• 경영과학
• /
• 제32권3호
• /
• pp.29-36
• /
• 2015

In this research, we analyze the sensitivity of the network density to the estimates for the Bass model parameters with both theoretical model and a simulation. Bass model describes the process that the non-adopters in the market potential adopt a new product or an innovation by the innovation effect and imitation effect. The imitation effect shows the word of mouth effect from the previous adopters to non-adopters. But it does not divide the underlying network structure from the strength of the influence over the network. With a network based Bass model, we found that the estimate for the imitation coefficient is highly sensitive to the network density and it is decreasing while the network density is decreasing. This finding implies that the interpersonal influence can be under-looked when the network density is low. It also implies that both of the network density and the interpersonal influence are important to facilitate the diffusion of an innovation.

• 한국지능시스템학회논문지
• /
• 제14권7호
• /
• pp.847-851
• /
• 2004

Bishop과 Nabnck에 의해 소개된 기존치 혼합 밀도 네트워크(Mixture Density Network)에서는 조건부 확률밀도 함수의 매개변수들(parameters)이 하나의 MLP(multi-layer perceptron)의 출력 벡터로 주어진다. 최근에는 변형된 혼합 밀도 네트워크(Modified Mixture Density Network)라고 하는 이름으로 조건부 확률밀도 함수의 선분포(priors), 조건부 평균(conditional means), 그리고 공분산(covariances) 등이 각각 독립적인 MLP의 출력벡터로 주어지는 경우를 다룬 연구가 보고된 바 있다. 본 논문에서는 조건부 평균이 입력에 관해 선형인 경우를 위한 버전에 대한 이론과 매트랩 프로그램 개발을 다룬다. 본 논문에서는 우선 일반적인 혼합 밀도 네트워크에 대해 간단히 설명하고, 혼합 밀도 네트워크의 출력인 다층 퍼셉트론의 매개변수를 각각 다른 다층 퍼셉트론에서 학습시키는 변형된 혼합 밀도 네트워크를 설명한 후, 각각 다른 다층 퍼셉트론을 통해 매개변수를 얻는 것은 동일하나 평균값은 선형함수를 통해 얻는 혼합 밀도 네트워크 버전을 소개한다. 그리고, 모의실험을 통하여 이러한 혼합 밀도 네트워크의 적용가능성에 대해 알아본다.

• 디지털산업정보학회논문지
• /
• 제10권2호
• /
• pp.47-59
• /
• 2014

In this paper, I propose a new energy efficient clustering scheme to prolong the network lifetime by reducing energy consumption at the sensor node. It is possible that a node determines whether to participate in clustering with certain probability based on local density. This scheme is useful under the environment that sensor nodes are deployed unevenly within the sensing area. By adjusting the probability of participating in clustering dynamically with local density of nodes, the energy consumption of the network is reduced. So, the lifetime of the network is extended. In the region where nodes are densely deployed, it is possible to reduce the energy consumption of the network by limiting the number of node which is participated in clustering with probability which can be adjusted dynamically based on local density of the node. Through computer simulation, it is verified that the proposed scheme is more energy efficient than LEACH protocol under the environment where node are densely located in a specific area.

• 대한전기학회논문지
• /
• 제45권2호
• /
• pp.325-328
• /
• 1996

In this paper, we proposed an estimation method of a posterior probability and PDF(Probability density function) using a feed forward neural network and code books of VQ(vector quantization). In this study, We estimates a posterior probability and probability density function, which compose a new parameter with well-known Mel cepstrum and verificate the performance for the five vowels taking from syllables by NN(neural network) and PNN(probabilistic neural network). In case of new parameter, showed the best result by probabilistic neural network and recognition rates are average 83.02%.

• 한국측량학회지
• /
• 제36권5호
• /
• pp.335-341
• /
• 2018

The KDE (Kernel Density Estimation) technique in GIS (Geographic Information System) has been widely used as a method for determining whether a phenomenon occurring in space forms clusters. Most human-generated events such as traffic accidents and retail stores are distributed according to a road network. Even if events on forward and rear roads have short Euclidean distances, network distances may increase and the correlation between them may be low. Therefore, the NKDE (Network-based KDE) technique has been proposed and applied to the urban space where a road network has been developed. KDE is being studied in the field of business GIS, but there is a limit to the microscopic analysis of economic activity along a road. In this study, the NKDE technique is applied to the analysis of urban phenomena such as the density of shops rather than traffic accidents that occur on roads. The results of the NKDE technique are also compared to pedestrian networks and road centerline networks. The results show that applying NKDE to microscopic trade area analysis can yield relatively accurate results. In addition, it was found that pedestrian network data that can consider the movement of actual pedestrians are necessary for accurate trade area analysis using NKDE.

• 한국전자통신학회논문지
• /
• 제9권6호
• /
• pp.657-664
• /
• 2014

본 연구는 SNS 이용자들을 대상으로 이용동기를 분석하여, 각 이용동기의 중간값을 기준으로 상, 중, 하로 구분하고, 정보교류, 네트워크 밀도, 정보신뢰도, 유대인식의 차이를 알아보았다. 소셜 네트워크 이용 동기는 정보추구 동기, 사회적 영향동기, 오락적 동기, 네트워크 형성동기로 나타났다. 이러한 이용동기 수준에 따라 종속변인으로 설정한 정보교류 정도, 네트워크 밀도, 정보신뢰도, 유대인식에 차이가 나타났다. 특히 정보교류 정도와 정보의 신뢰성은 4가지 동기 수준에 따라 차이가 나타났으며, 네트워크 밀도와 유대인식의 차이는 사회적 영향 동기 수준에 따라 차이가 나타났다.

