• Journal of the Korea Society of Computer and Information
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• v.28 no.10
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• pp.103-111
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• 2023

Mountains area, especially walking in open space is important for special active field which is based on mountain terrain. Recent research on pedestrian-path includes elements about pedestrian and various environment by analyzing network, but it is mainly focusing on limited space except for data-poor terrain like a mountain terrain. This paper proposes an architecture to generate walking path considering the slope for mountain terrain open space through virtual network made of mesh. This architecture shows that it reflects real terrain more effective when measuring distance using slope and is possible to generate mountain walking path using open space unlike other existing services, and is verified through the test. The proposed architecture is expected to utilize for pedestrian-path generation way considering mountain terrain open space in case of distress, mountain rescue and tactical training and so on.

• Journal of Korean Neurosurgical Society
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• v.66 no.6
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• pp.632-641
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• 2023

Central nervous system tumors are identified as tumors of the brain and spinal cord. The associated morbidity and mortality of cerebrospinal tumors are disproportionately high compared to other malignancies. While minimally invasive techniques have initiated a revolution in neurosurgery, artificial intelligence (AI) is expediting it. Our study aims to analyze AI's role in the neurosurgical management of cerebrospinal tumors. We conducted a scoping review using the Arksey and O'Malley framework. Upon screening, data extraction and analysis were focused on exploring all potential implications of AI, classification of these implications in the management of cerebrospinal tumors. AI has enhanced the precision of diagnosis of these tumors, enables surgeons to excise the tumor margins completely, thereby reducing the risk of recurrence, and helps to make a more accurate prediction of the patient's prognosis than the conventional methods. AI also offers real-time training to neurosurgeons using virtual and 3D simulation, thereby increasing their confidence and skills during procedures. In addition, robotics is integrated into neurosurgery and identified to increase patient outcomes by making surgery less invasive. AI, including machine learning, is rigorously considered for its applications in the neurosurgical management of cerebrospinal tumors. This field requires further research focused on areas clinically essential in improving the outcome that is also economically feasible for clinical use. The authors suggest that data analysts and neurosurgeons collaborate to explore the full potential of AI.

• Journal of the Korea Society of Computer and Information
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• v.29 no.6
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• pp.31-38
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• 2024

This study proposes a novel approach to enhancing the social inclusion and participation of individuals with developmental disabilities. Utilizing cutting-edge virtual reality (VR) technology, we designed and developed a metaverse simulator that enables individuals with developmental disabilities to safely and conveniently experience indoor handicapped handball sports. This simulator provides an environment where individuals with disabilities can experience and practice handball matches. For the modeling and animation of handball players, we employed advanced modeling and motion capture technologies to accurately replicate the movements required in handball matches. Additionally, we ported various training programs, including basic drills, penalty throws, and target games, onto XR (Extended Reality) devices. Through this research, we have explored the development of immersive assistive tools that enable individuals with developmental disabilities to more easily participate in activities that may be challenging in real-life scenarios. This is anticipated to broaden the scope of social participation for individuals with developmental disabilities and enhance their overall quality of life.

• Therapeutic Science for Rehabilitation
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• v.13 no.1
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• pp.9-21
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• 2024

Objective : The purpose of this study was to confirm the characteristics and quality of a single-subject research that conducted interventions to improve activities of daily living (ADL) in stroke patients. Methods : 'Stroke,' 'activities of daily living,' and 'single-subject studies' were searched as keywords among papers published in the last 15 years between 2009 and 2023 among Research Information Sharing Service, DBpia, and e-articles. A total of nine papers were examined for the characteristics and quality before analysis. Results : The independent variables applied to improve ADL included constraint-induced therapy, mental practice for performing functional activities, virtual reality-based task training, subjective postural vertical training without visual feedback, bilateral upper limb movement, core stability training program, traditional occupational therapy and neurocognitive rehabilitation, smooth pursuit eye movement, neck muscle vibration, and occupation-based community rehabilitation. Assessment of Motor and Process Skills was the most common evaluation tool for measuring dependent variables, with four articles, and Modified Barthel Index and Canadian Occupational Performance Measure were two articles each. As a result of confirming the qualitative level of the analyzed papers, out of a total of nine studies, seven studies were at a high level, two at a moderate level, and none were at a low level. Conclusion : Various types of rehabilitation treatments have been actively applied as intervention methods to improve the daily life activities of stroke patients; the quality level of single-subject studies applying ADL interventions was reliable.

• Bulletin of the Korean Chemical Society
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• v.33 no.5
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• pp.1707-1714
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• 2012

Grb2 is an adapter protein involved in the signal transduction and cell communication. The Grb2 is responsible for initiation of kinase signaling by Ras activation which leads to the modification in transcription. Ligand based pharmacophore approach was applied to built the suitable pharmacophore model for Grb2. The best pharmacophore model was selected based on the statistical values and then validated by Fischer's randomization method and test set. Hypo1 was selected as a best pharmacophore model based on its statistical values like high cost difference (182.22), lowest RMSD (1.273), and total cost (80.68). It contains four chemical features, one hydrogen bond acceptor (HBA), two hydrophobic (HY), and one ring aromatic (RA). Fischer's randomization results also shows that Hypo1 have a 95% significant level. The correlation coefficient of test set was 0.97 which was close to the training set value (0.94). Thus Hypo1 was used for virtual screening to find the potent inhibitors from various chemical databases. The screened compounds were filtered by Lipinski's rule of five, ADMET and subjected to molecular docking studies. Totally, 11 compounds were selected as a best potent leads from docking studies based on the consensus scoring function and critical interactions with the amino acids in Grb2 active site.

