• 한국지능정보시스템학회:학술대회논문집
• /
• 한국지능정보시스템학회 2000년도 추계정기학술대회:지능형기술과 CRM
• /
• pp.417-426
• /
• 2000

This study suggests integrated neural network models for Interest rate forecasting using change-point detection, classifiers, and classification functions based on structural change. The proposed model is composed of three phases with tee-staged learning. The first phase is to detect successive and appropriate structural changes in interest rare dataset. The second phase is to forecast change-point group with classifiers (discriminant analysis, logistic regression, and backpropagation neural networks) and their. combined classification functions. The fecal phase is to forecast the interest rate with backpropagation neural networks. We propose some classification functions to overcome the problems of two-staged learning that cannot measure the performance of the first learning. Subsequently, we compare the structured models with a neural network model alone and, in addition, determine which of classifiers and classification functions can perform better. This article then examines the predictability of the proposed classification functions for interest rate forecasting using structural change.

• 국제학술발표논문집
• /
• The 9th International Conference on Construction Engineering and Project Management
• /
• pp.253-260
• /
• 2022

Existing web-based cost databases have proved invaluable for construction cost estimating. These databases have been utilized to compute approximate cost estimates using assembly rates, unit rates, and etc. These web-based databases can be used independently with traditional cost estimation methods (manual methods) or used to support BIM-based cost estimating platforms. However, these databases are rigid, costly, and require a lot of manual inputs to reflect recent trends in prices or prices relative to a construction project's location. To address this gap, this study integrated deep learning techniques with web-based price analysis to develop a database that incorporates a project's location cost estimating standards and current cost trends in generating a cost estimate. The proposed method was tested in a case study project in Lagos, Nigeria. A cost estimate was successfully generated. Comparison of the experimental results with results using current industry standards showed that the proposed method achieved a 98.16% accuracy. The results showed that the proposed method was successful in generating approximate cost estimates irrespective of project's location.

• International journal of advanced smart convergence
• /
• 제13권2호
• /
• pp.16-24
• /
• 2024

With an increase in the relevance of next-generation integrated networking environments, the need to effectively utilize advanced networking techniques also increases. Specifically, integrating Software-Defined Networking (SDN) with Multi-access Edge Computing (MEC) is critical for enhancing network flexibility and addressing challenges such as security vulnerabilities and complex network management. SDN enhances operational flexibility by separating the control and data planes, introducing management complexities. This paper proposes a reinforcement learning-based network path optimization strategy within SDN environments to maximize performance, minimize latency, and optimize resource usage in MEC settings. The proposed Enhanced Proximal Policy Optimization (PPO)-based scheme effectively selects optimal routing paths in dynamic conditions, reducing average delay times to about 60 ms and lowering energy consumption. As the proposed method outperforms conventional schemes, it poses significant practical applications.

• 한국IT서비스학회지
• /
• 제20권5호
• /
• pp.147-158
• /
• 2021

The digital transformation and COVID-19 are also causing major changes in teaching-learning methods. The biggest change is the spread of remote training and the emergence of various innovative learning platforms. Distance education has been criticized for not meeting technology trends and field demands..However, the problem of distance education is being solved through a system that supports various interactions and collaborations and supports customized learning paths. The researcher conducted a case study on domestic and foreign learning platforms that provide non-face-to-face ICT education. Based on the case study results, the researcher presented the functional characteristics of a learning platform that effectively supports non-face-to-face learning. In common, these sites faithfully supported the basic functions of the information system. In addition to learning progress check and learning guidance, some innovative learning platforms were providing differentiated functions in practice support, performance management, mentoring, learning data analysis, curation provision, and CDP support. Most learning platforms supported one-way, superficial interaction. If the platform effectively supports a variety of learning experiences and provides an integrated learning experience thanks to the development of IT technology, user satisfaction with the learning platform, intention to continue learning, and achievement will increase.

