• Smart Structures and Systems
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• v.33 no.1
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• pp.65-91
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• 2024

The use of five optimization techniques for the prediction of a strength-based concrete mixture's best-fit model is examined in this work. Five optimization techniques are utilized for this purpose: Slime Mold Algorithm (SMA), Black Hole Algorithm (BHA), Multi-Verse Optimizer (MVO), Vortex Search (VS), and Whale Optimization Algorithm (WOA). MATLAB employs a hybrid learning strategy to train an artificial neural network that combines least square estimation with backpropagation. Thus, 72 samples are utilized as training datasets and 31 as testing datasets, totaling 103. The multi-layer perceptron (MLP) is used to analyze all data, and results are verified by comparison. For training datasets in the best-fit models of SMA-MLP, BHA-MLP, MVO-MLP, VS-MLP, and WOA-MLP, the statistical indices of coefficient of determination (R²) in training phase are 0.9603, 0.9679, 0.9827, 0.9841 and 0.9770, and in testing phase are 0.9567, 0.9552, 0.9594, 0.9888 and 0.9695 respectively. In addition, the best-fit structures for training for SMA, BHA, MVO, VS, and WOA (all combined with multilayer perceptron, MLP) are achieved when the term population size was modified to 450, 500, 250, 150, and 500, respectively. Among all the suggested options, VS could offer a stronger prediction network for training MLP.

• Safety and Health at Work
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• v.4 no.3
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• pp.166-176
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• 2013

Background: Effective policy implementation is essential for a healthy workplace. The Ryan-Kossek 2008 model for work-life policy adoption suggests that supervisors as gatekeepers between employer and employee need to know how to support and communicate benefit regulations. This article describes a workplace intervention on a national employee benefit, Family and Medical Leave Act (FMLA), and evaluates the effectiveness of the intervention on supervisor knowledge, awareness, and experience with FMLA. Methods: The intervention consisted of computer-based training (CBT) and a survey measuring awareness and experience with FMLA. The training was administered to 793 county government supervisors in the state of Oregon, USA. Results: More than 35% of supervisors reported no previous training on FMLA and the training pre-test revealed a lack of knowledge regarding benefit coverage and employer responsibilities. The CBT achieved: (1) a significant learning effect and large effect size of d = 2.0, (2) a positive reaction to the training and its design, and (3) evidence of increased knowledge and awareness regarding FMLA. Conclusion: CBT is an effective strategy to increase supervisors' knowledge and awareness to support policy implementation. The lack of supervisor training and knowledge of an important but complex employee benefit exposes a serious impediment to effective policy implementation and may lead to negative outcomes for the organization and the employee, supporting the Ryan-Kossek model. The results further demonstrate that long-time employees need supplementary training on complex workplace policies such as FMLA.

• Clinical Endoscopy
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• v.56 no.1
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• pp.1-13
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• 2023

The apprenticeship-based training method (ABTM) is highly effective for gastrointestinal (GI) endoscopic training. However, the conventional ABTM has significant issues. Although many supplementary training methods (TMs) have been developed and utilized, they cannot entirely replace the ABTM, which remains the major TM strategy. Currently, new TM construction is crucial and necessary due to financial constraints, difficulty of obtaining sufficient training time due to patient safety-related regulations, and catastrophic damage caused by disasters such as the coronavirus disease 2019 pandemic. The simulator-based TM (SBTM) is widely accepted as an alternative to the ABTM, owing to the SBTM's advantages. Since the 1960s, many GI endoscopy training simulators have been developed and numerous studies have been published on their effectiveness. While previous studies have focused on the simulator's validity, this review focused on the accessibility of simulators that were introduced by the end of 2021. Although the current SBTM is effective in GI endoscopic education, extensive improvements are needed to replace the ABTM. Incorporating simulator-incorporated TMs into an improved ABTM is an attempt to overcome the incompleteness of the current SBTM. Until a new simulator is developed to replace the ABTM, it is desirable to operate a simulator-integrated and well-coordinated TM that is suitable for each country and institution.

• Journal of Information Technology Applications and Management
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• v.25 no.4
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• pp.67-77
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• 2018

With the types and targets of cyber attacks expanding and with personal information leaks increasing, the quantitative demand for information security specialists has increased. The base for training the workforce has expanded accordingly, but joblessness and job-seeking still coexist. To resolve the gap between labor demand and supply, education and training systems that can supply demand quickly are needed. It takes a considerable amount of time for information security education and new manpower supply through universities and graduate schools to be reflected in the market. However, if information security retraining is carried out in terms of career development of information security and related workforce, the problem of lack of experts could be solved in a relatively short period. This paper investigates and analyzes the information security work of the information security workforce, the degree of skill level, the need for retraining, and the workplace migration experience; it also discusses the direction of career development retraining.

