• 한국콘텐츠학회논문지
• /
• 제9권4호
• /
• pp.81-94
• /
• 2009

유비쿼터스 환경에서 지능형 서비스 로봇의 실시간성 기술은 QoS를 보장하기 위해서 필수 불가결한 요소이다. 본 논문에서는 지능형 서비스 로봇에 실시간성을 지원하는 실시간 프레임워크를 설계 및 구현한 내용을 기술한다. 실시간 스케줄링 서비스를 제공하는 실시간 프레임워크는 범용 운영체제를 기반으로 동작하며, 범용 운영체제에서 제공하는 스케줄러의 실시간성 미 지원 문제를 해결한다. 본 논문에서는 또한 실시간 로봇 애플리케이션에 QoS를 보장하기 위한 실시간 스케줄링 서비스를 제안한다. 제안된 실시간 프레임워크의 성능 평가를 위해 윈도우즈 운영체제 상에 구현하였다. 실험 결과를 통해 쓰레드의 응답시간 향상과 실시간 프레임워크 탑재에 따른 성능상의 오버 헤드가 $62{\mu}s$로 미미하다는 것을 알 수 있다.

• 지식경영연구
• /
• 제19권3호
• /
• pp.173-187
• /
• 2018

This study was aimed at suggesting an integrative framework for creating collective intelligence and enhancing group performance after reviewing previous studies including those related to learning organizations, organizational learning, knowledge management, and collective intelligence. In the first, we examined that the similarities and differences between collective intelligence and other similar concepts, such as learning organizations, organizational learning, and knowledge management. Next, an integrative framework for creating collective intelligence and channeling it into strong group performance were suggested. In this process, we reviewed conditions for creating collective intelligence and segmented the major variables as expectancy, valence, and instrumentality, according to Vroom's (1964) expectancy theory. Characteristics of problems and the roles of leaders were respectively considered as valence for inducing collaboration and expectancy for managing probability to achieve goals. Instrumental factors were also adopted from conditions for creating group intelligence suggested from several researchers, such as creativity, openness, willingness for working together, horizontal communication, centralization in decision making, and building effective information and communication technology system and active usage of it. We discussed two potentially disputable matters about the scope and level of collective intelligence and group performance and suggest several theoretical and practical implications in the Discussion.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• 제13권6호
• /
• pp.2824-2837
• /
• 2019

Container technologies are widely used in infrastructures to deploy and manage applications in cloud computing environment. As containers are light-weight software, the cluster of cloud applications can easily scale up or down to provide Internet-based services. Container-based applications can well deal with fluctuate workloads by dynamically adjusting physical resources. Current works of scheduling applications often construct applications' performance models with collected historical training data, but these works with static models cannot self-adjust physical resources to meet the dynamic requirements of cloud computing. Thus, we propose a self-adaptive automatic container scheduling framework AutoScale for cloud applications, which uses a feedback-based approach to adjust physical resources by extending, contracting and migrating containers. First, a queue-based performance model for cloud applications is proposed to correlate performance and workloads. Second, a fuzzy Kalman filter is used to adjust the performance model's parameters to accurately predict applications' response time. Third, extension, contraction and migration strategies based on predicted response time are designed to schedule containers at runtime. Furthermore, we have implemented a framework AutoScale with container scheduling strategies. By comparing with current approaches in an experiment environment deployed with typical applications, we observe that AutoScale has advantages in predicting response time, and scheduling containers to guarantee that response time keeps stable in fluctuant workloads.

• 한국소프트웨어감정평가학회 논문지
• /
• 제17권1호
• /
• pp.101-113
• /
• 2021

본 논문에서는 화자 겹침 시스템을 소개하고 인공지능 분야에서 널리 사용되는 프레임워크에서 이미 구축된 시스템을 전환하는 과정을 고찰하고자 한다. 화자 겹침은 대화 과정에서 두 명 이상의 화자가 동시에 발성하는 것을 말하며, 사전에 화자 겹침을 탐지하여 음성인식이나 화자인식의 성능 저하를 예방할 수 있으므로 많은 연구가 진행되고 있다. 최근 인공지능을 이용한 다양한 응용 시스템의 활용도가 높아지면서 인공지능 프레임워크 (framework) 간의 전환이 요구되고 있다. 그러나 프레임워크 전환 시 각 프레임워크의 고유 특성에 의하여 성능 저하가 관찰되고 있으며 이는 프레임워크 전환을 어렵게 하고 있다. 본 논문에서는 케라스 (Keras) 기반 화자 겹침 시스템을 파이토치 (pytorch) 시스템으로 전환하는 과정을 기술하고 고려해야 할 구성 요소들을 정리하였다. 프레임워크 전환 결과 기존 케라스 기반 화자 겹침 시스템보다 파이토치로 전환된 시스템에서 더 좋은 성능을 보여 체계적인 프레임워크 전환의 기본 연구로서 가치를 지닌다고 할 수 있다.