• 한국언론정보학보
• /
• 제60권
• /
• pp.75-103
• /
• 2012

본 연구는 커뮤니케이션 네트워크의 사회자본적 의미와 효과를 기업명성 측면에서 실증적으로 검증하고자 하는 목적을 갖고 있다. 특히 사회자본의 구조적, 내용적, 관계적 차원에서 소비자의 커뮤니케이션 네트워크를 분석함으로써 명성 높은 기업의 커뮤니케이션 네트워크 구조 특성과 의미를 밝혀보고자 하였다. 본 연구는 서울 및 수도권 지역에 거주하는 만 20세 이상의 성인 200명을 대상으로 설문 조사를 실시했다. 본 연구는 명성 높은 기업의 커뮤니케이션 네트워크 구조 특성을 연결정도(degree), 연결정도 중심성(degree centrality), 밀도(density)라는 지표를 통해 분석하였다. 분석결과, 명성 높은 기업의 네트워크는 명성 낮은 기업에 비해 연결정도가 많고 연결정도 중심성이 높았으며, 밀도 역시 더 높았다. 이는 명성 높은 기업의 경우 소비자가 다양한 정보원을 통해 정보를 얻고 있으며, 중복된 정보원들을 사용하고 있는 소비자들이 많기 때문에 소비자들간 유사한 해석을 공유하고 있음을 시사한다. 또한 밀도가 높다는 점은 정보교류가 원활하고 정보 확산도 빠른 네트워크를 명성 높은 기업이 보유하고 있음을 함의한다. 또한 사회자본의 내용적 차원에서는 상품/서비스 정보네트워크가 기업이슈 정보네트워크보다 연결정도나 밀도가 높다는 특징을 보였고 정보습득 네트워크가 정보제공 네트워크보다 연결정도나 밀도가 높았다. 그리고 사회자본의 관계적 차원과 그 효과 면에서 네트워크 구조특성이 기업충성도와 어떤 관련성을 갖는지 검증한 결과, 연결정도 중심성이 클수록 충성도에 더 강한 영향력을 미치는 것으로 확인되었다. 즉, 소비자들이 유사한 정보원들을 통해 공유하는 정보가 많을수록 소비자들간의 연결정도가 강해지면서 정보교류와 확산이 커지게 되는데, 이는 기업명성과 충성도와 밀접한 관련성이 있다는 것을 입증한 것이다.

• 한국전산구조공학회:학술대회논문집
• /
• 한국전산구조공학회 2003년도 봄 학술발표회 논문집
• /
• pp.357-365
• /
• 2003

The major problems with the conventional neural network, especially Back Propagation Neural Network, arise from the necessity of many training data for neural network learning and ambiguity in the relation of neural network structure to the convergence of solution. In this paper, the PNN is used as a pattern classifier to detect the damage of structure to avoid those drawbacks of the conventional neural network. In the PNN-based pattern classification problems, the probability density function for patterns is usually assumed by Gaussian distribution. But, in this paper, several probability density functions are investigated in order to select the most approriate one for structural damage assessment.

• 한국항해항만학회지
• /
• 제38권3호
• /
• pp.307-315
• /
• 2014

This paper aims to empirically examine how shipping companies can effectively acquire knowledge from their strategic alliance partners. This paper adopts cooperative network embeddedness mechanism, such as network density and tie closeness, as a channel through which to acquire more knowledge for shipping participants within a strategic alliance network. This study also examines the moderating role of competition between alliance partners in reinforcing the effectiveness of the cooperative relationships on the knowledge acquisition. Based on the literature, hypotheses to predict the aforementioned associations between cooperative network embeddedness and knowledge acquisition and the moderating role of competition in facilitating that association are established. A quantitative research method using survey data conducted in the Korean shipping industry was employed in order to empirically test the presented hypotheses. The results show that if players in a shipping alliance network are embedded in a dense network and have close relationships with their alliance partners, this helps to facilitate a greater degree of knowledge acquisition from the partners; and the impact of network density on the knowledge acquisition would be intensified with the higher level of competition between shipping companies.

• Journal of Preventive Medicine and Public Health
• /
• 제46권6호
• /
• pp.336-345
• /
• 2013

Objectives: Research has shown that obesity appears to spread through social ties. However, the association between other characteristics of social networks and obesity is unclear. This study aimed to identify the association between social network characteristics and body mass index (BMI, $kg/m^2$) in an elderly Korean population. Methods: This cross-sectional study analyzed data from 657 Koreans (273 men, 384 women) aged 60 years or older who participated in the Korean Social Life, Health, and Aging Project. Network size is a count of the number of friends. Density of communication network is the number of connections in the social network reported as a fraction of the total links possible in the personal (ego-centric) network. Average frequency of communication (or meeting) measures how often network members communicate (or meet) each other. The association of each social network measure with BMI was investigated by multiple linear regression analysis. Results: After adjusting for potential confounders, the men with lower density (<0.71) and higher network size (4-6) had the higher BMI (${\beta}$=1.089, p=0.037) compared to the men with higher density (>0.83) and lower size (1-2), but not in the women (p=0.393). The lowest tertile of communication frequency was associated with higher BMI in the women (${\beta}$=0.885, p=0.049), but not in the men (p=0.140). Conclusions: Our study suggests that social network structure (network size and density) and activation (communication frequency and meeting frequency) are associated with obesity among the elderly. There may also be gender differences in this association.