• Journal of Sensor Science and Technology
• /
• v.25 no.1
• /
• pp.13-19
• /
• 2016

Nowadays, most major automobile manufacturers are very interested, and actively involved, in developing driver alcohol detection system for safety (DADSS) that serves to prevent driving under the influence. DADSS measures the blood alcohol concentration (BAC) from the driver's breath and limits the ignition of the engine of the vehicle if the BAC exceeds the reference value. In this study, to optimize the sensor array of the DADSS, we selected sensors by using three different methods, configured the sensor arrays, and then compared their performance. The Wilks' lambda, stepwise elimination and filter method (using a principal component) were used as the sensor selection methods [2,3]. We compared the performance of the arrays, by using the selectivity and sensitivity as criteria, and Sammon mapping for the analysis of the cluster type of each gas. The sensor array configured by using the stepwise elimination method exhibited the highest sensitivity and selectivity and yielded the best visual result after Sammon mapping.

• Proceedings of the Korea Inteligent Information System Society Conference
• /
• 2007.05a
• /
• pp.218-225
• /
• 2007

Recommendation system is one way of implementing personalized service. The collaborative filtering is one of the major techniques that have been employed for recommendation systems. It has proven its effectiveness in the recommendation systems for such domain as motion picture or music. However, it has some limitations, i.e., sparsity and scalability. In this research, as one way of overcoming such limitations, we proposed the stepwise collaborative filtering method. To show the practicality of our proposed method, we designed and implemented a movie recommendation system which we shall call Step_CF, and its performance was evaluated using MovieLens data. The performance of Step_CF was better than that of Basic_CF that was implemented using the original collaborative filtering method.

• Communications for Statistical Applications and Methods
• /
• v.23 no.1
• /
• pp.57-70
• /
• 2016

Type-II progressive censoring is one of the censoring methods frequently used in clinical studies, reliability trials, quality control of products and industrial experiments. Sometimes in Type-II progressive censoring experiments, the failure rate is low so the waiting time to observe the $m^{th}$ failure will be very long; however, the experimenter may have to terminate the experiment before a predetermined time. In this article, if two generalized types of Type-II progressive censoring are reminded, we then make some changes in the removal method of Type-II progressive censoring such that without reducing the deduction quality, the termination time of the experiment decreases. This can be done with decreasing withdraws throughout the steps of the experiment with a special reasonable method. A simulation study is done and the results are tabulated at the end of this article for a comparison between introduced method and Type-II progressive censoring.

• Mass Spectrometry Letters
• /
• v.9 no.1
• /
• pp.30-36
• /
• 2018

A quantitation method for free amino acids in human serum was developed using a stepwise-dilution method and a bimodal cation exchange (CEX)/hydrophilic interaction liquid chromatography (HILIC)-tandem mass spectrometry system equipped with an electrospray ionization source (ESI/MS/MS). This method, which was validated using quality control samples, was optimized for enhanced selectivity and sensitivity. Dithiothreitol (DTT) was used as a reducing agent to prevent the oxidation of a serum sample ($50{\mu}L$), which was then subjected to stepwise dilution using 3, 30, and 90 volumes of acetonitrile containing 0.1% formic acid. Chromatographic separation was performed on an Imtakt Intrada Amino Acid column ($50mm{\times}3mm$, $3{\mu}m$) in mixed mode packed with CEX and HILIC ligands embedded in the stationary phase. Underivatized free amino acids were eluted and separated within 10 min. As a result of the validation, the precision and accuracy for the inter- and intraday assays were determined as 2.11-11.51% and 92.82-109.40%, respectively. The lowest limit of quantification (LLOQ) was $0.5-4.0{\mu}g/mL$ and the matrix effect was 80.22-115.93%. The proposed method was successfully applied to the quantitative analysis of free amino acids in human serum.

