• Advances in aircraft and spacecraft science
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• v.4 no.3
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• pp.297-316
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• 2017

With rapid growth in the complexity of large scale engineering systems, the application of multidisciplinary analysis and design optimization (MDO) in the engineering design process has garnered much attention. MDO addresses the challenge of integrating several different disciplines into the design process. Primary challenges of MDO include computational expense and poor scalability. The introduction of a distributed, collaborative computational environment results in better utilization of available computational resources, reducing the time to solution, and enhancing scalability. SORCER, a Java-based network-centric computing platform, enables analyses and design studies in a distributed collaborative computing environment. Two different optimization algorithms widely used in multidisciplinary engineering design-VTDIRECT95 and QNSTOP-are implemented on a SORCER grid. VTDIRECT95, a Fortran 95 implementation of D. R. Jones' algorithm DIRECT, is a highly parallelizable derivative-free deterministic global optimization algorithm. QNSTOP is a parallel quasi-Newton algorithm for stochastic optimization problems. The purpose of integrating VTDIRECT95 and QNSTOP into the SORCER framework is to provide load balancing among computational resources, resulting in a dynamically scalable process. Further, the federated computing paradigm implemented by SORCER manages distributed services in real time, thereby significantly speeding up the design process. Part 1 covers SORCER and the algorithms, Part 2 presents results for aircraft panel design with curvilinear stiffeners.

• Advances in aircraft and spacecraft science
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• v.4 no.3
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• pp.317-334
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• 2017

With rapid growth in the complexity of large scale engineering systems, the application of multidisciplinary analysis and design optimization (MDO) in the engineering design process has garnered much attention. MDO addresses the challenge of integrating several different disciplines into the design process. Primary challenges of MDO include computational expense and poor scalability. The introduction of a distributed, collaborative computational environment results in better utilization of available computational resources, reducing the time to solution, and enhancing scalability. SORCER, a Java-based network-centric computing platform, enables analyses and design studies in a distributed collaborative computing environment. Two different optimization algorithms widely used in multidisciplinary engineering design-VTDIRECT95 and QNSTOP-are implemented on a SORCER grid. VTDIRECT95, a Fortran 95 implementation of D. R. Jones' algorithm DIRECT, is a highly parallelizable derivative-free deterministic global optimization algorithm. QNSTOP is a parallel quasi-Newton algorithm for stochastic optimization problems. The purpose of integrating VTDIRECT95 and QNSTOP into the SORCER framework is to provide load balancing among computational resources, resulting in a dynamically scalable process. Further, the federated computing paradigm implemented by SORCER manages distributed services in real time, thereby significantly speeding up the design process. Part 1 covers SORCER and the algorithms, Part 2 presents results for aircraft panel design with curvilinear stiffeners.

• Journal of Korean Society for Geospatial Information Science
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• v.16 no.3
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• pp.3-13
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• 2008

The coordinate of cadastral control points located over the area of different surveying origins is computed in a single surveying origin by trilateration adjustment of GPS baseline measurements. In every different surveying origins, well-matched control points are selected and mutually coinciding coordinates are computed by free network adjustment. Then, the coordinate of the other control points over the area is computed by joining these points to the adjusted points. In practice, by using 18 points of Gari, 17 points of Gyeyang, and 33 points of Central origin in Incheon, the coordinates of total 68 points in every surveying origin are computed. Between the points of different surveying origins, it is found that there are quantitative differences in azimuth and scale factors and the approximate point coordinate of other surveying origins is calculated by correcting the scale and azimuth.

• Journal of Korean Society of Transportation
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• v.21 no.1
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• pp.91-102
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• 2003

There are two goals in this paper. The one is development of existing CA(Cellular Automata) model to explain more realistic deceleration process to stop. The other is the application of the updated CA model to forecasting simulation to predict short term link travel time that takes a key rule in finding the shortest path of route guidance system of ITS. Car following theory of CA models don't makes not response to leading vehicle's velocity but gap or distance between leading vehicles and following vehicles. So a following vehicle running at free flow speed must meet steeply sudden deceleration to avoid back collision within unrealistic braking distance. To tackle above unrealistic deceleration rule, “Slow-to-stop” rule is integrated into NaSch model. For application to interrupted traffic flow, this paper applies “Slow-to-stop” rule to both normal traffic light and random traffic light. And vehicle packet method is used to simulate a large-scale network on the desktop. Generally, time series data analysis methods such as neural network, ARIMA, and Kalman filtering are used for short term link travel time prediction that is crucial to find an optimal dynamic shortest path. But those methods have time-lag problems and are hard to capture traffic flow mechanism such as spill over and spill back etc. To address above problems. the CA model built in this study is used for forecasting simulation to predict short term link travel time in Kangnam district network And it's turned out that short term prediction simulation method generates novel results, taking a crack of time lag problems and considering interrupted traffic flow mechanism.

