• Asian-Australasian Journal of Animal Sciences
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• v.32 no.3
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• pp.309-319
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• 2019

Phytochemicals which exist in various plants and fungi are non-nutritive compounds that exert numerous beneficial bioactive actions for animals. In recent years following the restriction of antibiotics, phytochemicals have been regarded as a primal selection when dealing with the challenges during the producing process in the poultry industry. The selected fast-growing broiler breed was more fragile when confronting the stressors in their growing environments. The disruption of oxidative balance that impairs the production performance in birds may somehow be linked to the immune system since oxidative stress and inflammatory damage are multi-stage processes. This review firstly discusses the individual influence of oxidative stress and inflammation on the poultry industry. Next, studies related to the application of phytochemicals or botanical compounds with the significance of their antioxidant and immunomodulatory abilities are reviewed. Furthermore, we bring up nuclear factor (erythroid-derived 2)-like 2 (Nrf2) and nuclear factor kappa B ($NF-{\kappa}B$) for they are respectively the key transcription factors involved in oxidative stress and inflammation for elucidating the underlying signal transduction pathways. Finally, by the discussion about several reports using phytochemicals to regulate these transcription factors leading to the improvement of oxidative status, heme oxygenase-1 gene is found crucial for Nrf2-mediated $NF-{\kappa}B$ inhibition.

• Journal of the Korean Institute of Intelligent Systems
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• v.10 no.4
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• pp.343-350
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• 2000

In this paper, we propose the Multi-FPNN(Fuzzy Polynomial Neural Networks) model based on FNN and PNN(Polyomial Neural Networks) for optimal system identifacation. Here FNN structure is designed using fuzzy input space divided by each separated input variable, and urilized both in order to get better output performace. Each node of PNN structure based on GMDH(Group Method of Data handing) method uses two types of high-order polynomials such as linearane and quadratic, and the input of that node uses three kinds of multi-variable inputs such as linear and quadratic, and the input of that node and Genetic Algorithms(GAs) to identify both the structure and the prepocessing of parameters of a Multi-FPNN model. Here, HCM clustering method, which is carried out for data preproessing of process system, is utilized to determine the structure method, which is carried out for data preprocessing of process system, is utilized to determance index with a weighting factor is used to according to the divisions of input-output space. A aggregate performance inddex with a wegihting factor is used to achieve a sound balance between approximation and generalization abilities of the model. According to the selection and adjustment of a weighting factor of this aggregate abjective function which it is acailable and effective to design to design and optimal Multi-FPNN model. The study is illustrated with the aid of two representative numerical examples and the aggregate performance index related to the approximation and generalization abilities of the model is evaluated and discussed.

• The Journal of the Korea Contents Association
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• v.15 no.5
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• pp.426-435
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• 2015

The aim of this study was to investigate the effects of an one-to-one fall prevention education on the falls and fall factors of adults who have had a stroke. 17 adults who have had a stroke were recruited and a total of four sessions of weekly one-to-one fall prevention educational program was developed considering the stroke population's cognitive abilities. Each sessions were composed of different fall-related subjects of introduction of fall, fall prevention exercise, fall prevention assistive device, and fall prevention environment modification. Dependent variables were the number of fall and fall danger in the recent month, balance ability, fear of falls, fall efficacy and depression. After four sessions of one-to-one fall prevention education, participants showed significantly positive changes in all dependent variables except for the balance ability(p<.05). An one-to-one fall prevention education to adults with stroke could decrease the number of fall and fall danger, fear of falls, depressive symptoms and fall efficacy. In order for the stroke adults to remain safely in their community and hospital, an one-to-one fall preventive education considering their cognitive level is needed.

• Journal of Korean Physical Therapy Science
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• v.19 no.3
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• pp.49-56
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• 2012

Background : The purpose of this study is to understand the effects of ankle joint taping on balancing abilities of the elderly and to provide preliminary data on preventing falls among the elderly. Methods : In this study, 20 students(8 male, 12 female) in their 20s from D University as well as 14 elderly(4 male, 10 female) in their 70s from S community center have participated. The participants were well informed about the experiment and voluntarily participated. We measured the difference in balancing ability before and after taping between the two groups using methods such as standing on single-leg stance, TUG, and plantar pressure. Kinesio taping, a stop-watch, and the EMED-system were used as equipment along with the SPSS 12.0 program, with a significance level of 0.05, to test the difference before and after taping between the two groups. Result : First, the 70s group showed a significant increase in the dorsal flexion angle after taping. Second, the 70s group showed a significant increase in duration time of standing on one foot after taping. Third, the 70s group's TUG time was significantly shorter. Fourth, the maximum peak value for static and dynamic plantar pressure showed a significant decrease after taping; and dynamic plantar pressure area value decreased as well within significant range. Conclusion : The study has shown that taping is effective on static dynamic balancing ability of the elderly.