• 한국콘텐츠학회논문지
• /
• 제17권5호
• /
• pp.552-564
• /
• 2017

본 연구는 전통적 학습역량 및 경력관리 시스템의 한계를 극복하면서, 대학의 교과 및 비교과 프로그램의 운영 관리를 위한 통합형 e포트폴리오의 기능과 시스템의 구성요소를 고안하고, 인쇄물 기반의 프로토타입을 개발하는 것을 목적으로 S대학의 맥락에서 실시되었다. 연구진은 2차에 걸친 전문가 타당화를 통해 통합형 e포트폴리오의 주요 메뉴와 기능을 도출하였으며 각 메뉴에 포함해야 할 하위기능을 찾고 타당성을 확보하였다. 통합형 e포트폴리오 시스템의 구성요소는 크게 6가지(기본정보, 학습 역량 관리, 진로 경력 관리, 포트폴리오 관리, 커뮤니티, 기타)로 도출되었다. 이 중 학습 역량 관리, 진로 경력 관리, 포트폴리오 관리는 전통적 e포트폴리오와 차별화된 기능으로 내용구성의 타당성이 우수하다고 평가받았다. 본 연구에서는 통합형 e포트폴리오 시스템을 바탕으로 인쇄물 기반의 e포트폴리오 프로토타입을 개발하여 실제 시스템 구현의 구체적 가이드를 제공함과 동시에 통합형 e포트폴리오의 개발 방향 설정에 대한 기관의 인식제고에 공헌한 것으로 분석되었다.

• Industrial Engineering and Management Systems
• /
• 제7권3호
• /
• pp.214-227
• /
• 2008

Today's dynamic competitiveness requires an organization to improve its performance measurement and management. Quality Management Systems (QMS) abound, the main ones being: ISO series, Malcolm Baldridge National Quality Award (MBNQA), European Forum for Quality Management (EFQM), Six Sigma Business Scorecard and the Balanced Scorecard. Based on the literature, the IPMMM (Integrated Performance Measurement and Management Model) identified 7 key synthesized factors: leadership, strategy management and policy, customer and market, learning and growth, partnership and resources, internal processes and business results that are employed to investigate the key performance indicators of a car assembler using the Delphi methodology. In the 2 rounds of Delphi panels consisting of 20 senior management personnel, the $1^{st}$ round of 198 indicators in the IPMMM yielded 90 indicators. The $2^{nd}$ round yielded 43 performance indicators with 18 rated as critical based on the % assigned in the $1^{st}$ and $2^{nd}$ priority rating of "very important factor" and "key performance indicator" that must be ranked high on both of the priorities. The very critical indicators appeared to be: defect percentage and first time capability (tie in $1^{st}$ place) and revenue, goal setting, customer satisfaction index, on-time delivery, brand image, return on investment, Claim Occurrence Ratio, and debt being ranked from $3^{rd}$ to $10^{th}$. It can be surmised that an organization can identify and develop an appropriate set of performance indicators through the Delphi methodology and implement and manage them based on the Balanced Scorecard.

• 인터넷정보학회논문지
• /
• 제12권4호
• /
• pp.135-143
• /
• 2011

스마트폰은 학습자에게 언제 어디서나 학습할 수 있는 환경을 만들어 주었다. 학습자는 항상 인터넷에 연결할 수 있는 환경이 주어지므로 이동 중 학습이 가능할 뿐만 아니라 스마트폰의 다양한 기능을 이용하여 효율적인 학습이 가능하다. 스마트러닝이란 정보 검색·공유 및 다양한 응용프로그램 활용이 가능한 모바일 디지털 기기 기반의 학습이라고 정의할 수 있다. 이러닝 시스템에서 스마트폰의 효과적인 활용을 위해서는 상호작용, 협동학습 등 효과적인 교수-학습 원리를 기반으로 콘텐츠 및 학습관리시스템(LMS) 등을 설계해야한다. 학습 콘텐츠는 스마트폰의 고유 기능과 융합하여 학습에 효과적인 콘텐츠 설계가 필요하며, 이동 중 학습이 편리한 소규모의 학습 주제별 콘텐츠 개발이 필요하다. 학습관리시스템(LMS)의 경우 PA에이전트 프로그램 등을 이용해 학습자 환경을 파악하여 학습자에게 적합한 맞춤형 학습 서비스를 제공해야한다.

