• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.16 no.4
• /
• pp.1146-1165
• /
• 2022

A huge amount of data in the form of videos and images is being produced owning to advancements in sensor technology. Use of low performance commodity hardware coupled with resource heavy image processing and analyzing approaches to infer and extract actionable insights from this data poses a bottleneck for timely decision making. Current approach of GPU assisted and cloud-based architecture video analysis techniques give significant performance gain, but its usage is constrained by financial considerations and extremely complex architecture level details. In this paper we propose a data pipeline system that uses open-source tools such as Apache Spark, Kafka and OpenCV running over commodity hardware for video stream processing and image processing in a distributed environment. Experimental results show that our proposed approach eliminates the need of GPU based hardware and cloud computing infrastructure to achieve efficient video steam processing for face detection with increased throughput, scalability and better performance.

• Journal of KIISE
• /
• v.42 no.8
• /
• pp.1010-1021
• /
• 2015

Big data systems are widely used to collect large-scale log data, so it is very important for these systems to operate with a high level of performance. However, the current Hadoop-based big data system architecture has a problem in that its performance is low as a result of redundant processing. This paper solves this problem by improving the design of the Hadoop system architecture. The proposed architecture uses the batch-based data collection of the existing architecture in combination with a single processing method. A high level of performance can be achieved by analyzing the collected data directly in memory to avoid redundant processing. The proposed architecture guarantees system expandability, which is an advantage of using the Hadoop architecture. This paper confirms that the proposed architecture is approximately 30% to 35% faster in analyzing and processing data than existing architectures and that it is also extendable.

• IE interfaces
• /
• v.25 no.1
• /
• pp.13-20
• /
• 2012

Recently, the collaboration among small and medium-sized enterprises(SMEs) has been recognized as an effective competitive tool. As several systems have been developed to boost the collaboration, it is necessary to analyze the effectiveness of the systems in terms of their contribution to enhance operational performance of SMEs through objective and quantitative validation. In particular, the analysis for SMEs rather than large-scaled enterprises has not received much attention due to lack of relevant information and difficulty of collecting data. This paper presents a framework for analyzing the effectiveness of the collaboration support system, called i-manufacturing hub, which has been implemented by Korean government. Identification of influential factors to the effectiveness of collaboration hub, and constructing necessary hypotheses are proposed. To overcome the difficulty in data collection only by means of surveys through subjective questionnaires, we exploit system log data that are generated while SMEs use the system. As an initial phase to analyze the effectiveness through hypothesis validation, we discuss several interesting observations and challenges in the direction of enhancing collaboration among SMEs for better operational performance improvement and more participation in the collaboration hub.

• Journal of the Korean Operations Research and Management Science Society
• /
• v.26 no.3
• /
• pp.1-20
• /
• 2001

The amount of financial information in sophisticated large data bases is huge and makes interfirm performance comparisons very difficult or at least very time consuming. The purpose of this paper is to investigate whether neural networks in the form of self-organizing maps (SOM) can be successfully employed to manage the complexity for competitive financial benchmarking. SOM is known to be very effective to visualize results by projecting multi-dimensional financial data into two-dimensional output space. Using the SOM, we overcome the problems of finding an appropriate underlying distribution and the functional form of data when structuring and analyzing a large data base, and show an efficient procedure of competitive financial benchmarking through clustering firms on two-dimensional visual space according to their respective financial competitiveness. For the empirical purpose, we analyze the data base of annual reports of 100 Korean listed companies over the years 1998, 1999, and 2000.

• Proceedings of the Korean Institute of Building Construction Conference
• /
• 2023.05a
• /
• pp.243-244
• /
• 2023

Noise, dust, etc. caused by road pavement cutting work, which frequently occurs in new construction or reconstruction of buildings, construction of complexes, etc., are environmental hazards and cause civil complaints. Recently, an eco-friendly pavement cutter is being developed to make the work low in noise and dust, however, the on-site cutting performance of the equipment has not been quantified. In this study, in order to derive a standard value for comparing the cutting performance of the eco-friendly cutter under development, a conventional pavement cutter was applied to four residential sites in Seoul and Gyeonggi-do, and the cutting data was collected. As a result of analyzing the collected data, the conventional pavement cutter showed a cutting performance of 12.3 to 20.2 sec/m, and the average was 27.2 sec/m. In the future, additional cutting experiments with various mixing ratios, materials, and depths are planned to confirm the performance of conventional pavement cutter in more detail.

