• Title/Summary/Keyword: Optimized algorithm

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Analysis of shopping website visit types and shopping pattern (쇼핑 웹사이트 탐색 유형과 방문 패턴 분석)

  • Choi, Kyungbin;Nam, Kihwan
    • Journal of Intelligence and Information Systems
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    • v.25 no.1
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    • pp.85-107
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    • 2019
  • Online consumers browse products belonging to a particular product line or brand for purchase, or simply leave a wide range of navigation without making purchase. The research on the behavior and purchase of online consumers has been steadily progressed, and related services and applications based on behavior data of consumers have been developed in practice. In recent years, customization strategies and recommendation systems of consumers have been utilized due to the development of big data technology, and attempts are being made to optimize users' shopping experience. However, even in such an attempt, it is very unlikely that online consumers will actually be able to visit the website and switch to the purchase stage. This is because online consumers do not just visit the website to purchase products but use and browse the websites differently according to their shopping motives and purposes. Therefore, it is important to analyze various types of visits as well as visits to purchase, which is important for understanding the behaviors of online consumers. In this study, we explored the clustering analysis of session based on click stream data of e-commerce company in order to explain diversity and complexity of search behavior of online consumers and typified search behavior. For the analysis, we converted data points of more than 8 million pages units into visit units' sessions, resulting in a total of over 500,000 website visit sessions. For each visit session, 12 characteristics such as page view, duration, search diversity, and page type concentration were extracted for clustering analysis. Considering the size of the data set, we performed the analysis using the Mini-Batch K-means algorithm, which has advantages in terms of learning speed and efficiency while maintaining the clustering performance similar to that of the clustering algorithm K-means. The most optimized number of clusters was derived from four, and the differences in session unit characteristics and purchasing rates were identified for each cluster. The online consumer visits the website several times and learns about the product and decides the purchase. In order to analyze the purchasing process over several visits of the online consumer, we constructed the visiting sequence data of the consumer based on the navigation patterns in the web site derived clustering analysis. The visit sequence data includes a series of visiting sequences until one purchase is made, and the items constituting one sequence become cluster labels derived from the foregoing. We have separately established a sequence data for consumers who have made purchases and data on visits for consumers who have only explored products without making purchases during the same period of time. And then sequential pattern mining was applied to extract frequent patterns from each sequence data. The minimum support is set to 10%, and frequent patterns consist of a sequence of cluster labels. While there are common derived patterns in both sequence data, there are also frequent patterns derived only from one side of sequence data. We found that the consumers who made purchases through the comparative analysis of the extracted frequent patterns showed the visiting pattern to decide to purchase the product repeatedly while searching for the specific product. The implication of this study is that we analyze the search type of online consumers by using large - scale click stream data and analyze the patterns of them to explain the behavior of purchasing process with data-driven point. Most studies that typology of online consumers have focused on the characteristics of the type and what factors are key in distinguishing that type. In this study, we carried out an analysis to type the behavior of online consumers, and further analyzed what order the types could be organized into one another and become a series of search patterns. In addition, online retailers will be able to try to improve their purchasing conversion through marketing strategies and recommendations for various types of visit and will be able to evaluate the effect of the strategy through changes in consumers' visit patterns.

Reconstruction of Stereo MR Angiography Optimized to View Position and Distance using MIP (최대강도투사를 이용한 관찰 위치와 거리에 최적화 된 입체 자기공명 뇌 혈관영상 재구성)

