• The Journal of the Korea Contents Association
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• v.19 no.3
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• pp.72-79
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• 2019

Autonomous locomotion has two essential functionalities: mapping builds and updates maps by uncertain position information and measured sensor inputs, and localization is to find the positional information with the inaccurate map and the sensor information. In addition, obstacle detection, avoidance, and path designs are necessarily required for autonomous locomotion by combining the probabilistic methods based on uncertain locations. The sensory inputs, which are measured by a metric-based scanner, have difficulties of distinguishing moving obstacles like humans from static objects like walls in given environments. This paper proposes the low resolution grid map combined with reinforcement learning, which is compared with the conventional recognition method for detecting static and moving objects to generate obstacle avoiding path. Finally, the proposed method is verified with experimental results.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.22 no.11
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• pp.1421-1427
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• 2018

Due to the rapid development of Internet-of-Things technology, different types of smart sensors are now devised and deployed widely. These smart sensors are now used in animal husbandry which was traditionally managed by the experience of farmers, such that wearable sensors for livestock, and the smart farm which is equipped with multiple sensors are utilized to increase the efficiency of livestock management. Herein, we consider a scheme in which the body temperature and the level of activity are measured by smart sensor which is attached to the neck of dairy cattle and the health condition is monitored based on collected data. Especially, we find that the estrous of dairy cattle which is one of most important metric in milk production, can be predicted with high precision using various machine learning techniques. By utilizing the proposed prediction scheme, estrous of cattle can be detected immediately and this can improve the efficiency of cattle management.

• KIPS Transactions on Software and Data Engineering
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• v.8 no.7
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• pp.265-274
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• 2019

The reliability test performed when developing the weapon system software is classified into static test and dynamic test. In static test, checking the coding rules, vulnerabilities and source code metric are performed without executing the software. In dynamic test, its functions are verified by executing the actual software based on requirements and the code coverage is measured. The purpose of this static/dynamic test is to find out defects that exist in the software. However, there still exist defects that can't be detected only by the current reliability test on the weapon system software. In this paper, whether defects that may occur in the software can be detected by static test and dynamic test of the current reliability test on the weapon system is analyzed through experiments. As a result, we provide guidance on improving the reliability test of weapon system software, especially the dynamic test.

• Journal of the Korean Society of Fisheries and Ocean Technology
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• v.55 no.1
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• pp.1-6
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• 2019

The annual production of silver croaker (Argyrosomus argentatus) in Korean towed fishing gears has been increased in recent five years. In 2017, the annual production of silver croaker in metric ton was increased 99.2% compared to 2013. However, the research for silver croaker has been focused on ecology in Korea. There has not been enough research in terms of fishing gears. Therefore, the research for retention probability for towed gears was conducted on covered codend method from June, 2016 to July, 2018. During the experiments, the total catch of silver croaker was 1,563. The geometry of the experimental trawl gear was controlled by trawl monitoring system; net height was 3.3 m, distance of trawldoors was 59.8 m and distance of wing net was 17.3 m. The selection curve for silver croaker was estimated by a logit model. The analysis was applied with the confidence interval to reduce uncertainty of the estimation. The $l_{50}$ was 13.87 cm and its selection range was 2.71 cm. P-value was estimated at 0.99. The mesh size for silver croaker in towed gears needs to be adjusted by considering its minimum maturity length, stakeholder's interests and fisheries regulations.

• The Research Journal of the Costume Culture
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• v.29 no.5
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• pp.634-650
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• 2021

This study was conducted to investigate the effect of relationship and service marketing on the brand interest and behaviors among Korean and Chinese active senior consumers and whether this effect differed between the two groups. A survey was conducted by having participants complete questionnaires administered by a research firm. For empirical analysis, frequency, EFA, CFA, SEM, the metric invariance test, and multiple-group comparison analysis were performed. The analysis results revealed that relationship marketing positively affected both brand interest and consumer behavior. Although service marketing positively affected brand interest, it did not have a significant effect on consumer behavior. In other words, brand interest positively affected consumer behavior through relationship and service marketing. Multiple-group comparison analysis demonstrated that no difference existed between Korean and Chinese active consumers in terms of how relationship marketing affected their brand interest, but a difference existed in how it affected their behavior. Service marketing had a greater influence on Chinese active senior consumers' brand interest than on Korean active senior consumers. However no difference existed between the two groups with respect to how service marketing affected their behaviors. Finally, brand interest had a positive effect only on Korean active senior consumers' behavior through relationship and service marketing, but not on Chinese active senior consumers. In conclusion, relationship and service marketing should be used to enhance the brand interest among Korean active senior consumers, and business activities should be planned by building relationships with Chinese active senior consumers to affect their behavior.

