• Journal of Information Processing Systems
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• v.19 no.3
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• pp.310-322
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• 2023

Although the network environment is gradually improving, the virtual nature of the network is still the same fact, which has brought a great influence on the supervision of Weibo network public opinion dissemination. In order to reduce this influence, the user information of Weibo network public opinion dissemination is studied by using Python technology. Specifically, the 2019 "Ethiopian air crash" event was taken as the research subject, the relevant data were collected by using Python technology, and the data from March 10, 2019 to June 20, 2019 were constructed by using the implicit Dirichlet distribution topic model and the naive Bayes classifier. The Weibo network public opinion user identity graph model under the "Ethiopian air crash" on June 20 found that the public opinion users of ordinary netizens accounted for the highest proportion and were easily influenced by media public opinion users. This influence is not limited to ordinary netizens. Public opinion users have an influence on other types of public opinion users. That is to say, in the network public opinion space of the "Ethiopian air crash," media public opinion users play an important role in the dissemination of network public opinion information. This research can lay a foundation for the classification and identification of user identity information types under different public opinion life cycles. Future research can start from the supervision of public opinion and the type of user identity to improve the scientific management and control of user information dissemination through Weibo network public opinion.

• Journal of the Korean Society of Costume
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• v.64 no.4
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• pp.21-36
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• 2014

The purpose of this study is to suggest an effective fashion design process using social network services(SNS) as a method to develop designs. Fashion design process was systemized through literature study. The characteristics of social network, and element and method of network formation were investigated, and then design processes using SNS were suggested through survey study. This was done by applying formation of network and its method in SNS with contents of fashion to stage of process to develop fashion design. The study results are as follows. First, Fashion design process using SNS is composed of 5 stages. Second, SNS types with contents of fashion were classified to five types: blog, community, connection of fashion web service and SNS, fashion SNS, and fashion SNS game. Among them, types where development of fashion design and product distribution was done by formation of network are connected type of fashion web service and SNS, fashion SNS type. Fashion design development can be done by compiling, having contests, and cooperative work. A method that can be used for making assessments and decision is voting and predicting the market. Third, Fashion design process using SNS is composed of the stages such as planning, compiling, analysis, decision, implementation, and formation of network. It was analyzed that by connecting stages of collection and evaluation of information through participation of users, new contents were produced and there was a structure that was cycled continuously.

• Journal of Korea Multimedia Society
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• v.17 no.8
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• pp.977-987
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• 2014

Many of the recent performance evaluation of clustering schemes in wireless sensor networks considered one sink node operation and fixed sink node location without mentioning about any network application requirements. However, application environments have variable requirements about their networks. In addition, network performance is sufficiently influenced by different sink node location scenarios in multi-hop based network. We also know that sink location can influence to the sensor network performance evaluation because of changed multipath of sensor nodes and changed overload spots in multipath based wireless sensor network environment. Thus, the performance evaluation results are hard to trust because sensor network is easily changed their network connection through their routing algorithms. Therefore, we suggest that these schemes need to evaluate with different sink node location scenarios to show fair evaluation result. Under the results of that, network performance evaluation results are acknowledged by researchers. In this paper, we measured several clustering scheme's performance variations in accordance with various types of sink node location scenarios. As a result, in the case of the clustering scheme that did not consider various types of sink location scenarios, fair evaluation cannot be expected.

• International Journal of Computer Science & Network Security
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• v.21 no.9
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• pp.223-229
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• 2021

Classification of different blood cell types is an essential task for human's medical treatment. The white blood cells have different types of cells. Counting total White Blood Cells (WBC) and differential of the WBC types are required by the physicians to diagnose the disease correctly. This paper used transfer learning methods to the pre-trained deep learning models to classify different WBCs. The best pre-trained model was Inception ResNetV2 with Adam optimizer that produced classification accuracy of 98.4% for the dataset comprising four types of WBCs.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.13 no.11
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• pp.5218-5228
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• 2012

The aim of this study is to classify the social network types among elderly people with dementia, and to examine the relationship of network type to quality of life. This is to identify influence of social network on quality of life of elderly people with dementia. And the study seeks to identify the differences of quality of life among types of social network. The data of 222 elderly people used in this study were collected from the health center and elderly people with dementia living in the community. The interview was conducted from July 17 to August 31 in 2012 using a structured questionnaire. Descriptive statistics, one way ANOVA, multiple regression analysis and also cluster analysis with the SPSS 18.0 program were used to analyze the data. As a results, three network types were classified.:(1) inactive isolated, (2) active independent (3) inactive dependent networks. Respondents in the different network type are found to have different degrees of quality of life. Respondents inactive independent network is reported to have the highest quality of life, while those with inactive isolated network are the lowest. The results of the study suggest that the classification of network types allows consideration of the interpersonal environments of elderly people with dementia. The relative effects on quality of life for elderly people with dementia, evident in the current analysis, are the case in point. Therefore Social service programs should focus on different groups based on social network type.

