• Proceedings of the Korea Information Processing Society Conference
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• 2020.05a
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• pp.28-31
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• 2020

한정된 고성능 자원을 여러 사용자들에게 제공해야하는 슈퍼컴퓨터와 같은 시스템은 제한된 기간 내에 보다 많은 양의 작업이 실행되도록 시스템 활용률을 높이는 방안이 필요하다. 이를 위해 시스템 관리자가 수행할 응용 프로그램에 대한 사전 정보를 파악하는 것이 유용하다. 대부분의 고성능 컴퓨팅 시스템 운영에 있어 작업을 실행할 때 사용자로부터 실행 기간 자원 요구사항들에 대한 정보를 제공 받거나 시스템 사용 통계 값을 사용하여 필요한 정보를 생성하는 등의 프로파일링 기술을 바탕으로 시스템 활용률을 높이는데 활용하고 있다. 본 논문의 선행연구에서 하드웨어 성능 카운터를 이용하여 응용 특성 분석을 실행하고 이 결과를 바탕으로 작업 스케줄링을 최적화하는 기술을 개발한 바 있다. 본 논문에서는 슈퍼컴퓨터 최적 실행 지원을 위한 프로파일링 테스트베드를 구축하고 단일노드를 기반으로 분석한 응용 프로그램 특성 결과를 활용한 스케줄링 최적화 기법이 확장성 있게 동작함을 보이고자 하였다. 또한 중규모 클러스터에 개발한 스케줄링 최적화 기법을 적용한 결과 전체 응용 프로그램이 실행 시간을 단축함으로써 최대 33%의 성능 향상 효과를 얻었다.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.26 no.4D
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• pp.661-670
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• 2006

The utilization of simulation has been limited in planning construction process because it is difficult to collect data and build a model using simulation method. This study collects construction operation data and analyzes the characteristics of its distribution. Through the statistical analysis on the empirical data, this study identifies Beta distribution functions is one of the most proper in duplicating the characteristics of construction equipment operation data into a computer simulation. The information obtained in this study can support preparing input data for another simulation.

• International conference on construction engineering and project management
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• 2022.06a
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• pp.686-693
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• 2022

Construction is a collaborative endeavor. The complexity in delivering construction projects successfully is impacted by the effective collaboration needs of a multitude of stakeholders throughout the project life-cycle. Technologies such as Building Information Modelling and relational project delivery approaches such as Alliancing and Integrated Project Delivery have developed to address this conundrum. However, with the onset of the pandemic, the digital economy has surged world-wide and advances in technology such as in the areas of machine learning (ML) and Artificial Intelligence (AI) have grown deep roots across specializations and domains to the point of matching its capabilities to the human mind. Several recent studies have both explored the role of AI in the construction process and highlighted its benefits. In contrast, literature in the organization studies field has highlighted the fear that tasks currently done by humans will be done by AI in future. Motivated by these insights and with the understanding that construction is a labour intensive sector where knowledge is both fragmented and predominantly tacit in nature, this paper explores the integration of AI in construction processes across project phases from planning, scheduling, execution and maintenance operations using literary evidence and experiential insights. The findings show that AI can complement human skills rather than provide a substitute for them. This preliminary study is expected to be a stepping stone for further research and implementation in practice.

• International conference on construction engineering and project management
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• 2013.01a
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• pp.459-466
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• 2013

Risk exists in all construction projects and resides among the collection of subcontractors and their array of individual activities. Wherever risk resides, the interrelation of participants to one another becomes paramount for the way in which risk is measured. Inherent risk becomes recognizable and quantifiable within network schedules in the form of consuming float - the flexibility to absorb delays. Allocating, owning, valuing, and expending such float in network schedules has been debated since the inception of the critical path method itself. This research investigates the foundational element of a three-part approach that examines how float can be traded as a commodity, a concept whose promise remains unfulfilled for lack of a holistic approach. The Capital Asset Pricing Model (CAPM) of financial portfolio theory, which describes the relationship between risk and expected return of individual stocks, is explored as an analogy to quantify the inherent risk of the participants in construction projects. The inherent relationship between them and their impact on overall schedule performance, defined as schedule risk -the likelihood of failing to meet schedule plans and the effect of such failure, is matched with the use of CAPM's beta component - the risk correlation measure of an individual stock to that of the entire market - to determine parallels with respect to the inner workings and risks represented by each entity or activity within a schedule. This correlation is the initial theoretical extension that is required to identify where risk resides within construction projects, allocate and commoditize it, and achieve actual tradability.

• International conference on construction engineering and project management
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• 2011.02a
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• pp.58-65
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• 2011

Construction Productivity is one of the most important elements in construction management. It is used in construction process scheduling and cost management, which are significant sector in construction management. It is important to make appropriate schedule and monitor how works are done within schedule. But construction project contains uncertainty and inexactitude, modifying construction schedule is being an issue to manage construction works well. Even though prediction and monitoring of productivity can be principal activity, it is hard to predict productivity with manager's experience and a standard of estimate. A large number of factors influencing productivity, such as drawing, construction method, weather, labor, material, equipment, etc. But current calculation of productivity depends on empirical probability, not consider difference of each influencing factor. In this research, the aim is to present a productivity predicting regression model of form work, which includes effectiveness of influences factors. 5 variables existed inside form work are selected by interview and site research based on literature review of existed various productivity influencing factors. The effectiveness and correlation of productivity influencing factors are analyzed by statistical approach, and it is used to make productivity regression model. The finding of this research will improves monitoring and controlling of project schedule in construction phase.