• Journal of Intelligence and Information Systems
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• v.19 no.2
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• pp.101-123
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• 2013

Recently due to the advancements of science and information technology, the socio-economic business areas are changing from the industrial economy to a knowledge economy. Furthermore, companies need to do creation of new value through continuous innovation, development of core competencies and technologies, and technological convergence. Therefore, the identification of major trends in technology research and the interdisciplinary knowledge-based prediction of integrated technologies and promising techniques are required for firms to gain and sustain competitive advantage and future growth engines. The aim of this paper is to understand the recent research trend in management of technology (MOT) and to foresee promising technologies with deep knowledge for both technology and business. Furthermore, this study intends to give a clear way to find new technical value for constant innovation and to capture core technology and technology convergence. Bibliometrics is a metrical analysis to understand literature's characteristics. Traditional bibliometrics has its limitation not to understand relationship between trend in technology management and technology itself, since it focuses on quantitative indices such as quotation frequency. To overcome this issue, the network focused bibliometrics has been used instead of traditional one. The network focused bibliometrics mainly uses "Co-citation" and "Co-word" analysis. In this study, a keywords network analysis, one of social network analysis, is performed to analyze recent research trend in MOT. For the analysis, we collected keywords from research papers published in international journals related MOT between 2002 and 2011, constructed a keyword network, and then conducted the keywords network analysis. Over the past 40 years, the studies in social network have attempted to understand the social interactions through the network structure represented by connection patterns. In other words, social network analysis has been used to explain the structures and behaviors of various social formations such as teams, organizations, and industries. In general, the social network analysis uses data as a form of matrix. In our context, the matrix depicts the relations between rows as papers and columns as keywords, where the relations are represented as binary. Even though there are no direct relations between papers who have been published, the relations between papers can be derived artificially as in the paper-keyword matrix, in which each cell has 1 for including or 0 for not including. For example, a keywords network can be configured in a way to connect the papers which have included one or more same keywords. After constructing a keywords network, we analyzed frequency of keywords, structural characteristics of keywords network, preferential attachment and growth of new keywords, component, and centrality. The results of this study are as follows. First, a paper has 4.574 keywords on the average. 90% of keywords were used three or less times for past 10 years and about 75% of keywords appeared only one time. Second, the keyword network in MOT is a small world network and a scale free network in which a small number of keywords have a tendency to become a monopoly. Third, the gap between the rich (with more edges) and the poor (with fewer edges) in the network is getting bigger as time goes on. Fourth, most of newly entering keywords become poor nodes within about 2~3 years. Finally, keywords with high degree centrality, betweenness centrality, and closeness centrality are "Innovation," "R&D," "Patent," "Forecast," "Technology transfer," "Technology," and "SME". The results of analysis will help researchers identify major trends in MOT research and then seek a new research topic. We hope that the result of the analysis will help researchers of MOT identify major trends in technology research, and utilize as useful reference information when they seek consilience with other fields of study and select a new research topic.

• International Journal of Contents
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• v.13 no.2
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• pp.29-34
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• 2017

Cloud computing is becoming an effective and efficient way of computing resources and computing service integration. Through centralized management of resources and services, cloud computing delivers hosted services over the internet, such that access to shared hardware, software, applications, information, and all resources is elastically provided to the consumer on-demand. The main enabling technology for cloud computing is virtualization. Virtualization software creates a temporarily simulated or extended version of computing and network resources. The objectives of virtualization are as follows: first, to fully utilize the shared resources by applying partitioning and time-sharing; second, to centralize resource management; third, to enhance cloud data center agility and provide the required scalability and elasticity for on-demand capabilities; fourth, to improve testing and running software diagnostics on different operating platforms; and fifth, to improve the portability of applications and workload migration capabilities. One of the key features of cloud computing is elasticity. It enables users to create and remove virtual computing resources dynamically according to the changing demand, but it is not easy to make a decision regarding the right amount of resources. Indeed, proper provisioning of the resources to applications is an important issue in IaaS cloud computing. Most web applications encounter large and fluctuating task requests. In predictable situations, the resources can be provisioned in advance through capacity planning techniques. But in case of unplanned and spike requests, it would be desirable to automatically scale the resources, called auto-scaling, which adjusts the resources allocated to applications based on its need at any given time. This would free the user from the burden of deciding how many resources are necessary each time. In this work, we propose an analytical and efficient VM-level scaling scheme by modeling each VM in a data center as an M/M/1 processor sharing queue. Our proposed VM-level scaling scheme is validated via a numerical experiment.

