• Tribology and Lubricants
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• v.17 no.3
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• pp.228-235
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• 2001

EHL analysis of connecting rod bearing is proposed which includes effects of temperature variation in lubrication film. Lubrication film temperature is treated as a time-dependent, two-dimensional variable which is averaged over the film thickness, while connecting rod big end temperature is assumed to be time-independent and three-dimensional. It is assumed that a portion of the heat generated by viscous dissipation in the lubrication film is absorbed by the film itself, and the remainder flows into the bearing surface. Mass-conserving cavitation algorithm is applied and the effect of variable viscosity is included to solve the Reynolds equation. Simulation results of the connecting rod bearing in internal combustion engine are presented. It is shown that the temperature variation has remarkable effects on the bearing performance. It is concluded that the EHL analysis considering effects of the temperature variation is strongly recommended to predict the connecting rod bearing performance in internal combustion engine.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.22 no.50
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• pp.127-137
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• 1999

This study is concerned with the loading problems in flexible manufacturing system(FMS). The loading problem in FMS is a complex one, when the number of machine and job is increased. It may be time-consuming and even impossible to achieve an optimal solution about this problem mathematically. Thus, a heuristic method is recommended in order to gain near-optimal solutions in a practically acceptable time. A new loading algorithm is developed with a multi-criterion objective of considering the workload unbalance, and maximizing the machine utilization, throughput for critical resources such as the number of tool slots and the number of working hours in a scheduling period and so on. The results of SAS analysis indicated that true average throughput of proposed heuristic loading statistically exceeds that of Shanker and Srinivasulus loading algorithm at the significance level of 0.1.

• The Transactions of the Korean Institute of Electrical Engineers C
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• v.52 no.1
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• pp.25-34
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• 2003

Gas insulated switchgear(GIS) is an important equipment in a substation. It is highly desirable to measure a partial discharge(PD) in GIS which is a symptom before insulation breakdown occurs. The issue is that the PD signal is weak and sensitive to external noise. In this paper, the algorithm for detection of PD in GIS using wavelet transform is proposed. The wavelet transform provides a direct quantitative measure of spectral content, "dynamic spectrum", in the time-frequency domain. The recommended mother wavelet is 'Daubechies' wavelet. 'db4', the most commonly applied mother wavelet in the power quality analysis, can be used most properly in disturbance phenomena which occurs rapidly for a short time. Through the procedure of wavelet transform, noise extraction and reconstruction, the signal is Analyzed to determine the magnitude of PD in GIS. In experimental results, we can know that partial discharge is exactly detected in combination of Dl and D2 using wavelet transform.transform.

• Korean Journal of Remote Sensing
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• v.19 no.5
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• pp.403-409
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• 2003

Since SPOT4 satellite contained VEGETATION 1 sensor launched, the noise in VEGETATION data was occasionally arisen a difficulty for the data traitement. Blind line noise types were studied in VEGETATION-l short wave infrared channel(SWIR). In order to provide a precis product, the procedure for removing this noise is strongly recommended. In the case that the blind values are clearly distinguished from contamination-free values a simple threshold method was applied, while a changeable threshold method was used for the blind value mixed with contamination-free values. New algorithm presented in this study is consists of two method for each type of SWIR blind. After removing blind line, there were again some residual pixels of blind, because the threshold is not determinated sufficiently low. Lower threshold could remove the blind line as well as the contamination-free pixels. Nevertheless, the results showed a good qualitative improvement as compared with other algorithm.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.9
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• pp.4684-4705
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• 2019

Collaborative filtering recommender systems are vulnerable to shilling attacks in which malicious users may inject biased profiles to promote or demote a particular item being recommended. To tackle this problem, many robust collaborative recommendation methods have been presented. Unfortunately, the robustness of most methods is improved at the expense of prediction accuracy. In this paper, we construct a robust Bayesian probabilistic matrix factorization model for collaborative filtering recommender systems by incorporating the detection of user anomaly rating behaviors. We first detect the anomaly rating behaviors of users by the modified K-means algorithm and target item identification method to generate an indicator matrix of attack users. Then we incorporate the indicator matrix of attack users to construct a robust Bayesian probabilistic matrix factorization model and based on which a robust collaborative recommendation algorithm is devised. The experimental results on the MovieLens and Netflix datasets show that our model can significantly improve the robustness and recommendation accuracy compared with three baseline methods.