• Journal of the Korean Society of Physical Medicine
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• v.17 no.4
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• pp.103-111
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• 2022

PURPOSE: This study was performed to investigate the effects of the whole-body vibration exercise combined with ankle joint mobilization on the gait and balancing ability in patients with hemiplegic stroke. METHODS: A total of 19 patients at a rehabilitation hospital who had suffered a hemiplegic stroke were randomly assigned to the experimental group (whole-body vibration exercise combined with ankle joint mobilization, n=10) or control group (whole-body vibration exercise, n=9). All participants underwent 30 min of comprehensive rehabilitation therapy (5 × /week for 6 weeks). Additionally, the experimental group performed the whole body vibration exercise and ankle joint mobilization (15 minutes each, 30 minutes total, 3 × / week for 6 weeks). In the control group, only the whole- body vibration exercise was performed in the same manner and not the ankle joint mobilization. The gait and balancing abilities were measured before and after the 6-week training. RESULTS: Significant improvements were observed in the 10-m walk test, timed up-and-go (TUG) test, center of pressure (COP) path length, and COP path velocity in the experimental group (p < .05). The experimental group showed a larger decrease in the COP path length and velocity than the control group (COP path length, -10.27 mm vs. -3.67 mm, p < .05; COP path velocity, -.33 cm/sec vs. -.13 cm/sec, p < .05, respectively). CONCLUSION: The whole-body vibration exercise combined with ankle joint mobilization could be effective in improving the gait and balancing ability of stroke patients and could also be more effective for improving the static balance ability than the general whole-body vibration exercise alone.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.53 no.1
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• pp.40-49
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• 2004

In this paper, we propose a new architecture of Genetic Algorithms(GAs)-based Self-Organizing Polynomial Neural Networks(SOPNN), discuss a comprehensive design methodology and carry out a series of numeric experiments. The conventional SOPNN is based on the extended Group Method of Data Handling(GMDH) method and utilized the polynomial order (viz. linear, quadratic, and modified quadratic) as well as the number of node inputs fixed (selected in advance by designer) at Polynomial Neurons (or nodes) located in each layer through a growth process of the network. Moreover it does not guarantee that the SOPNN generated through learning has the optimal network architecture. But the proposed GA-based SOPNN enable the architecture to be a structurally more optimized network, and to be much more flexible and preferable neural network than the conventional SOPNN. In order to generate the structurally optimized SOPNN, GA-based design procedure at each stage (layer) of SOPNN leads to the selection of preferred nodes (or PNs) with optimal parameters- such as the number of input variables, input variables, and the order of the polynomial-available within SOPNN. An aggregate performance index with a weighting factor is proposed in order to achieve a sound balance between approximation and generalization (predictive) abilities of the model. A detailed design procedure is discussed in detail. To evaluate the performance of the GA-based SOPNN, the model is experimented with using two time series data (gas furnace and NOx emission process data of gas turbine power plant). A comparative analysis shows that the proposed GA-based SOPNN is model with higher accuracy as well as more superb predictive capability than other intelligent models presented previously.

• The Journal of the Korea Contents Association
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• v.8 no.1
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• pp.339-347
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• 2008

A balanced game is one where the main determining factor for the success of the player is the skill level of that player Random events can occur, but a better player should be more successful than a poor one unless the player has an unusually long run of bad luck. Balancing a game is a very difficult to define a purpose, and to implement process. The possible ways are somewhat subjective and depend on the nature of the game. This paper provides new algorithm for character adjustment using log function with some nature-based Ideas. The algorithm shows not only how we decide the exact point of character adjustment but also how much we have to modify the parameters for changing abilities of the character. This paper shows the experimental results of the algorithm and shows differences between normal game playing and playing with character adjustment.

