• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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• v.9 no.11
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• pp.1133-1144
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• 2019

Recently, the amount of image on the Internet has rapidly increased, due to the advancement of smart devices and various approaches to effective image retrieval have been researched under these situation. Existing image retrieval methods simply detect the objects in a image and carry out image retrieval based on the label of each object. Therefore, the semantic gap occurs between the image desired by a user and the image obtained from the retrieval result. To reduce the semantic gap in image retrievals, we connect the module for multiple objects classification based on deep learning with the module for human behavior classification. And we combine the connected modules with a behavior ontology. That is to say, we propose an image retrieval system considering the relationship between objects by using the combination of deep learning and behavior ontology. We analyzed the experiment results using walking and running data to take into account dynamic behaviors in images. The proposed method can be extended to the study of automatic annotation generation of images that can improve the accuracy of image retrieval results.

• Journal of Digital Convergence
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• v.17 no.6
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• pp.211-217
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• 2019

This study suggested the alternatives for improving consumers' engagement with digital signage (DS) by analyzing the researches of the effectiveness of DS in marketing and public areas, which is recognized as an essential communication tool for commercial or public matters. According to the results, affective DS ad content of DS resulted in positive shoppers' buying behaviors and perceiving buying environment; DS was also effective for public affairs, which how proper channel and message for the target public resulted in solving community problems. However, it was rare to measure precisely the level of consumers' engagement with DS content and what DS content aroused higher engagement in both areas. Thus, DS content should be more customized based on multiple converged contents for consumers' engagement and the research efforts of DS should be focused on the development of not only its device technology, but also creative content.

• Clinical Psychopharmacology and Neuroscience
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• v.16 no.4
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• pp.415-421
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• 2018

Objective: Autism spectrum disorder (ASD) is a neurodevelopmental disorder characterized by impairment in social skills and communication with repetitive behaviors. Etiology is still unclear although it is thought to develop with interaction of genes and environmental factors. Oxytocin has extensive effects on intrauterine brain development. Vitamin D, affects neural development and differentiation and contributes to the regulation of around 900 genes including oxytocin receptor gene. In the present study, the contribution of D vitamin receptor and oxytocin receptor gene polymorphisms in the development of ASD in Turkish community was investigated. To our knowledge, this is the first study examining these two associated genes together in the literature. Methods: Eighty-five patients diagnosed with ASD according to DSM-5 who were referred to outpatient clinics of Child and Adolescent Psychiatry of Başkent University and Mersin University and 52 healthy, age and gender-matched controls were included in the present study. Vitamin D receptor gene rs731236 (Taq1), rs2228570 (Fok1), rs1544410 (Bsm1), rs7975232 (Apa1) polymorphisms and oxytocin receptor gene rs1042778 and rs2268493 polymorphisms were investigated using real time polymerase chain reaction method. Results: No significant difference between groups in terms of distribution of genotype and alleles in each of polymorphisms for these genes could be found. Conclusion: Knowledge of genes and polymorphisms associated with the development of ASD may be beneficial for early diagnosis and future treatment. Further studies with larger populations are required to demonstrate molecular pathways which may play part in the development of ASD in Turkey.

• KIPS Transactions on Computer and Communication Systems
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• v.8 no.2
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• pp.35-40
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• 2019

Traditional Malware Detection is susceptible for detecting malware which is modified by polymorphism or obfuscation technology. By learning patterns that are embedded in malware code, machine learning algorithms can detect similar behaviors and replace the current detection methods. Data must collected continuously in order to learn malicious code patterns that change over time. However, the process of storing and processing a large amount of malware files is accompanied by high space and time complexity. In this paper, an HDFS-based distributed processing system is designed to reduce space complexity and accelerate feature extraction time. Using a distributed processing system, we extract two API features based on filtering basis, 2-gram feature and APICFG feature and the generalization performance of ensemble learning models is compared. In experiments, the time complexity of the feature extraction was improved about 3.75 times faster than the processing time of a single computer, and the space complexity was about 5 times more efficient. The 2-gram feature was the best when comparing the classification performance by feature, but the learning time was long due to high dimensionality.

• The Korean Journal of Franchise Management
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• v.11 no.2
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• pp.17-22
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• 2020

Purpose: As consumers have difficulty in brand choice due to excessive information, using brand popularity as an advertising cue (e.g., Sales No. 1, Hit Product) has been getting more attention as an effective curation strategy for decreasing consumers' cognitive efforts. Accordingly, recent studies empirically demonstrate that consumers tend to prefer and choose a brand with a popularity cue and offer a useful information regarding how to use a popularity cue in marketing communication. However, extant research has mainly focused on investigating the impact of "brand popularity in a domestic market" on consumer behaviors. Thus, little is known about the effect of "brand popularity in a foreign market" on local consumers' decision-making process. Given that domestic consumers tend to purchase imported products from overseas countries, it can be meaningful information for global companies. Therefore, this research derives and tests the five hypotheses to examine how local consumers respond to brand popularity in a foreign market as an advertising cue. Specifically, it tests the three hypotheses regarding the direct and indirect effects of brand popularity in a foreign market on risk perception and purchase intention. Then, it tests two additional hypotheses about moderating effects of psychic distance on the relationship between brand popularity and risk perception as well as on the relationship between brand popularity and purchase intention. Seventy participants are exposed to an advertisement for an Indian cosmetic brand using a popularity cue in Indian market and answer the questions about brand evaluation. For data analysis, regression analysis is employed. The findings of this research show that perceived brand popularity lowers local consumers' perceived risk with a foreign brand. However, perceived brand popularity does not have a direct impact on purchase intention while it has an indirect effect through perceived risk. Meanwhile, psychic distance moderates the effect of perceived brand popularity on perceived risk level, but it has no impact on the relationship between brand popularity and purchase intention. This research is one of the first studies that demonstrate the positive impact of brand popularity in a foreign market on a local consumer's purchase decision, and it shows the effect can be moderated by psychic distance.

