• Journal of Korean Society of Industrial and Systems Engineering
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• v.43 no.4
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• pp.93-106
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• 2020

This research explores how imported automobile companies can develop their strategies to improve the outcome of their recalls. For this, the researchers analyzed patterns of recall demand, classified recall types based on the demand patterns and examined response strategies, considering plans on how to procure parts and induce customers to visit workshops, recall execution capacity and costs. As a result, recalls are classified into four types: U-type, reverse U-type, L- type and reverse L-type. Also, as determinants of the types, the following factors are further categorized into four types and 12 sub-types of recalls: the height of maximum demand, which indicates the volatility of recall demand; the number of peaks, which are the patterns of demand variations; and the tail length of the demand curve, which indicates the speed of recalls. The classification resulted in the following: L-type, or customer-driven recall, is the most common type of recalls, taking up 25 out of the total 36 cases, followed by five U-type, four reverse L-type, and two reverse U-type cases. Prior studies show that the types of recalls are determined by factors influencing recall execution rates: severity, the number of cars to be recalled, recall execution rate, government policies, time since model launch, and recall costs, etc. As a component demand forecast model for automobile recalls, this study estimated the ARIMA model. ARIMA models were shown in three models: ARIMA (1,0,0), ARIMA (0,0,1) and ARIMA (0,0,0). These all three ARIMA models appear to be significant for all recall patterns, indicating that the ARIMA model is very valid as a predictive model for car recall patterns. Based on the classification of recall types, we drew some strategic implications for recall response according to types of recalls. The conclusion section of this research suggests the implications for several aspects: how to improve the recall outcome (execution rate), customer satisfaction, brand image, recall costs, and response to the regulatory authority.

• Journal of Institute of Control, Robotics and Systems
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• v.7 no.4
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• pp.304-308
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• 2001

The increase of video data makes the demand of efficient retrieval, storing, and browsing technologies necessary. In this paper, a video segmentation method (scene change detection method, or shot boundary detection method) for the development of such systems is proposed. For abrupt cut detection, inter-frame similarities are computed using luminance and edge histograms and a cut is declared when the similarities are under th predetermined threshold values. A gradual scene change detection is based on the similarities between the current frame and the previous shot boundary frame. A correlation method is used to obtain universal threshold values, which are applied to various video data. Experimental results show that propose method provides 90% precision and 98% recall rates for abrupt cut, and 59% precision and 79% recall rates for gradual change.

• 한국데이터정보과학회:학술대회논문집
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• 2004.10a
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• pp.43-51
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• 2004

The reliability guarantee insurance policy for parts and materials was introduced to the market in 2003. This policy indemnifies manufactures of products for the repair/failure costs, recall expenses of products and business interruption losses found to be defective by users or demand companies during the terms of guarantee and after the user acquired physical possession of the product. In this paper, owing to the nature of the policy, we propose a new rate-making system considering the type of product and industry, quality control circumstances, record of guarantee performance, and exposure.

• Journal of Internet Computing and Services
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• v.11 no.6
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• pp.111-122
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• 2010

Since educating digital convergence is to unite various sciences and technologies with computer as the central figure, it has different range and methods of education. Therefore, it has problems with recommending limited conceptual information because of difficulties to standardize education plan and teaching strategies. In this paper, I propose education plan and teaching strategy system by using Spearman correlation coefficients. This system is to find a solution against disadvantage of recommending limited conceptual information by ranking relations of teaching strategies from the information based on the demand of industrial and academic fields, and then provides lists of teaching strategy information suitable for user's atmosphere and characteristics. Performance test is to compare effects of precision and recall with existing service systems. The test shows 90.4% of precision and 77.6% of recall.

• Transactions of the Korean Society of Automotive Engineers
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• v.21 no.4
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• pp.62-69
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• 2013

Visual demands associated with in-vehicle display usage and text messaging distract a driver's visual attention from the roadway. To minimize eyes-off-the-road demands, voice interaction systems are widely introduced. Under cognitively distracted condition, however, awareness of the operating environment will be degraded although the driver remains oriented to the roadway. It is also know that the risk of inattentive driving varies with age, thus systematic analysis of driving risks is required for the older drivers. This paper aims to understand the age-related driving performance degradation and visual attention changes under auditory cognitive demand which consists of three graded levels of cognitive complexity. In this study, two groups, aged 25-35 and 60-69, engaged in a delayed auditory recall task, so called N-back task, while driving a simulated highway. Comparisons of younger and older drivers' driving performance including mean speed, speed variability and standard deviation of lane position, and gaze dispersion changes, which consist of x-axis and y-axis of visual attention, were conducted. As a result, it was observed that gaze dispersion decreased with each level of demand, demonstrating that these indices can correctly rank order cognitive workload. Moreover, gaze dispersion change patterns were quite consistent in younger and older age groups. Effects were also observed on driving performance measures, but they were subtle, nonlinear, and did not effectively differentiate the levels of cognitive workload.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.1
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• pp.38-57
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• 2016

