• Proceedings of the Korea Society of Design Studies Conference
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• 한국디자인학회 2005년도 추계 학술발표대회 논문집
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• pp.16-17
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• 2005

• The KIPS Transactions:PartA
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• 제12A권5호
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• pp.451-460
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• 2005

We present a methodology to design energy-efficient data paths using FPGAs. Our methodology integrates domain specific modeling, coarse-grained performance evaluation, design space exploration, and low-level simulation to understand the tradeoffs between energy, latency, and area. The domain specific modeling technique defines a high-level model by identifying various components and parameters specific to a domain that affect the system-wide energy dissipation. A domain is a family of architectures and corresponding algorithms for a given application kernel. The high-level model also consists of functions for estimating energy, latency, and area that facilitate tradeoff analysis. Design space exploration(DSE) analyzes the design space defined by the domain and selects a set of designs. Low-level simulations are used for accurate performance estimation for the designs selected by the DSE and also for final design selection We illustrate our methodology using a family of architectures and algorithms for matrix multiplication. The designs identified by our methodology demonstrate tradeoffs among energy, latency, and area. We compare our designs with a vendor specified matrix multiplication kernel to demonstrate the effectiveness of our methodology. To illustrate the effectiveness of our methodology, we used average power density(E/AT), energy/(area x latency), as themetric for comparison. For various problem sizes, designs obtained using our methodology are on average $25\%$ superior with respect to the E/AT performance metric, compared with the state-of-the-art designs by Xilinx. We also discuss the implementation of our methodology using the MILAN framework.

• Journal of the Microelectronics and Packaging Society
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• 제20권4호
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• pp.75-79
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• 2013

A power distribution network (PDN) is a network that provides connection between the voltage source supply and the power/ground terminals of a microprocessor chip. It consists of a voltage regulator module, a printed circuit board, a package substrate, a microprocessor chip as well as decoupling capacitors. For power integrity analysis, the board and package layouts have to be transformed into an electrical network of resistor, inductor and capacitor components which may be expressed using the S-parameters models. This modeling process generally takes from several hours up to a few days for a complete board or package layout. When the board and package layouts change, they need to be re-extracted and the S-parameters models also need to be re-generated for power integrity assessment. This not only consumes a lot of resources such as time and manpower, the task of PDN modeling is also tedious and mundane. In this paper, a block-based PDN modeling is proposed. Here, the board or package layout is partitioned into sub-blocks and each of them is modeled independently. In the event of a change in power rails routing, only the affected sub-blocks will be reextracted and re-modeled. Simulation results show that the proposed block-based PDN modeling not only can save at least 75% of processing time but it can, at the same time, keep the modeling accuracy on par with the traditional PDN modeling methodology.

• International Journal of Computer Science & Network Security
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• 제21권9호
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• pp.247-260
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• 2021

Data modeling is a process of developing a model to design and develop a data system that supports an organization's various business processes. A conceptual data model represents a technology-independent specification of structure of data to be stored within a database. The model aims to provide richer expressiveness and incorporate a set of semantics to (a) support the design, control, and integrity parts of the data stored in data management structures and (b) coordinate the viewing of connections and ideas on a database. The described structure of the data is often represented in an entity–relationship (ER) model, which was one of the first data-modeling techniques and is likely to continue to be a popular way of characterizing entity classes, attributes, and relationships. This paper attempts to examine the basic ER modeling notions in order to analyze the concepts to which they refer as well as ways to represent them. In such a mission, we apply a new modeling methodology (thinging machine; TM) to ER in terms of its fundamental building constructs, representation entities, relationships, and attributes. The goal of this venture is to further the understanding of data models and enrich their semantics. Three specific contributions to modeling in this context are incorporated: (a) using the TM model's five generic actions to inject processing in the ER structure; (b) relating the single ontological element of TM modeling (i.e., a thing/machine or thimac) to ER entities and relationships; and (c) proposing a high-level integrated, extended ER model that includes structural and time-oriented notions (e.g., events or behavior).

• Information Systems Review
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• 제4권2호
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• pp.209-222
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• 2002

EDI (Electronic Data Interchange) has been widely utilized to support Business Activities since it has such advantages as fast transfer of information, less documentation work, efficient information exchange etc. Recently e-business environment has urged the traditional EDI system to be changed to ebXML framework. To apply the ebXML framework to a certain industry, it is required to implement Business Process (BP), Core Component (CC), Collaboration Protocol Profile (CPP), Collaboration Protocol Agreement (CPA), Messaging system etc. We have selected the port and logistics industry as a target domain to apply ebXML framework, since the EDI usage ratio of it is relatively higher than other industries. In this paper, we have analyzed the current status of EDI system and transaction processes in the port and logistics industry. We have defined the business process that will be registered in the registry/repository, the main component of ebXML framework, using UN/CEFACT modeling methodology. And Business Collaborations, Business Transactions, Business Document Flows, Choreography, Pattern, etc. are represented using UML according to UN/ CEFACT modeling methodology, to apply ebXML Framework to the port and logistics distribution industry. Also we have suggested the meta methodology for applying the ebXML framework to other industries.

