• World Technopolis Review
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• v.7 no.1
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• pp.15-43
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• 2018

The lack of appropriate performance appraisal and evaluation of incubatees of technology incubation programmes in relation to entrepreneurship development in Nigeria is a major gap that needs to be bridged. This study examined the effect of selected technology incubation programme variables such as training, financing and marketing on entrepreneurship development in Nigeria. A closed-ended questionnaire was used for data collection from the quota-sampled population of the six (6) geo-political zones of Nigeria. Descriptive statistics were used to analyse the data while multiple regression was used to test the hypotheses. The results revealed that technology incubation training has a significant effect on entrepreneurial ability in Nigeria; there is a significant and positive effect of technology incubation financing on entrepreneurial funding portfolio; there is no significant impact of technology incubation marketing programme on entrepreneurial turnover; and technology incubation has no significant impact on entrepreneurial propensity. The study recommended that the National Board for Technology Incubation (NBTI) expand the training modules to capture pre, post and virtual incubatees; to facilitate access to risk funds, cheap capital and encourage establishment of venture capital; to improve on its marketing programme to encompass all marketing needs of incubatees beyond trade-fair participation. However, trade-fairs participation has a significant but limited effect on entrepreneurial turnover, while a technology incubation programme has no significant impact on entrepreneurial propensity, as only six (6) out of the twenty-nine (29) respondents started new venture from the incubation centers which are industrial training students and staff of the incubatees.

• Child Health Nursing Research
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• v.25 no.4
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• pp.496-506
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• 2019

Purpose: The purpose of this study was to examine the effects of a virtual reality simulation and a blended simulation on nursing care for children with asthma through an evaluation of critical thinking, problem-solving processes, and clinical performance in both education groups before and after the educational intervention. Methods: The participants were 48 nursing students. The experimental group (n=22) received a blended simulation, combining a virtual reality simulation and a high-fidelity simulation, while the control group (n=26) received only a virtual reality simulation. Data were collected from February 25 to 28, 2019 and analyzed using SPSS version 25 for Windows. Results: The pretest and posttest results of each group showed statistically significant improvements in critical thinking, problem-solving processes, and clinical performance. In a comparison of the results of the two education groups, the only statistically significant difference was found for critical thinking. Conclusion: Simulation-based education in child nursing has continued to involve high-fidelity simulations that are currently run in many programs. However, incorporating a new type of blended simulation, combining a virtual reality simulation and a high-fidelity simulation, into the nursing curriculum may contribute to the further development of nursing education.

• Journal of the Korean Society of Industry Convergence
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• v.14 no.4
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• pp.157-165
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• 2011

The study figures out the alternatives of training BIM design experts which is the biggest obstacle in training manpower of professional BIM designer, the largest problem when the plant introduce BIM design about the change in Construction Environment by Equipment Based BIM Design in reality of design followed by equipment based BIM design, education institution plan. BIM is the system which is built to make these information be used easier and technique which enables design construction and maintenance in 3-dimensional virtual space by designing buildings in 3-dimensional space, and by data-basing the generated information of every life-cycle information. As the essential contents of the study, educational institutions with the public authority should invest the opening of educational programs, recruit of experts and development of textbooks from a long-term perspective. And also, the role of public institution is important above all for the development of construction industry.

• Journal of KIISE:Computer Systems and Theory
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• v.33 no.4
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• pp.231-241
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• 2006

Creating controllable, responsive avatars is an important problem in computer games and virtual environments. Recently, large collections of motion capture data have been exploited for increased realism in avatar animation and control. Large motion sets have the advantage of accommodating a broad variety of natural human motion. However, when a motion set is large, the time required to identify an appropriate sequence of motions is the bottleneck for achieving interactive avatar control. In this paper, we present a novel method for training avatar behaviors from unlabelled motion data in order to animate and control avatars at minimal runtime cost. Based on machine learning technique, called Q-teaming, our training method allows the avatar to learn how to act in any given situation through trial-and-error interactions with a dynamic environment. We demonstrate the effectiveness of our approach through examples that include avatars interacting with each other and with the user.

• Journal of Computing Science and Engineering
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• v.10 no.3
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• pp.75-84
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• 2016

Medical cyber-physical systems (MCPS) integrate sensors, actuators, and software to improve patient safety and quality of healthcare. These systems introduce major challenges to safety analysis because the patient's physiology is complex, nonlinear, unobservable, and uncertain. To cope with the challenge that unidentified physiological parameters may exhibit short-term variances in certain clinical scenarios, we propose a novel run-time predictive safety monitoring technique that leverages a maximal model coupled with online training of a computational virtual subject (CVS) set. The proposed monitor predicts safety-critical events at run-time using only clinically available measurements. We apply the technique to a surgical glucose control case study. Evaluation on retrospective real clinical data shows that the algorithm achieves 96% sensitivity with a low average false alarm rate of 0.5 false alarm per surgery.