• Journal of the Architectural Institute of Korea Planning & Design
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• v.34 no.6
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• pp.57-66
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• 2018

In Japan, apartment housing occupies a great proportion of residence due to high population density like Korea. Although Korea and Japan are similar in big proportions of apartment housing, and apartment housing management systems and utilization behaviors, there are considerable differences. This paper examined Japanese public facilities and the status of public facility management and utilization, which differ from those in Korea. In order to analyze the status of public facilities from a perspective of management companies, a preliminary survey was conducted targeting apartment management companies in the top 100 and a field study on public facilities was conducted targeting chief directors and managers of individual housing facilities to look into public facility utilization methods, problems with public facility management, demands of residents, and utilization situations. Also, the present state of facility utilization and utilization promotion plans were investigated, based on the drawings of facilities collected. As the result, results were found in three respects; 'elements, related to building plans', 'elements, related to utilization promotion', and 'elements, related to facility remodeling, including changes of uses'. In relation to the use of public facilities in the future, a more active communication between managers and users would be needed for planning. Also, there would be a need to provide public facilities for visitors when there are events for both occupants and visitors in order to promote the use of facilities and management companies would have to share information of excellent facility models.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.23 no.10
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• pp.1216-1227
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• 2019

We propose TITAN (Tool for IoT ApplicatioN testing), a developer support tool that enables efficient testing of IoT applications. TITAN is designed to allow IoT application developers to run their applications under the development environment without being restricted by physical environments and users' behaviors required to test application logic being developed. Using TITAN, IoT application developers can save the time and effort needed to repeatedly perform the testing of application logic while they develop their applications. In this paper, we present the system architecture of TITAN and its current prototype implementation. We evaluate the usefulness and usability of TITAN through a small user study with two example IoT applications. The study participants show their positive perception about the usefulness of TITAN. We further discuss the limitations of the current study and future research directions.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.4
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• pp.603-610
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• 2021

In this paper, we extract the user's power consumption patterns, and model the optimal consumption patterns by applying the user's environment and emotion. Based on the comparative analysis of these two patterns, we present an efficient power consumption method through changes in the user's power consumption behavior. To extract significant consumption patterns, vector standardization and binary data transformation methods are used, and learning about the ensemble's ensemble with k-means clustering is applied, and applying the support factor according to the value of k. The optimal power consumption pattern model is generated by applying forced and emotion-based control based on the learning results for ensemble aggregates with relatively low average consumption. Through experiments, we validate that it can be applied to a variety of windows through the number or size adjustment of clusters to enable forced and emotion-based control according to the user's intentions by identifying the correlation between the number of clusters and the consistency ratios.

• The Journal of the Korea Contents Association
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• v.21 no.6
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• pp.128-137
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• 2021

The purpose of this study is to examine the effect of sympathetic reactions to public service advertisement video messages produced for health campaigns. To this end, based on the empathy response scale proposed by Campbell & Babrow (2004), the empathy response to the images of nine health campaigns with themes of smoking cessation, tuberculosis, and suicide triggered fear of health risks and health behaviors (information seeking, preventive actions). As a result of the analysis, among the factors of empathy reaction, the reality of the message creative, the match of emotions, and the identification of the characters in the video each played a role in raising fear, and it is rather fear that logically understanding the situation that causes health problems through the health campaign video It was found that it played a role in reducing health information seeking behavior. On the other hand, it was found that the higher the degree of interest, such as sympathy for the characters in the video, among the factors of the sympathetic response to the health campaign, the higher the intention of preventive action to reduce the health risk.

• Journal of Digital Convergence
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• v.19 no.6
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• pp.1-9
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• 2021

Artificial intelligence (AI) devices are rapidly emerging as a core platform of next-generation information and communication technology (ICT), this study investigated consumer usage behavior and user experience through AI devices that are widely applied to consumers' daily lives. To this end, data was collected from 600 consumers with experience in using AI devices were derived to recognize the attributes and behavior of AI devices. The analysis results are as follows. First, music listening was the most used among various attributes and it was found that simple functions such as providing weather information were usefully recognized. Second, the main devices used by AI device users were identified as AI speakers, smartphone, PC and laptops. Third, associative images of AI devices appeared in the order of fun, useful, novel, smart, innovative, and friendly. Therefore, practical implications are suggested to contribute to provision of user services using AI devices in the future by analyzing usage behaviors that reflect the characteristics of AI devices.