Big Data Analytics of Multi-Relationship Online Social Network Based on Multi-Subnet Composited Complex Network

Gengxin Sun,Sheng Bin,Yixin Zhou 보안공학연구지원센터 2015 International Journal of Database Theory and Appli Vol.8 No.5

Online social networks such as Twitter and Facebook are becoming popular form of social information networks. There are frequently many kinds of relationships in an online social network. Complex Network acting as one kind of big data technologies is often used to analyze users' social activities. By studying the Douban network, which is a representative multi-relationship online social network in China, big data of friendship relationship and book comments similar relationship are crawled through network topology measurement software, from the perspective of topological characteristics of complex network, the basic topologies of the two relationship networks constructed individually by the two relationships are analyzed. Based on these, a multi-relationship online social network based on Multi-subnet Composited Complex Network Model is constructed through loading book comments similar relationship subnet to follower relationship subnet, and accurate understanding of topologies of Douban multi-relationship network is obtained. These findings provide a deep understanding on the evolution of multi-relationship online social network, and can provide guidelines on how to build an efficient multi-relationship online social network evolution model.

읽기 활동의 복잡계 네트워크 특성 고찰

김도남 한국국어교육학회 2015 새국어교육 Vol.0 No.104

The purpose of this study is to inquire about a trait of reader’s reading activity from a point of view in complex network system. In this viewpoint, the reader hold in the trait of a complex network system during reading a text. In reading, the reader represents all sorts of information in mind and links them to clusters. If the reader does not construct one network by linking all the cluster, then the reader fall into complexity. In holding complexity the reader make efforts to establish order information clusters, he should bring the connect factor among the clusters. So, information clusters are composed of systematic network by linking each other. At this moment, the reader can clear up a complexity and find out new meaning. This reader’s activity is called ‘emergence’. The emergence is happened when the reader links the cluster to network. The emergence meaning become different from type of network of the cluster, that the reader how to link the cluster. We must study about reading activity in viewpoint of the complex network and the complex system. 이 논의에서는 독자의 읽기 활동을 복잡계 네트워크 이론의 관점에서 살펴보았다. 복잡계 네트워크의 관점에서 보면, 독자가 텍스트를 읽고 표상한 정보들은 복잡성을 띠고 있는데 독자는 이들 정보들을 질서 있는 네트워크로 구성하여 복잡성을 해소하고 의미를 창발한다. 독자가 표상한 정보의 복잡성은 텍스트와 독자의 정보가 연결되어 구성된 정보 클러스터들이 질서 있는 네트워크를 이루지 못할 때 생긴다. 독자는 표상한 정보의 복잡성을 느끼면, 이를 해소하려고 노력한다. 이를 위하여 독자는 특정 클러스터를 허브 클러스터로 지정하여 다른 클러스터들을 연결한다. 이 연결은 정보 클러스터들이 특정한 관계를 갖는 네트워크를 이루도록 한다. 네트워크를 이룬 정보 클러스터들의 특정한 관계 속에서 의미가 창발된다. 독자가 창발한 의미는 어떤 클러스터를 허브 클러스터로 지정하여 네트워크로 구성하느냐에 따라 달라지는 것이다. 독자가 표상한 정보 클러스터들을 네트워크로 구성하여 의미를 창발한다고 보는 이 접근은 창의적 읽기를 부분적으로 설명한다. 이 복잡계 네트워크의 이론으로 읽기를 설명하기 위해서는 앞으로 많은 논의가 필요하다.