• Journal of the Korea Institute of Military Science and Technology
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• v.25 no.3
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• pp.300-310
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• 2022

A vast amount of labeled data is required for deep neural network training. A typical strategy to improve the performance of a neural network given a training data set is to use data augmentation technique. The goal of this work is to offer a novel image augmentation method for improving object detection accuracy. An object in an image is removed, and a similar object from the training data set is placed in its area. An in-painting algorithm fills the space that is eliminated but not filled by a similar object. Our technique shows at most 2.32 percent improvements on mAP in our testing on a military vehicle dataset using the YOLOv4 object detector.

• Proceedings of the Korea Database Society Conference
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• 1997.10a
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• pp.24-48
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• 1997

. Supported byㆍDARPA′s image Understanding (IU) program under "Video Retrieval Based on Language and image Analysis" project.DARPA′s Computer Assisted Education and Training Initiative program (CAETI)ㆍObjective: Develop practical systems for automatic understanding and indexing of video sequences using both audio and video tracks(omitted)

• Journal of Electrical Engineering and Technology
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• v.12 no.2
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• pp.911-917
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• 2017

There are generally three folds when developing neural network classifiers. They are as follows: 1) discriminant function; 2) lots of parameters in the design of classifier; and 3) high dimensional training data. Along with this viewpoint, we propose space search optimized polynomial neural network classifier (PNNC) with the aid of data preprocessing technique and simultaneous tuning strategy, which is a balance optimization strategy used in the design of PNNC when running space search optimization. Unlike the conventional probabilistic neural network classifier, the proposed neural network classifier adopts two type of polynomials for developing discriminant functions. The overall optimization of PNNC is realized with the aid of so-called structure optimization and parameter optimization with the use of simultaneous tuning strategy. Space search optimization algorithm is considered as a optimize vehicle to help the implement both structure and parameter optimization in the construction of PNNC. Furthermore, principal component analysis and linear discriminate analysis are selected as the data preprocessing techniques for PNNC. Experimental results show that the proposed neural network classifier obtains better performance in comparison with some other well-known classifiers in terms of accuracy classification rate.

• Journal of The Korean Association of Information Education
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• v.19 no.3
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• pp.261-270
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• 2015

In this paper, a strategy of cooperation activities was conducted to analyze on the impact of what effect appears in teacher training. We classified with satisfaction, effectiveness and academic achievement as effects of teacher training. We were divided into three groups that are cooperative-reflection activity group using the SNS, self-reflection activity group and general training group. Depending on the type of reflection activity, we have one-way ANOVA analysis for the effectiveness of teacher training. By the results of the analysis, we found to have a positive impact that cooperative reflection activity group were more an academic achievement, satisfaction and effectiveness of training. Accordingly, we have found the SNS-based collaborative reflection activity is very effective in teacher training.

• Journal of Korean Physical Therapy Science
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• v.16 no.2
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• pp.1-9
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• 2009

Background: The ability for backward walking is considered to be necessary for the neuromuscular control and maintenance of balance in daily ambulatory activity. This study aimed to determine the effect of backward walking training on the walking speed and balance control in patients with hemiplegia. Methods: Fourteen patients with hemiplegia were randomly allocated to an experimental and control groups of seven patients each. For the experimental group, we performed both conventional training and backward walking training, and conventional training only for the control group. The conventional training programs for the 2 groups were conducted for 30 min, twice a day, 5 times a week for 4 weeks, and backward walking training for the experimental group was conducted for 30 min, 3 times a week. The outcomes were assessed using the functional reach test (FRT), timed up-and-go (TUG) Test, and the 10 meter walk time test (10mWT). Result: A comparison of the FRT, TUG test, and 10mWT scores obtained before and after the 4-week treatment revealed statistically significant differences (p<.05) for the experimental group; however, there was no such difference in the case of the control group (p>.05). On assessment after the 4-week treatment, statistically significant differences were noted in the TUG test and 10mWT scores of the experimental group (p<.05). Conclusion: Our findings suggest that backward walking training is an effective clinical strategy for improving the walking speed and functional mobility of patients with hemiplegia.

• Health Policy and Management
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• v.28 no.3
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• pp.294-300
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• 2018

The development and management of epidemiology intelligence service (EIS) officer with more specialized competence to cope with and prepare for health threats, including pandemic of emerging and re-emerging infectious diseases, is a high priority policy issue in Korea. First of all, we need to establish the training goal of EIS officer. It is necessary to establish manpower training and management system with at least three tiers including quantitative and qualitative targets. Second, at least 50% of all EIS officer must secure a physician and secure expertise and competence for epidemic. Third, for the ultimate purpose of EIS officer, the establishment of a public health expert should expand the scope of epidemiologist's work to health and medical care, occupational environment, and various disasters. Fourth, it is essential to expand the epidemiologist training and education program to the level of advanced countries. Especially, the training course should be expanded at least twice of current times. Fifth, it is necessary to independently install and operate the 'EIS Officer Training Center' as a mid- and long-term goal. Stewardship and governance are secured with the organization, personnel, etc. that can fully manage the planning, management, and evaluation of the EIS system. In the future, it will be necessary to establish a systematic and phased operational base of education and training programs for EIS officer, and establish a sustainable implementation system for strategy development. In addition, it is urgent to revise the guidelines for training public health professionals and strengthening competencies, and for establishing professional educational institutions.