• Journal of Arbitration Studies
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• v.28 no.2
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• pp.3-43
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• 2018

The emergence of a multi-door courthouse is related with a couple of reasons as follows: First, a multi-door courthouse was originally initiated by the United States government that increasingly became impatient with the pace and cost of protracted litigation clogging the courts. Second, dockets of courts are overcrowded with legal suits, making it difficult for judges to handle those legal suits in time and causing delays in responding to citizens' complaints. Third, litigation is not suitable for the disputant that has an ongoing relationship with the other party. In this case, even if winning is achieved in the short run, it may not be all that was hoped for in the long run. Fourth, international organizations such as the World Bank, UNDP, and Asia Development Bank urge to provide an increased access to women, residents, and the poor in local communities. The generic model of a multi-door courthouse consists of three stages: The first stage includes a center offering intake services, along with an array of dispute resolution services under one roof. At the second stage, the screening unit at the center would diagnose citizen disputes, then refer the disputants to the appropriate door for handling the case. At the third stage, the multi-door courthouse provides diverse kinds of dispute resolution programs such as mediation, arbitration, mediation-arbitration (med-arb), litigation, and early neutral evaluation. This study suggests the extended model of multi-door courthouse comprised of five layers: intake process, diagnosis and door-selection process, neutral-selection process, implementation process of dispute resolution, and process of training and education. One of the major characteristics of extended multi-door courthouse model is the detailed specification of individual department corresponding to each process within a multi-door courthouse. The intake department takes care of the intake process. The screening department plays the role of screening disputes, diagnosing the nature of disputes, and determining a suitable door to handle disputes. The human resources department manages experts through the construction and management of the data base of mediators, arbitrators, and judges. The administration bureau manages the implementation of each process of dispute resolution. The education and training department builds long-term planning to procure neutrals and experts dealing with various kinds of disputes within a multi-door courthouse. For this purpose, it is necessary to establish networks among courts, law schools, and associations of scholars in order to facilitate the supply of manpower in ADR neutrals, as well as judges in the long run. This study also provides six case studies of multi-door courthouses across continents in order to grasp the worldwide picture and wide spread phenomena of multi-door courthouse. For this purpose, the United States and Latin American countries including Argentina and Brazil, Middle Eastern countries, and Southeast Asian countries (such as Malaysia and Myanmar), Australia, and Nigeria were chosen. It was found that three kinds of patterns are discernible during the evolution of a multi-door courthouse model. First, the federal courts of the United States, land and environment court in Australia, and Lagos multi-door courthouse in Nigeria may maintain the prototype of a multi-door courthouse model. Second, the judicial systems in Latin American countries tend to show heterogenous patterns in terms of the adaptation of a multi-door courthouse model to their own environments. Some court systems of Latin American countries including those of Argentina and Brazil resemble the generic model of a multi-door courthouse, while other countries show their distinctive pattern of judicial system and ADR systems. Third, it was found that legal pluralism is prevalent in Middle Eastern countries and Southeast Asian countries. For example, Middle Eastern countries such as Saudi Arabia have developed various kinds of dispute resolution methods, such as sulh (mediation), tahkim (arbitration), and med-arb for many centuries, since they have been situated at the state of tribe or clan instead of nation. Accordingly, they have no unified code within the territory. In case of Southeast Asian countries such as Myanmar and Malaysia, they have preserved a strong tradition of customary laws such as Dhammthat in Burma, and Shriah and the Islamic law in Malaysia for a long time. On the other hand, they incorporated a common law system into a secular judicial system in Myanmar and Malaysia during the colonial period. Finally, this article proposes a couple of factors to strengthen or weaken a multi-door courthouse model. The first factor to strengthen a multi-door courthouse model is the maintenance of flexibility and core value of alternative dispute resolution. We also find that fund raising is important to build and maintain the multi-door courthouse model, reflecting the fact that there has been a competition surrounding the allocation of funds within the judicial system.

• Journal of the Korea Safety Management & Science
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• v.12 no.1
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• pp.51-57
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• 2010