• 한국ITS학회 논문지
• /
• 제18권6호
• /
• pp.191-201
• /
• 2019

본 연구에서는 다양한 외부 조건 하에서 촬영된 영상을 대상으로 신속하고 정확하게 교통 객체를 검출하는 교통 객체 검출 통합 프레임워크를 개발하였다. 제안된 프레임워크는 딥러닝 기술 기반의 직접 객체 인식 기술과 다중 객체 추적 기술, 그리고 동영상 전처리 기술로 구성되며, 영상의 안정성, 기상, 촬영 각도 등의 다양한 외부 조건에서 촬영된 영상을 대상으로 승용차, 버스, 트럭, 및 미니밴과 같은 교통 객체를 인식하고, 이를 실시간으로 추적하여 교통량 데이터를 계수한다. 제안된 방법의 성능 검증을 위해 다양한 외부 조건에서 촬영된 영상 8개를 대상으로 제안된 방법의 성능 검증을 수행한 결과, 우천 및 강설을 제외한 모든 조건에서 98% 이상의 높은 정확도를 보이는 것으로 나타났다.

• International journal of advanced smart convergence
• /
• 제12권4호
• /
• pp.126-133
• /
• 2023

Recent advancements in cloud service virtualization technologies have witnessed a shift from a Virtual Machine-centric approach to a container-centric paradigm, offering advantages such as faster deployment and enhanced portability. Container orchestration has emerged as a key technology for efficient management and scheduling of these containers. However, with the increasing complexity and diversity of heterogeneous workloads and service types, resource scheduling has become a challenging task. Various research endeavors are underway to address the challenges posed by diverse workloads and services. Yet, a systematic approach to container orchestration for effective cloud management has not been clearly defined. This paper proposes the DRA-Engine (Dynamic Resource Allocation Engine) for resource scheduling in container orchestration. The proposed engine comprises the Request Load Procedure, Required Resource Measurement Procedure, and Resource Provision Decision Procedure. Through these components, the DRA-Engine dynamically allocates resources according to the application's requirements, presenting a solution to the challenges of resource scheduling in container orchestration.

• Journal of Computing Science and Engineering
• /
• 제4권1호
• /
• pp.80-95
• /
• 2010

In order to truly integrate e-Learning system into regular curriculum at a university, mobile access to Learning Management Systems has to be enabled. Mobile devices have the potential to be integrated into the classroom, because they contain unique characteristics such as portability, social interactivity, context sensitivity, connectivity and individuality. Adoption of Learning Management Systems by students is still on the low rate, mostly because of poor usability of existing e-Learning systems. Our initial research has confirmed this hypothesis. Usability issue is rising to the higher level on the mobile platform, because of the mobile devices' limited screen size, input interfaces and bandwidth, and also because of the context of use. Our second hypothesis was that it is wrong to consider a mobile device as a surrogate for desktop or laptop personal computer (PC). By just adopting the existing Learning Management System on mobile devices with adaptive technologies such as Google proxy, we do not acquire the satisfactory results. Usability can prove to be even lower compared to desktop application. One possible solution to the problem could be development of rich client applications for today's mobile devices that would raise the usability to a higher level. We developed a PocketPC prototype application by using user-centered design principles, which we presented as a third alternative in usability research conducted among university students. Results gathered in such a way have confirmed that development of e-Learning system, in order to be widely accepted by students, needs to have the user(student) in the center of development process.