Earticle

Obtaining and applying information is considered as a critical task in the modern informationized society. Finding the one’s necessary information and processing it into a detailed knowledge are becoming more priortized in the enormous amount of information. Data modelling is the process that does not only reflect the demands of the user but the one that also facilitates the user's comprehension of the model itself. Ultimately, data modelling fully supports the processes that are requisite for the implementation of a data base and minimizes the alternations of the model during the development of applications.

It has been a huge amount of capacity of 10GB data base in a decade ago so far. Nowadays, however, 10TB is the common data base and even bigger capacities are available. So, new generation of Very Large Data Base (VLDB) has begun. Moving in to the new generation of VLDB has been caused major problems like backing up, restoring, and managing especially performance. It is very hard to export necessary data rapidly now due to the huge amount of data base. In the past, such kind of problems was out of the questions because of less data. As time goes on, however, optimization of performance became a big issue when the VLDB is common. Therefore, new professional technics are urgently required to maintain and optimize the data base that has become a VLDB or one that is in the progress of becoming one.

데이터는 살아 움직이고 있다. 10년 전만 해도 10GB 정도의 데이터라면 대용량 데이터라고 불리던 시절이 있었다. 하지만 지금은 10TB보다 큰 데이터베이스도 흔하다. 결국, 대용량 데이터베이스(VLDB)의 시대가 개막된 것이다. VLDB로 변한 데이터베이스에는 백업, 복구, 관리와 같은 문제점이 있지만 그 중에서도 성능 문제를 빼놓을 수 없다. 데이터베이스에 많은 데이터가 있고 그렇게 많은 데이터 중에서 필요한 몇 건의 데이터만 추출하는 것이 쉬운 일이 아니다. 과거에는 데이터가 적었기 때문에 이러한 것이 큰 문제가 아니었지만 이제는 VLDB가 되면서 성능 최적화는 일상적이고도 중요한 이슈가 되었다. 따라서 VLDB가 된 데이터베이스나 VLDB로 변하고 있는 데이터베이스에서 성능 관리를 하고 최적화할 수 있는 전문 기술이 필요하다.

본 논문에서는 제조업체의 공장자동화 환경을 클라우드 컴퓨팅의 SaaS 구축기술을 활용하여 전용 NC포스트프로세서를 웹 환경에서 서비스 받을 수 있도록 융합기술을 적용한 사례를 기술하였다. 개발된 WPS시스템은 기존 소프트웨어 개발방법론인 SPLE을 보완한 SCoD 방법론을 활용하여 안정되고 지속적인 시스템 서비스를 제공하도록 구현하였다. WPS는 범용의 NC포스트프로세서를 사용자 인터페이스와 프로세서 엔진으로 분리하여 각각의 사용자 PC와 클라우드 팜에 설치하고, 이 두 모듈을 네트워크로 연결하는 구조로 설계하였다. WPS는 철판절단 및 금형생산 공정 등에 활용할 수 있도록 현업에서 기능상의 테스트를 완료하였고, 사용자의 편의성을 개선하고 과금을 위한 모듈을 추가하는 등의 보완 작업을 거쳐 상용 서비스를 진행 중에 있다.

In this paper, we describe a case of utilizing SaaS technology to build NC Post -processor(WBS) based cloud computing. Developed WPS system was implemented to provide stable and continuous system service by utilizing SCoD methodology. WPS is designed user interface module and control engine module. The interface module is downloaded in a client PC and the control engine is installed in cloud parm area. These modules are connected with computer network. WPS was completed a function test for sheet cutting field and mold manufacturing field, and it is processing a commercial service using with improve the user's convenience and adding a bill charge module.

RFID/USN, are recognized as the new growth engines for the future, regardless of the advanced and developing countries. RFID, in particular, already entered practical stage by global companies. EPCIS, which is the one of the EPC golabal network components, makes a huge load on the system due to the large amount of entering data by following events. In this study, a data model developed based on ER-WIN by collecting four kind information that occurred in the EPC global networks. This model supports both in processing of high performance and huge capacity of data by a considerable storage capacity and input speed. A simulation was developed in order to verify the performance. Each model tested several times and results were compared.

In developing information systems, conceptual modeling is among the most fundamental means. The importance attributed to conceptual modeling has not only given rise to a lot of modeling methods, but also to the “yet another modeling approach (YAMA)" syndrome and the “not another modeling approach (NAMA)" hysteria. Criticism of conceptual modeling methods usually targets their lacking of theoretical foundations. In response to such criticism, various approaches towards theoretical foundations of conceptual modeling have been proposed so far. One of the recent responses to the Quest for theoretical foundations of conceptual modeling is the reference to the philosophical ontology. The currently most prominent of diverse approaches towards ontological foundations of conceptual mOdeling appears to be the BungeWand-Weber (BWW) ont이 ogy. Recent approaches attempt to regard BWW ontology as another conceptual data model as well as a criterion for evaluating various conceptual models. However, unfortunatelY, relatively few researches have been made on interoperability between the Entity-Relationship (ER) model , which is the most dominant conceptual data model, and ontology based model. In this paper, we investigate the interoperability between ontology and the ER model. In detail we (i) reclassify components of ER model with respect to ontology concepts, (ii) identify some components that cannot be directly represented in ontology notation, and (iii) present alternative representations to the components to aCQuire ontologically clear ER diagrams. Additionally, we (iv) present a set of mapping rules for converting the ontologically clear ER diagram into the corresponding ontology. In a case study, we show the process of converting an ER diagram for a concise Project Management System (PMS) into the ont이 ogically clear ER diagram and the corresponding ontology. We also describe an experiment that we undertook to test whether users understand the Ontologically-Clear ER diagram better.