• Journal of Distribution Science
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• v.7 no.3
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• pp.49-69
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• 2009

With the proliferation of electronic commerce, online transactions have become a norm. Its enormous potential, however, can be truly realized if consumers feel comfortable facing invisible sellers over the Internet, a virtual business channel. Trust has been identified as a key component in many e-Commerce studies. The purpose of this study is to find out which factors play a major role in building buyer trust and how the build-up trust affects buyer's purchase intention in online used car transactions. Based on the information asymmetry, TAM (Technology Acceptance Model), and the trust theory, our research model includes factors such as a buyer's propensity-to-trust, institutional characteristics (inspection and warranty policy), word-of-mouth referral, perceived size, and perceived benefits as independent variables. The model also includes trust as a mediate variable, purchase intention as a dependent variable, and perceived quality risk as a moderate variable. The research model is tested by analyzing 448 sample data gathered from used car websites. The result shows that the trust has significant effects on the online purchase intention, and institutional characteristics have been identified as one of the most significant factors for trust building in used car websites. For those who perceive quality risk high, actual purchasing behavior occurs only when they have trust on the used car websites, indicating that trust plays a vital role as a mediate variable. This study suggests that buyer trust on the used car websites is important to increase buyer's online purchase behavior.

• Journal of the Korean Society of Hazard Mitigation
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• v.10 no.4
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• pp.63-68
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• 2010

Utility-Pipe Conduit is, Housing and city effectively accommodate what they absolutely need power, communications, gas, pipeline, water supply, drainage, energy facilities etc, according to expansion of urban infrastructure are derived, several ways to solve problems in, collection facilities in place are maintained and managed facility. If Utility-Pipe Conduit is damaged, as well as national security, because their impact on society as a whole, by introducing large vulnerability in the fire prevention activities and suppression measures and disaster for our situation by introducing measures, comprehensive analysis of the fire risk, it shall establish fire prevention activities and suppression through analysis of Utility-Pipe Conduit design, institutional issues, the problem of fire protection facilities, fire spread phenomenon etc. Because of Utility-Pipe Conduit is an enclosed place, so incomplete combustion due to lack of oxygen supply that there are problem such dark smoke, carbon monoxide etc, toxic combustion products and heat generation and visual impairment is an issue difficult to enter. As well as fire prevention activities, the fire In light of the particularity of the under ground than above ground fire, so this phenomenon is weak fire fighting that fire to become effective fire fighting tactics, basically it is necessary difficulty softening, non-burn softening and prevent combustion expansion of the cable is installed on the Utility-Pipe Conduit, having to considering the specificity of the response command system and relevant organizations to establish an on-site, Structural identification and other information gathering required to record of Response agencies, keep air conditioning system 24 hours and strengthening Virtual Total Training of Response agen

• The Journal of Korean Institute of Communications and Information Sciences
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• v.37C no.11
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• pp.1094-1103
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• 2012

Recently, software industry regarding national defense increases system development of distributed simulation system of M&S based to overcome limit of resource and expense. It is one of key technologies for offering of mutual validation among objects and reuse of objects which are discussed for developing these systems. RTI, implementation of HLA interface specification as software providing these technologies uses Federation Object Model for exchanging information with joined federates in the federation and each federate has a characteristic that is supposed to have identical FOM in the federation. This technology is a software which is to provide the core technology which was suggested by the United state's military M&S standard framework. Simulator, virtual simulation, and inter-connection between military weapons system S/W which executes on network which is M&S's core base technology, and it is a technology which also can be used for various inter-connection between S/W such as game and on-line phone. These days although RTI is used in military war game or tactical training unit field, there is none in Korea. Also, it is used in mobile-game, distribution game, net management, robot field, and other civilian field, but the number of examples are so small and informalized. Through this developing project, we developed the core technique and RTI software and provided performance of COTS level to improve communication algorithms.

• Cartoon and Animation Studies
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• s.43
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• pp.363-386
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• 2016

This research is to design basic framework for developing teaching and learning method in the field of art and design major in university. Especially taking off from oneway e-learning teaching method, it is focused on increasing reality of student learning situation with applying AR contents process to augment virtual condition on reality condition. The processing of framework design and developing teaching and learning method are about practice education based on AR for model experiment research which was published "The E-Learning for Practice Training Using Augmented Reality in the College Education". This thesis is supposed to be a precedent study of the pre-published, and the purpose of those two studies were for experiment test in earnest in studying effect research. The classification of learning method divided basically as Face-to-Face Learning(FFL), Blended Learning(BL), fully E-Learning(EL), and Augmented Reality based E-Learning(AREL). This research compares and analyzes each frame of FFL, BL, and EL. And then, designed framework lead to the over-all conclusion with the type of AREL. Additionally, AREL for PBE suggests the ways of advanced teaching learning.

• KIPS Transactions on Computer and Communication Systems
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• v.9 no.8
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• pp.171-180
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• 2020

Smart Factory consists of digital automation solutions throughout the production process, including design, development, manufacturing and distribution, and it is an intelligent factory that installs IoT in its internal facilities and machines to collect process data in real time and analyze them so that it can control itself. The smart factory's equipment works in a physical combination of numerous hardware, rather than a virtual character being driven by a single object, such as a game. In other words, for a specific common goal, multiple devices must perform individual actions simultaneously. By taking advantage of the smart factory, which can collect process data in real time, if reinforcement learning is used instead of general machine learning, behavior control can be performed without the required training data. However, in the real world, it is impossible to learn more than tens of millions of iterations due to physical wear and time. Thus, this paper uses simulators to develop grid sortation systems focusing on transport facilities, one of the complex environments in smart factory field, and design cooperative multi-agent-based reinforcement learning to demonstrate efficient behavior control.