• The Journal of Korean Institute of Information Technology
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• v.17 no.4
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• pp.87-97
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• 2019

SRS was proposed for immediate processing of the meaning of sensor data on mobile devices independent from specific sensor networks and sensor type. However, each time new sensor data is received, sensor data inspection operations are performed repeatedly, and it cause resulting in low performance. App profile-based SRS has been proposed to resolve the problem. The app profile-based SRS has improved the SRS problem through the profile, but has been tested in a virtual simulation environment. After that the test was experimented in a real-time environment, but has not been tested with a variety of dynamic factors. Therefore, this paper experiment considering such as user mobility and sensor density in real-time environment. And this paper also evaluate performance of the App profile-based through analysis of the results of the experiment. As a result, app profile-based SRS is high influence by density and sensor type, and the number of sensor node is not influence.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.05a
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• pp.374-376
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• 2022

The Malware App Analysis Tool is a system that analyzes Android-based apps by the AI-based algorithm defined in the tool and detects whether malware code is included. Currently, as the spred of smartphones is activated, crimes using malware apps have increased, and accordingly, security for malware apps is required. Android operating systems used in smartphones have a share of more than 70% and are open-source-based, so not only will there be many vulnerabilities and malware, but also more damage to malware apps, increasing demand for tools to detect and analyze malware apps. However, this paper is proposed because there are many difficulties in designing and developing a malware app analysis tool because the security functional requirements for the malware app analysis tool are not clearly specified. Through the developed protection profile, technology can be improved based on the design and development of malware app analysis tools, safety can be secured by minimizing damage to malware apps, and furthermore, trust in malware app analysis tools can be guaranted through common criteria.

• Journal of Korean Elementary Science Education
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• v.38 no.1
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• pp.116-129
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• 2019

This study investigated elementary students' spatial thinking and visualization when they learned the shape of volcanoes. For this purpose we used GeoMapApp to design instruction program and assessment items. In the instruction, students were asked to connect the floor plan view of Jeju island with the cross-sectional view of the same figure producted by GeoMapApp. Then they were asked to classify four sets of pictures of volcanoes based on the similarities of figures, that is, dome-shaped and shield volcanoes. In the assessment students solved three questions which examined how they connected the plan view and cross-sectional profile of Kilauea, draw cross-sectional profile of Mt. Fuji, and distinguished a shield volcano and dome-shaped one. Students' discourse data during the class were analyzed according to the amount to showing their spatial thinking and visualization. The instruction program using GeoMapApp assisted students to facilitate their spatial thinking for understanding of volcanoes. The outcomes of assessment showed even elementary students had good spatial thinking and visualization. Therefore, we argued spatial thinking and visualization for geoscientific understanding need to be included in the national science curriculum for elementary students.

• Asia Marketing Journal
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• v.24 no.4
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• pp.169-177
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• 2023

In the current study, we explore how women decide whether to accept or reject a potential match offered by a dating app (Tinder). Specifically, we were trying to identify overlying factors that influence the decision and understand how women make a judgment based on limited cues provided by a Tinder profile. Women largely base their decision on the perceived attractiveness and character of the potential match. The findings suggest that attractiveness is highly subjective, with no universal rules that can be quantified; thus, it is hard to predict acceptance of the potential match. There are however factors that contribute significantly to profile rejection, such as a big age difference and the inability to clearly see the face of the person.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2019.05a
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• pp.316-318
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• 2019

Recently, healthy life has become an issue in an aging society, and the number of people who have been interested in continuous health care for better life is increasing. In this paper, we implemented a personalized recommendation systm to provide convenient healthcare management for user. The PHR (Personal Health Record) of user could be stored in the server along with health related information such as lifestyle, disease, and physical condition. The users could be classified into similar clusters according to the PHR profile in order to provide healthcare contents to the users who had similar PHR profile. K-Means clustering was applied to generate clusters based on PHR profile and ACDT(Ant Colony Decision Tree) algorithm was used to provide personalised recommendation of health information stored in knowledge base. The app system developed in this paper is useful for users to perform healthcare themselves by providing information on serious diseases and lifestyle habits to be improved according to the clusters classified by PHR profile.

• Journal of Software Engineering Society
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• v.28 no.1
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• pp.1-6
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• 2019

Google released an initial version of Android that runs Dex(Dalvik Executable) through the Dalvik Runtime. Since Dalvik Runtime is based on interpreter, JIT(Just-in-time) compilation has been applied to improve performance. After Lollipop(Android 5.0) Dalvik Runtime has replaced with ART Runtime which support AOT (Ahead-of-time) compilation of Dex into Native Code. The late st Android has a problem that the application execution speed is slow until the AOT compilation is completed according to the actual usage record after the installation of the app. To improve the problem we have investigate the characteristics of profile that can improve the execution speed of the application and generate the profile automatically. Finally we propose a method that can optimize the application at install time. With the proposed method we can optimize selectively at install time and can help improving the execution speed of the app from the initial execution.

