• Journal of Engineering Education Research
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• v.6 no.1
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• pp.15-21
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• 2003

This paper reports the results of course restructuring employing design projects in an introductory mechanics of materials course at Pennsylvania State University. Unlike traditional lecture courses, students were encouraged to learn the rudiments of mechanical design and how materials standards, economics, manufacturing, environmental, legal (liability) and societal (safety) concerns relate to design. Through conducting collaborative design projects, the instructors helped students to acquire more advanced skills such as team-based decision making, integration and establishment of criteria, use of modern design theory, consideration of alternative solutions, and application of realistic constraints. In order to examine the impact of new course changes on students' learning, a survey was conducted in 1998 Fall semester. According to the results of survey analyses, students reported high values on this introductory mechanics of materials course. However, they did not give high values on the design projects. Rather, they preferred lecture sessions. Additionally, it was also found that students who earned higher grades from a prerequisite course(statics) showed lower values on the design projects. Implications for engineering educators and suggestions for future research studies were discussed.

• Journal of Internet Computing and Services
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• v.17 no.3
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• pp.67-73
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• 2016

With the rapid development of mobile services and the prevalence of education robots, robots are being developed to become a part of our lives and they can be utilized to assist teachers in giving education or learning to students. This standard has been proposed to define the degree of autonomy for education robot. The autonomy is an ability to perform a given work based on current state and sensor value without human intervention. The degree of autonomy is a scale indicating the extent of autonomy and it is determined in between 1 and 10 by considering the level of work and human intervention. It has been adapted as per standard and education robots can be utilized in teaching the students autonomously. Education robots can be beneficial in education and it is expected to contribute in assisting the teacher's education.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.7
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• pp.2938-2956
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• 2020

Objective image quality assessment (IQA) models have been developed by effective features to imitate the characteristics of human visual system (HVS). Actually, HVS is extremely sensitive to color degradation and complex texture changes. In this paper, we firstly reveal that many existing full reference image quality assessment (FR-IQA) methods can hardly measure the image quality with contrast and masking texture changes. To solve this problem, considering texture masking effect, we proposed a novel FR-IQA method, called Texture and Color Quality Index (TCQI). The proposed method considers both in the masking effect texture and color visual perceptual threshold, which adopts three kinds of features to reflect masking texture, color difference and structural information. Furthermore, random forest (RF) is used to address the drawbacks of existing pooling technologies. Compared with other traditional learning-based tools (support vector regression and neural network), RF can achieve the better prediction performance. Experiments conducted on five large-scale databases demonstrate that our approach is highly consistent with subjective perception, outperforms twelve the state-of-the-art IQA models in terms of prediction accuracy and keeps a moderate computational complexity. The cross database validation also validates our approach achieves the ability to maintain high robustness.

• Journal of Engineering Education Research
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• v.11 no.3
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• pp.70-77
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• 2008

This study investigates the level of the construction student's familiarity and interest in sustainability, their attitude toward sustainability, and the factors for bringing student's attitude toward sustainability. To accomplish the main objectives, this study employes a survey instrument created and developed by the authors. This is a descriptive and correlation study using responses from construction students at the Building Construction department at Virginia Polytechnic Institute and State University in Virginia. The results of descriptive statistics and multiple regression using SPSS version 16 present the following findings. Construction students perceive that they have a relatively high level of familiarity with sustainable construction and sustainability. Secondly, student's attitude toward sustainability is changed based on several factors such as sustainable construction courses, a professor who is interested in sustainability, their interest in the construction industry, university initiative, and the level of sustainability for student's learning facilities. Finally, the construction student's attitude toward sustainability can be improved by offering sustainable construction courses in construction programs, having professors who teach and research sustainability, and adopting sustainable initiatives at the university level such as campus recycling and various sustainable programs.

• International Journal of Human Ecology
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• v.12 no.2
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• pp.13-24
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• 2011

This study compared actual weight with perceived weight, described the prevalence of unhealthy weight control behavior, determined the differences in psychological and personal variables between participants that reported unhealthy weight control behavior and those who did not, and examined the relationship of eating habits to unhealthy weight control behavior for Korean adolescents. The study population consisted of a nationally representative sample of middle and high school students who completed the Fifth Korea Youth Risk Behavior Web-based Survey (KYRBWS): Fifth in 2009. Among the 75,066 participants of KYRBWS, 35,473 (n = 18,851 girls and 16,622 boys) were eligible for a research focused on unhealthy weight control behavior. The results of this research were as follows: First, there were considerable discrepancies (45.1% of girls and 32.8% of boys) between the perceived weight and the actual weight. Second, overall, unhealthy weight control behavior was more prevalent in girls and fasting was the most commonly reported behavior. Third, participants that reported unhealthy weight control behavior scored significantly lower on scaled measures of happiness, health, academic achievement, and economic status; in addition, they scored higher on stress measures. Fourth, girls and boys shared common protective factors of having breakfast and vegetables more often, perceiving their weight as underweight rather than overweight, and having a correct weight conception. Protective factors unique to girls were having lunch and dinner more often. Girls and boys shared common risk factors of the consumption of soda, fast food, instant noodles, and snacks more often, while consumption of fruit more often was a risk factor only for girls. The improvement of protective factors and minimization of risk factors through Home Economics classes (and other classes relevant to health) may mitigate unhealthy weight control behavior of adolescents.