딥러닝 예측 결과 정보를 적용하는 복합 미생물배양기를 위한 딥러닝 구조 개발

김홍직,이원복,이승호 한국전기전자학회 2023 전기전자학회논문지 Vol.27 No.1

In this paper, we develop a deep learning structure for a complex microbial incubator that applies deep learning prediction result information. The proposed complex microbial incubator consists of pre-processing of complex microbial data, conversion of complex microbial data structure, design of deep learning network, learning of the designed deep learning network, and GUI development applied to the prototype. In the complex microbial data preprocessing, one-hot encoding is performed on the amount of molasses, nutrients, plant extract, salt, etc. required for microbial culture, and the maximum-minimum normalization method for the pH concentration measured as a result of the culture and the number of microbial cells to preprocess the data. In the complex microbial data structure conversion, the preprocessed data is converted into a graph structure by connecting the water temperature and the number of microbial cells, and then expressed as an adjacency matrix and attribute information to be used as input data for a deep learning network. In deep learning network design, complex microbial data is learned by designing a graph convolutional network specialized for graph structures. The designed deep learning network uses a cosine loss function to proceed with learning in the direction of minimizing the error that occurs during learning. GUI development applied to the prototype shows the target pH concentration (3.8 or less) and the number of cells (10⁸ or more) of complex microorganisms in an order suitable for culturing according to the water temperature selected by the user. In order to evaluate the performance of the proposed microbial incubator, the results of experiments conducted by authorized testing institutes showed that the average pH was 3.7 and the number of cells of complex microorganisms was 1.7 × 10⁸. Therefore, the effectiveness of the deep learning structure for the complex microbial incubator applying the deep learning prediction result information proposed in this paper was proven.

단백질 상호작용 네트워크를 이용한 기능성군 사이의 계층구조에 대한 연구

고영진,육순형,김엽 한국물리학회 2008 새물리 Vol.56 No.1

Detecting community structures and hierarchy among communities has been one of the most attractive research topics in complex network studies. In this study, we regard each protein as an oscillator that interacts with its neighboring proteins. The interaction between the proteins produces a complex network. First, we study the synchronizability of the proteins in the same functional classes of the protein-protein interaction network (PIN). In order to define the hierarchy among the functional classes based on the synchronizability of each functional class, we introduce a parameter $r_{link}$. Here, $r_{link}$ represents the fraction of all possible links whose end nodes are synchronized. Some possible relationships between the observed hierarchical structure of the functional classes and the properties of the PIN are also discussed. 각 노드들이 연결된 커뮤니티들 사이에서 커뮤니티 구조와 계층구조를 검출하는 것은 복잡계 네트워크 연구 분야에서 가장 흥미로운 연구 주제 중 하나 이다. 본 연구에서는 개별 단백질을 이웃하는 단백질과 상호작용하는 진동자로서 간주한다. 이러한 단백질들 사이의 상호작용은 복잡계 네트워크 (complex network)로 나타낼 수 있다. 본 논문에서 우리는 단백질 상호작용 네트워크 (protein interaction network)에서 기능성군 (functional class)들의 동기화에 대하여 알아보았다. 그리고 각각의 기능성군의 동기화를 바탕으로 기능성군 사이의 계층구조 (hierarchy)를 정의하기 위하여 매개변수 ${r}_{link}$를 도입하였다. 여기에서 ${r}_{link}$는 국소적 동기화의 정도를 나타내는 변수 이다. 이를 이용하여 단백질 상호작용 네트워크의 성질과 기능성군의 계층적인 구조사이의 관련성에 대하여 논의했다.

Visualizing Complex Supply Chain Network on RFID-based Environment by Using Clustering Approach in ProM Framework

Muhammad Rifqi Ma’arif(무하마드 리프키 마리프),Yong-Han Lee(이용한) 대한산업공학회 2013 대한산업공학회 춘계학술대회논문집 Vol.2013 No.5

Nowadays, the emergence of RFID technology can help the organization for collecting the information about the distribution of their commodities to satisfy the consumer demand. By aggregating the transaction (a pair of shipping and receiving event in RFID based supply chain) organization can capture the internal structure of their supply chain network. But, for supply network which consist of numerous stakeholders, the structure of supply chain network will be very complex and hard to understand. The complexity of supply chain network structure make a company fail to get valuable insight. If company fail to get an insight of their supply chain network they will fail to perform a quick and proper analysis that in turns will hampering them to improve their supply chain network. The main objective of this paper is to outlines some clustering approaches for presenting the complex supply network (specifically on the distribution channel level) in understandable form.