• International Journal of Control, Automation, and Systems
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• v.1 no.2
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• pp.194-202
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• 2003

In this paper, we introduce a category of Multi-FNN (Fuzzy-Neural Networks) models, analyze the underlying architectures and propose a comprehensive identification framework. The proposed Multi-FNNs dwell on a concept of fuzzy rule-based FNNs based on HCM clustering and evolutionary fuzzy granulation, and exploit linear inference being treated as a generic inference mechanism. By this nature, this FNN model is geared toward capturing relationships between information granules known as fuzzy sets. The form of the information granules themselves (in particular their distribution and a type of membership function) becomes an important design feature of the FNN model contributing to its structural as well as parametric optimization. The identification environment uses clustering techniques (Hard C - Means, HCM) and exploits genetic optimization as a vehicle of global optimization. The global optimization is augmented by more refined gradient-based learning mechanisms such as standard back-propagation. The HCM algorithm, whose role is to carry out preprocessing of the process data for system modeling, is utilized to determine the structure of Multi-FNNs. The detailed parameters of the Multi-FNN (such as apexes of membership functions, learning rates and momentum coefficients) are adjusted using genetic algorithms. An aggregate performance index with a weighting factor is proposed in order to achieve a sound balance between approximation and generalization (predictive) abilities of the model. To evaluate the performance of the proposed model, two numeric data sets are experimented with. One is the numerical data coming from a description of a certain nonlinear function and the other is NOx emission process data from a gas turbine power plant.

• Journal of the Ergonomics Society of Korea
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• v.34 no.4
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• pp.327-334
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• 2015

Objective: The purpose of this study was to evaluate Korean workers' work ability and to identify its contributing factors. Background: In order for Korea to overcome the phenomena of becoming an aged society, older adults must participate in the workforce to balance out the population; workers' work ability must also be maintained. In addition, influential factors in employees' capabilities and degrees of importance thereof should be identified in advance to maintain work ability. Method: The Work Ability Index (WAI) questionnaire was completed by 5,708 Korean workers. Survey questionnaire consisted items of current work ability, physical and mental demands of the job, numbers of diseases, work impairment due to diseases, sick leaves, work ability in 2 years and mental resources. Results: Results indicated that work ability and length of service increased with age. It was also found that employees in administrative positions had greater work ability than site workers, workers directly managed by a supervisor had greater work ability than workers in cooperative firms, and workers who performed intellectual tasks had greater work ability than workers who performed physical labor. Job stress was additionally observed to contribute towards overall work ability. And musculoskeletal disorders (MSDs) were found to negatively affect work ability. Conclusion: The strongest determining factors in the work ability of Korean workers were stress level and mental state. Therefore, when the WAI is used to assess Korean workers, the weighting of WAI items pertaining to physical and mental abilities should be adjusted accordingly to account for these factors. Application: The result is expected to suggest that workers maintain work ability in an aged society.

• Physical Therapy Rehabilitation Science
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• v.5 no.3
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• pp.143-148
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• 2016

Objective: This study aimed to quantify one of the useful upper extremity movements to evaluate motor control abilities between the groups of people with mild and moderate arm impairments performing a door handling task. Design: Cross-sectional study. Methods: Twenty-one healthy participants and twenty-one persons with chronic stroke (9 mild stroke and 12 moderate stroke) were recruited for this study. Stroke participants were divided into 2 groups based on Fugle-Meyer Assessment scores of 58-65 (mild arm) and 38-57 (moderate arm). All they performed door handling task including the pronation and supination phases 3 times. We measured some movement factors which were reaction time, movement time, hand of peak velocity, hand of movement units to perform door handling task using the three-dimensional motion analysis. Results: The majority of kinematic variables showed significant differences among study groups (p<0.05). The reaction time, total and phase of movement time, hand of peak velocity, the number of movement units discriminated between healthy participants and persons with moderate upper limb stroke (p<0.05). In addition, reaction time, total and phase of movement time, the number of movement units discriminated between those with moderate and mild upper limbs of stroke patients (p<0.05). Conclusions: Three-dimensional kinematic motion analysis in this study was a useful tool for assessing the upper extremity function in different subgroups of people with stroke during the door handling task. These kinematic variables may help clinicians understand the arm movements in door handling task and consist of discriminative therapeutic interventions for stroke patients on upper extremity rehabilitation.