• Journal of the Korea Institute of Information Security & Cryptology
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• v.31 no.4
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• pp.731-751
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• 2021

The Internet of Things is a huge group of devices communicating each other and the interconnection of objects in the network is a basic requirement. Choosing a reliable device is critical because malicious devices can compromise networks and services. However, it is difficult to create a trust management model due to the mobility and resource constraints of IoT devices. For the centralized approach, there are issues of single point of failure and resource expansion and for the distributed approach, it allows to expand network without additional equipment by interconnecting each other, but it has limitations in data exchange and storage with limited resources and is difficult to ensure consistency. Recently, trust management models using fog nodes and blockchain have been proposed. However, blockchain has problems of low throughput and delay. Therefore, in this paper, a trust management model for selecting reliable devices in a fog-based IoT environment is proposed by applying IOTA, a blockchain technology for the Internet of Things. In this model, Directed Acyclic Graph-based ledger structure manages trust data without falsification and improves the low throughput and scalability problems of blockchain.

• Journal of Korea Society of Industrial Information Systems
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• v.27 no.6
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• pp.41-49
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• 2022

The Internet Engineering Task Force (IETF) has standardized RPL (IPv6 Routing Protocol for Low-power Lossy Network) as a routing protocol for Low Power and Lossy Networks (LLNs), a low power loss network environment. RPL creates a route through an Objective Function (OF) suitable for the service required by LLNs and builds a Destination Oriented Directed Acyclic Graph (DODAG). Existing studies check the residual energy of each node and select a parent with the highest residual energy to build a DODAG, but the energy exhaustion of the parent can not avoid the network disconnection of the children nodes. Therefore, this paper proposes EC-RPL (Enhanced Connectivity-RPL), in which ta node leaves DODAG in advance when the remaining energy of the node falls below the specified energy threshold. The proposed protocol is implemented in Contiki, an open-source IoT operating system, and its performance is evaluated in Cooja simulator, and the number of control messages is compared using Foren6. Experimental results show that EC-RPL has 6.9% lower latency and 5.8% fewer control messages than the existing RPL, and the packet delivery rate is 1.7% higher.

• KIPS Transactions on Software and Data Engineering
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• v.2 no.5
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• pp.359-368
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• 2013

Mashup is a web application that combines several different sources to create new services using Open APIs(Application Program Interfaces). Although the mashup has become very popular over the last few years, there are several challenging issues when combining a large number of APIs into the mashup, especially when composite APIs are manually integrated by mashup developers. This paper proposes a novel algorithm for automatic Open API composition. The proposed algorithm consists of constructing an operation connecting graph and searching composition candidates. We construct an operation connecting graph which is based on the semantic similarity between the inputs and the outputs of Open APIs. We generate directed acyclic graphs (DAGs) that can produce the output satisfying the desired goal. In order to produce the DAGs efficiently, we rapidly filter out APIs that are not useful for the composition. The algorithm is evaluated using a collection of REST and SOAP APIs extracted from ProgrammableWeb.com.

• Proceedings of the Korea Information Processing Society Conference
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• 2006.05a
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• pp.35-38
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• 2006

데이터 웨어하우스에서는 OLAP(On-Line Analytical Processing) 연산을 제공하기 위해 다차원 데이터를 큐브의 형태로 관리한다. 특히, 공간 차원과 같이 데이터 큐브의 차원에 개념 계층이 존재하는 경우 사용자는 특정 계층에 대한 집계 결과를 요구한다. 기조의 데이터 큐브의 구조들은 차원의 개념 계층을 지원하지 못하거나 지원하더라도 시간이나 공간적 비용에 대해 비효율적이다. 본 논문에서는 공간 데이터 웨어하우스에서 공간 개념 계층을 이용하여 효율적인 계층별 영역 집계연산을 지원하는 공간 데이터 큐브를 제안한다. 이는 개념 계층을 DAG(Directed Acyclic Graph) 형태로 표현하여 구성된 여러 개의 차원들을 공간차원의 지역성을 기준으로 연결한 구조이다. 이러한 구조를 갖는 큐브를 이용하면, 데이터 검색 시 상위 계층부터 아래 방향으로 탐색하기 때문에 각 차원에 대한 효율적인 검색이 가능하다. 특히, 공간 개념 계층에 대한 DAG를 이용하면, 공간적 지역성에 따른 영역 검색을 지원할 수 있다. 성능평가에서 개념 계층이 적용된 질의에 대한 실험을 통해 제안 기법이 기존 기법들에 비해 저장 공간 효율성 및 질의 응답 성능이 우수함을 증명한다.

• Journal of the Korea Society of Computer and Information
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• v.12 no.6
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• pp.105-113
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• 2007

A gene regulatory network is a network of genes representing how genes influence the activities of other genes. Nowadays from microarray experiments, a large number of measurements on the expression levels of genes are available. One of typical data is the so-called "steady-state model" data measuring the expression levels of other genes after knocking out a particular gene. This paper shows how to reverse engineer a parsimonious gene regulatory network, using these measurement data. Our model considers auto-regulation, which forms a cycle in a genetic network. We also model repressor and enhancer roles of genes. which are not considered in previous known methods.

