• 제목/요약/키워드: Network transformation

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e-Transformation Strategy : From EDI to Web-based e-Business Standard Framework

  • Kim, Min-Soo;Kim, Dong-Soo;Kim, Hoon-Tae;Yoon, Jung-Hee
    • 한국전자거래학회:학술대회논문집
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    • 한국전자거래학회 2005년도 e-Biz World Conference 2005
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    • pp.149-154
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    • 2005
  • Recently, lots of EDI-VAN (Electronic Data Interchange-Value Added Network) companies challenge to convert their business systems into Web-based e-business frameworks to avoid high cost and closed structure of EDI system. This research proposes e-Transformation strategies for EDI-VAN companies to adopt Web-based e-business standard frameworks such as ebXML (e-business using XML) and RosettaNet. Four migration strategies for EDI companies are presented, and their properties are described in detail. Transformation procedures of two representative strategies are also provided fur the convenience of medium-sized companies. The result of this work can be used as a practical guideline for EDI companies to develop there own transformation strategy suitable to its scale and capability, while minimizing the impacts on the pre-existing business processes.

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스파이킹 신경망 추론을 위한 심층 신경망 가중치 변환 (Deep Neural Network Weight Transformation for Spiking Neural Network Inference)

  • 이정수;허준영
    • 스마트미디어저널
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    • 제11권3호
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    • pp.26-30
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    • 2022
  • 스파이킹 신경망은 실제 두뇌 뉴런의 작동원리를 적용한 신경망으로, 뉴런의 생물학적 메커니즘으로 인해 기존 신경망보다 학습과 추론에 소모되는 전력이 적다. 최근 딥러닝 모델이 거대해지며 운용에 소모되는 비용 또한 기하급수적으로 증가함에 따라 스파이킹 신경망은 합성곱, 순환 신경망을 잇는 3세대 신경망으로 주목받으며 관련 연구가 활발히 진행되고 있다. 그러나 스파이킹 신경망 모델을 산업에 적용하기 위해서는 아직 선행되어야 할 연구가 많이 남아있고, 새로운 모델을 적용하기 위한 모델 재학습 문제 역시 해결해야 한다. 본 논문에서는 기존의 학습된 딥러닝 모델의 가중치를 추출하여 스파이킹 신경망 모델의 가중치로 변환하는 것으로 모델 재학습 비용을 최소화하는 방법을 제안한다. 또한, 변환된 가중치를 사용한 추론 결과와 기존 모델의 결과를 비교해 가중치 변환이 올바르게 작동함을 보인다.

유전 알고리즘에서의 자기 조직화 신경망의 활용 (New Usage of SOM for Genetic Algorithm)

  • 김정환;문병로
    • 한국정보과학회논문지:소프트웨어및응용
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    • 제33권4호
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    • pp.440-448
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    • 2006
  • 자기 조직화 신경망 (SOM: Self-Organizing Map)은 자율 학습 신경망으로 사전 지식이 존재하지 않는 자료에 존재하는 구조적 관계성을 보전하는데 이용된다. 자기 조직화 신경망은 벡터 양자화, 조합 최적화, 패턴 인식과 같은 복잡한 문제 해결을 위한 연구에 많이 이용되어 왔다. 이 논문에서는 좀더 효율적인 유전 알고리즘을 얻기 위한 스키마 변환 도구로서 자기 조직화 신경망을 이용하는 새로운 사용법에 대해서 제안한다. 즉, 각 자식해는 탐색 공간에서 좀더 바람직한 모양을 가지는 동질의 인공 신경망으로 변환된다. 이 변환으로 인해 강한 상위(epistasis)를 가지는 유전자들은 염색체 상에서 서로 인접하게 되는 것이다. 실험 결과는 기존 결과에 비해서 주목할만한 성능 개선이 있음을 보여준다.

Multi-Sided Networks of Digital Platform Ecosystem: The Case of Ride-Hailing in Indonesia

  • Mohammad Nabil Almunawar;Muhammad Anshari
    • Asia pacific journal of information systems
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    • 제30권4호
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    • pp.808-831
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    • 2020
  • The business world has been undergoing a digital transformation. The adoption of multi-sided digital platform across the world has sped up this transformation. Multi-sided digital platforms create value by mediating interactions and transactions of distinct groups of users. A platform and its stakeholders need to be considered as a business ecosystem. Elements or components in the ecosystem exchange values and together form a network of exchange values. The objective of this paper is to construct a framework for crafting and observing digital business ecosystems. The foundation theories used to construct the framework are transaction cost economy (TCE), multi-sided markets, and value network. This paper uses Go-Jek, a growing ride-hailing platform from Indonesia, as a case to discuss how the framework works in mapping Go-Jek's digital business ecosystem, and then explain its expansion strategy. This paper has both theoretical and managerial contributions. It provides a formal definition of digital business ecosystems as a network of exchange values. The framework does not only help studies the existing business ecosystems but also can be used to craft a new business ecosystem. It can also be used to study value exchanges within the ecosystem, assessing or crafting ecosystem expansion strategies.