• The Korean Journal of Pain
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• v.35 no.4
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• pp.403-412
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• 2022

Background: Most pain management techniques for challenging procedures are still performed under the guidance of the C-arm fluoroscope although it is sometimes difficult for even experienced clinicians to understand the modified three-dimensional anatomy as a two-dimensional X-ray image. To overcome these difficulties, the development of a virtual simulator may be helpful. Therefore, in this study, the authors developed a virtual simulator and presented its clinical application cases. Methods: We developed a computer program to simulate the actual environment of the procedure. Computed tomography (CT) Digital Imaging and Communications in Medicine (DICOM) data were used for the simulations. Virtual needle placement was simulated at the most appropriate position for a successful block. Using a virtual C-arm, the authors searched for the position of the C-arm at which the needle was visualized as a point. The positional relationships between the anatomy of the patient and the needle were identified. Results: For the simulations, the CT DICOM data of patients who visited the outpatient clinic was used. When the patients revisited the clinic, images similar to the simulated images were obtained by manipulating the C-arm. Transforaminal epidural injection, which was difficult to perform due to severe spinal deformity, and the challenging procedures of the superior hypogastric plexus block and Gasserian ganglion block, were successfully performed with the help of the simulation. Conclusions: We created a pre-procedural virtual simulation and demonstrated its successful application in patients who are expected to undergo challenging procedures.

• Journal of the Korean Operations Research and Management Science Society
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• v.33 no.2
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• pp.1-16
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• 2008

The purpose of this paper is to propose a new binary classification method for predicting corporate failure based on genetic algorithm, and to validate its prediction power through empirical analysis. Establishing virtual companies representing bankrupt companies and non-bankrupt ones respectively, the proposed method measures the similarity between the virtual companies and the subject for prediction, and classifies the subject into either bankrupt or non-bankrupt one. The values of the classification variables of the virtual companies and the weights of the variables are determined by the proper model to maximize the hit ratio of training data set using genetic algorithm. In order to test the validity of the proposed method, we compare its prediction accuracy with ones of other existing methods such as multi-discriminant analysis, logistic regression, decision tree, and artificial neural network, and it is shown that the binary classification method we propose in this paper can serve as a premising alternative to the existing methods for bankruptcy prediction.

• KEPCO Journal on Electric Power and Energy
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• v.8 no.2
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• pp.137-141
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• 2022

To inspect the power facility faults using artificial intelligence, it need that improve the accuracy of the diagnostic model are required. Data augmentation skill using generative adversarial network (GAN) is one of the best ways to improve deep learning performance. GAN model can create realistic-looking fake images using two competitive learning networks such as discriminator and generator. In this study, we intend to verify the effectiveness of virtual data generation technology by including the fake image of power facility generated through GAN in the deep learning training set. The GAN-based fake image was created for damage of LP insulator, and ResNet based normal and defect classification model was developed to verify the effect. Through this, we analyzed the model accuracy according to the ratio of normal and defective training data.

• International conference on construction engineering and project management
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• 2022.06a
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• pp.893-903
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• 2022

Recently, computer vision (CV)-based safety monitoring (i.e., object detection) system has been widely researched in the construction industry. Sufficient and high-quality data collection is required to detect objects accurately. Such data collection is significant for detecting small objects or images from different camera angles. Although several previous studies proposed novel data augmentation and synthetic data generation approaches, it is still not thoroughly addressed (i.e., limited accuracy) in the dynamic construction work environment. In this study, we proposed a game engine-driven synthetic data generation model to enhance the accuracy of the CV-based object detection model, mainly targeting small objects. In the virtual 3D environment, we generated synthetic data to complement training images by altering the virtual camera angles. The main contribution of this paper is to confirm whether synthetic data generated in the game engine can improve the accuracy of the CV-based object detection model.

• Journal of the Korean Society of Marine Environment & Safety
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• v.7 no.3
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• pp.85-92
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• 2001

Ship handling simulator has much merit to provide trainees with real-like circumstances in doing virtual education and training. To improve the quality of the education, it should be included both the mathematical model which can explain complicated ship's manoeuvrability and graphic tools for 3D images which can embody the visual scenes of reality on screen. This paper is focused on how to construct the marine environment DB(data Base) using S-57 data of ENC(Electronic Navigational Chart).