• Annual Conference on Human and Language Technology
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• 1994.11a
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• pp.217-222
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• 1994

한글 글꼴을 새롭게 만들려면 지금까지는 기본 글자인 자소를 디자인하든지 아니면 완성된 글자 전체를 디자인해야 했다. 조합형의 글자디자인의 경우, 전체 글자가 아니라 부분적인 한글 전자사전은 많은 양의 데이타를 저장할 수 있어야 하며, 빠른 검색 속도를 제공해야 한다. 기존의 트라이는 공통접두사만을 압축하기 때문에 사전의 크기가 방대하다는 단점이 있다. 본 논문에서는 DAWG(Directed Acyclic Word Graph)를 이용하여 공통접미사까지 압축하였고, 검색과 기억장소의 효율을 위하여, 링크드리스트 구조의 DAWG를 유형별 배열 구조로 바꾸었다. 전국의 각 학교 이름들을 대상으로 실험한 결과, 본 논문에서 제안한 DAWG를 이용한 배열 구조의 사전은 트라이와 비교하여 볼 때, 검색 연산의 성능은 동일하게 유지하면서 기억 장소의 효율과 압축율에서 효과적이었다. 또한, 트라이보다 주기억장치와 보조기억장치와의 블록 입출력횟수를 줄임으로써 전체 검색 시간을 낮출 수 있었다.소를 디자인하기 때문에 전체 글자의 모양이 좋지 않다는 단점이 있었고 완성형의 경우 완성된 글자 전체를 모두 디자인해야하는 단점이 있었다. 본 논문에서는 한글 글꼴 개발의 한 방법으로 제한된 글자의 디자인에 의한 전체 글꼴 생성에 관한 한 방법을 제시한다. 이 방법은 표준으로 설정된 몇 글자를 디자인하면 그 글자를 분석하여 자소들을 위한 글꼴 화일이 만들어지고 자소 글꼴 화일로부터 다른 모든 글자를 만들어 낸다.

• Industrial Engineering and Management Systems
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• v.9 no.2
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• pp.141-156
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• 2010

Despite all attempts to prevent fraud, it continues to be a major threat to industry and government. Traditionally, organizations have focused on fraud prevention rather than detection, to combat fraud. In this paper we present a role mining inspired approach to represent user behaviour in Enterprise Resource Planning (ERP) systems, primarily aimed at detecting opportunities to commit fraud or potentially suspicious activities. We have adapted an approach which uses set theory to create transaction profiles based on analysis of user activity records. Based on these transaction profiles, we propose a set of (1) anomaly types to detect potentially suspicious user behaviour, and (2) scenarios to identify inadequate segregation of duties in an ERP environment. In addition, we present two algorithms to construct a directed acyclic graph to represent relationships between transaction profiles. Experiments were conducted using a real dataset obtained from a teaching environment and a demonstration dataset, both using SAP R/3, presently the predominant ERP system. The results of this empirical research demonstrate the effectiveness of the proposed approach.

• Genomics & Informatics
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• v.7 no.2
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• pp.122-130
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• 2009

A systems biology approach for the identification of perturbed molecular functions is required to understand the complex progressive disease such as breast cancer. In this study, we analyze the microarray data with Gene Ontology terms of molecular functions to select perturbed molecular functional modules in breast cancer tissues based on the definition of Gene ontology Functional Code. The Gene Ontology is three structured vocabularies describing genes and its products in terms of their associated biological processes, cellular components and molecular functions. The Gene Ontology is hierarchically classified as a directed acyclic graph. However, it is difficult to visualize Gene Ontology as a directed tree since a Gene Ontology term may have more than one parent by providing multiple paths from the root. Therefore, we applied the definition of Gene Ontology codes by defining one or more GO code(s) to each GO term to visualize the hierarchical classification of GO terms as a network. The selected molecular functions could be considered as perturbed molecular functional modules that putatively contributes to the progression of disease. We evaluated the method by analyzing microarray dataset of breast cancer tissues; i.e., normal and invasive breast cancer tissues. Based on the integration approach, we selected several interesting perturbed molecular functions that are implicated in the progression of breast cancers. Moreover, these selected molecular functions include several known breast cancer-related genes. It is concluded from this study that the present strategy is capable of selecting perturbed molecular functions that putatively play roles in the progression of diseases and provides an improved interpretability of GO terms based on the definition of Gene Ontology codes.

• Journal of Aerospace System Engineering
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• v.18 no.2
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• pp.1-11
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• 2024

This paper applies a relative impact angle control guidance law to a communication-based multi-missile network system with uncertainties and disturbances. The multi-missile network system is represented as a transitive reduction directed acyclic graph. Furthermore, this paper introduces both centralized and decentralized guidance laws based on the graph's structure. The relationship between these guidance laws is analyzed by comparing them based on the communication structure and the presence of system noise. To analyze the effects of decentralized optimal cooperative guidance law, this paper assumes uncertainty in missile dynamics and predicted impact point information for the relative impact angle control mission. Monte Carlo simulations are conducted for various mission environments to analyze the impact of communication and its structure on the system.

• The Journal of Society for e-Business Studies
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• v.20 no.4
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• pp.61-76
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• 2015

In general, we have utilized the hierarchical concept tree as a crucial data structure for indexing huge amount of textual data. This paper proposes a generality rank-based method that can automatically develop hierarchical concept structures with the Wikipedia data. The goal of the method is to regard each of Wikipedia articles as a concept and to generate hierarchical relationships among concepts. In order to estimate the generality of concepts, we have devised a special ranking function that mainly uses the number of hyperlinks among Wikipedia articles. The ranking function is effectively used for computing the probabilistic subsumption among concepts, which allows to generate relatively more stable hierarchical structures. Eventually, a set of concept pairs with hierarchical relationship is visualized as a DAG (directed acyclic graph). Through the empirical analysis using the concept hierarchy of Open Directory Project, we proved that the proposed method outperforms a representative baseline method and it can automatically extract concept hierarchies with high accuracy.