Identifying Factors Increasing and Decreasing Economic Resilience During COVID-19 Crisis

  • Zakharov, Vladimir Yakovlevich;Ludushkina, Elena Nikolaevna;Kornilova, Elena Valerievna;Kislinskaya, Marina Vladimirovna;Brykalov, Sergei Mikhailovich
    • International Journal of Computer Science & Network Security
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    • 제22권7호
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    • pp.181-190
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    • 2022
  • The article contains an overview of the results of recent research by think tanks in different countries, devoted to the analysis of economic resilience factors in the Covid-19 crisis and the development of recommendations for improving preparedness for the next crises. The authors consider and propose a theoretical framework for the concept of the resilience of economic systems. The impact of the COVID-19 crisis on national economies is analyzed. Factors explaining the different cability of economic systems to withstand shock in the short and long term are identified. The reactions of market participants and national governments to the crisis are assessed. It is shown how the COVID-19 crisis has affected the digital transformation of economic systems, and how digital transformation helps to increase the resilience of national economies so that the latter can emerge from the crisis even stronger.

Impact of Digitalization On the Banking System Transformation

  • Shcherbatykh, Denis;Shpileva, Vira;Riabokin, Maryna;Zham, Olena;Zalizniuk, Viktoriia
    • International Journal of Computer Science & Network Security
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    • 제21권12spc호
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    • pp.513-520
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    • 2021
  • The purpose of the article is to study the impact of digitalization on the transformation of the banking system, taking into account current innovative development trends. The article analyzes the impact of key factors on the development of the digital economy. Ukraine's ranking positions in terms of digital competitiveness are shown. The necessity of using digital technologies in the sphere of banking activity is substantiated. The dynamics of changes in the number of operating banks in Ukraine is analyzed. The directions of introduction of information technologies in the sphere of banking activity are determined. An analysis of changes in the share of the population of individual EU member states that use the Internet for Internet banking. It is noted that modern transformation trends, digitalization of the economy have a significant impact on the landscape of the banking sector, in this context, the rating of Ukrainian banks in the categories of "Internet Banking" and "Mobile Banking". The advantages and disadvantages of using the capabilities of Internet banking are identified. Based on the study, the importance of expanding the boundaries of digitalization of the domestic banking system is substantiated, which will further increase the level of availability of online services in the field of banking. Prospects for further research are identified in the study of the impact of digitalization on the development of the banking system of foreign countries.

Political and Legal Aspects of the Transformation of the Content and Forms of Education Under the Pressure of the Pandemic

  • Serhieiev, Viacheslav;Zahurska-Antoniuk, Viktoriia;Kobetiak, Andrii;Yemelianov, Roman;Tohobytska, Violeta
    • International Journal of Computer Science & Network Security
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    • 제22권10호
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    • pp.131-136
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    • 2022
  • The main purpose of the article is to study the legal aspects of the transformation of the content and forms of education under the pressure of the pandemic. The global COVID-19 pandemic that began in 2020 exacerbated the global economic and social crisis and revealed new social problems that need to be addressed urgently. First of all, these are problems in the field of human health, problems of medicine and its financing, psychological problems caused by the total restriction of social contacts of people, problems of suicides, aggressive behavior, intolerance, violence and many other social problems. It would seem that the problems of education are not relevant today. But we cannot agree with this. A number of theoretical methods of analysis were applied during the study. Based on the results of the study, key legal aspects of the transformation of the content and forms of education under the pressure of the pandemic were identified.

Impact on Requirement Elicitation Process when Transforming Software from Product Model to a Service Model

  • Sameen Fatima;Amna Anwer;Adil Tareen
    • International Journal of Computer Science & Network Security
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    • 제23권8호
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    • pp.199-203
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    • 2023
  • Influential trend that widely reflected the software engineering industry is service oriented architecture. Vendors are migrating towards cloud environment to benefit their organization. Companies usually offer products and services with a goal to solve problems at customer end. Because customers are more interested in solution of their problem rather than focusing on products or services. In software industry the approach in which customers' problems are solved by providing services is known as software as a service. However, software development life cycle encounters enormous changes when migrating software from product model to service model. Enough research has been done on the overall development process but a limited work has been done on the factors that influence requirements elicitation process. This paper focuses on those changes that influence requirement elicitation process and proposes a systematic methodology for transformation of software from product to service model in a successful manner. The paper then elaborates the benefits that inherently come along with elicitation process in cloud environment. The paper also describes the problems during transformation. The paper concludes that requirement engineering process turn out to be more profitable after transformation of traditional software from product to service model.

Natural vibration analysis of diagonal networks

  • Chai, W.S.;Li, Y.;Chan, H.C.
    • Structural Engineering and Mechanics
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    • 제6권5호
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    • pp.517-527
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    • 1998
  • This paper describes an exact method of analysis for natural vibration of diagonal networks by considering an equivalent cyclic periodic structure and adopting the double U-transformation technique. Both a lumped mass system and a distributed mass system are considered to investigate the diagonal networks. The exact solution for the frequency equations and the natural modes of the networks can be derived. As numerical examples, square diagonal cable networks with different meshes are worked out.

COMPARISON OF VARIABLE SELECTION AND STRUCTURAL SPECIFICATION BETWEEN REGRESSION AND NEURAL NETWORK MODELS FOR HOUSEHOLD VEHICULAR TRIP FORECASTING

  • Yi, Jun-Sub
    • Journal of applied mathematics & informatics
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    • 제6권2호
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    • pp.599-609
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    • 1999
  • Neural networks are explored as an alternative to a regres-sion model for prediction of the number of daily household vehicular trips. This study focuses on contrasting a neural network model with a regression model in term of variable selection as well as the appli-cation of these models for prediction of extreme observations, The differences in the models regarding data transformation variable selec-tion and multicollinearity are considered. The results indicate that the neural network model is a viable alternative to the regression model for addressing both messy data problems and limitation in variable structure specification.