• Journal of Multimedia Information System
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• v.8 no.1
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• pp.69-74
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• 2021

This paper accumulates the product structure data such as bond obligation ratio and investment ratio for variable insurance using crawling from the insurance company's API, also accumulates variable insurance income and project expenses for variable insurance using crawling from the API of life insurance association. From these accumulated data, the correlation coefficient between fund product and customer preference is calculated with an investment algorithm, and variable insurance funds by customer investment preference and product structure are recommended according to market conditions. From the simulation results, it is shown that the proposed variable insurance management system properly recommends and manages variable insurance according to customer preferences.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.24 no.10A
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• pp.1501-1506
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• 1999

DSRC(Dedicated Short Range Communications), which is a radio mobile communication protocol in ITS, is suited for traffic related information services. But in WAC(Wide-Area wireless communications), we could consider a conventional communication infrastructure in the case of supporting other applications besides ITS. Especially considering the current the trends to introduce wireless internet service into the mobile communication network, wireless internet service in ITS system is valuable. Although ITS LLC(Logical Link Control) protocols recommended by Europe and Japan are effective for traffic related services, it is not suitable for services related with geographical information, image or internet. That is because the data traffic characteristics is changed according to service types. Therefore we suggest a logical link control algorithm effective for traffic information related services as well as internet web service, and analyze its performance. As a result of numerical analysis and simulation, proposed algorithm shows larger performance improvements. For traffic information related services, the performance of DSRC LLC recommended by Europe and Japan is the same as that of proposed LLC protocol. However, for wireless internet web service, the performance of proposed protocol is much better than that of LLC protocol used in Europe and Japan.

• Anxiety and mood
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• v.12 no.1
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• pp.47-55
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• 2016

30% of patients with panic disorder (PD) show treatment-resistant and chronic waxing and waning course. Therefore, adequate treatment strategies for PD by evidence based pharmacotherapy and combined cognitive behavioral therapy (CBT) are recommended. Regarding how and why CBT for PD works, three hypotheses include the cognitive theory, anxiety control theory, and behavioral theory were discussed. The recent findings that the altered activation in frontal lobe is normalized after CBT, suggest a reduction of an altered top-down fear processing in the neural correlates of CBT in PD. In order to improve accessibility to CBT, brief CBT and internet based CBT for PD were suggested. Despite limitations of sample sizes and study design, most of studies suggest that brief CBT is more effective than control conditions, and even as equally effective as standard CBT. The evidences suggest that internet based CBT may not be significantly different from face-to-face CBT in reducing anxiety. Several advances within the field of third-wave CBT for PD have led to the development of new techniques based on mindfulness, such as mindfulness-based cognitive therapy and acceptance and commitment therapy. Based on Korean algorithm project for panic disorder, especially the psychological education and cognitive reconstruction components were recommended in CBT with PD.

• Journal of the Korean Society for Precision Engineering
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• v.23 no.11 s.188
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• pp.58-67
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• 2006

Due to the variety of signal processing and complicated mathematical analysis, it is not easy to accomplish 3D bin-picking with non-contact sensor. To solve this difficulties the reliable signal processing algorithm and a good sensing device has been recommended. In this research, 3D laser scanner and CCD camera is applied as a sensing device respectively. With these sensor we develop a two-step bin-picking method and reliable algorithm for the recognition of 3D bin object. In the proposed bin-picking, the problem is reduced to 2D intial recognition with CCD camera at first, and then 3D pose detection with a laser scanner. To get a good movement in the robot base frame, the hand eye calibration between robot's end effector and sensing device should be also carried out. In this paper, we examine auto-calibration technique in the sensor calibration step. A new thinning algorithm and constrained hough transform is also studied for the robustness in the real environment usage. From the experimental results, we could see the robust bin-picking operation under the non-aligned 3D hole object.

• Journal of Korea Society of Digital Industry and Information Management
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• v.6 no.3
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• pp.19-29
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• 2010

A marketing model is changed from a customer acquisition to customer retention and it is being moved to a way that enhances the quality of customer interaction to add value to our customers. Such personalization is emerging from this background. The Web site is accelerate the adoption of a personalization, and in contrast to the rapid growth of data, quantitative analytical experience is required. For the automated analysis of large amounts of data and the results must be passed in real time of personalization has been interested in technical problems. A recommendation algorithm is an algorithm for the implementation of personalization, which predict whether the customer preferences and purchasing using the database with new customers interested or likely to purchase. As recommended number of users increases, the algorithm increases recommendation time is the problem. In this paper, to solve this problem, a recommendation system based on clustering and dimensionality reduction is proposed. First, clusters customers with such an orientation, then shrink the dimensions of the relationship between customers to low dimensional space. Because finding neighbors for recommendations is performed at low dimensional space, the computation time is greatly reduced.