• Photonics industry news
• /
• s.1
• /
• pp.18-21
• /
• 2000

• Proceedings of the Korean Information Science Society Conference
• /
• 2007.06b
• /
• pp.138-142
• /
• 2007

컴포넌트 기반 개발 방법론이 지향하는 목표는 독립적으로 개발된 컴포넌트들을 소스 수정 없이 바이너리 형태로 조립하여 소프트웨어를 개발하는 것이다. 그러나 기존 컴포넌트 모델 기반으로 개발된 컴포넌트들은 자신이 제공하는 서비스에 대해서는 그 사용계약을 독자적인 인터페이스를 통하여 정의하는 반면, 하위 컴포넌트와의 연동은 하위 컴포넌트가 정의한 인터페이스에 따르는 코딩을 통해 이루어진다. 이러한 컴포넌트 모델들은 다계층 구조로 개발되고 있는 현대 엔터프라이즈 정보시스템에서 상위 컴포넌트들이 하위 컴포넌트가 정의한 인터페이스에 정적으로 단단히 결합되는 문제점을 갖고 있다. 따라서 하위 컴포넌트에 의존하지 않는 간단한 GUI용 컴포넌트들만 재사용되고 비즈니스 논리를 처리하는 중간 계층 컴포넌트들의 재사용율은 지극히 낮은 실정이다. 본 논문은 하위 컴포넌트가 정의한 인터페이스 규격에 따르는 대신 독자적으로 호출규격을 정의하여 사용하고 이에 대한 메타데이터를 공개함으로써 독립적으로 개발된 바이너리 컴포넌트들간의 연동을 보장하는 새로운 컴포넌트 모델을 제안하고 이 모델에 따라 개발된 컴포넌트들을 조립하는 방법을 제안하였다. 또한 이들을 구현함으로써 이미 개발된 컴포넌트를 실제 소스 수정 없이 바이너리 코드 형태로 조립 가능한 것을 증명하였다.

• Journal of KIISE:Software and Applications
• /
• v.36 no.5
• /
• pp.386-395
• /
• 2009

Business entities with which most service components interact are kind of cross-cutting concerns in a multi-layered distributed application architecture. When business entities are modified, service components related to them should also be modified, even though they implement common functions of the application framework. This paper proposes what we call DTT (Data Type-Tolerant) component model to process the variability of business entities, or externalized data, which feature modern application architectures. The DTT component model expresses the data variability of product lines at the implementation level by means of SCDTs (Self-Contained Data Types) and variation point interfaces. The model improves the efficiency of application engineering through data type converters which support type conversion between SCDTs and business entities of particular applications. The value of this model lies in that data and functions are coupled locally in each component again by allowing service components to deal with SCDTs only instead of externalized business eutities.

• Journal of Advanced Navigation Technology
• /
• v.21 no.1
• /
• pp.78-83
• /
• 2017

Linux was born under the influence of Unix except for the kernel, Linux was used to bring the Unix system and relevant program package, commands, etc. However, the latest version of Enterprise Linux, RHEL 7 was adopted systemd instead of init to boot program and management services. The adoption of systemd was building its own Linux system, the system only. Also noteworthy point is that given the considerable number of features specific to a particular package and instructions. As Linux has been recognized as a subtype of Unix itself as a catch all this time the turn of the tide in the cloud era and there on their own to try various changes, the start of the adoption of these changes can be called systemd. Linux is the future beyond the confines of Unix is noteworthy not attempt any changes.

• Journal of Digital Convergence
• /
• v.20 no.3
• /
• pp.343-348
• /
• 2022

Recently, With the recent rapid development of technology, the amount of data generated by various systems is increasing, and enterprise servers and data centers that have to handle large amounts of big data need to apply high-stability and high-performance storage devices even if costs increase. In such systems, SSD(solid state disk) that provide high performance of read/write are often used as storage devices. However, due to the characteristics of reading and writing on a page-by-page basis, erasing operations on a block basis, and erassing-before-writing, there is a problem that performance is degraded when duplicate writes occur. Therefore, in order to delay this performance degradation problem, over-provision technology of SSD has been applied internally. However, since over-provided technologies have the disadvantage of consuming a lot of storage space instead of performance, the application of inefficient technologies above the right performance has a problem of over-costing. In this paper, we proposed a method of measuring the performance and cost incurred when various over-provisions are applied in an SSD and predicting the system-optimized over-provided ratio based on this. Through this research, we expect to find a trade-off with costs to meet the performance requirements in systems that process big data.

• Information Systems Review
• /
• v.21 no.4
• /
• pp.143-156
• /
• 2019

Types of innovation can be categorized into simplification, information, automation, and intelligence. Intelligence is the highest level of innovation, and RPA can be seen as one of intelligence. Robotic Process Automation(RPA), a software robot with artificial intelligence, is an example of intelligence that is suited for simple, repetitive, large-scale transaction processing tasks. The RPA, which is already in operation in many companies in Korea, shows what needs to be done to naturally focus on the core tasks in a situation where the need for a strong organizational culture is increasing and the emphasis is on voluntary leadership, strong teamwork and execution, and a professional working culture. The introduction was considered naturally according to the need to find. Robotic Process Automation, or RPA, is a technology that replaces human tasks with the goal of quickly and efficiently handling structural tasks. RPA is implemented through software robots that mimic humans using software such as ERP systems or productivity tools. RPA robots are software installed on a computer and are called robots by the principle of operation. RPA is integrated throughout the IT system through the front end, unlike traditional software that communicates with other IT systems through the back end. In practice, this means that software robots use IT systems in the same way as humans, repeat the correct steps, and respond to events on the computer screen instead of communicating with the system's application programming interface(API). Designing software that mimics humans to communicate with other software can be less intuitive, but there are many advantages to this approach. First, you can integrate RPA with virtually any software you use, regardless of your openness to third-party applications. Many enterprise IT systems are proprietary because they do not have many common APIs, and their ability to communicate with other systems is severely limited, but RPA solves this problem. Second, RPA can be implemented in a very short time. Traditional software development methods, such as enterprise software integration, are relatively time consuming, but RPAs can be implemented in a relatively short period of two to four weeks. Third, automated processes through software robots can be easily modified by system users. While traditional approaches require advanced coding techniques to drastically modify how they work, RPA can be instructed by modifying relatively simple logical statements, or by modifying screen captures or graphical process charts of human-run processes. This makes RPA very versatile and flexible. This RPA is a good example of the application of digital to intelligence(D2I).