Most of enterprises depend on a data modeler during developing their management information systems. In formulating business requirements for information systems, they widely and naturally use the interview method between a data modeler and a field worker. But, the discrepancy between both parties would certainly cause information loss and distortion that lead to let the systems not faithful to real business works. To improve or avoid modeler-dependant data modeling process, many automated data design CASE tools have been introduced. However, since most of traditional CASE tools just support drawing works for conceptual data design, a data modeler could not generate an ERD faithful to real business works and a user could not use them without any knowledge on database. Although some CASE tools supported conceptual data design, they still required too much preliminary database knowledge for a user. Against these traditional CASE tools, we proposed a Requirement-Oriented Entity Relationship Model for automated data design tool, called ROERM. Based on Non-Stop Methodology, ROERM adopts inner systematic modules for complete and sound ERD that is faithful to real field works, where modules are composed of interaction modules with a user, rules of schema operations and sentence translations. In addition to structure design of ROERM, we also devise detailed algorithms and perform an experiment for a case study.

Although some CASE tools supported conceptual data design, they required for users too much preliminary knowledge to learn how to use and handle them. In addition, in a number of studies on conceptual data design with natural language, they claimed passive participation for users with conforming to messages predefined by CASE tools. As an alternative to these traditional CASE tools, we proposed an ERD formulator for automated data design tool, called ERDF, so that even ordinary users, not necessarily data modeler, are capable of formulating ERD on business requirements by use of ERDF. We, first of all, introduced NSM as the standard methodology. We also designed the structure of ERDF including main controller, input controller, operation controller, regulation controller, schema controller, and output controller. We then defined conceptual domains and basic operations to lay down schema operations as well as sentence rules to handle input sentence in natural language. To get an ERD that is faithful to business requirements, we laid out supplementary design for dialogue and confirmation of soundness and completion.

Research in multi-dimensional magnetotelluric (MT) modeling and inversion, particularly within anisotropic media, is gaining substantial interest. One-dimensional (1-D) modeling is utilized as boundary conditions necessary for accurate 2-D or 3-D anisotropic modeling. Based on Maxwell’s equations and interface boundary conditions, we developed a new algorithm to calculate electromag- netic fields for both 1-D isotropic and anisotropic layered models. However, this algorithm encounters stability issues at considerable depths or within exceptionally thick layers. To address these challenges, we introduced two stabilization strategies. The first strategy alters the exponential terms in the plane-wave solutions to mitigate instabilities, while the second evaluates each layer’s contribution to numerical instability, replacing problematic thick layers with an infinite half-space. Through numerical tests on a four-layer anisotropic model, these strategies proved effective, ensuring stable computations of electromagnetic fields at any depth and in configurations with thick layers, thereby enhancing the model’s applicability for in-depth anisotropic analyses.

Purpose: The purpose of this study was to identify the supportive care needs of parents of preterm children in South Korea using text data from a portal site. Methods: In total, 628 online newspaper articles and 1,966 social network service posts published between January 1 and December 31, 2019 were analyzed. The procedures in this study were conducted in the following order: keyword selection, data collection, morpheme analysis, keyword analysis, and topic modeling. Results: The term "yirundung-yi", which is a native Korean word referring to premature infants, was confirmed to be a useful term for parents. The following four topics were identified as the supportive care needs of parents of preterm children: 1) a vague fear of caring for a baby upon imminent neonatal intensive care unit discharge, 2) real-world difficulties encountered while caring for preterm children, 3) concerns about growth and development problems, and 4) anxiety about possible complications. Conclusion: Supportive care interventions for parents of preterm children should include general parenting methods for babies. A team composed of multidisciplinary experts must support the individual growth and development of preterm children and manage the complications of prematurity using highly accessible media.

Data modeling in data warehousing is a multifaceted process crucial for effective data management and analysis. Through techniques like conceptual, logical, and physical modeling, data architects organize complex data structures. The iterative nature of modeling allows adaptation to evolving business needs. The analysis shows that most organizations used the hybrid approach to create the data modeling in the data warehouse because this approach helps to create a good and efficient model of data in the data warehouse. But on the other hand, when we talk about the anomalies, researchers used an isolation forest and an LSTM algorithm based on net earnings by month. This is the way that helps to remove maximum anomalies from the data warehouse during storing data from sources. In this era, mostly people use Big data concept for data model for data warehousing but this technique is much complex for storing data and retrieval of data in this technique just single thing is missed for the data modeling named as reusability in future working of big data if we majorly emphasize on reusability of data the this tech can be most efficient as compare to present.

Bankruptcy prediction has been studied to develop predictive models based on financial variables. Using only financial variables may be insufficient in bankruptcy prediction modeling because they do not reflect the latest information, essentially when using past corporate accounting information. Thus, exploiting qualitative information with quantitative information is required to supplement the limited accounting information. Among big data analytics techniques, text mining is used for processing qualitative information. In this study, we propose an integrated approach for bankruptcy prediction using market sentiment extracted from economic news as qualitative information and financial variables as quantitative information for bankruptcy prediction. Unlike previous sentiment analysis approaches, consideration of topics extracted from economic news in sentiment analysis is included to mitigate the ambiguity of capturing the sentiment for single terms. This study validates the effectiveness of incorporating topic-based market sentiment into the conventional bankruptcy prediction model using financial variables in terms of predictive performance.