• International Journal of Computer Science & Network Security
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• 제21권11호
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• pp.119-130
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• 2021

This study aimed at Evaluate Students' Interaction and Happiness in Distance Learning Among Students with Learning-Difficulties, by identifying the level of students' interaction in distance education and differences between them, as well as its impact on their happiness to learn. To achieve the aim of the study, two scales were designed for this purpose and were applied to a sample consisting of (310) individuals. The results showed that the level of students' interaction through the e-learning platform was at a high level. The results also showed that there was no statistically significant difference between the mean scores of males and females in the scale of students' interaction through the e-learning platform. There was no statistically significant difference between them in their happiness for distance learning via the online platform. There were also no statistically significant differences related to the grade variable in the level of interaction through the electronic platform and in the happiness to learn, while there was a positive statistically significant effect of interaction through the electronic platform on students' happiness to learn.

• 디지털융복합연구
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• 제10권6호
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• pp.33-39
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• 2012

본 연구는 대학에서 이루어지고 있는 강의에 있어 전통적인 오프라인 강의실 강의에 정보기술 발달과 함께 급속도로 확산되고 있는 SNS(Social Network Service)를 접목할 경우 학습성과의 변화에 어떠한 영향을 미치는지를 살펴보기 위해 시작되었다. 이를 위하여 101명을 대상으로 설문조사를 실시하였고 분석결과는 다음과 같다. 첫째, 소셜 네트워킹 참여(online social networking engagement)와 사회적 수용(acculturation)은 교수와의 상호작용 품질(interaction quality with professors)에 영향을 미치는 것으로 나타났다. 또한 교수와의 상호작용품질은 협력학습(collaborative learning)과 학습성과(learning performance)에 유의한 영향을 미치는 것으로 나타났다.

• 농촌계획
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• 제15권1호
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• pp.47-59
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• 2009

The aim of this study is to analyze the green-tourism centrality considering spatial interaction using Gravity Model and social network method. The degree centrality and prestige centrality were applied as green-tourism centrality index. The rural amenity resources and human resources were counted as attraction factors, and a distance among villages was used as friction factor in gravity model. The weights of rural tourism amenity resources were calculated using the analytic hierarchy process(AHP) method and applied to evaluate green-tourism potentiality. The distance was measured with the shortest path among villages using geographic information system(GIS) network analysis. The spatial interaction from gravity model were employed as link weights between nodal points; a pair villages. Using the spatial interaction, the degree-centrality and prestige-centrality indices were calculated by social network analysis and demonstrated possibility of developing integrated green-tourism region centered on high centrality villages.

• 한국콘텐츠학회논문지
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• 제9권4호
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• pp.114-120
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• 2009

본 연구는 질병과 관련이 있는 단백질들은 질병 네트워크를 형성함에 있어서 매우 중요한 인자로 작용할 가능성이 있다는 아이디어에서 출발한다. 우리는 Online Medelian Inheritance in Man(OMIM)으로부터 아토피관련 43개 단백질 데이터베이스를 확보하고 이 단백질들과 상호작용하는 단백질 네트워크를 구축하였다. 아토피관련 단백질 네트워크를 바탕으로 질병 네트워크를 구축하였다. 질병 네트워크로부터 질병단백체인 CCR5, CCL11, 및 IL4R을 발굴하였는데, 이들 모두는 단백질 네트워크에서 허브 단백질로 작용하는 것들이다. 허브단백질은 세포에서 필수단백질로 작용하는 것으로 알려져 있는데, 본 연구에서는 허브단백질이면서 동시에 질병에서 매우 중요한 역할을 할 것으로 기대되는 질병단백체로 역할하고 있음을 확인하였다. 본 연구에서 소규모 아토피 관련 질병네트워크를 구축하여 분석하였지만, 여기에 제안한 질병네트워크 분석이 복잡한 인간 질병체계의 분자 기작 및 생물학적 진행과정을 이해하는데 실마리를 제공할 것으로 기대한다.

• BMB Reports
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• 제50권11호
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• pp.535-536
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• 2017

A novel approach has been used to identify functional interactions relevant to human disease. Using high-throughput human-yeast genetic interaction screens, a first draft of disease interactome was obtained. This was achieved by first searching for candidate human disease genes that confer toxicity in yeast, and second, identifying modulators of toxicity. This study found potentially disease-relevant interactions by analyzing the network of functional interactions and focusing on genes implicated in amyotrophic lateral sclerosis (ALS), for example. In the subsequent proof-of-concept study focused on ALS, similar functional relationships between a specific kinase and ALS-associated genes were observed in mammalian cells and zebrafish, supporting findings in human-yeast genetic interaction screens. Results of combined analyses highlighted MAP2K5 kinase as a potential therapeutic target in ALS.