• Journal of The Korean Association of Information Education
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• v.22 no.5
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• pp.509-517
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• 2018

As the necessity of maker education is being emphasized and the app generation is now entering school, expectations concerning the impact of app development education are rising in the field of education. The introduction and rise in popularity of a new type of education, such as app development education, requires a change in attitude among teachers. Therefore, this study focused on the concerns of in-service teachers regarding app development education by applying the Concerns-Based Adoption Model (CBAM) of Hall and Hord (2015). For this purpose, the data was collected from 23 in-service teachers who attended a short teacher training session that introduced app development training. The data was converted to the relative intensity based on the stage of concerns questionnaire (SoCQ) scoring device and was expressed as the SoCQ profile. The results of the survey concerning app development education showed that the stage 0 concern (unconcerned) was reported most frequently by teachers and the stage 4 concern (consequence) was reported least frequently. This kind of result, which is typical at the beginning of the introduction of a new education program, indicates that teachers recognize app development education but do not have sufficient information regarding it. Qualitative results also showed that teachers understand the educational possibilities of app development education, but they were worried about the difficulties expected to be applied in the field. Based on these results, we suggest that more detailed information on app development education be provided through teacher training.

• Journal of IKEEE
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• v.22 no.1
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• pp.29-37
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• 2018

In recent years, there have been increasing interests in the mobile crowdsourcing that exploits multiple sensors, communication and user interfaces, and the computation power of widespread smartphones. In this paper, we present a novel mobile crowdsourcing-based driver assistance systems (MC-DAS) that crowdsource the sensor data of smartphone app having already passed a road segment, generate its profile information through a massive data processing, and forward this profile to the smartphone app of vehicle entering the road segment. Based on the MC-DAS platform, we also design and implement a new navigation system that advices the vehicle speed depending on the speedbump and on the road curvature profile. We expect that the proposed MC-DAS platform will be used as a platform for emerging new mobile crowdsourcing applications.

• YAKHAK HOEJI
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• v.56 no.6
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• pp.366-371
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• 2012

In this present study, we determined whether or not there is an immunoadjuvant effect of ochnaflavone, a biflavone isolated from Lonicera japonica. As an antigenic source, the cell wall (CACW) of Candida albicans, a fungal pathogen, was used. CACW consists of 95% carbohydrate (mannan). In the experiments, BALB/c mice were immunized with emersion forms of CACW combined with or without ochnaflavone (Och) in the presence of IFA containing mineral oil or CACW alone. Then, the amounts of antisera collected from these mice groups were measured by the ELISA method. Data from these experiments showed that CACW combined with Och (CACW/Och/IFA) provoked the production of antisera app. 2.2 or 5 times more than the corresponding CACW/IFA or CACW alone (CACW/DPBS), respectively, in mice (P<0.05). We further examined the immune response type induced by Och. Analysis of the values of the IgG1/IgG2a ratios obtained from IgG isotyping revealed that Och induced Th2-immunity more dominantly than Th1. This finding was confirmed by cytokine profile. CACW/Och/IFA formulation induced IL-4 (Th2-type cytokine) more than IFN${\gamma}$ (Th1-type cytokine) as compared with CACW/IFA and CACW/DPBS formulations (P<0.05). All data combined, Och appears to have an immunoadjuvant activity that may convert Th1 immunity into Th2 immunity.

• Proceedings of the Korea Information Processing Society Conference
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• 2016.10a
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• pp.857-860
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• 2016

이 논문에서는 모바일 앱 프로파일 기반의 센서 레지스트리 시스템을 실시간 환경에서 실험하고 평가한다. 이기종 사물인터넷 환경에서 센서 레지스트리 시스템은 모바일 기기에 센서 메타데이터를 제공하여 센서 데이터 처리의 즉시성을 제공한다. 하지만 불필요한 센서 데이터까지 처리하여 성능 측면에서 개선사항이 요구된다. 이를 개선하기 위해 앱 프로파일을 기반으로 한 센서 필터링 기법을 제안한다. 유효한 센서 식별을 위한 센서의 정보를 프로파일 형태로 모바일 기기에 저장 후 사용하여 불필요한 센서 데이터를 필터링함으로써 전체적인 처리 속도가 개선된다. 기존 연구는 시뮬레이션 평가를 통하여 처리 속도의 향상성을 확인한다. 하지만 실시간 환경을 통한 다양한 상황의 실험이 부족하여, 이 논문에서는 기존 센서 레지스트리 시스템과 앱 프로파일 기반의 센서 레지스트리 시스템을 실시간 환경에 맞춰 구축하고 실험 및 평가한다.