• The Transactions of The Korean Institute of Electrical Engineers
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• v.58 no.10
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• pp.1855-1860
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• 2009

This paper caused a distribution utility to generation of analysis fault several cases on the ground of substation in a energy meter three phase current, voltage data measurement to fault type and characteristics. Mother wavelet transformation of suitable to method algorithm from the distribution utility to generation of fault in image impedance etc several parameter for utility characteristics effective to probatory fault point extraction.

• KIPS Transactions on Software and Data Engineering
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• v.4 no.11
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• pp.499-508
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• 2015

High utility itemset(HUI) mining refers to the discovery of itemsets with high utilities which are not less than a user-specified minimum utility threshold, by considering both the quantities and weight factors of items in a transaction database. Recently the utility-list based HUI mining algorithms have been proposed to avoid numerous candidate itemsets and the algorithms need the costly join operations. In this paper, we propose a new HUI mining algorithm, using the utility-list with additional attributes of transaction utility and common utility of itemsets. The new algorithm decreases the number of join operations and efficiently prunes the search space. Experimental results on both synthetic and real datasets show that the proposed algorithm outperforms other recent algorithms in runtime, especially when datasets are dense or contain many long transactions.

• Journal of Information Technology Applications and Management
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• v.15 no.4
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• pp.21-36
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• 2008

As the great disturbance from abusing credit cards in Korea becomes stabilized, credit card companies need to interpret credit-card delinquents classification models from the viewpoint of profit. However, hit ratio which has been used as a measure of goodness of classification models just tells us how much correctly they classified rather than how much profits can be obtained as a result of using classification models. In this research, we tried to develop a new utility-based measure from the viewpoint of profit and then used this new measure to analyze two classification models(Neural Networks and Decision Tree models). We found that the hit ratio of neural model is higher than that of decision tree model, but the utility value of decision tree model is higher than that of neural model. This experiment shows the importance of utility based measure for credit-card delinquents classification models. We expect this new measure will contribute to increasing profits of credit card companies.

• ETRI Journal
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• v.43 no.6
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• pp.1024-1037
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• 2021

Mining high utility itemsets (HUIs) from transaction databases considers such factors as the unit profit and quantity of purchased items. Two-phase tree-based algorithms transform a database into compressed tree structures and generate candidate patterns through a recursive pattern-growth procedure. This procedure requires a lot of memory and time to construct conditional pattern trees. To address this issue, this study employs two compressed tree structures, namely, Utility Count Tree and String Utility Tree, to enumerate valid patterns and thus promote fast utility computation. Furthermore, the study presents an algorithm called single-phase utility computation (SPUC) that leverages these two tree structures to mine HUIs in a single phase by incorporating novel pruning strategies. Experiments conducted on both real and synthetic datasets demonstrate the superior performance of SPUC compared with IHUP, UP-Growth, and UP-Growth+algorithms.

• Journal of the Korean Data and Information Science Society
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• v.23 no.2
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• pp.365-374
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• 2012

Weather derivatives designed to manage casual changes of weather, as opposed to catastrophic risks of weather, are relatively a new class of financial instruments. There are still many theoretical and practical challenges to the effective use of these instruments. The objective of this paper is to develop a pricing approach for valuing weather derivatives and presents a case study that is practical enough to be used by the risk managers of electrical utility firms. Utilizing daily average temperature data of Guangzhou, China from $1^{st}$ January 1978 to $31^{st}$ December 2010, this paper adopted a univariate time series model to describe weather behavior dynamics and calculates equilibrium prices for weather futures and options for an electrical utility firm in the region. The results imply that the risk premium is an important part of derivatives prices and the market price of risk affects option values much more than forward prices. It also demonstrates that weather innovation as well as weather risk management significantly affect the utility's financial outcomes.

• Interdisciplinary Bio Central
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• v.2 no.2
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• pp.3.1-3.4
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• 2010

In the present research, we assessed the utility of the structural information of drugs for predicting human in vivo intrinsic clearance from in vitro intrinsic clearance data obtained by human hepatic microsome experiment. To compare with the observed intrinsic clearance, human intrinsic clearance values for 51 drugs were estimated by the classical methods using in vivo-in vitro scale-up and by the new methods using the in vitro experimental data and selected molecular descriptors of drugs by the forward selection technique together. The results showed that taking consideration of molecular descriptors into prediction from in vitro experimental data could improve the prediction accuracy. The in vitro experiment is very useful when the data can estimate in vivo data accurately since it can reduce the cost of drug development. Improvement of prediction accuracy in the present approach can enhance the utility of in vitro data.