  • Shin, Seok-Hyun;Hwang, Do-Sik
    • Investigative Magnetic Resonance Imaging
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    • v.16 no.1
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    • pp.67-75
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    • 2012
  • Purpose : We studied enhanced method to view the vessels in the brain using Magnetic Resonance Angiography (MRA). Noticing that Maximum Intensity Projection (MIP) image is often used to evaluate the arteries of the neck and brain, we propose a new method for view brain vessels to stereo image in 3D space with more superior and more correct compared with conventional method. Materials and Methods: We use 3T Siemens Tim Trio MRI scanner with 4 channel head coil and get a 3D MRA brain data by fixing volunteers head and radiating Phase Contrast pulse sequence. MRA brain data is 3D rotated according to the view angle of each eyes. Optimal view angle (projection angle) is determined by the distance between eye and center of the data. Newly acquired MRA data are projected along with the projection line and display only the highest values. Each left and right view MIP image is integrated through anaglyph imaging method and optimal stereoscopic MIP image is acquired. Results: Result image shows that proposed method let enable to view MIP image at any direction of MRA data that is impossible to the conventional method. Moreover, considering disparity and distance from viewer to center of MRA data at spherical coordinates, we can get more realistic stereo image. In conclusion, we can get optimal stereoscopic images according to the position that viewers want to see and distance between viewer and MRA data. Conclusion: Proposed method overcome problems of conventional method that shows only specific projected image (z-axis projection) and give optimal depth information by converting mono MIP image to stereoscopic image considering viewers position. And can display any view of MRA data at spherical coordinates. If the optimization algorithm and parallel processing is applied, it may give useful medical information for diagnosis and treatment planning in real-time.

Dose comparison according to Smooth Thickness application of Range compensator during proton therapy for brain tumor patient (뇌종양 환자의 양성자 치료 시 Range Compensator의 Smooth Thickness 적용에 따른 선량비교)

  • Kim, Tae Woan;Kim, Dae Woong;Kim, Jae Weon;Jeong, Kyeong Sik
    • The Journal of Korean Society for Radiation Therapy
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    • v.28 no.2
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    • pp.139-148
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    • 2016
  • Purpose : Range Compensator used for proton therapy compensates the proton beam dose which delivers to the normal tissues according to the Target's Distal Margin dose. We are going to check the improvement of dose on the target part by comparing the dose of PTV and OAR according to applying in different method of Smooth Thickness of Range Compensator which is used in brain tumor therapy. Materials and Methods : For 10 brain tumor patients taking proton therapy in National Cancer Center, Apply Smooth Thickness applied in Range Compensator in order from one to five by using Compensator Editor of Eclipse Proton Planning System(Version 10.0, Varian, USA). The therapy plan algorithm used Proton Convolution Superposition(version 8.1.20 or 10.0.28), and we compared Dmax, Dmin, Homogeneity Index, Conformity Index and OAR dose around tumor by applying Smooth Thickness in phase. Results : When Smooth Thickness was applied from one to five, the Dmax of PTV was decreased max 4.3%, minimum at 0.8 and average of 1.81%. Dmin increased max 1.8%, min 1.8% and average. Difference between max dose and minimum dose decreased at max 5.9% min 1.4% and average 2.6%. Homogeneity Index decreased average of 0.018 and Conformity Index didn't had a meaningful change. OAR dose decreased in Brain Stem at max 1.6%, min 0.1% and average 0.6% and in Optic Chiasm max 1.3%, min 0.3%, and average 0.5%. However, patient C and patient E had an increase each 0.3% and 0.6%. Additionally, in Rt. Optic Nerve, there was a decrease at max 1.5%, min 0.3%, and average 0.8%, however, patient B had 0.1% increase. In Lt. Optic Nerve, there was a decrease at max 1.8%, min 0.3%, and average 0.7%, however, patient H had 0.4 increase. Conclusion : As Smooth Thickness of Range Compensator which is used as the proton treatment for brain tumor patients is applied in stages, the resolution of Compensator increased and as a result the most optimized amount of proton beam dose can be delivered. This is considered to be able to irradiate the equal amount at PTV and reduce the unnecessary dose applied at OAR to reduce the side effects.

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Speech Recognition Using Linear Discriminant Analysis and Common Vector Extraction (선형 판별분석과 공통벡터 추출방법을 이용한 음성인식)

  • 남명우;노승용
    • The Journal of the Acoustical Society of Korea
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    • v.20 no.4
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    • pp.35-41
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    • 2001
  • This paper describes Linear Discriminant Analysis and common vector extraction for speech recognition. Voice signal contains psychological and physiological properties of the speaker as well as dialect differences, acoustical environment effects, and phase differences. For these reasons, the same word spelled out by different speakers can be very different heard. This property of speech signal make it very difficult to extract common properties in the same speech class (word or phoneme). Linear algebra method like BT (Karhunen-Loeve Transformation) is generally used for common properties extraction In the speech signals, but common vector extraction which is suggested by M. Bilginer et at. is used in this paper. The method of M. Bilginer et al. extracts the optimized common vector from the speech signals used for training. And it has 100% recognition accuracy in the trained data which is used for common vector extraction. In spite of these characteristics, the method has some drawback-we cannot use numbers of speech signal for training and the discriminant information among common vectors is not defined. This paper suggests advanced method which can reduce error rate by maximizing the discriminant information among common vectors. And novel method to normalize the size of common vector also added. The result shows improved performance of algorithm and better recognition accuracy of 2% than conventional method.

