• Convergence Security Journal
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• v.4 no.3
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• pp.1-8
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• 2004

Large distributed systems such as computational and data grids require that a substantial amount of monitoring data be collected for various tasks such as fault detection, performance analysis, performance tuning, performance prediction, security analysis and scheduling. to cope with this problem, they are needed network monitoring architecture which can collect various network characteristic and analyze network security state. In this paper, we suggest network performance and security analysis system based on network monitoring. The System suggest that users can see distance network state with tuning network parameters.

• Journal of Korea Multimedia Society
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• v.18 no.11
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• pp.1367-1374
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• 2015

In this paper, we propose a model which can prioritize the performance improvement work by analyzing the major risks and their influence, which can cause performance degradation in the system and show an example of a performance improvement using this model. In presentation-tier, as a result of log data analysis before and after the performance improvement of key processes which handle financial transactions, this model brought the CPU utilization and memory enhancement in the performance improvement work of the financial system which was carried out by applying the proposed model. It has been confirmed that the entire end-user can be accommodated. In the web-tier, the available memory increased by 200MB and we were able to improve the server restart(Recycling) that was sustained in the existing system. In the business logic-tier, we have been able to see better figures after performance improvements through the graph which analyzes the log collected with the key performance counters such as CPU%, Batch Requests/sec. In the data-tier, it has been confirmed that CPU usage and standby operation were reduced and the throughput was found to increase.

• Journal of the Korea Management Engineers Society
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• v.23 no.4
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• pp.125-141
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• 2018

As global competition is intensifying, companies are entering not only developed markets but also emerging and developing countries. In emerging and developing countries, business-to-governmental relations are an essential factor influencing the firm performance. The purpose of this research is to examine the effects of corporate political activities on firm performance. Using the BEEPS data developed by the EBRD and the World Bank, the effect of various bribery activities regarded as corporate political activities on the firm performance was examined. Also, the moderating effect of competition type on the firm performance was proved. As the results, the bribery contribution, which is a corporate political activity, has a positive effect on the firm performance. Specifically, when infrastructure bribery occurred, costs and sales were higher, and when permission bribery was granted, profits, costs, and sales were higher. In addition, the effect of bribery as a corporate political activity on firm performance is moderated by competition type. These findings have academic and practical implications for empirical analyzing of SMEs' firm performance, guidelines suggestion for entry into the other countries, generalization possibility of using credible data, developing and designing export support systems and programs. Finally, limitations of the research and future research directions were discussed.

• The Transactions of the Korea Information Processing Society
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• v.6 no.3
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• pp.710-721
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• 1999

In this paper, we have designed and implemented a parameter extraction system for analyzing Internet using SNMP. The extraction system has two modules; one is collection request module, and the other is analysis request module. The collection request module generates a polling script, which is used to collect management information from the managed system periodically. With this collected data, analysis request module extracts analysis parameters. These parameters are traffic flow analysis, interface traffic analysis, packet traffic analysis, and management traffic analysis parameter. For management activity, we have introduced two-step-analysis-view. One is Summary-View, which is used find out malfunction of a system among the entire managed systems. The Other is Specific-View. With this view we can analyze the specific system with all our analysis parameters. To show available data as indicators for line capacity planning, network redesigning decision making of performance upgrade for a network device and things like that.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.6
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• pp.2078-2094
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• 2015

Now a days, Efficient processing of Broadcast Queries is of critical importance with the ever-increasing deployment and use of mobile technologies. BQs have certain unique characteristics that the traditional spatial query processing in centralized databases does not address. In novel query processing technique, by maintaining high scalability and accuracy, latency is reduced considerably in answering BQs. Novel approach is based on peer-to-peer sharing, which enables us to process queries without delay at a mobile host by using query results cached in its neighboring mobile peers. We design and evaluate cooperative caching techniques to efficiently support data access in ad hoc networks. We first propose two schemes: Cache Data, which caches the data, and Cache Path, which caches the data path. After analyzing the performance of those two schemes, we propose a hybrid approach (Hybrid Cache), which can further improve the performance by taking advantage of Cache Data and Cache Path while avoiding their weaknesses. Cache replacement policies are also studied to further improve the performance. Simulation results show that the proposed schemes can significantly reduce the query delay and message complexity when compared to other caching schemes.