• Knowledge Management Research
• /
• v.13 no.5
• /
• pp.43-64
• /
• 2012

Emerging technologies have significant implications in establishing competitive advantages and are characterized by continuous rapid development. Efficient benchmarking is more and more important in the development of emerging technologies. Similar input level and importance are two necessary criteria need to be considered for emerging technology's benchmarking. In this study, we proposed a sequential use of self-organizing map(SOM), data envelopment analysis(DEA) and analytical hierarchy process(AHP) method for the stepwise benchmarking of emerging technology. The proposed method uses two-level SOM to cluster the emerging technologies with similar required input levels together, then, in each cluster, uses DEA-BCC model to evaluate the efficiencies of the emerging technologies and do tier analysis to form tiers. On each tier, AHP rating method is used to calculate each emerging technology's importance priority. The optimal benchmarking path of each cluster is established by connecting the emerging technologies with the highest importance priority. In order to validate the proposed method, we apply it to a case of biotechnology. The result shows the proposed method can overcome difficulties in benchmarking, select suitable benchmarking targets and make the benchmarking process more efficient and reasonable.

• KIEE International Transactions on Power Engineering
• /
• v.2A no.3
• /
• pp.121-128
• /
• 2002

This study proposes a new method for transmission system expansion planning using fuzzy integer programming. It presents stepwise cost characteristics analysis which is a practical condition of an actual system. A branch and bound method which includes the network flow method and the maximum flow - minimum cut set theorem has been used in order to carry out the stepwise cost characteristics analysis. Uncertainties of the permissibility of the construction cost and the lenient reserve rate and load forecasting of expansion planning have been included and also processed using the fuzzy set theory in this study. In order to carry out the latter analysis, the solving procedure is illustrated in detail by the branch and bound method which includes the network flow method and maximum flow-minimum cut set theorem. Finally, case studies on the 21- bus test system show that the algorithm proposed is efficiently applicable to the practical expansion planning of transmission systems in the future.

• Journal of the Korean Institute of Intelligent Systems
• /
• v.19 no.4
• /
• pp.574-579
• /
• 2009

There have been much difficulties to construct an optimized neural network in complex nonlinear regression problems such as selecting the networks structure and avoiding overtraining problem generated by noise. In this paper, we propose a stepwise constructive method for neural networks using a flexible incremental algorithm. When the hidden nodes are added, the flexible incremental algorithm adaptively controls the number of hidden nodes by a validation dataset for minimizing the prediction residual error. Here, the ELM (Extreme Learning Machine) was used for fast training. The proposed neural network can be an universal approximator without user intervene in the training process, but also it has faster training and smaller number of hidden nodes. From the experimental results with various benchmark datasets, the proposed method shows better performance for real-world regression problems than previous methods.

• Journal of the Korean Data and Information Science Society
• /
• v.21 no.3
• /
• pp.513-521
• /
• 2010

Most of universities have carried out course evaluation to apply the performance appraisal for professor. But, course evaluation depends on characteristics of each class such as class size, type of lecture, evaluator's grade and so on. As the results, such characteristics of each class lead to serious bias which makes lecturers distrust the course evaluation results. Hence, we propose a equating method for the course evaluation by regression analysis which use stepwise variable selection. And we compare proposed method with the other method by Cho et al. (2009) with respect to efficiencies. Also we give the example to which the method is applied.

• The Journal of the Institute of Internet, Broadcasting and Communication
• /
• v.21 no.4
• /
• pp.183-188
• /
• 2021

Collaborative filtering based recommender systems are currently indispensable function of commercial systems in various fields, being a useful service by providing customized products that users will prefer. However, there is a high possibility that the prediction of preferrable products is inaccurate, when the user's rating data are insufficient. In order to overcome this drawback, this study suggests a stepwise method for prediction of product ratings. If the application conditions of the prediction method corresponding to each step are not satisfied, the method of the next step is applied. To evaluate the performance of the proposed method, experiments using a public dataset are conducted. As a result, our method significantly improves prediction and precision performance of collaborative filtering systems employing various conventional similarity measures and outperforms performance of the previous methods for solving rating data sparsity.

• Korean Journal of Computational Design and Engineering
• /
• v.4 no.2
• /
• pp.100-109
• /
• 1999

The bearing design includes the steps of selection bering type, selection bearing subtype, and determining the peripheral equipments. In this paper decision making methodologies are compared to propose a stepwise decision methodology to the bearing selection problem. An artificial neural network trained with design cases is used for selecting a bearing type in the first step. Then the subtype of the bearing is selected using the weighting method, high is a kind of multi-criteria decision making method. Finally, the types of peripheral equipments such as lubrication devices, seals and bearing housings are determined using a rule-based expert system.