• Journal of Information Technology Applications and Management
• /
• v.14 no.2
• /
• pp.169-187
• /
• 2007

Most private and public organizations use, for their works, information systems that change their organizational structures. Nowadays, many organizations have team-based structures where typically a cross functional team is in charge of a business process. The effective communication among the members of a team is an important factor of team performance in that communication facilitates trust building, knowledge exchange, change acceptance, and safety improvement. This paper reviews methods for analyzing communication among team members from three aspects such as the content, the amount, and the structure of communication.

• Journal of Korean Institute of Industrial Engineers
• /
• v.23 no.4
• /
• pp.755-767
• /
• 1997

Analyzing autocorrelated data set is still an open problem. Developing on easy and efficient method for severe positive correlated data set, which is common in simulation output, is vital for the simulation society. Bootstrap is on easy and powerful tool for constructing non-parametric inferential procedures in modern statistical data analysis. Conventional bootstrap algorithm requires iid assumption in the original data set. Proper choice of resampling units for generating replicates has much to do with the structure of the original data set, iid data or autocorrelated. In this paper, a new bootstrap resampling scheme is proposed to analyze the autocorrelated data set : the Threshold Bootstrap. A thorough literature search of bootstrap method focusing on the case of autocorrelated data set is also provided. Theoretical foundations of Threshold Bootstrap is studied and compared with other leading bootstrap sampling techniques for autocorrelated data sets. The performance of TB is reported using M/M/1 queueing model, else the comparison of other resampling techniques of ARMA data set is also reported.

• The Journal of Asian Finance, Economics and Business
• /
• v.8 no.3
• /
• pp.69-77
• /
• 2021

The objective of this research is to explore the inconclusive theoretical and empirical association between institutional ownership and firm performance in the context of emerging Pakistani economy. The data set consists of all the non-financial firms listed on the Pakistan Stock Exchange (PSX). Annual data set covers the period ranging from 2010 to 2015. However, the econometric analysis does not include those firms with incomplete data. Thus the final data set comprised of an unbalanced panel of sample of 276 firms with 1231 firms years observations. Data related to the institutional ownership and other variables taken for the study were extracted through the annual financial reports of the firms. The research used Tobin's Q as a proxy of market measure of firm performance and tested the endogenous relation with institutional ownership through OLS and 2SLS approach. The study also applied Durbin-Wu-Hausman test to determine the endogeneity before analyzing the 2SLS model. The Durbin-Wu-Hausman Test (DWH) conform the endogenous link between institutional ownership and performance and vice versa. The results derived from 2SLS also confirm a highly significant relationship and two way direct proportional relationships between the institutional investment and corporate performance in the studied companies.

• Proceedings of the KIEE Conference
• /
• 2006.07b
• /
• pp.1099-1100
• /
• 2006

The running of the electric train are done by powering, breaking and coasting. Powering to start and accelerate the rolling stock means driving the three-phase electric induction motors controlled by VVVF inverters which are connected to overhead power line directly(DC) or indirectly(AC, DC/AC). Breaking is achieved by blending control which is the proportional combination between regenerative breaking of VVVF inverter and air pressure control of breaking operating unit(BOU). Therefore, Data obtained during two operation are very important items to evaluate the running performance of RS. This paper has investigated in real time data acquired from VVVF inverter and measured by pressure sensor directly connected to air breaking line(motor car and trailer car). By analyzing data in the region of time and frequency, fundamental methods for eavaluating the running performance of RS quantitatively and objectively have been suggested.

• Korea Journal of Hospital Management
• /
• v.28 no.2
• /
• pp.66-78
• /
• 2023

Purposes: This study explored the difference analysis of financial performance and technological innovation according to the ESG management activities of healthcare companies based on the time before and after the mandatory ESG management reporting of listed Chinese healthcare companies in China. Methodology: This study collected ESG management activities, corporate financial performance, and technological innovation data of Chinese listed healthcare companies by using Bloomberg Database and China-listed company reports to collect data for analyzing differences between groups through T-test. Findings: ESG activities in the healthcare industry have a certain impact on corporate financial performance, but have no impact on corporate technological innovation. Like the world trend, the ESG activities and financial results of China's healthcare industry have shown a positive development direction in recent years, and ESG scores are rising. Practical Implication: Since 2018, ESG activities in China's healthcare industry have flourished, and ESG activities and financial performance have developed in a positive direction.