• KIPS Transactions on Software and Data Engineering
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• v.7 no.2
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• pp.69-76
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• 2018

Referring expressions are natural language constructions used to identify particular objects within a scene. In this paper, we propose a new deep neural network model for referring expression comprehension. The proposed model finds out the region of the referred object in the given image by making use of the rich information about the referred object itself, the context object, and the relationship with the context object mentioned in the referring expression. In the proposed model, the object matching score and the relationship matching score are combined to compute the fitness score of each candidate region according to the structure of the referring expression sentence. Therefore, the proposed model consists of four different sub-networks: Language Representation Network(LRN), Object Matching Network (OMN), Relationship Matching Network(RMN), and Weighted Composition Network(WCN). We demonstrate that our model achieves state-of-the-art results for comprehension on three referring expression datasets.

• Journal of the Korean Institute of Intelligent Systems
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• v.15 no.4
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• pp.457-466
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• 2005

In this paper, we propose a wavelet neural network(WNN) based predictive control method for path tracking of mobile robots with multi-input and multi-output. In our control method, we use a WNN as a state predictor which combines the capability of artificial neural networks in learning processes and the capability of wavelet decomposition. A WNN predictor is tuned to minimize errors between the WNN outputs and the states of mobile robot using the gradient descent rule. And control signals, linear velocity and angular velocity, are calculated to minimize the predefined cost function using errors between the reference states and the predicted states. Through a computer simulation for the tracking performance according to varied track, we demonstrate the efficiency and the feasibility of our predictive control system.

• Journal of the Korea Society of Computer and Information
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• v.25 no.5
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• pp.1-9
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• 2020

In this paper, we propose a model that performs more natural facial attribute editing by utilizing mask information in the hair and hat region. STGAN, one of state-of-the-art research of facial attribute editing, has shown results of naturally editing multiple facial attributes. However, editing hair-related attributes can produce unnatural results. The key idea of the proposed method is to additionally utilize information on the face regions that was lacking in the existing model. To do this, we apply three ideas. First, hair information is supplemented by adding hair ratio attributes through masks. Second, unnecessary changes in the image are suppressed by adding cycle consistency loss. Third, a hat segmentation network is added to prevent hat region distortion. Through qualitative evaluation, the effectiveness of the proposed method is evaluated and analyzed. The method proposed in the experimental results generated hair and face regions more naturally and successfully prevented the distortion of the hat region.

• 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.

• Proceedings of the Safety Management and Science Conference
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• 2009.11a
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• pp.15-24
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• 2009

Cycling that transform human energy into mechanical energy is one of the man-machine systems out of sports fields. Benchmarking means " improving ourselves by learning from others ", therefore benchmarking toward dominant cyclist is necessary on field. the goals of this study were to provide important factors on multi-disciplines (kinematics, physiology, power, psychology) for a tailored-training program that is suitable to individual characteristics. Two cyclist participated in this study and gave consent to the experimental procedure. one was dominant cyclist (years:21 yrs, height:177 cm, mass:70 kg), and the other was non-dominant cyclist(years:21, height:176, mass:70). Kinematic data were recorded using six infrared cameras (240Hz) and QTM (software). Physiological data (VO2max, AT) were acquired according to graded exercising test with cycle ergometer and power with Wingate test used by Bar-Or et. al ( 1977) and to evaluate muscle function with Cybex. Psychological data were collected with competitive state anxiety inventory (CSAI-2) that were devised by Martens et. al (1990) and with athletes' self-management questionnaire (ASMQ) of Huh (2003). It appears that the dominant's CV(coefficient of variability) was higher than non-dominant's CV in Sports Biomechanics domain, that the dominant's values for all factors ware higher than non-dominant's values in physical, and physiological domain, and their values between cognitive anxiety and somatic anxiety were contrary to each other in psychology. Further research on multi-disciplines may lead to the development of tailored-optimal training programs applicable with key factors to enhance athletic performance by means of research including athlete, coach and parents.