• International Journal of Computer Science & Network Security
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• v.21 no.8
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• pp.267-275
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• 2021

Smart application is developed in this paper by using an android-based platform to automatically determine the human emergency state (Lifesaver) by using different technology sensors of the mobile. In practice, this Lifesaver has many applications, and it can be easily combined with other applications as well to determine the emergency of humans. For example, if an old human falls due to some medical reasons, then this application is automatically determining the human state and then calls a person from this emergency contact list. Moreover, if the car accidentally crashes due to an accident, then the Lifesaver application is also helping to call a person who is on the emergency contact list to save human life. Therefore, the main objective of this project is to develop an application that can save human life. As a result, the proposed Lifesaver application is utilized to assist the person to get immediate attention in case of absence of help in four different situations. To develop the Lifesaver system, the GPS is also integrated to get the exact location of a human in case of emergency. Moreover, the emergency list of friends and authorities is also maintained to develop this application. To test and evaluate the Lifesaver system, the 50 different human data are collected with different age groups in the range of (40-70) and the performance of the Lifesaver application is also evaluated and compared with other state-of-the-art applications. On average, the Lifesaver system is achieved 95.5% detection accuracy and the value of 91.5 based on emergency index metric, which is outperformed compared to other applications in this domain.

• Biomolecules & Therapeutics
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• v.29 no.3
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• pp.249-262
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• 2021

The most effective way to control newly emerging infectious disease, such as the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic, is to strengthen preventative or therapeutic public health strategies before the infection spreads worldwide. However, global health systems remain at the early stages in anticipating effective therapeutics or vaccines to combat the SARS-CoV-2 pandemic. While maintaining social distance is the most crucial metric to avoid spreading the virus, symptomatic therapy given to patients on the clinical manifestations helps save lives. The molecular properties of SARS-CoV-2 infection have been quickly elucidated, paving the way to therapeutics, vaccine development, and other medical interventions. Despite this progress, the detailed biomolecular mechanism of SARS-CoV-2 infection remains elusive. Given virus invasion of cells is a determining factor for virulence, understanding the viral entry process can be a mainstay in controlling newly emerged viruses. Since viral entry is mediated by selective cellular proteases or proteins associated with receptors, identification and functional analysis of these proteins could provide a way to disrupt virus propagation. This review comprehensively discusses cellular machinery necessary for SARS-CoV-2 infection. Understanding multifactorial traits of the virus entry will provide a substantial guide to facilitate antiviral drug development.

• Smart Media Journal
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• v.10 no.3
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• pp.23-30
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• 2021

Although the manufacturing time series data clustering technique is an important grouping solution in the field of detecting and improving manufacturing large data-based equipment and process defects, it has a disadvantage of low accuracy when applying the existing static data target clustering technique to time series data. In this paper, an evolutionary computation-based time series cluster analysis approach is presented to improve the coherence of existing clustering techniques. To this end, first, the image shape resulting from the manufacturing process is converted into one-dimensional time series data using linear scanning, and the optimal sub-clusters for hierarchical cluster analysis and split cluster analysis are derived based on the Pearson distance metric as the target of the transformation data. Finally, by using a genetic algorithm, an optimal cluster combination with minimal similarity is derived for the two cluster analysis results. And the performance superiority of the proposed clustering is verified by comparing the performance with the existing clustering technique for the actual manufacturing process image.

• Journal of Information Science Theory and Practice
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• v.10 no.4
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• pp.53-65
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• 2022

Altmetrics or alternative metrics gauge the digital attention received by scientific outputs from the web, which is treated as a supplement to traditional citation metrics. In this study, we performed a meta-analysis of correlations between classic citation metrics and altmetrics indicators of library and information science (LIS) articles. We followed the systematic review method to select the articles and Erasmus Rotterdam Institute of Management Guidelines for reporting the meta-analysis results. To select the articles, keyword searches were conducted on Google Scholar, Scopus, and ResearchGate during the last week of November 2021. Eleven articles were assessed, and eight were subjected to meta-analysis following the inclusion and exclusion criteria. The findings reported negative and positive associations between citations and altmetric indicators among the selected articles, with varying correlation coefficient values from -.189 to 0.93. The result of the meta-analysis reported a pooled correlation coefficient of 0.47 (95% confidence interval, 0.339 to 0.586) for the articles. Sub-group analysis based on the citation source revealed that articles indexed on the Web of Science showed a higher pooled correlation coefficient (0.41) than articles indexed in Google Scholar (0.30). The study concluded that the pooled correlation between citation metrics with altmetric indicators was positive, ranging from low to moderate. The result of the study gives more insights to the scientometrics community to propose and use altmetric indicators as a proxy for traditional citation indicators for quick research impact evaluation of LIS articles.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.24 no.3
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• pp.441-447
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• 2020

In a situation in which around 50 million metric tons of electrical and electronic products is generated globally per year, the total installed base of Internet of Things (IoT) devices is projected to amount to around 75 billion worldwide by 2025. However, there is very little research on identification schemes for end-of-life treatment (EoLT) of IoT devices. To address this issue, this paper proposes new identifiers including EoLT information such as recyclability rate (Rcyc) and recoverability rate (Rcov) of an IoT device, recycling rate (RCR) and recovery rate (RVR) of each part in the IoT device, etc. and implements them by using object identifier (OID), mobile radio frequency identification (RFID) and quick response (QR) code. The implemented OID and mobile RFID can be used with cooperation of a remote server via communication networks and the implemented QR code can be used simply with a smartphone app.