Visualizing Complex Supply Chain Network on RFID-based Environment by Using Clustering Approach in ProM Framework

Muhammad Rifqi Ma’arif(무하마드 리프키 마리프),Yong-Han Lee(이용한) 한국경영과학회 2013 한국경영과학회 학술대회논문집 Vol.2013 No.5

Nowadays, the emergence of RFID technology can help the organization for collecting the information about the distribution of their commodities to satisfy the consumer demand. By aggregating the transaction (a pair of shipping and receiving event in RFID based supply chain) organization can capture the internal structure of their supply chain network. But, for supply network which consist of numerous stakeholders, the structure of supply chain network will be very complex and hard to understand. The complexity of supply chain network structure make a company fail to get valuable insight. If company fail to get an insight of their supply chain network they will fail to perform a quick and proper analysis that in turns will hampering them to improve their supply chain network. The main objective of this paper is to outlines some clustering approaches for presenting the complex supply network (specifically on the distribution channel level) in understandable form.

복잡계 네트워크 기반 무선 네트워크를 위한 브로드캐스트 스케줄링 기법

박종홍 ( Jong-hong Park ),서순호 ( Sunho Seo ),정종문 ( Jong-moon Chung ) 한국인터넷정보학회 2016 인터넷정보학회논문지 Vol.17 No.5

본 논문에서는 복잡계 네트워크 이론에 기반한 무선 네트워크 토폴로지를 구성하고, 실제 환경의 토폴로지 구성을 반영한 척도없는 네트워크의 노드 링크 분포 확률을 분석하여 실제 무선 네트워크를 위한 브로드캐스트 전송 스케줄링 알고리즘 기법을 제안한다. 본 논문에서는 기존의 브로드캐스트 스케줄링 알고리즘 기법들이 반영하지 못한 복잡계 네트워크의 특성을 분석하고 그 특성에 맞는 알고리즘 기법과 분석 기법에 대하여 제안한다. 실험 결과를 통해 제안하는 방식의 알고리즘법이 네트워크의 지연시간 감소와 전송효율에 있어서의 우수함을 밝히고, 복잡계 네트워크 기반 무선 네트워크의 전송효율과 전체지연시간에 대한 최적화 방식의 기법을 제안한다. This paper proposes a novel broadcast scheduling algorithm for wireless large-scale networks based on theory of complex networks. In the proposed algorithm, the network topology is formed based on a scale-free network and the probability of link distribution is analyzed. In this paper, the characteristics of complex systems are analyzed (which are not concerned by the existing broadcast scheduling algorithm techniques) and the optimization of network transmission efficiency and network time delay are provided.

Exploring the Characteristics of High-Speed Rail and Air Transportation Networks in China: A Weighted Network Approach

Qingyu Qi,Oh Kyoung Kwon 인하대학교 정석물류통상연구원 2021 JOURNAL OF INTERNATIONAL LOGISTICS AND TRADE Vol.19 No.2

This study explores the characteristics of high-speed rail (HSR) and air transportation networks in China based on the weighted complex network approach. Previous related studies have largely implemented unweighted (binary) network analysis, or have constructed a weighted network, limited by unweighted centrality measures. This study applies weighted centrality measures (mean association [MA], triangle betweenness centrality [TBC], and weighted harmonic centrality [WHC]) to represent traffic dynamics in HSR and air transportation weighted networks, where nodes represent cities and links represent passenger traffic. The spatial distribution of centrality results is visualized by using ArcGIS 10.2. Moreover, we analyze the network robustness of HSR, air transportation, and multimodal networks by measuring weighted efficiency (WE) subjected to the highest weighted centrality node attacks. In the HSR network, centrality results show that cities with a higher MA are concentrated in the Yangtze River Delta and the Pearl River Delta; cities with a higher TBC are mostly provincial capitals or regional centers; and cities with a higher WHC are grouped in eastern and central regions. Furthermore, spatial differentiation of centrality results is found between HSR and air transportation networks. There is a little bit of difference in eastern cities; cities in the central region have complementary roles in HSR and air transportation networks, but air transport is still dominant in western cities. The robustness analysis results show that the multimodal network, which includes both airports and high-speed rail stations, has the best connectivity and shows robustness.

