• International conference on construction engineering and project management
• /
• 2015.10a
• /
• pp.294-298
• /
• 2015

In the United States, the completion of Construction Work Zone (CWZ) impact assessments for all federally-funded highway infrastructure improvement projects is mandated, yet it is regarded as a daunting task for state transportation agencies, due to a lack of standardized analytical methods for developing sounder Transportation Management Plans (TMPs). To circumvent these issues, this study aims to create a spatiotemporal modeling framework, dubbed "SWAT" (Spatiotemporal Work zone Assessment for TMPs). This study drew a total of 43,795 traffic sensor reading data collected from heavily trafficked highways in U.S. metropolitan areas. A multilevel-cluster-driven analysis characterized traffic patterns, while being verified using a measurement system analysis. An artificial neural networks model was created to predict potential 24/7 traffic demand automatically, and its predictive power was statistically validated. It is proposed that the predicted traffic patterns will be then incorporated into a what-if scenario analysis that evaluates the impact of numerous alternative construction plans. This study will yield a breakthrough in automating CWZ impact assessments with the first view of a systematic estimation method.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.17 no.8
• /
• pp.2292-2313
• /
• 2023

With improving computing performance, various digital platforms are being developed to enable easily utilization of high-performance computing environments. EDISON 1.0 is an online simulation platform widely used in computational science and engineering education. As the research paradigm changes, the demand for developing the EDISON 1.0 platform centered on simulation into the EDISON 2.0 platform centered on data and artificial intelligence is growing. Herein, a data framework, a core module for data-centric research on EDISON 2.0 digital platform, is proposed. The proposed data framework provides the following three functions. First, it provides a data repository suitable for the data lifecycle to increase research reproducibility. Second, it provides a new data model that can integrate, manage, search, and utilize heterogeneous data to support a data-driven interdisciplinary convergence research environment. Finally, it provides an exploratory data analysis (EDA) service and data enrichment using an AI model, both developed to strengthen data reliability and maximize the efficiency and effectiveness of research endeavors. Using the EDISON 2.0 data framework, researchers can conduct interdisciplinary convergence research using heterogeneous data and easily perform data pre-processing through the web-based UI. Further, it presents the opportunity to leverage the derived data obtained through AI technology to gain insights and create new research topics.

• Journal of the Korean Operations Research and Management Science Society
• /
• v.37 no.2
• /
• pp.31-43
• /
• 2012

Delivery of a good quality of service in an efficient manner requires matching the supply of capacity with customer demand. Much research has employed queueing models that analyzed the service system on the basis of independent and stationary customer arrivals. However, the appointment system, which is widely used to facilitate customer access to service in many industries including healthcare, has significant influence on the customer arrival process so that the independent and stationary assumption does not hold in an appointment-based service system. In this regard, this paper aims to propose a model for accurate illustration of the appointment-based customer arrival process. The use of the proposed model allows us to evaluate the overall system performance such as mean waiting time and service level under various appointment policies instead of conducting simulation studies.

• The KIPS Transactions:PartD
• /
• v.15D no.1
• /
• pp.87-98
• /
• 2008

In company with the demand of powerful processing units for embedded systems, the method to develop embedded software is also required to support the demand in new approach. In order to improve the resource utilization and system performance, software modeling techniques have to consider the features of hardware architecture. This paper proposes a partitioning technique of UML-based software models, which focus the generation of the allocatable software components into multiprocessor architecture. Our partitioning technique, at first, transforms UML models to CBCFGs(Constraint-Based Control Flow Graphs), and then slices the CBCFGs with consideration of parallelism and data dependency. We believe that our proposition gives practical applicability in the areas of platform specific modeling and performance estimation in model-driven embedded software development.

• International Journal of Computer Science & Network Security
• /
• v.24 no.3
• /
• pp.113-124
• /
• 2024

One of the goals of the Saudi Arabia 2030 vision is to ensure full employment of its citizens. Recruitment of graduates depends on the quality of skills that they may have gained during their study. Hence, the quality of education and ensuring that graduates have sufficient knowledge about the in-demand skills of the market are necessary. However, IT graduates are usually not aware of whether they are suitable for recruitment or not. This study builds a prediction model that can be deployed on the web, where users can input variables to generate predictions. Furthermore, it provides data-driven recommendations of the in-demand skills in the Saudi IT labor market to overcome the unemployment problem. Data were collected from two online job portals: LinkedIn and Bayt.com. Three machine learning algorithms, namely, Support Vector Machine, k-Nearest Neighbor, and Naïve Bayes were used to build the model. Furthermore, descriptive and data analysis methods were employed herein to evaluate the existing gap. Results showed that there existed a gap between labor market employers' expectations of Saudi workers and the skills that the workers were equipped with from their educational institutions. Planned collaboration between industry and education providers is required to narrow down this gap.

