• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.1
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• pp.333-337
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• 2021

Companion animals are physically, mentally, and socially beneficial to humans, giving us great comfort in living in the Corona19 (COVID-19) era. It is also an era of the Fourth Industrial Revolution, featuring the convergence of information and communication technology. Korea, which is facing a super-aged society, has the highest suicide rate among OECD countries, and companion animals that are effective in emotional stability can be the answer. This study is about companion animals that are effective in stabilizing the emotions of the elderly, one of the major problems in the Republic of Korea, which is about to solve in a super-aged society with more than 20 percent of the elderly aged 65 or older, needs to solve. The impact of knowledge of raising companion animals on the satisfaction level of the elderly was investigated through the management and awareness of infectious diseases. Although the level of care of companion animals had a very significant (p<0.001) effect on the satisfaction of the companion animals, the recognition of infectious diseases has no statistical significance (p>0.05). Raising companion animals with knowledge of rearing increases the satisfaction level and can lead to a happier life. While personal learning is important, it is also believed that supporting education will be necessary as a policy consideration.

• Journal of Digital Convergence
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• v.19 no.3
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• pp.203-209
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• 2021

In this study, a prototype design model was proposed for developing an online recruitment system through multi-dimensional data crawling and social media analysis, and validates text information and video interview in job application process. This study includes a comparative analysis process through text mining to verify the authenticity of job application paperwork and to effectively hire and allocate workers based on the potential job capability. Based on the prototype system, we conducted performance tests and analyzed the result for key performance indicators such as text mining accuracy and interview STT(speech to text) function recognition rate. If commercialized based on design specifications and prototype development results derived from this study, it may be expected to be utilized as the intelligent online recruitment system technology required in the public and private recruitment markets in the future.

• Journal of the Korean Society of Radiology
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• v.15 no.4
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• pp.473-479
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• 2021

The diagnostic criteria for diffuse thyroid disease are ambiguous and there are many errors due to the subjective diagnosis of experts. Also, studies on ultrasound imaging of thyroid nodules have been actively conducted, but studies on diffuse thyroid disease are insufficient. In this study, features were extracted by applying the GLCM algorithm to ultrasound images of normal and diffuse thyroid disease, and quantitative analysis was performed using the extracted feature values. Using the GLCM algorithm for thyroid ultrasound images of patients diagnosed at W hospital, 199 normal cases, 132 mild cases, and 99 moderate cases, a region of interest (50×50 pixel) was set for a total of 430 images, and Autocorrelation, Sum of squares, sum average, sum variance, cluster prominence, and energy were analyzed using six parameters. As a result, in autocorrelation, sum of squares, sum average, and sum variance four parameters, Normal, Mild, and Moderate were distinguished with a high recognition rate of over 90%. This study is valuable as a criterion for classifying the severity of diffuse thyroid disease in ultrasound images using the GLCM algorithm. By applying these parameters, it is expected that errors due to visual reading can be reduced in the diagnosis of thyroid disease and can be utilized as a secondary means of diagnosing diffuse thyroid disease.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.20 no.6
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• pp.117-132
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• 2021

Due to the terrain in Korea, there are many road sections passing through mountainous areas. During the winter, there is a higher risk of traffic accidents, due to black ice caused by the lack of sunlight. Despite domestic road freezing safety measures, accidents caused by road freezing results in severe traffic accidents. Under these considerations, this study analyzed whether traffic safety signs that change in response to the external temperature help drivers recognize frozen road segments. The study was conducted through analysis of the effect of the signs on a driver's perspective. For the signs under development, out of the signs designed by experts, the sign design which received the highest visibility and effectiveness evaluation ratings from the general public was selected. The sign was implemented through Virtual Reality (VR) and installed on the right side of the road to analyze the effect on gazing and driving behavior. As a result of analyzing the driver's driving behavior, a speed reduction of about 7km/h or more was found in the sign section. Therefore, It was found that the existence of the sign had a strong relationship with the rate of the drivers' speed reduction.

• The Journal of the Convergence on Culture Technology
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• v.8 no.4
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• pp.361-366
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• 2022

Although safety and health education is reported to be very effective in reducing the industrial accident rate, the demand for improvement in safety and health education is also very high. The purpose of this study is to present measures to enhance effectiveness by investigating the effectiveness and demand for safety and health education for supervisors among the safety and health education systems. As a result of the study, it was found that the satisfaction and effectiveness of safety and health education were low. As the most important competency required for supervisors, it was investigated that job competency was the ability to discover harmful risk factors and formulate disaster prevention measures in the work process and work environment, and base competency was communication ability. In addition to designated safety and health education institutions, there was a high demand for recognition as education completion time even when professional education by job was completed by other professional education institutions. Therefore, in safety and health education for supervisors, it is necessary to focus on major items to improve supervisors' job competency and base competency, and to recognize that they have completed education at a wide range of educational institutions. We believe that it can increase the supervisor's capacity for safety management and improve the effectiveness of safety and health education.

