• The Journal of Korean Physical Therapy
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• v.26 no.6
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• pp.386-390
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• 2014

Purpose: We aimed to investigate whether visuomotor function would be modulated, when healthy subjects performed tracking task after tDCS application over the primary sensorimotor cortex (SM1) in the non-dominant hemisphere. Methods: Thirty four right-handed healthy participants were enrolled, who randomly and evenly divided into two groups, real tDCS group and sham control group. Direct current with intensity of 1 mA was delivered over SM1 for 15 minutes. After tDCS, tracking task was measured, and their performance was calculated by an accuracy index (AI). Results: No significant difference in AI at the baseline between the two groups was observed. The AI of the real tDCS group was significantly increased after electrical stimulation, compared to the sham control group. Two way ANOVA with repeated measurement showed a significant finding in a large main effects of time and group-by-repeated test interaction. Conclusion: This study indicated that application of the anodal tDCS over the SM1 could facilitate higher visuomotor coordination, compared to sham tDCS group. These findings suggest possibility that tDCS can be used as adjuvant brain modulator for improvement of motor accuracy in healthy individuals as well as patients with brain injury.

• Microbiology and Biotechnology Letters
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• v.51 no.1
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• pp.69-82
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• 2023

Nitrilases are a hydrolase group of enzymes that catalyzes nitrile compounds and produce industrially important organic acids. The current objective is to optimize nitrilase production using statistical methods assisted with artificial intelligence (AI) tool from novel nitrile degrading isolate. A nitrile hydrolyzing bacteria Bacillus subtilis AGAB-2 (GenBank Ascension number- MW857547) was isolated from industrial effluent waste through an enrichment culture technique. The culture conditions were optimized by creating an orthogonal design with 7 variables to investigate the effect of the significant factors on nitrilase activity. On the basis of obtained data, an AI-driven support vector machine was used for the fitted regression, which yielded new sets of predicted responses with zero mean error and reduced root mean square error. The results of the above global optimization were regarded as the theoretical optimal function conditions. Nitrilase activity of 9832 ± 15.3 U/ml was obtained under optimized conditions, which is a 5.3-fold increase in compared to unoptimized (1822 ± 18.42 U/ml). The statistical optimization method involving Plackett Burman Design and Response surface methodology in combination with an AI tool created a better response prediction model with a significant improvement in enzyme production.

• Journal of Information Science Theory and Practice
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• v.10 no.spc
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• pp.12-24
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• 2022

This study attempted to investigate changes in collaboration structure for each stage of national Research and Development (R&D) in the artificial intelligence (AI) field through analysis of a co-author network for papers written under national R&D projects. For this, author information was extracted from national R&D outcomes in AI from 2014 to 2019. For such R&D outcomes, NTIS (National Science & Technology Information Service) information from the KISTI (Korea Institute of Science and Technology Information) was utilized. In research collaboration in AI, power function structure, in which research efforts are led by some influential researchers, is found. In other words, less than 30 percent is linked to the largest cluster, and a segmented network pattern in which small groups are primarily developed is observed. This means a large research group with high connectivity and a small group are connected with each other, and a sporadic link is found. However, the largest cluster grew larger and denser over time, which means that as research became more intensified, new researchers joined a mainstream network, expanding a scope of collaboration. Such research intensification has expanded the scale of a collaborative researcher group and increased the number of large studies. Instead of maintaining conventional collaborative relationships, in addition, the number of new researchers has risen, forming new relationships over time.

• Journal of Wellbeing Management and Applied Psychology
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• v.6 no.2
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• pp.27-31
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• 2023

Purpose: Establishment of a real-time monitoring system for odor control in traditional markets in Gangwon-do and a system for linking prevention facilities. Research design, data and methodology: Build server and system logic based on data through real-time monitoring device (sensor-based). A temporary data generation program for deep learning is developed to develop a model for odor data. Results: A REST API was developed for using the model prediction service, and a test was performed to find an algorithm with high prediction probability and parameter values optimized for learning. In the deep learning algorithm for AI modeling development, Pandas was used for data analysis and processing, and TensorFlow V2 (keras) was used as the deep learning library. The activation function was swish, the performance of the model was optimized for Adam, the performance was measured with MSE, the model method was Functional API, and the model storage format was Sequential API (LSTM)/HDF5. Conclusions: The developed system has the potential to effectively monitor and manage odors in traditional markets. By utilizing real-time data, the system can provide timely alerts and facilitate preventive measures to control and mitigate odors. The AI modeling component enhances the system's predictive capabilities, allowing for proactive odor management.

• International journal of advanced smart convergence
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• v.11 no.4
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• pp.68-80
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• 2022

Since the launch of AI, technology development to implement complete and sophisticated AI functions has continued. In efforts to develop technologies for complete automation, Machine Learning techniques and deep learning techniques are mainly used. These techniques deal with supervised learning, unsupervised learning, and reinforcement learning as internal technical elements, and use the Big-data Analysis method again to set the cornerstone for decision-making. In addition, established decision-making is being improved through subsequent repetition and renewal of decision-making standards. In other words, big data analysis, which enables data classification and recognition/recognition, is important enough to be called a key technical element of AI function. Therefore, big data analysis itself is important and requires sophisticated analysis. In this study, among various tools that can analyze big data, we will use a Python program to find out what variables can affect addiction according to smartphone use in a decision tree environment. We the Python program checks whether data classification by decision tree shows the same performance as other tools, and sees if it can give reliability to decision-making about the addictiveness of smartphone use. Through the results of this study, it can be seen that there is no problem in performing big data analysis using any of the various statistical tools such as Python and R when analyzing big data.