• Journal of Internet Computing and Services
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• v.18 no.4
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• pp.7-17
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• 2017

Despite various types of online social networks having different topological and functional characteristics, the kinds of online social networks considered in social recommendations are highly restricted. The pervasiveness of social networks has brought scholarly attention to expanding the scope of social recommendations into more diverse and less explored types of online social networks. As a preliminary attempt, this study examined the information-sharing patterns of a new type of online social network - unilateral (directed) network - and assessed the feasibility of the network as a useful information source. Specifically, this study mainly focused on the presence of shared interests in unilateral networks, because the shared information is the inevitable condition for utilizing the networks as a feasible source of personalized recommendations. As the results, we discovered that user pairs with direct and distant links shared significantly more similar information than the other non-connected pairs. Individual users' social properties were also significantly correlated with the degree of their information similarity with social connections. We also found the substitutability of online social networks for the top cohorts anonymously chosen by the collaborative filtering algorithm.

• International Journal of Internet, Broadcasting and Communication
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• v.12 no.1
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• pp.14-26
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• 2020

We categorize partnership types between network operators and a global video streaming or over-the-top service provider, Netflix from 2011 to the first quarter 2018. The options are based on the integration of over-the-top (OTT), Netflix with pay TV and telecommunication operators in the form of carrier billing, access to over-the-top (OTT) via devices or the development of their tariff plans. Options of the Type 3, 'cooperation' or the Type 4, 'agreement' entails a kind of the technical involvement between two partners and commercial agreement. The types of partnership are evolving from one to others. Some partnerships have characteristics of more than one type. The majority of technical or service integration cooperation of Type 3 entail bundling and marketing promotion of Type 2 and Type 1. Similarly, the 'agreement' of Type 4, co-branded or white-label service initiative entail tariff or device user interface (UI) integration of the 'cooperation' of Type 3 and joint marketing initiatives of Type 1.

• Korean Journal of Fisheries and Aquatic Sciences
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• v.51 no.3
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• pp.321-327
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• 2018

To classify seafloor sediments using a probabilistic neural network (PNN), the frequency-dependent characteristics of broadband acoustic scattering, which make it possible to qualitatively categorize seabed type, were collected from three different geographical areas in Korea. The echo data samples from three types of seafloor sediment were measured using a chirp sonar system operating over a frequency range of 20-220 kHz. The spectrum amplitudes for frequency responses of 35-75 kHz were fed into the PNN as input feature parameters. The PNN algorithm could successfully identify three seabed types: mud, mud/shell and concrete sediments. The percentage probabilities of the three seabed types being correctly classified were 86% for mud, 66% for mud/shell and 72% for concrete sediment.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.49 no.3
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• pp.157-163
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• 2000

In this paper, an Evolving Neural Network Controller(ENNC) which its structure and its connection weights are optimized simultaneously by Real Variable Elitist Genetic Algoithm(RVEGA) was presented for stabilization of an Inverter Pendulum(IP) system with nonlinearity. This proposed ENNC was described by a simple genetic chromosome. And the deletion of neuron, the determinations of input or output neuron, the deleted neuron and the activation functions types are given according to the various flag types. Therefore, the connection weights, its structure and the neuron types in the given ENNC can be optimized by the proposed evolution strategy. Through the simulations, we showed that the finally acquired optimal ENNC was successfully applied to the stabilization control of an IP system.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.33B no.10
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• pp.130-138
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• 1996

In this paper, we propose a neural network which detect edges of different orentation and spatial frequency in arbitrary image data. We constructed the proposed neural network iwth two different types neural network. A diffusion network performs the gaussian operation efficiently by the diffusion process. And the spatial difference network has specially designed connections suitble to detect the contours of a specific oriention. Simulation results showed that the proposed neural network can extract the edges of selected orientation efficiently by applying the neural network to a test pattern and the real image.