained modes with labeling data and 'True Positive' data in monitoring of deep learning-based CCTV accident detection system, which is under operation at a tunnel monitoring center. Those types of 'False Positive' to 'fire' or 'person' objects were frequently taking place for lights of working vehicle, reflecting sunlight at tunnel entrance, long black feature which occurs to the part of lane or car, etc. To solve this problem, a deep learning model was developed by simultaneously training the 'False Positive' data generated in the field and the labeling data. As a result, in comparison with the model that was trained only by the existing labeling data, the re-inference performance with respect to the labeling data was improved. In addition, re-inference of the 'False Positive' data shows that the number of 'False Positive' for the persons were more reduced in case of training model including many 'False Positive' data. By training of the 'False Positive' data, the capability of field application of the deep learning model was improved automatically.
The appearnace of web technology has accelerated the development of the multimedia technology, the computer communication technology and the multimedia application contents. Researches on WBI(Web-based Instruction) system have combined the technology of the digital library and LOD,. REcently WBI(Web-based Instruction) model which is based on web has been proposed in the part of the new activity model of teaching-learning. As the demand of the customized coursewares from the lwarners is increased, the needs of the efficient and automated education agents in the web-based instruction are recognized. In this paper we propose a system monitors learner's behaviors constantly, evaluates them, and calculates his accomplishment. And the system offers suitable course to learner applying this accomplishment degree to agent's schedules. Therefore, the learner achieves an active and complete learning from the repeated and suitable course semantic-based retrieval.
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