Cycling that transform human energy into mechanical energy is one of the man-machine systems out of sports fields. Benchmarking means "improving ourselves by learning from others', therefore benchmarking toward dominant cyclist is necessary on field. The goals of this study were to provide important factors on multi-disciplines (kinematics, physiology, power, psychology) for a tailored-training program that is suitable to individual characteristics. Two cyclists participated in this study and gave consent to the experimental procedure. One was dominant cyclist (years: 21 yrs, height: 177 cm, mass: 70 kg), and the other was non-dominant cyclist (years: 21, height: 176, mass: 70). Kinematic data were recorded using six infrared cameras (240Hz) and QTM (software). Physiological data (VO2max, AT) were acquired according to graded exercising test with cycle ergometer and power with Wingate test used by Bar-Or et. al (1977) and to evaluate muscle function with Cybex. Psychological data were collected with competitive state anxiety inventory (CSAI-2) that was devised by Martens et. al (1990) and athletes' self-management questionnaire (ASMQ) of Huh (2003). It appears that the dominant's CV of ankle joint angle was higher than non-dominant's CV and dominant's pedaling pattern was consistent in biomechanics domain, which the dominant's values for all factors ware higher than non-dominant's values in physical, and physiological domain, and their values between cognitive anxiety and somatic anxiety were contrary to each other in psychology. Further research on multi-disciplines may lead to the development of tailored-optimal training programs applicable with key factors to enhance athletic performance by means of research including athlete, coach and parents.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.1
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• pp.413-435
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• 2018

Although the accuracy of handwritten character recognition based on deep networks has been shown to be superior to that of the traditional method, the use of an overly deep network significantly increases time consumption during parameter training. For this reason, this paper took the training time and recognition accuracy into consideration and proposed a novel handwritten character recognition algorithm with newly designed network structure, which is based on an extended nonlinear kernel residual network. This network is a non-extremely deep network, and its main design is as follows:(1) Design of an unsupervised apriori algorithm for intra-class clustering, making the subsequent network training more pertinent; (2) presentation of an intermediate convolution model with a pre-processed width level of 2;(3) presentation of a composite residual structure that designs a multi-level quick link; and (4) addition of a Dropout layer after the parameter optimization. The algorithm shows superior results on MNIST and SVHN dataset, which are two character benchmark recognition datasets, and achieves better recognition accuracy and higher recognition efficiency than other deep structures with the same number of layers.

• Proceedings of the Safety Management and Science Conference
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• 2009.11a
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• pp.15-24
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• 2009

Cycling that transform human energy into mechanical energy is one of the man-machine systems out of sports fields. Benchmarking means " improving ourselves by learning from others ", therefore benchmarking toward dominant cyclist is necessary on field. the goals of this study were to provide important factors on multi-disciplines (kinematics, physiology, power, psychology) for a tailored-training program that is suitable to individual characteristics. Two cyclist participated in this study and gave consent to the experimental procedure. one was dominant cyclist (years:21 yrs, height:177 cm, mass:70 kg), and the other was non-dominant cyclist(years:21, height:176, mass:70). Kinematic data were recorded using six infrared cameras (240Hz) and QTM (software). Physiological data (VO2max, AT) were acquired according to graded exercising test with cycle ergometer and power with Wingate test used by Bar-Or et. al ( 1977) and to evaluate muscle function with Cybex. Psychological data were collected with competitive state anxiety inventory (CSAI-2) that were devised by Martens et. al (1990) and with athletes' self-management questionnaire (ASMQ) of Huh (2003). It appears that the dominant's CV(coefficient of variability) was higher than non-dominant's CV in Sports Biomechanics domain, that the dominant's values for all factors ware higher than non-dominant's values in physical, and physiological domain, and their values between cognitive anxiety and somatic anxiety were contrary to each other in psychology. Further research on multi-disciplines may lead to the development of tailored-optimal training programs applicable with key factors to enhance athletic performance by means of research including athlete, coach and parents.

• Journal of Advanced Navigation Technology
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• v.27 no.5
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• pp.674-684
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• 2023

In this paper, a real-time prediction technique for gravity disturbances is proposed using a multi-layer perceptron (MLP) model. To select a suitable MLP model, 4 models with different network sizes were designed to compare the training accuracy and execution time. The MLP models were trained using the data of vehicle moving along the surface of the sea or land, including their positions and gravity disturbance. The gravity disturbances were calculated using the 2160^th degree and order EGM2008 with SHM. Among the models, MLP4 demonstrated the highest training accuracy. After training, the weights and biases of the 4 models were stored in the embedded computer of the INS to implement the MLP network. MLP4 was found to have the shortest execution time among the 4 models. These research results are expected to contribute to improving the navigation accuracy of INS through gravity disturbance compensation in the future.

• Convergence Security Journal
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• v.24 no.3
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• pp.41-49
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• 2024

A tokenizer, which is a key component of the Transformer model, lacks the ability to effectively comprehend numerical data. Therefore, to develop a Transformer-based intrusion detection model that can operate within a real-world network environment by training packet payloads as sentences, it is necessary to convert the hexadecimal packet payloads into a character-based format. In this study, we applied three character encoding methods to convert packet payloads into numeric or character format and analyzed how detection performance changes when training them on transformer architecture. The experimental dataset was generated by extracting packet payloads from PCAP files included in the UNSW-NB15 dataset, and the RoBERTa was used as the training model. The experimental results demonstrate that the ISO-8859-1 encoding scheme achieves the highest performance in both binary and multi-class classification. In addition, when the number of tokens is set to 512 and the maximum number of epochs is set to 15, the multi-class classification accuracy is improved to 88.77%.