• Journal of Korean Society for Geospatial Information Science
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• v.15 no.3
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• pp.41-49
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• 2007

In this study, the software to compute Bessel coordinates by trilateration adjustment was developed, and the software was used to determine coordinates of the cadastral control points over the southern Korean peninsula. The baseline measured by GPS was reduced to the distance on geoid surface by applying PNU95 geoid model, and the distance on geoid surface was reduced to the plane grid distance by applying scale factor of map projection of Bessel coordinates. Using the plane grid distance, Bessel coordinates of 32 CORS (Continuously Operating Reference Station) were computed by free adjustment at first, and then the coordinates of the cadastral control points were computed by joining the control points to adjacent CORS. The result shows a possibility of construction of highly accurate and consistent cadastral survey network with coordinate error less than 1ppm of distance, when newly computing the coordinates of the control points by using distances measured by GPS.

• International Commerce and Information Review
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• v.13 no.1
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• pp.97-120
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• 2011

Purpose of this study is to define competitiveness and attribution factors of Busan port on attracting high value added business such as transshipment cargo. Research finds condition to become optimal transshipment port comprises both internal and external circumstances. As for the internal circumstance, scale and location of the distripark as well as port facilities and the rates, for the external circumstance, international network and information technology on logistics managements are providing positive effects. Optimal plans to attract transshipment cargo should include, first, development of total logistics management system from port entry to unloading, transportation, processing, loading to departure. Second, assign port as free trade zone under customs law to attract foreign investment and goods traffic through tax exemption. Third, unless it is illegal, government needs to grant substantial freedom to shift capital for the foreign investors which will lead increase in cargo traffic and foreign investment.

• Journal of Trauma and Injury
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• v.35 no.2
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• pp.76-83
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• 2022

Purpose: Ventilator-associated pneumonia is the most common nosocomial infection in patients with mechanical ventilation. In 2013, the new concept of ventilator-associated events (VAEs) replaced the traditional concept of ventilator-associated pneumonia. We analyzed risk factors for VAE occurrence and in-hospital mortality in trauma patients who received mechanical ventilatory support. Methods: In this retrospective review, the study population comprised patients admitted to the Jeju Regional Trauma Center from January 2020 to January 2021. Data on demographics, injury characteristics, and clinical findings were collected from medical records. The subjects were categorized into VAE and no-VAE groups according to the Centers for Disease Control and Prevention/National Healthcare Safety Network VAE criteria. We identified risk factors for VAE occurrence and in-hospital mortality. Results: Among 491 trauma patients admitted to the trauma center, 73 patients who received ventilator care were analyzed. Patients with a chest Abbreviated Injury Scale (AIS) score ≥3 had a 4.7-fold higher VAE rate (odds ratio [OR], 4.73; 95% confidence interval [CI], 1.46-17.9), and those with a glomerular filtration rate (GFR) <75 mL/min/1.73 m² had 4.1-fold higher odds of VAE occurrence (OR, 4.15; 95% CI, 1.32-14.1) and a nearly 4.2-fold higher risk for in-hospital mortality (OR, 4.19; 95% CI, 1.30-14.3). The median VAE-free duration of patients with chest AIS ≥3 was significantly shorter than that of patients with chest AIS <3 (P=0.013). Conclusions: Trauma patients with chest AIS ≥3 or GFR <75 mL/min/1.73 m² on admission should be intensively monitored to detect at-risk patients for VAEs and modify the care plan accordingly. VAEs should be closely monitored to identify infections early and to achieve desirable results. We should also actively consider modalities to shorten mechanical ventilation in patients with chest AIS ≥3 to reduce VAE occurrence.

• Journal of Korea Society of Industrial Information Systems
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• v.12 no.5
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• pp.1-13
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• 2007

In this research, we found out that bridging nodes have great effect on the robustness of protein-protein interaction networks. Until now, many researchers have focused on node's degree as node's essentiality. Hub nodes in the scale-free network are very essential in the network robustness. Some researchers have tried to relate node's essentiality with node's betweenness centrality. These approaches with betweenness centrality are reasonable but there is a positive relation between node's degree and betweenness centrality value. So, there are no differences between two approaches. We first define a bridging node as the node with low connectivity and high betweenness value, we then verify that such a bridging node is a primary factor in the network robustness. For a biological network database from Internet, we demonstrate that the removal of bridging nodes defragment an entire network severally and the importance of the bridging nodes in the network robustness.