• Korean Medical Education Review
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• v.26 no.2
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• pp.108-117
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• 2024

Interprofessional collaboration is crucial for patient-centered care and safety. Since healthcare students will be part of interprofessional teams in the future, they need to understand the unique contributions of various healthcare professions to patient care and develop skills in collaboration, communication, leadership, and mutual respect. In response to this need, healthcare faculties have adopted interprofessional education as an innovative teaching method. However, traditional health education has typically taken place within individual schools, resulting in a limited understanding of other professional roles and identities. In our study, we introduced an interprofessional education model involving two different colleges. A total of 152 undergraduate students, comprising 101 medical students from Chung Ang University and 51 nursing students from Sungshin Women's University, participated in the program. A one-day interprofessional education program was conducted to promote collaboration between medical and nursing students. The program included team building and communication games, scenario-based simulations, such as a "room of errors," and tabletop exercises. Key factors for successful interprofessional education include carefully planned scheduling, leadership, and commitment from participating colleges, faculty support and training, the use of diverse teaching methods and technology, and alignment regarding educational directions among the faculty. We believe that this model may provide valuable insights for healthcare institutions aiming to develop and implement interprofessional curricula.

• Journal of the Institute of Electronics and Information Engineers
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• v.52 no.5
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• pp.225-234
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• 2015

Nowadays a Virtual Power Plant (VPP) represents an aggregation of distributed energy resource such as Distributed Generation (DG), Combined Heat and Power generation (CHP), Energy Storage Systems (ESS) and load in order to operate as a single power plant by using Information and Communication Technologies, ICT. The VPP has been developed and verified based on a single virtual plant platform which is connected with a number of various distributed energy resources. As the VPP's distributed energy resources increase, so does the number of data from distributed energy. Moreover, it is obviously inefficient in the aspects of technique and cost that a virtual plant platform operates in a centralized manner over widespread region. In this paper the concept of the large-scale VPP which can reduce a error probability of system's load and increase the robustness of data exchange among distributed energy resources will be proposed. In addition, it can directly control and supervise energy resource by making small size's virtual platform which can make a optimal resource scheduling to consider of variable and sensitive load in the large-scale VPP. It makes certain the result is verified by simulation.

• Korean Journal of Construction Engineering and Management
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• v.16 no.5
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• pp.54-64
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• 2015

The modular construction has several advantages such as high quality of product, safe work condition and short construction duration. The manufacturing planning of modular construction should consider time frame of manufacturing, transport and erection process with limited resources (e.g., modular units, transporter and workers). The manufacturing planning of multi modular construction project manages the modular construction's characteristics and diversity of projects, as a type of modular unit, modular unit quantities, and date for delivery. However, current modular manufacturing planning techniques are weak in dealing with resource interactions and each project requirement in multi modular construction project environments. Inefficient allocation of resources during multi modular construction project may cause delays and cost overruns to construction operation. In this circumstance, this research suggest a manufacturing planning model for schedule optimization of multi project of modular construction, using genetic algorithm as one of the powerful method for schedule optimization with multiple constrained resources. Comparing to the result of the existed schedule of case study, setting optimized scheduling for multi project decrease the total factory producing schedule. By using proposed optimization tool, efficient allocation of resource and saving project time is expected.

• Journal of KIISE:Software and Applications
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• v.31 no.12
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• pp.1637-1648
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• 2004

When digital libraries are developed by the traditional client/sever system using a single agent on the distributed environment, several problems occur. First, as the search method is one dimensional, the search results have little relationship to each other. Second, the results do not reflect the user's preference. Third, whenever a client connects to the server, users have to receive the certification. Therefore, the retrieval of documents is less efficient causing dissatisfaction with the system. I propose a new platform of mobile multiagents for a personal digital library to overcome these problems. To develop this new platform I combine the existing DECAF multiagents platform with the Voyager mobile ORB and propose a new negotiation algorithm and scheduling algorithm. Although there has been some research for a personal digital library, I believe there have been few studies on their integration and systemization. For searches of related information, the proposed platform could increase the relationship of search results by subdividing the related documents, which are classified by a supervised neural network. For the user's preference, as some modular clients are applied to a neural network, the search results are optimized. By combining a mobile and multiagents platform a new mobile, multiagents platform is developed in order to decrease a network burden. Furthermore, a new negotiation algorithm and a scheduling algorithm are activated for the effectiveness of PDS. The results of the simulation demonstrate that as the number of servers and agents are increased, the search time for PDS decreases while the degree of the user's satisfaction is four times greater than with the C/S model.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.49 no.5
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• pp.21-26
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• 2012

Intra-session network coding has been proposed to improve throughput by simplifying scheduling of multi-hop wireless network and efficiency of packet transmission. Multi-rate transmission has been used in multihop wireless networks. An opportunistic routing with multirate shows throughput improvement compared with single rate. In this paper, we propose a method of throughput improvement in multi-hop wireless network by using multi-rate and intra-session network coding. We suggest a method to select an local optimal transmission rate at each node. The maximum throughput is evaluated by using linear programming (LP). To solve the LP, we use MATLAB and lp_solve IDE program. The performance evaluation results show that end-to-end throughput is improved by using multirate and intra-session network coding can achieve better throughput than opportunistic routing.