Evaluation of the resilience of air transportation network with adaptive capacity

Suhyung Yoo,여화수 서울시립대학교 도시과학연구원 2016 도시과학국제저널 Vol.20 No.2

Securing network resilience of air transportation system is essential to provide a stable level of service as one of major transport modes carrying international passengers and freights. In 2014, about 851 million passengers and 39 billion pounds of freights were delivered by over 9.5 million flights in the United States. As seen in Iceland volcano eruption in 2010, a deficiency of hub airports can bring a huge impact on the whole transport system and even on the world economy. So how the failure of individual node affects the overall network resilience is an important issue to study. Air transportation is known to be a scale-free network, which has few of hubs having high degree. So it is relatively robust against failure but vulnerable to targeted attack on a hub. There are numerous studies devoted to measure node vulnerability and evaluate network robustness; however, previous studies could not consider the node capacity for evaluating overall network performance. This study focuses on the network resilience, where the nodes are located in a real space and have a capacity to function. Using the data from Federal Aviation Administration, the simulation demonstrates and evaluates the resilience of the US air transportation network. This study proposes the indices of adaptative capacity for quantifying network resilience, which represent the ability of a network to replace an attacked node by other adjacent nodes. The simulation has two parts to measure the adaptive capacity of networks: under a single attack and a sustained attack. The results identify the susceptible nodes degrading the adaptive capacity of the network and evaluate each sub-network’s resilience in case of cascading node failures. Therefore, this study can help us to diagnose the vulnerable node and contribute the plan for improvement of network resilience.

글로벌 금융위기와 세계경제 거버넌스 변화: 복합네트워크론의 유용성과 한계

김치욱 세종연구소 2011 국가전략 Vol.17 No.2

The 2008 global financial crisis has arguably dealt a blow to the West's political economic leadership in the world, but boosted China and emerging economies up to the new powerhouses. Reshuffling the distribution of economic capabilities among major powers entails a more visible change in global economic governance. From the perspective of complex networks, this article analyzes the key characteristics of a new mode of economic governance. Such 'complex network governance' is a type of governance in which, along with traditional bilateral inter-state relationships, multistakeholders such as intergovernmental organizations and networks, and transnational networks share responsibility and authority. In particular, the G20, officially recognized as a focal point of world economic cooperation, has promoted a networked governance of world economy by functionally connecting the existing bilateral and multilateral, formal and informal, state actors. The G20 has some weaknesses as a facilitator of complex network governance in that it has allowed a very limited involvement of non-state actors and that its institutional sustainability is still shaky. Korea's economic diplomacy needs to focus on maximizing connectedness within the networks and utilizing the overlapped and embedded governance networks. 글로벌 금융위기 이후 서구의 정치경제적 지도력에 대한 회의론이 비등하고 경제력의 중심이 중국과 아시아 및 신흥시장으로 이동하면서 세계경제 거버넌스에 중요한 변화가 가시화되었다. 이 논문은 복합네트워크론의 시각으로 글로벌 경제 거버넌스의 주요 특징을 분석했다. 복합네트워크 거버넌스는 국민국가 간 양자관계뿐 아니라, 다자적인 차원에서 정부간 국제기구, 정부네트워크, 그리고 초정부 네트워크 등이 일정한 책임과 권한을 공유하는 시스템이다. 특히 세계경제협력의 초점으로 공인된 G20정상회의는 기존의 양자 및 다자, 공식 또는 비공식 국가 행위자들을 기능적 연결망으로 꿰면서 거버넌스의 복합네트워크화를 촉진했다. 다만, G20 프로세스는 시민사회 등 비국가행위자의 참여가 제한적이고 제도로서 지속가능성이 불확실하다는 점에서 복합네트워크의 촉진자로서 일정한 한계점을 지닌다. 정보화와 세계화의 흐름을 타고 가속화될 복합네트워크 시기의 한국 외교는 네트워크 내 연결성을 극대화하면서, 네트워크 간의 중첩성과 중복성을 최대한 활용하는 전략이 요구된다.