• Journal of The Korean Society of Integrative Medicine
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• v.12 no.1
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• pp.109-124
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• 2024

Purpose : The purpose of this study was to examine the effects of a virtual reality-based complex cognitive training program for depression, cognitive function, and digital divide reduction in the elderly who have not been diagnosed with dementia or MCI. Methods : We enrolled 16 participants who were over 65 years old and not been diagnosed with dementia or MCI. We randomly divided into three groups (A, B, C). Participants underwent an 8-week virtual reality-based complex cognitive training program (60 minutes each session, twice per week). At a baseline, all participants completed questionnaires on general features, depression and cognitive function. After four weeks, all participants completed questionnaires on depression and cognitive function. After the end of the last program, participants conducted questionnaires on depression, cognitive function, and usability evaluation. Results : At the 8-week follow-up, 16 participants completed the program. Compared to the baseline, the average score of cognitive function was increased (from 26.5 to 28.5), although it was not statistically significant (p<.061). There were no significant differences between baseline and post-training evaluations on depression scores. The average score of usability evaluation was 75.56, which corresponds to good. Conclusion : Even though the results showed no statistically significant findings in cognitive function and depression after the virtual reality-based complex cognitive training intervention, this pilot study proposed the possibility of utilizing the virtual reality program as a tool that provides active learning opportunities for the elderly and helps improve their cognitive function through multi-sensory components. Also, the findings of this study suggested a positive reevaluation of the elderly's digital access capabilities while reducing the digital divide. A virtual reality-based complex cognitive training program improved the social network of the elderly. We expect that it will expand in size and help with their social participation of the elderly.

• Korean Journal of Fisheries and Aquatic Sciences
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• v.5 no.1
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• pp.11-16
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• 1972

During the period from 1966 to 1968, total catches of Spanish mackerel averaged 6,000 to 7,000M/T per annual in Korea, and approximately 70 per cent of this amount was captured by drift nets. In an effort to improve the efficiency of drift nets, some experiments were conducted in 1969 to investigate the selectivity of material and mesh sizes. Seven different mesh sizes (80,85,95,100,105,110 and 115 mm) of both multi- and mono-filament netting were used, and the following results were obtained : 1, The body weight of Spanish mackerel taken with the seven different mesh sizes ranges from 0.5kg to 2.9kg, and the mode of body weight consists of three groups, 1kg ($21%$), 1.3kg($15\%$) and 1.5kg($19\%$). 2. For multi-filament net, 80 to 105mm mesh sizes were suitable to catch those three groups, and a little smalter than these for mono-filament net. 3. For Spanish mackerel only, the mono-filament material proved to have 1.5 times better selectivity than multi-filament : however, the latter proved superior for miscellaneous fish species due to its different size and shape. 4. Multi-filament net showed better selectivity for smaller species than mono-filament. (and mono-filament in general indicated opposite phenomenon.)

• Journal of the Korean Society for information Management
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• v.33 no.2
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• pp.33-59
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• 2016

This study examined the factors affecting the performance of automatic classification for the domestic conference papers based on machine learning techniques. In particular, In view of the classification performance that assigning automatically the class labels to the papers in Proceedings of the Conference of Korean Society for Information Management using Rocchio algorithm, I investigated the characteristics of the key factors (classifier formation methods, training set size, weighting schemes, label assigning methods) through the diversified experiments. Consequently, It is more effective that apply proper parameters (${\beta}$, ${\lambda}$) and training set size (more than 5 years) according to the classification environments and properties of the document set. and If the performance is equivalent, I discovered that the use of the more simple methods (single weighting schemes) is very efficient. Also, because the classification of domestic papers is corresponding with multi-label classification which assigning more than one label to an article, it is necessary to develop the optimum classification model based on the characteristics of the key factors in consideration of this environment.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.19 no.3
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• pp.115-120
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• 2019

Hemiplegic patients who suffered from a stroke struggle with a deterioration in upper limb functions, which can both be psychologically and physically discomforting; this can also limit patients' daily tasks involving any upper limb motions. In this study, we developed an assistive device for hemiplegic patients to improve their upper limb functions. It was manufactured to train patients by using their grip strength and the range of motion of the arm. Furthermore, we produced game contents in virtual reality to induce users' immersion and interaction. It was configured as a multi-player game to help ease the mental burden of receiving the training alone, hence allowing the patient and the caregiver to join the rehabilitation training simultaneously. The assistive device and game contents developed in this study enables patients and caregivers to easily check the degree of improvements in upper limb function by viewing quantitative analysis and visualized results.