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A study of the plan dosimetic evaluation on the rectal cancer treatment (직장암 치료 시 치료계획에 따른 선량평가 연구)

  • Jeong, Hyun Hak;An, Beom Seok;Kim, Dae Il;Lee, Yang Hoon;Lee, Je hee
    • The Journal of Korean Society for Radiation Therapy
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    • v.28 no.2
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    • pp.171-178
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    • 2016
  • Purpose : In order to minimize the dose of femoral head as an appropriate treatment plan for rectal cancer radiation therapy, we compare and evaluate the usefulness of 3-field 3D conformal radiation therapy(below 3fCRT), which is a universal treatment method, and 5-field 3D conformal radiation therapy(below 5fCRT), and Volumetric Modulated Arc Therapy (VMAT). Materials and Methods : The 10 cases of rectal cancer that treated with 21EX were enrolled. Those cases were planned by Eclipse(Ver. 10.0.42, Varian, USA), PRO3(Progressive Resolution Optimizer 10.0.28) and AAA(Anisotropic Analytic Algorithm Ver. 10.0.28). 3fCRT and 5fCRT plan has $0^{\circ}$, $270^{\circ}$, $90^{\circ}$ and $0^{\circ}$, $95^{\circ}$, $45^{\circ}$, $315^{\circ}$, $265^{\circ}$ gantry angle, respectively. VMAT plan parameters consisted of 15MV coplanar $360^{\circ}$ 1 arac. Treatment prescription was employed delivering 54Gy to recum in 30 fractions. To minimize the dose difference that shows up randomly on optimizing, VMAT plans were optimized and calculated twice, and normalized to the target V100%=95%. The indexes of evaluation are D of Both femoral head and aceta fossa, total MU, H.I.(Homogeneity index) and C.I.(Conformity index) of the PTV. All VMAT plans were verified by gamma test with portal dosimetry using EPID. Results : D of Rt. femoral head was 53.08 Gy, 50.27 Gy, and 30.92 Gy, respectively, in the order of 3fCRT, 5fCRT, and VMAT treatment plan. Likewise, Lt. Femoral head showed average 53.68 Gy, 51.01 Gy and 29.23 Gy in the same order. D of Rt. aceta fossa was 54.86 Gy, 52.40 Gy, 30.37 Gy, respectively, in the order of 3fCRT, 5fCRT, and VMAT treatment plan. Likewise, Lt. Femoral head showed average 53.68 Gy, 51.01 Gy and 29.23 Gy in the same order. The maximum dose of both femoral head and aceta fossa was higher in the order of 3fCRT, 5fCRT, and VMAT treatment plan. C.I. showed the lowest VMAT treatment plan with an average of 1.64, 1.48, and 0.99 in the order of 3fCRT, 5fCRT, and VMAT treatment plan. There was no significant difference on H.I. of the PTV among three plans. Total MU showed that the VMAT treatment plan used 124.4MU and 299MU more than the 3fCRT and 5fCRT treatment plan, respectively. IMRT verification gamma test results for the VMAT plan passed over 90.0% at 2mm/2%. Conclusion : In rectal cancer treatment, the VMAT plan was shown to be advantageous in most of the evaluation indexes compared to the 3D plan, and the dose of the femoral head was greatly reduced. However, because of practical limitations there may be a case where it is difficult to select a VMAT treatment plan. 5fCRT has the advantage of reducing the dose of the femoral head as compared to the existing 3fCRT, without regard to additional problems. Therefore, not only would it extend survival time but the quality of life in general, if hospitals improved radiation therapy efficiency by selecting the treatment plan in accordance with the hospital's situation.

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