• Journal of Internet Computing and Services
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• v.24 no.5
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• pp.67-73
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• 2023

The Digital Age calls for improvement of information literacy particularly among children and youth who are vulnerable to cybergrooming. Taking an interdisciplinary approach by leveraging our team's expertise including child and adolescent development, data analytics, and cybersecurity, this study proposes an interactive artificial intelligence (AI)-based preventive simulation program that raises youth knowledge and awareness about the risk of cybergrooming as well as increases resilient self-efficacy in their cybersecurity-relevant skills. The primary purpose of this project is to evaluate the effectiveness of the simulation program on preventing cybergrooming. More specifically, this study is designed to examine developmental changes in self-efficacy of cybersecurity-relevant skills among youth participants as a function of the preventive simulation program. Further, this study will identify risk and protective factors that explain interindividual differences in the ability of children and youth either to fall victim to advances from a cyber predator or to recognize and deter such threats. The preliminary data will help improve the effectiveness of the preventive simulation program as well as the methods of implementation to large groups of youth. The findings from the proposed study will contribute to making specific recommendations to parents, educators, practitioners, and policy makers for the prevention of cybergrooming.

• Tuberculosis and Respiratory Diseases
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• v.42 no.2
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• pp.206-217
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• 1995

Background: In patients with obstructive sleep apnea syndrome(OSAS), there are several factors increasing upper airway resistance and there is a predisposition to compromised respiratory function during waking and sleep related to constitutional factors including a tendency to obesity. Several recent studies have suggested a possible relationship between sleep apnea(SA) and systemic hypertension. But the possible pathophysiologic link between SA and hypertension is still unclear. In this study, we have examined the relationship among age, body mass index(BMI), pulmonary function parameters and polysomnographic data in patients with OSAS. And also we tried to know the difference among these parameters between hypertensive OSAS and normotensive OSAS patients. Methods: Patients underwent a full night of polysomnography and measured pulmonary function during waking. OSAS was diagnosed if patients had more than 5 apneas per hour(apnea index, AI). A careful history of previously known or present hypertension was obtained from each patient, and patients with systolic blood pressure $\geq$ 160mmHg and/or diastolic blood pressure $\geq$ 95mmHg were classified as hypertensives. Results: The noctural nadir of arterial oxygen saturation($SaO_2$ nadir) was negatively related to AI and respiratory disturbance index(RDI), and the degree of noctural oxygen desaturation(DOD) was positively related to AI and RDI. BMI contributed to AI, RDI, $SaO_2$ nadir and DOD values. And also BMI contributed to $FEV_1,\;FEV_1/FVC$ and DLco values. There was a correlation between airway resistance(Raw) and AI, and there was a inverse correlation between DLco and DOD. But there was no difference among these parameters between hypertensive OSAS and normotensive OSAS patients. Conclusion: The obesity contributed to the compromised respiratory function and the severity of OSAS. AI and RDI were important factors in the severity of hypoxia during sleep. The measurement of pulmonary function parameters including Raw and DLco may be helpful in the prediction and assessment of OSAS patients. But we could not find clear difference between hypertensive and normotensive OSAS patients.

• Ocean Systems Engineering
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• v.10 no.2
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• pp.227-241
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• 2020

This paper deals with the problem of the global stabilization for a class of tension leg platform (TLP) nonlinear control systems. Problem and objective: Based on the relaxed method, the chaotic system can be stabilized by regulating appropriately the parameters of dither. Scope and method: If the frequency of dither is high enough, the trajectory of the closed-loop dithered chaotic system and that of its corresponding model-the closed-loop fuzzy relaxed system can be made as close as desired. Results and conclusion: The behavior of the closed-loop dithered chaotic system can be rigorously predicted by establishing that of the closed-loop fuzzy relaxed system.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.24 no.5 s.176
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• pp.1124-1132
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• 2000

Viscoplastic response and densification behaviors of Ti-6AI-4V powder compacts under uniaxial compression are studied at room and high temperatures with various initial relative densities and strain rates. The yield function and strain-hardening law proposed by Kim and co-workers were implemented into a finite element program (ABAQUS) to compare experimental data with finite element calculations for porous Ti6A14V powder compacts. Displacement-relative density, displacement-load relations and deformed geometry of Ti-A14V powder compacts were compared with finite element results. Density distributions in Ti-6AI-4V powder compacts were also measured and compared with finite element results.

• Proceedings of the KWS Conference
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• 2003.05a
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• pp.114-116
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• 2003

The multi function sprayed coating is used for direct-heating, wear resistance and high bonding strength. The merits of surface direct-heating coatings are short warming time, low power consumption and better wear resistance that can be used in many organization parts. In this study, the surface direct-heating and wear resistance can be improved by spraying the proper materials on the surface $Al_2$O$_3$40%TiO$_2$ powder and Ni-20%Cr powder that had the properties of conduction and high wear resistivity are used in order to improve wear resistance, electrical properties and bonding strength.