• Journal of Information Processing Systems
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• 제13권4호
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• pp.987-999
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• 2017

Extraction of influential people from their respective domains has attained the attention of scholastic community during current epoch. This study introduces an innovative interaction strength metric for retrieval of the most influential users in the online social network. The interactive strength is measured by three factors, namely re-tweet strength, commencing intensity and mentioning density. In this article, we design a novel algorithm called IPRank that considers the communications from perspectives of followers and followees in order to mine and rank the most influential people based on proposed interaction strength metric. We conducted extensive experiments to evaluate the strength and rank of each user in the micro-blog network. The comparative analysis validates that IPRank discovered high ranked people in terms of interaction strength. While the prior algorithm placed some low influenced people at high rank. The proposed model uncovers influential people due to inclusion of a novel interaction strength metric that improves results significantly in contrast with prior algorithm.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2005년도 제36회 하계학술대회 논문집 D
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• pp.2771-2773
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• 2005

In network human-robot interaction, human can access services of a robot system through the network The communication is done by interacting with the distributed sensors via voice, gestures or by using user network access device such as computer, PDA. The service organization and exploration is very important for this distributed system. In this paper we propose a new agent-based framework to integrate partners of this distributed system together and help users to explore the service effectively without complicated configuration. Our system consists of several robots. users and distributed sensors. These partners are connected in a decentralized but centralized control system using agent-based technology. Several experiments are conducted successfully using our framework The experiments show that this framework is good in term of increasing the availability of the system, reducing the time users and robots needs to connect to the network at the same time. The framework also provides some coordination methods for the human robot interaction system.

• Genomics & Informatics
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• 제21권1호
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• pp.6.1-6.8
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• 2023

Glaucoma is the second leading cause of irreversible blindness, and primary open-angle glaucoma (POAG) is the most common type. Due to inadequate diagnosis, treatment is often not administered until symptoms occur. Hence, approaches enabling earlier prediction or diagnosis of POAG are necessary. We aimed to identify novel drugs for glaucoma through bioinformatics and network analysis. Data from 36 samples, obtained from the trabecular meshwork of healthy individuals and patients with POAG, were acquired from a dataset. Next, differentially expressed genes (DEGs) were identified to construct a protein-protein interaction (PPI) network. In both stages, the genes were enriched by studying the critical biological processes and pathways related to POAG. Finally, a drug-gene network was constructed, and novel drugs for POAG treatment were proposed. Genes with p < 0.01 and |log fold change| > 0.3 (1,350 genes) were considered DEGs and utilized to construct a PPI network. Enrichment analysis yielded several key pathways that were upregulated or downregulated. For example, extracellular matrix organization, the immune system, neutrophil degranulation, and cytokine signaling were upregulated among immune pathways, while signal transduction, the immune system, extracellular matrix organization, and receptor tyrosine kinase signaling were downregulated. Finally, novel drugs including metformin hydrochloride, ixazomib citrate, and cisplatin warrant further analysis of their potential roles in POAG treatment. The candidate drugs identified in this computational analysis require in vitro and in vivo validation to confirm their effectiveness in POAG treatment. This may pave the way for understanding life-threatening disorders such as cancer.

• 한국HCI학회:학술대회논문집
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• 한국HCI학회 2009년도 학술대회
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• pp.45-51
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• 2009

본 논문은 에너지 바운딩 알고리즘 (EBA: Energy Bounding Algorithm) 기반의 힘 반향 원격 제어 시스템의 투명성을 분석하고 이를 기반한 네트워크 적응형 전송기법을 제안한다. EBA 는 양방향 원격 조작의 안정성을 확보하는 알고리즘으로 시간지연의 크기와 변동 및 손실에 상관없이 양방향 원격 조작의 안정성을 보장한다. 하지만 네트워크 지연 및 손실에 의한 투명성 저하는 EBA 로 극복하기에는 한계가 있다. 따라서 효과적인 전송기법을 이용하여 투명성을 향상시킬 필요가 있다. 제안하는 투명성 분석은 네트워크 지연 및 손실에 따른 힘 피드백의 왜곡 현상을 수식화한다. 이를 기반으로 촉감 데이터 동기화 기법 및 전송률 제어 기법의 투명성을 향상시킨다. 조작자가 요구하는 투명성 요구 조건과 현재 네트워크 상황에 맞추어 투명한 촉감 상호작용을 위한 동기화 지연 시간과 전송되어야 하는 촉감데이터량을 결정한다. Matlab 시뮬레이션을 통해서 제안한 투명성 분석의 타당성을 검증하고 촉감데이터 동기화 기법 및 전송률 제어 기법의 투명성을 확인한다.

• Genomics & Informatics
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• 제10권4호
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• pp.256-262
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• 2012

Most common complex traits, such as obesity, hypertension, diabetes, and cancers, are known to be associated with multiple genes, environmental factors, and their epistasis. Recently, the development of advanced genotyping technologies has allowed us to perform genome-wide association studies (GWASs). For detecting the effects of multiple genes on complex traits, many approaches have been proposed for GWASs. Multifactor dimensionality reduction (MDR) is one of the powerful and efficient methods for detecting high-order gene-gene ($G{\times}G$) interactions. However, the biological interpretation of $G{\times}G$ interactions identified by MDR analysis is not easy. In order to aid the interpretation of MDR results, we propose a network graph analysis to elucidate the meaning of identified $G{\times}G$ interactions. The proposed network graph analysis consists of three steps. The first step is for performing $G{\times}G$ interaction analysis using MDR analysis. The second step is to draw the network graph using the MDR result. The third step is to provide biological evidence of the identified $G{\times}G$ interaction using external biological databases. The proposed method was applied to Korean Association Resource (KARE) data, containing 8838 individuals with 327,632 single-nucleotide polymorphisms, in order to perform $G{\times}G$ interaction analysis of body mass index (BMI). Our network graph analysis successfully showed that many identified $G{\times}G$ interactions have known biological evidence related to BMI. We expect that our network graph analysis will be helpful to interpret the biological meaning of $G{\times}G$ interactions.