• Journal of Korea Technology Innovation Society
• /
• v.21 no.2
• /
• pp.491-521
• /
• 2018

This paper aims to uncover success factors in technology transfer of Korean government sponsored research institutes. It presents an analytical framework of technology transfer integrating factors concerning actors, object and process. Qualitative analysis mainly based on In-depth interviews is designed and conducted to examine characteristics, similarities and differences of three types technology transfer including a supply-push model, a demand-pull model, and an interactive model. Empirical results show that capabilities and experiences of researchers, capabilities and willingness of the company and active communications in the technology transfer appear to be important factors. In particular, it was found that technology transfer was led by TLO in the demand-pull model. In addition, the demand-pull and interactive approaches tends to be more effective in the technology development and transfer process compared to the supply-push model. In other words, market-oriented R&D is needed instead of technology-driven R&D. This paper also pointed out that one of the major factors in successful technology transfer is the enhancement of TLO capacity, and the improvement of recognition about TLO.

• IE interfaces
• /
• v.20 no.4
• /
• pp.547-559
• /
• 2007

In this paper, we design Real-Time Postal Logistics Operational Model and System as a to-be system. Current postal logistics information system, named PostNet, is a basic infra system designed for an end-to-end IT-driven process, from mail acceptance to delivery, linked with internal and external systems. Recent competing circumstances drive demand for more intelligent information system. So we design real-time postal logistics operational system focused on site operations. we analyze postal logistics operation and interview field workers and establish real-time postal logistics operational model to solve operational issues. Finally we suggest system specifications.

• Journal of KIISE:Software and Applications
• /
• v.37 no.12
• /
• pp.892-908
• /
• 2010

Services in SOA are typically perceived as black-box to service consumers, and can be dynamically evolved at runtime, and run on a number of unknown and heterogeneous environments. Because of these characteristics of the services, effective and efficient monitoring of various aspects on services is an essential functionality for autonomous management of service. But the problem with or limitation in conventional or existing approaches is, that they focus on services themselves, ignoring the effects by business processes. Consequently, there is a room for service monitoring which provides more useful information of business level by acquisition of only external monitoring data that depend on specific BPEL engine and middleware. Moreover, there is a strong demand to present effective methods to reduce monitoring overhead which can degrade quality of services. EDA can cope with such limitations in SOA by collecting and analyzing events efficiently. In this paper, we first describe EDA benefits in service monitoring, and classify monitorring target, and present an appropriate monitoring method for each monitoring target. Also to provide the applicability of our approach, an event meta-model is defined, and event processing model and architecture based on the meta-model are proposed. And, with the proposed architecture and method, we implement a prototype of an event-driven dynamic monitoring framework which can collect and process internal and external data at runtime. Finally, we present the result of a case study to demonstrate the effectiveness and applicability of the proposed approach.

• 한국정보교육학회:학술대회논문집
• /
• 2021.08a
• /
• pp.25-30
• /
• 2021

With the introduction of AI education in the 2022 Revised Curriculum emphasizing the need for data related education, it is necessary to improve students' data based problem solving skills. This study seeks to study SW education methods to improve students' data based problem solving skills in accordance with these needs. Based on the ADDIE model, the demand analysis survey was conducted on teachers to analyze their needs. Based on the results of the demand analysis, we designed education programs under the theme of data based problem solving skills using microbit. In this study, we raise the importance of data based problem solving and the need for its capabilities. Subsequent studies need to reveal how data based problem solving SW education will demonstrate significant effects on problem solving skills.

• Journal of Digital Convergence
• /
• v.11 no.12
• /
• pp.275-285
• /
• 2013

As the world economy has been changed into the knowledge-based society, all economic activities have globalized and intensified competition in the marketplace, and the forces of these changes are even more aggressively pressuring today's business. According to many businesses are focused on the core competence and various functions are outsourced by service providers, many firms pay heavily attention to business service. Although the importance of business service, domestic business service industry shows a low labor productivity. On the other hand, foreign business service companies in korea take a substantial portion of business service market. Thus, domestic business service needs to increase a competitiveness because of potential growth opportunities. This study attempts to find out the ripple effect of business service industry on other industry.