• Journal of the Korea Society for Simulation
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• 제18권4호
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• pp.127-136
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• 2009

Modeling and Simulation, especially in mobile ad hoc network(MANET), are the most effective way to analyze performance or optimize system parameters without establishing real network environment. Focusing mainly on overall network behaviors in MANET concerns dynamics of network transport operations, which can efficiently be characterized with event based system states rather than execution details of protocols. We thus consider the network as a discrete event system to analyze dynamics of network transport performance. Zeigler's set-theoretic DEVS(Discrete Event Systems Specification) formalism can support specification of a discrete event system in hierarchical, modular manner. The DEVSim++ simulation environment can not only provide a rigorous modeling methodology based on the DEVS formalism but also support modelers to develop discrete event models using the hierarchical composition methodology in object-orientation. This environment however hardly supports to specify connection paths of network nodes, which are continuously altered due to mobility of nodes. This paper proposes a DEVS-based modeling and simulation methodology of enabling node mobility, and develops DEVS models for the mobile ad hoc network. We also simulate developed models with the DEVSim++ engine to verify the proposal.

• Journal of Intelligence and Information Systems
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• 제28권1호
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• pp.131-154
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• 2022

Recently, researches on unstructured data analysis have been actively conducted with the development of information and communication technology. In particular, topic modeling is a representative technique for discovering core topics from massive text data. In the early stages of topic modeling, most studies focused only on topic discovery. As the topic modeling field matured, studies on the change of the topic according to the change of time began to be carried out. Accordingly, interest in dynamic topic modeling that handle changes in keywords constituting the topic is also increasing. Dynamic topic modeling identifies major topics from the data of the initial period and manages the change and flow of topics in a way that utilizes topic information of the previous period to derive further topics in subsequent periods. However, it is very difficult to understand and interpret the results of dynamic topic modeling. The results of traditional dynamic topic modeling simply reveal changes in keywords and their rankings. However, this information is insufficient to represent how the meaning of the topic has changed. Therefore, in this study, we propose a method to visualize topics by period by reflecting the meaning of keywords in each topic. In addition, we propose a method that can intuitively interpret changes in topics and relationships between or among topics. The detailed method of visualizing topics by period is as follows. In the first step, dynamic topic modeling is implemented to derive the top keywords of each period and their weight from text data. In the second step, we derive vectors of top keywords of each topic from the pre-trained word embedding model. Then, we perform dimension reduction for the extracted vectors. Then, we formulate a semantic vector of each topic by calculating weight sum of keywords in each vector using topic weight of each keyword. In the third step, we visualize the semantic vector of each topic using matplotlib, and analyze the relationship between or among the topics based on the visualized result. The change of topic can be interpreted in the following manners. From the result of dynamic topic modeling, we identify rising top 5 keywords and descending top 5 keywords for each period to show the change of the topic. Existing many topic visualization studies usually visualize keywords of each topic, but our approach proposed in this study differs from previous studies in that it attempts to visualize each topic itself. To evaluate the practical applicability of the proposed methodology, we performed an experiment on 1,847 abstracts of artificial intelligence-related papers. The experiment was performed by dividing abstracts of artificial intelligence-related papers into three periods (2016-2017, 2018-2019, 2020-2021). We selected seven topics based on the consistency score, and utilized the pre-trained word embedding model of Word2vec trained with 'Wikipedia', an Internet encyclopedia. Based on the proposed methodology, we generated a semantic vector for each topic. Through this, by reflecting the meaning of keywords, we visualized and interpreted the themes by period. Through these experiments, we confirmed that the rising and descending of the topic weight of a keyword can be usefully used to interpret the semantic change of the corresponding topic and to grasp the relationship among topics. In this study, to overcome the limitations of dynamic topic modeling results, we used word embedding and dimension reduction techniques to visualize topics by era. The results of this study are meaningful in that they broadened the scope of topic understanding through the visualization of dynamic topic modeling results. In addition, the academic contribution can be acknowledged in that it laid the foundation for follow-up studies using various word embeddings and dimensionality reduction techniques to improve the performance of the proposed methodology.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 한국항해항만학회 2001년도 Proceeding of KIN-CIN Joint Symposium 2001 on Satellite Navigation/AIS, lntelligence , Computer Based Marine Simulation System and VDR
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• pp.89-99
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• 2001

Optimum Ship Routing can be defined as “The selection of an optimum track for a transoceanic crossing by the application of long-range predictions of wind, waves and currents to the knowledge of how the routed vessel reacts to these variables”. This paper treats the methodology how to serve optimum ship routing problem by network modeling and reveals the validity of the network model by some numerical experiments.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 한국퍼지및지능시스템학회 1998년도 The Third Asian Fuzzy Systems Symposium
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• pp.634-639
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• 1998

A methodology based on the concept of variable string length GA(VGA) is developed for determining automatically the number of hyperplanes and their appropriate arrangement for modeling the class boundaries of a given training data set in RN. The genetic operators and fitness functionare newly defined to take care of the variability in chromosome length. Experimental results on different artificial and real life data sets are provided.

• 한국IT서비스학회:학술대회논문집
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• 한국IT서비스학회 2007년도 추계학술대회
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• pp.413-418
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• 2007

국내 외 많은 컨설팅 및 SI회사들이 나름대로의 SOA방법론을 개발 및 적응하고 있다. 하지만 각 회사의 방법론 마다, SOA 사상 관점에 따라 접근 방향이 상이하고, 수행 방법과 태스크 또한 실제 적응하기에는 상세성이 부족하다. 이 연구에서는 국내 외 SOA 방법론을 비교 분석하고, 실제 적응된 사례를 통하여 특정 도메인에 무관한 현업 사용자 위주의 서비스 식별이라는 명제를 반영한 유저인터페이스 기반의 서비스 분석 및 모델링 방법론을 제시한다.