• Journal of Information Processing Systems
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• v.5 no.3
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• pp.151-158
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• 2009

This paper proposes a utility-based data rate allocation algorithm to provide high-quality mobile video streaming over femtocell networks. We first derive a utility function to calculate the optimal data rates for maximizing the aggregate utilities of all mobile users in the femtocell. The total sum of optimal data rates is limited by the link capacity of the backhaul connections. Furthermore, electromagnetic cross-talk poses a serious problem for the backhaul connections, and its influence passes on to mobile users, as well as causing data rate degradation in the femtocell networks. We also have studied a fixed margin iterative water-filling algorithm to achieve the target data rate of each backhaul connection as a counter-measure to the cross-talk problem. The results of our simulation show that the algorithm is capable of minimizing the transmission power of backhaul connections while guaranteeing a high overall quality of service for all users of the same binder. In particular, it can provide the target data rate required to maximize user satisfaction with the mobile video streaming service over the femtocell networks.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.8
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• pp.3328-3349
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• 2020

With rapid development of ubiquitous computing and location-based services (LBSs), human trajectory data and associated activities are increasingly easily recorded. Inappropriately publishing trajectory data may leak users' privacy. Therefore, we study publishing trajectory data while preserving privacy, denoted privacy-preserving activity trajectories publishing (PPATP). We propose S-PPATP to solve this problem. S-PPATP comprises three steps: modeling, algorithm design and algorithm adjustment. During modeling, two user models describe users' behaviors: one based on a Markov chain and the other based on the hidden Markov model. We assume a potential adversary who intends to infer users' privacy, defined as a set of sensitive information. An adversary model is then proposed to define the adversary's background knowledge and inference method. Additionally, privacy requirements and a data quality metric are defined for assessment. During algorithm design, we propose two publishing algorithms corresponding to the user models and prove that both algorithms satisfy the privacy requirement. Then, we perform a comparative analysis on utility, efficiency and speedup techniques. Finally, we evaluate our algorithms through experiments on several datasets. The experiment results verify that our proposed algorithms preserve users' privay. We also test utility and discuss the privacy-utility tradeoff that real-world data publishers may face.

• Korean Journal of Clinical Pharmacy
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• v.19 no.2
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• pp.153-158
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• 2009

Background: Patients with chronic myeloid leukemia(CML) have different health status according to their disease conditions such as chronic phase(CP), accelerated phase(AP), blast crisis(BC), stage with MCyR(Major Cytogenetic Response); therefore, every patient has different quality of life related to their disease condition. Objectives: To measure the quality of life, this study compared and analyzed the utility weight in patients with CML. This study also evaluated the utility weight in order to view comparisons between the quality of life in a patient with CML to a patient with diabetes, which is a representative chronic disease. Methods: The disease scenario described 5 symptoms of the CP, AP, BC of the CML, the CML which gets the MCyR and the diabetes. Utility weight was developed using the EQ-5D method. All statistical data were analyzed by STATA 10.0 Results: 57 nurses(95%) out of 60 answered the questionnaire. In CP, the utility weight was 0.7946. In AP, it was 0.5301. and in BC, it was -0.2793. Survey data indicate that the worse the condition of a disease, the lower the utility weight. In case of the CML which gets the MCyR, the result was 0.7731(95% CI : 0.7384 - 0.8079). The general diabetes which has no complicating disease, the utility weight was 0.7481(95% CI : 0.6983 - 0.7978). Based on the result, it is evident that those with MCyR are not significantly different from people with general diabetes (p=0.4096) in views of the quality of life.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.20 no.2
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• pp.171-181
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• 2002

As the result of the analysis of the underground utility map made before, we could have divided the kind of errors into the two types, position error of geometric data and attribute error and knew the fact that mainly position error is derived from the process of detecting and surveying the underground utility, and attribute is inputting data. In this study we showed the way improving accuracy in detecting and surveying underground utility by field test, and the way to reduce attribute error by process refinement.