Service discovery is one of the major challenges in cloud computing environment with a large number of service providers and heterogeneous services. Non-uniform naming conventions, varied types and features of services make cloud service discovery a grueling problem. With the proliferation of cloud services, it has been laborious to find services, especially from Internet-based service repositories. To address this issue, services are crawled and clustered according to their similarity. The clustered services are maintained as a catalogue in which the data published on the cloud provider's website are stored in a standard format. As there is no standard specification and a description language for cloud services, new efficient and intelligent mechanisms to discover cloud services are strongly required and desired. This paper also proposes a key-value representation to describe cloud services in a formal way and to facilitate matching between offered services and demand. Since naïve users prefer to have a query in natural language, semantic approaches are used to close the gap between the ambiguous user requirements and the service specifications. Experimental evaluation measured in terms of precision and recall of retrieved services shows that the proposed approach outperforms existing methods.

• Journal of Integrative Natural Science
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• v.14 no.3
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• pp.107-115
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• 2021

The demand for traceability of meat and livestock supply chains is growing due to the high-profile incidents of hormonal contamination. E. coli, dioxin, BSE, and antibiotics have been recorded. In this paper, we present blockchain-based poultry information management system design and implementation using Hyperledger Fabric. The proposed system offers accurate, decentralized, immutable and consensus process that promote trust and transparency between stakeholders. The main tasks of the system include the recording of the information associated with poultry rearing (from a hatchery to a farm), status report of the farm activities on a monthly basis. The system can track movement of docks through the supply chain until delivery to the final consumer through the retail outlet. The ability to trace the source of livestock product through all the stages of rearing/production, processing and distribution is essential for ensuring food safety as recall of contaminated product can easily be done thereby increasing consumer confidence.

• International Journal of Computer Science & Network Security
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• v.23 no.3
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• pp.57-66
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• 2023

Rice is an important food crop for most of the population in the world and it is largely cultivated in Pakistan. It not only fulfills food demand in the country but also contributes to the wealth of Pakistan. But its production can be affected by climate change. The irregularities in the climate can cause several diseases such as brown spots, bacterial blight, tungro and leaf blasts, etc. Detection of these diseases is necessary for suitable treatment. These diseases can be effectively detected using deep learning such as Convolution Neural networks. Due to the small dataset, transfer learning models such as vgg16 model can effectively detect the diseases. In this paper, vgg16, inception and xception models are used. Vgg16, inception and xception models have achieved 99.22%, 88.48% and 93.92% validation accuracies when the epoch value is set to 10. Evaluation of models has also been done using accuracy, recall, precision, and confusion matrix.

• Journal of Korean Society of Archives and Records Management
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• v.22 no.4
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• pp.25-43
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• 2022

The ultimate record management's purpose is preservation and utilization. However, the National Archives of Korea (NAK)s Portal has problems such as search system aging and search tools dualization. As a result, the users' search satisfaction is not satisfied, and the improvement demand increases. This study aimed to evaluate the NAK's search quality as a preliminary study for NAK search system advancement. To this end, we analyzed the current status of CAMS and NAK's Portal. Then, we established the test sets and evaluated the NAK's Portal quality from the user's point of view. Evaluation results were analyzed using Precision, Recall, F-score, and MRR. The analysis results showed that the overall search performance was low, particularly in the "advanced subject search," which showed low performance in Precision, Recall, and MRR. Thus, improvement is urgently needed. The test sets established for this study are expected to be used as a basis for objectively measuring the improvement of the search performance after the NAK search system advancement.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.25 no.4
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• pp.849-861
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• 2015

As the rise in popularity of online games, the users start exchanging rare items for real money. As RMT (Real Money Trade) is prevalent, GFG (Gold Farming Group) who abuse RMT shows up. GFG causes social problems such as identity theft, privacy leaks. Because they needs many bot characters to gather game items. In addition, GFG induce RMT that makes in-game problems such as a destroying game economy, account hacking. Therefore, It is very important work to collapse GFG at the perspective of social and in-game. In this paper, we proposed a fundamental method for detecting RMT buyers for the collapse of GFG at the perspective of buyer by Law of Demand and Supply. We found two type of RMT by analyzing actual game data and detected RMT buyers with high recall ratio of 98% by ruled-based detection.