• Journal of Intelligence and Information Systems
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• v.28 no.2
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• pp.57-74
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• 2022

Recently, artificial intelligence parking control systems have increased the recognition rate of vehicle license plates using deep learning, but there is a problem that they cannot determine vehicles with fake license plates. Despite these security problems, several institutions have been using the existing system so far. For example, in an experiment using a counterfeit license plate, there are cases of successful entry into major government agencies. This paper proposes an improved system over the existing artificial intelligence parking control system to prevent vehicles with such fake license plates from entering. The proposed method is to use the degree of matching of the front feature points of the vehicle as a passing criterion using the ORB algorithm that extracts information on feature points characterized by an image, just as the existing system uses the matching of vehicle license plates as a passing criterion. In addition, a procedure for checking whether a vehicle exists inside was included in the proposed system to prevent the entry of the same type of vehicle with a fake license plate. As a result of the experiment, it showed the improved performance in identifying vehicles with fake license plates compared to the existing system. These results confirmed that the methods proposed in this paper could be applied to the existing parking control system while taking the flow of the original artificial intelligence parking control system to prevent vehicles with fake license plates from entering.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.16 no.1
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• pp.41-49
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• 2023

A convolutional neural network (CNN) is a representative algorithm for implementing artificial neural networks. CNNs have improved on the issues of rapid increase in calculation amount and low object classification rates, which are associated with a conventional multi-layered fully-connected neural network (FNN). However, because of the rapid development of IT devices, the maximum resolution of images captured by current smartphone and tablet cameras has reached 108 million pixels (MP). Specifically, a traditional CNN algorithm requires a significant cost and time to learn and process simple, high-resolution images. Therefore, this study proposes an improved CNN algorithm for implementing an object classification learning model for simple, high-resolution images. The proposed method alters the adjacency matrix value of the pooling layer's max pooling operation for the CNN algorithm to reduce the high-resolution image learning model's creation time. This study implemented a learning model capable of processing 4, 8, and 12 MP high-resolution images for each altered matrix value. The performance evaluation result showed that the creation time of the learning model implemented with the proposed algorithm decreased by 36.26% for 12 MP images. Compared to the conventional model, the proposed learning model's object recognition accuracy and loss rate were less than 1%, which is within the acceptable error range. Practical verification is necessary through future studies by implementing a learning model with more varied image types and a larger amount of image data than those used in this study.

• Journal of the Korean Geotechnical Society
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• v.23 no.4
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• pp.5-13
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• 2007

Many construction projects adopt grouting technology to prevent the leakage of groundwater or to improve the shear strength of the ground. Recognition as a feasible field procedure dates back to 1925. Since then, developments and field use have increased rapidly. According to improvement of grout materials, theoretical study on grout penetration characteristics is demanded. Fluid of grout always tends to flow from higher hydraulic potential to lower one and the motion of grout is also a function of formation permeability. Viscosity of pout is changed by chemical action while grout moves through pores. Due to the increment of viscosity, permeability is decreased. Permeability is also reduced by grout particle deposits to the soil aggregates. In this paper, characteristics of new cement grout material that has been developed recently are studied: injectable volume of new grout material is tested in two different grain sizes of sands; and the method to calculate injectable volume of grout Is suggested with consideration of change in viscosity and clogging phenomena. The calculated values are compared with injection test results. Viscosity of new grout material is found to increase as an exponential function of time. And lumped parameter $\delta$ of new grout material to be used for assessing deposition characteristics is estimated by comparing deposit theory with injection test results considering different soil types and different injection pressures. Injection test results show that grout penetration rate is decreased by the increase of grout viscosity and clogging phenomena.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.23 no.3
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• pp.145-151
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• 2023

3D-CNN is one of the deep learning techniques for learning time series data. Such three-dimensional learning can generate many parameters, so that high-performance machine learning is required or can have a large impact on the learning rate. When learning dynamic hand-gestures in spatiotemporal domain, it is necessary for the improvement of the efficiency of dynamic hand-gesture learning with 3D-CNN to find the optimal conditions of input video data by analyzing the learning accuracy according to the spatiotemporal change of input video data without structural change of the 3D-CNN model. First, the time ratio between dynamic hand-gesture actions is adjusted by setting the learning interval of image frames in the dynamic hand-gesture video data. Second, through 2D cross-correlation analysis between classes, similarity between image frames of input video data is measured and normalized to obtain an average value between frames and analyze learning accuracy. Based on this analysis, this work proposed two methods to effectively select input video data for 3D-CNN deep learning of dynamic hand-gestures. Experimental results showed that the learning interval of image data frames and the similarity of image frames between classes can affect the accuracy of the learning model.

• Korean small business review
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• v.41 no.1
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• pp.53-73
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• 2019

Recently, as the number of shopping facilities has increased, such as complex shopping malls, warehouse type superstores, large fashion outlets, and so on, the conflicts over the opening of large stores between neighboring municipalities are increasing. However, current regulations on the opening of large-scale stores, such as the impact analysis on commercial area, do not adequately reflect the characteristics of new type shopping facilities. In this study, we tried to suggest a rational policy alternative with more realistic suitability by analyzing the characteristics of 'regional shopping facilities' beyond the scope of the municipalities, and analyzing the impact on the regional merchants. The main results of the study are summarized as follows. First, unlike previous researches, which are limited to small business sector, this study presents the results of comprehensively comparing and analyzing the impact on the detailed sectors of the whole distribution market, including the large distribution sector and online distribution sector. Second, in this study, we calculated the total (average) amount of market penetration rate of existing shopping facilities by the entire regional shopping facilities in the Seoul metropolitan area, and this is considered to be of great value in relation to the recognition of problems at the whole level of the metropolitan area and the search for alternative solutions.