• 한국컴퓨터정보학회논문지
• /
• 제17권1호
• /
• pp.53-60
• /
• 2012

본 논문은 분산 시스템 기반에서 경량급 프레임워크의 간단한 개발 주기를 지원하며 분산 처리가 가능한 IPO(Input-Process-Output) 모델 기반의 프레임워크를 제안한다. 제안 프레임워크는 입력 함수, 처리 함수, 출력 함수를 가진 클래스를 개발하면 분산 시스템의 표현 계층과 중간 계층에서 하나의 응용 프로그램으로 실행되도록 지원해준다. 또한 이 기법의 특징으로 응용 프로그램 개발시 분산 시스템 의존적인 부분을 제거하며, 개발-구축-배치-검증의 개발 주기를 개발-검증 주기로 감소시킨다. 이 기법의 생산성 향상과 성능 검증하기 위해 기존의 분산 시스템과 경량급 프레임워크의 응용 프로그램을 제안 기법의 응용 프로그램과 비교 분석한다. 그 결과 상당한 코드 감소와 분산 시스템 의존적인 부분이 감소하여 개발 생산성을 향상시키고 경량급 시스템에 비해 상대적으로 안전적인 성능을 보인다.

• 산업공학
• /
• 제16권3호
• /
• pp.382-391
• /
• 2003

Supply chain performance management is the essential part of various business activities in supply chain management area, and integrating it with general business management improves the supply chain performance. Although supply chain performance management is important and expected of market growth, there are few researches on this area and lack of practical applications. To resolve these problems, this paper presents a new performance management methodology for a supply chain integrating SCOR (Supply Chain Operational Reference) model and Balanced Scorecard (BSC). And we develop a framework of the Supply Chain Performance Management System (SCPMS) based on this methodology, and implement a prototype system.

• 인터넷정보학회논문지
• /
• 제23권2호
• /
• pp.97-105
• /
• 2022

Web services show a rapid evolution and integration to meet the increased users' requirements. Thus, web services undergo updates and may have performance degradation due to undetected faults in the updated versions. Due to these faults, many performances and regression anomalies in web services may occur in real-world scenarios. This paper proposed applying the deep learning model and innovative explainable framework to detect performance and regression anomalies in web services. This study indicated that upper bound and lower bound values in performance metrics provide us with the simple means to detect the performance and regression anomalies in updated versions of web services. The explainable deep learning method enabled us to decide the precise use of deep learning to detect performance and anomalies in web services. The evaluation results of the proposed approach showed us the detection of unusual behavior of web service. The proposed approach is efficient and straightforward in detecting regression anomalies in web services compared with the existing approaches.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• 제8권1호
• /
• pp.232-248
• /
• 2014

A series of kernel regression (KR) algorithms, such as the classic kernel regression (CKR), the 2- and 3-D steering kernel regression (SKR), have been proposed for image and video super-resolution. In existing KR frameworks, a single algorithm is usually adopted and applied for a whole image/video, regardless of region characteristics. However, their performances and computational efficiencies can differ in regions of different characteristics. To take full advantage of the KR algorithms and avoid their disadvantage, this paper proposes a kernel regression framework for video super-resolution. In this framework, each video frame is first analyzed and divided into three types of regions: flat, non-flat-stationary, and non-flat-moving regions. Then different KR algorithm is selected according to the region type. The CKR and 2-D SKR algorithms are applied to flat and non-flat-stationary regions, respectively. For non-flat-moving regions, this paper proposes a similarity-assisted steering kernel regression (SASKR) algorithm, which can give better performance and higher computational efficiency than the 3-D SKR algorithm. Experimental results demonstrate that the computational efficiency of the proposed framework is greatly improved without apparent degradation in performance.

• 한국IT서비스학회지
• /
• 제18권2호
• /
• pp.161-183
• /
• 2019

Researches on the business value of IT and ICT in the past has been focused on static content researches such as study of IT ICT itself and study of the relationship between IT ICT and performance. In recent years, however, the need for discussions on the "process of IT and ICT making economic value (performance) difference between companies" is growing. In particular, there is a need for an framework to analyze the process of qualitative change (progress, evolution, improvement) of IT and ICT affecting the competitive advantage. In this paper, we present a framework for analyzing the process of creating competitive advantage by IT ICT and show the structure of how IT and ICT resources lead to the creation of competitive advantage. In order to achieve these objectives, this paper proposes a framework for the process of creating competitive advantage by linking IT and ICT related resources, value activities, value chains, and business processes.

• 한국경영공학회지
• /
• 제23권4호
• /
• pp.165-177
• /
• 2018

Smart technology has been utilized in various fields of all kinds of industries. Manufacturing industry has built its smart technology environment appropriate for its manufacturing fields in order to strengthen its manufacturing performance and competitiveness. The advance of smart technology for manufacturing industry needs to efficiently produce products, and response customer's demands and services in a global industrial environment. The smart technology capability of manufacturing fields is very crucial for the innovative production and efficient operation activities, and for efficient advancement of the manufacturing performance. We have necessitated a scientific and objective method that can gauge a smart technology ability in order to manage and strengthen the smart technology ability of manufacturing fields. This research provides a comprehensive framework that can rationally gauge the smart technology capability of manufacturing fields for effectively managing and advancing their smart technology capabilities. In this research, we especially develop a structural framework that can gauge the smart technology capability for a smart factory of manufacturing fields, with verifying by reliability analysis and factor analysis based on previous literature. This study presents a 13-item framework that can measure the smart technology capability for a smart factory of manufacturing fields in a smart technology perspective.