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

• 한국경영정보학회:학술대회논문집
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• 2007.11a
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• pp.343-348
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• 2007

In a customer-driven economy, single-business level analysis may not be sufficient. A large number of loosely interconnected participants who depend on one another for their mutual effectiveness and survival make up a business ecosystem. A business ecosystem is a holistic view of vital flows and relationships that sustain business activity. Businesses need to understand their physical condition in a business ecosystem to evaluate their capabilities. This paper defines the healthiness of business ecosystems in order to understand their competitiveness. It can give business an actionable guide. Healthy ecosystem means a business environment that has had four capabilities to survive. IT plays a leading part in healthy business ecosystem. It looks into business strategies and the role of IT in business ecosystems.

• Proceedings of the Korean Institute of Building Construction Conference
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• 2012.05a
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• pp.147-148
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• 2012

According to the analysis report of construction fall accident, situation not installed safety facilities caused the largest of disaster in temporary structure. Therefore, actionable measures will be needed identifying the installation of safety facilities immediately. In this study proposed plan by the safety facilities to effectively visualize, supervision can be easily for reduce fall accident. This system can be used BIM and augmented reality technology by combining in the field in real-time. Through this study, safety facilities management is improved and expected to prevent a accident.

• East Asian Journal of Business Economics (EAJBE)
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• v.12 no.2
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• pp.1-7
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• 2024

Purpose: This study delves into the application of the Ohlson 1995 valuation model, particularly addressing the intricacies of the "Other information" variable. Our goal is to pinpoint the most suitable variables for substitution within this category, focusing specifically on the Mongolian Stock Exchange (MSE) context. Research design, data, and methodology: Employing data spanning from 2012 to 2022 from 60 MSE-listed companies, we conduct a comprehensive analysis encompassing both financial and non-financial indicators. Through meticulous examination, we aim to identify which variables effectively substitute for the "Other information" component of the Ohlson model. Results: Our findings reveal significant outcomes. While all financial variables within the model exhibit importance, certain non-financial indicators, notably the company's level and state ownership participation, emerge as particularly influential in determining stock prices on the MSE. Conclusions: This study not only contributes to a deeper understanding of valuation dynamics within the MSE but also provides actionable insights for future research endeavors. By refining key variables within the Ohlson model, this research enhances the accuracy and efficacy of financial analysis practices. Moreover, the implications extend to practitioners, offering valuable insights into the determinants of stock prices in the MSE and guiding strategic decision-making processes.

• Journal of Korean Library and Information Science Society
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• v.37 no.1
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• pp.29-53
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• 2006

The continuous accumulation of printed materials prompts rethinking of library space problem and systematic preservation of library collection. To respond to this challenge, this study provides actionable models for the National Repository library and the Cooperative Repository Network. The development of the models is based on the analysis of overseas best practices as well as data derived from current state of public library cooperative network administered by the National Library of Korea. This study also offers a range of strategies for the operation of repository library system.

• Journal of Distribution Science
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• v.22 no.1
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• pp.79-94
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• 2024

Purpose: The popularity of social media has altered how customers interact with businesses, and an increasing number of customers prefer to voice their complaints on social media. Bystanders can observe the customer complaint process on social media, but the impact of transparency on bystanders remains uncertain. Therefore, this study established and verified a model for defining the effect of transparency and service recovery types on bystanders. Research Design and Methodology: In this study, we used the internet survey platform "So Jump" to collect data. And we validated three studies with SPSS 26.0 and Smart PLS 4.0. Result: First, we showed that the transparency process (vs. result) is more likely to increase customer forgiveness and E-loyalty and reduce E-NWOM intention among bystanders. Second, customer forgiveness also plays a complementary mediating role between transparency and E-loyalty, as well as between transparency and E-NWOM intention. Finally, we found a modest interaction effect between transparency (process vs. result) and service recovery types (psychological vs. tangible vs. hybrid) on bystanders' customer forgiveness and E-loyalty. Conclusions: This study provides actionable recommendations for how service managers can effectively employ social media as a means for distributing feedback information to manage service recovery in the future.

• Journal of the Korean Society of Systems Engineering
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• v.15 no.2
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• pp.72-78
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• 2019

Pathology is the motor that drives healthcare to understand diseases. The way pathologists diagnose diseases, which involves manual observation of images under a microscope has been used for the last 150 years, it's time to change. This paper is specifically based on tumor detection using deep learning techniques. Pathologist examine the specimen slides from the specific portion of body (e-g liver, breast, prostate region) and then examine it under the microscope to identify the effected cells among all the normal cells. This process is time consuming and not sufficiently accurate. So, there is a need of a system that can detect tumor automatically in less time. Solution to this problem is computational pathology: an approach to examine tissue data obtained through whole slide imaging using modern image analysis algorithms and to analyze clinically relevant information from these data. Artificial Intelligence models like machine learning and deep learning are used at the molecular levels to generate diagnostic inferences and predictions; and presents this clinically actionable knowledge to pathologist through dynamic and integrated reports. Which enables physicians, laboratory personnel, and other health care system to make the best possible medical decisions. I will discuss the techniques for the automated tumor detection system within the new discipline of computational pathology, which will be useful for the future practice of pathology and, more broadly, medical practice in general.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.9 no.6
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• pp.95-100
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• 2009

Nowadays there are many studies and there's huge development about USN/RFID which have great developmental potential to many kinds of applications. More and more real time application apply USN/RFID technology to identify data collect and locate objects. Wide deployment of USN/RFID will generate an unprecedented volume of primitive data in a short time. Duplication and redundancy of primitive data will affect real time performance of application. Thus, security applications must filter primitive data and correlate them for complex pattern detection and transform them to events that provide meaningful, actionable information to end application. In this paper, we design a ECA Rule system for security monitoring of exhibition. This system will process USN/RFID primitive data and event and perform data transformation. It's had applied each now in exhibition hall through this study and efficient data transmission and management forecast that is possible.

• Journal of Service Research and Studies
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• v.2 no.2
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• pp.35-43
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• 2012

Data mining is an interest area in all field around us not in any specific areas, which could be used applications in a number of areas heavily. In other words, it is used in the decision-making process, data and correlation analysis in hidden relations, for finding the actionable information and prediction. But some of the data sets contains many missing values in the variables and do not exist a large number of records in the data set. In this paper, missing values are handled in accordance with the model tree algorithm. Cholesterol value is applied for predicting. For the performance analysis, experiments are approached for each treatment. Through this, efficient alternative is presented to apply the missing data.

• Journal of Advanced Navigation Technology
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• v.22 no.6
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• pp.670-674
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• 2018

Social network service (SNS) related data including comments/text, images, videos, blogs, and user experiences contain a wealth of information which can be used to build recommendation systems for various clients' and provide insightful data/results to business analysts. Multimedia data, especially visual data like image and videos are the richest source of SNS data which can reflect particular region, and cultures values/interests, form a gigantic portion of the overall data. Mining such huge amounts of data for extracting actionable intelligence require efficient and smart data analysis methods. The purpose of this paper is to focus on this particular modality for devising ways to model, index, and retrieve data as and when desired.