• Journal of Fisheries and Marine Sciences Education
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• v.19 no.1
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• pp.74-83
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• 2007

These days business logistics has become one of the very important factors of logistics cost reduction and customer service satisfaction. In order to control business logistics more effectively, many companies must be concerned about logistics performance.This study aims at analyzing information system characteristic and logistics performance. The information system characteristic variables are considered IS resource, IS strategic role. The logistics performance variables are considered logistic cost, customer service.For data on the 301 sampled company, a mail survey using a questionnaire was conducted in this study. The following results were obtained.First, IS characteristic variables were significant for logistics performance. Specially, efficient management of IS manpower and IS planning, present IS were significant for logistics performance. Second, there also were IS manpower and IS planning, present IS that indentifing high logistics performance group and low logistics performance group.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.26 no.3
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• pp.482-490
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• 2002

This paper presents modelling and analyzing method of centrifugal chiller which has a rated capacity of 200 RT(703 kW) through on-site performance test. Field performance data of a chiller installed in a research building of KIST have been collected. Simple models were developed for predicting the heat exchanger and system performances by regression of chiller operation data during 5 days in August. The models proposed here account for the effect of variations of cooling capacity, temperatures and flew rates of secondary fluids. The proposed models can predict the actual performance data from June to September within $\pm$ 5% error. The COP of centrifugal chiller are estimated under the standard rating conditions and reduced mass flow rates of chilled and cooling water.

• Journal of information and communication convergence engineering
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• v.6 no.3
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• pp.323-326
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• 2008

Data Envelopment Analysis (DEA) is a theoretically sound framework for performance analysis that offers many advantages over traditional methods such as performance ratios and regression analysis. Largely the result of multidisciplinary research during the last three decades in economics, engineering and management, DEA is best described as an effective new way of visualizing and analyzing performance data. Besides, overseas information technology companies have aggressively tried to enter the domestic market. In the age of globalization and high competition, it is imperative that the system integration (SI) companies need to introduce the performance evaluation models of SI projects, including Capability Maturity Model and Software Process Improvement and Capability Determination, to gain a competitive advantage. Therefore, it makes our research regarding evaluation of SI projects very opportune. The purpose of the study is not only to evaluate efficiency of each project by DEA but also to gain insight into various factors such as project complexity, team members' man-months structure, and process index(project management index) that link to the projects performance.

• IE interfaces
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• v.25 no.1
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• pp.71-78
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• 2012

Most manufacturing companies participate in various types of active collaboration to enhance competitive advantages in their arenas. In this paper, we introduce a data warehouse system that is designed for manufacturing collaboration. Just as enterprise information systems, collaboration support systems also need functions of performance measurement and monitoring. For this reason, we devise a new approach to measuring and evaluating performance of manufacturing collaboration. Specifically, we first present a concept of process warehouses for manufacturing collaboration. Next, we design a data schema of collaborative process warehouses to store and monitor collaboration performances. Finally, we implement a prototype system to support performance management of manufacturing collaboration. The proposed system can be used to effectively maintain and continuously improve collaboration in manufacturing industry.

• Nuclear Engineering and Technology
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• v.52 no.2
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• pp.287-295
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• 2020

Group method of data handling (GMDH) is considered one of the earliest deep learning methods. Deep learning gained additional interest in today's applications due to its capability to handle complex and high dimensional problems. In this study, multi-layer GMDH networks are used to perform uncertainty quantification (UQ) and sensitivity analysis (SA) of nuclear reactor simulations. GMDH is utilized as a surrogate/metamodel to replace high fidelity computer models with cheap-to-evaluate surrogate models, which facilitate UQ and SA tasks (e.g. variance decomposition, uncertainty propagation, etc.). GMDH performance is validated through two UQ applications in reactor simulations: (1) low dimensional input space (two-phase flow in a reactor channel), and (2) high dimensional space (8-group homogenized cross-sections). In both applications, GMDH networks show very good performance with small mean absolute and squared errors as well as high accuracy in capturing the target variance. GMDH is utilized afterward to perform UQ tasks such as variance decomposition through Sobol indices, and GMDH-based uncertainty propagation with large number of samples. GMDH performance is also compared to other surrogates including Gaussian processes and polynomial chaos expansions. The comparison shows that GMDH has competitive performance with the other methods for the low dimensional problem, and reliable performance for the high dimensional problem.