• Journal of Intelligence and Information Systems
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• v.24 no.1
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• pp.205-225
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• 2018

Convolutional Neural Network (ConvNet) is one class of the powerful Deep Neural Network that can analyze and learn hierarchies of visual features. Originally, first neural network (Neocognitron) was introduced in the 80s. At that time, the neural network was not broadly used in both industry and academic field by cause of large-scale dataset shortage and low computational power. However, after a few decades later in 2012, Krizhevsky made a breakthrough on ILSVRC-12 visual recognition competition using Convolutional Neural Network. That breakthrough revived people interest in the neural network. The success of Convolutional Neural Network is achieved with two main factors. First of them is the emergence of advanced hardware (GPUs) for sufficient parallel computation. Second is the availability of large-scale datasets such as ImageNet (ILSVRC) dataset for training. Unfortunately, many new domains are bottlenecked by these factors. For most domains, it is difficult and requires lots of effort to gather large-scale dataset to train a ConvNet. Moreover, even if we have a large-scale dataset, training ConvNet from scratch is required expensive resource and time-consuming. These two obstacles can be solved by using transfer learning. Transfer learning is a method for transferring the knowledge from a source domain to new domain. There are two major Transfer learning cases. First one is ConvNet as fixed feature extractor, and the second one is Fine-tune the ConvNet on a new dataset. In the first case, using pre-trained ConvNet (such as on ImageNet) to compute feed-forward activations of the image into the ConvNet and extract activation features from specific layers. In the second case, replacing and retraining the ConvNet classifier on the new dataset, then fine-tune the weights of the pre-trained network with the backpropagation. In this paper, we focus on using multiple ConvNet layers as a fixed feature extractor only. However, applying features with high dimensional complexity that is directly extracted from multiple ConvNet layers is still a challenging problem. We observe that features extracted from multiple ConvNet layers address the different characteristics of the image which means better representation could be obtained by finding the optimal combination of multiple ConvNet layers. Based on that observation, we propose to employ multiple ConvNet layer representations for transfer learning instead of a single ConvNet layer representation. Overall, our primary pipeline has three steps. Firstly, images from target task are given as input to ConvNet, then that image will be feed-forwarded into pre-trained AlexNet, and the activation features from three fully connected convolutional layers are extracted. Secondly, activation features of three ConvNet layers are concatenated to obtain multiple ConvNet layers representation because it will gain more information about an image. When three fully connected layer features concatenated, the occurring image representation would have 9192 (4096+4096+1000) dimension features. However, features extracted from multiple ConvNet layers are redundant and noisy since they are extracted from the same ConvNet. Thus, a third step, we will use Principal Component Analysis (PCA) to select salient features before the training phase. When salient features are obtained, the classifier can classify image more accurately, and the performance of transfer learning can be improved. To evaluate proposed method, experiments are conducted in three standard datasets (Caltech-256, VOC07, and SUN397) to compare multiple ConvNet layer representations against single ConvNet layer representation by using PCA for feature selection and dimension reduction. Our experiments demonstrated the importance of feature selection for multiple ConvNet layer representation. Moreover, our proposed approach achieved 75.6% accuracy compared to 73.9% accuracy achieved by FC7 layer on the Caltech-256 dataset, 73.1% accuracy compared to 69.2% accuracy achieved by FC8 layer on the VOC07 dataset, 52.2% accuracy compared to 48.7% accuracy achieved by FC7 layer on the SUN397 dataset. We also showed that our proposed approach achieved superior performance, 2.8%, 2.1% and 3.1% accuracy improvement on Caltech-256, VOC07, and SUN397 dataset respectively compare to existing work.

• Maxillofacial Plastic and Reconstructive Surgery
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• v.18 no.4
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• pp.570-593
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• 1996

This study was intended to perform the influence of condyle positional change after surgical correction of skeletal Class III malocclusion after BSSRO in 20 patients(males 9, females 11) using computed tomogram that were taken in centric occlusion before, immediate, and long term after surgery and lateral cephalogram that were taken in centric occlusion before, 7 days within the period intermaxillary fixation, 24hour after removing intermaxillary fixation and long term after surgery. 1. Mean intercondylar distance was $84.45{\pm}4.01mm$ and horizontal long axis of condylar angle was $11.89{\pm}5.19^{\circ}$on right, $11.65{\pm}2.09^{\circ}$on left side and condylar lateral poles were located about 12mm and medial poles about 7mm from reference line(AA') on the axial tomograph. Mean intercondylar distance was $84.43{\pm}3.96mm$ and vertical axis angle of condylar angle was $78.72{\pm}3.43^{\circ}$on right, $78.09{\pm}6.12^{\circ}$on left. 2. No statistical significance was found on the condylar change(T2C-T1C) but it had definitive increasing tendency. There was significant decreasing of the distance between both condylar pole and the AA'(p<0.05) during the long term(TLC-T2C). 3. On the lateral cephalogram, no statistical significance was found between immediate after surgery and 24 hours after the removing of intermaxillary fixation but only the lower incisor tip moved forward about 0.33mm(p<0.05). Considering individual relapse rate, mean relapse rate was 1.2% on L1, 5.0% on B, 2.0% on Pog, 9.1% on Gn, 10.3% on Me(p<0.05). 4. There was statistical significance on the influence of the mandibular set-back to the total mandibular relapse(p<0.05). 5. There was no statistical significance on the influence of the mandibular set-back(T2-T1) to the condylar change(T2C-T1C), the condylar change(T2C-T1C, TLC-T2C) to the mandibular total relapse, the pre-operative condylar position to the condylar change(T2C-T1C, TLC-T2C), the pre-operative mandibular posture to the condylar change(T2C-T1C, TLC-T2C)(p>0.05). 6. The result of multiple regression analysis on the influence of the pre-operative condylar position to the total mandibular relapse revealed that the more increasing of intercondylar distance and condylar vertical axis angle and decreasing of condyalr head long axis angle, the more increasing of mandibular horizontal relapse(L1,B,Pog,Gn,Me) on the right side condyle. The same result was founded in the case of horizontal relapse(L1,Me) on the left side condyle.(p<0.05). 7. The result of multiple regression analysis on the influence of the pre-operative condylar position to the pre-operative mandibular posture revealed that the more increasing of intercondylar distance and condylar vertical axis angle and decreasing of condylar head long axis angle, the more increasing of mandibular vertical length on the right side condyle. and increasing of vertical lengh & prognathism on the left side condyle(p<0.05). 8. The result of simple regression analysis on the influence of the pre-operative mandibular posture to the mandibular total relapse revealed that the more increasing of prognathism, the more increasing of mandibular total relapse in B and the more increasing of over-jet the more increasing of mandibular total relapse(p<0.05). Consequently, surgical mandibular repositioning was not significantly influenced to the change of condylar position with condylar reposition method.

• MISULJARYO - National Museum of Korea Art Journal
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• v.98
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• pp.226-241
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• 2020

Located on the right side of the third floor of the State Hermitage Museum in St. Petersburg, the "Art of Central Asia" exhibition boasts the world's finest collection of artworks and artifacts from the Silk Road. Every item in the collection has been classified by region, and many of them were collected in the early twentieth century through archaeological surveys led by Russia's Pyotr Kozlov, Mikhail Berezovsky, and Sergey Oldenburg. Some of these artifacts have been presented around the world through special exhibitions held in Germany, France, the United Kingdom, the Netherlands, Korea, Japan, and elsewhere. The fruits of Russia's Silk Road expeditions were also on full display in the 2008 exhibition The Caves of One Thousand Buddhas - Russian Expeditions on the Silk Route on the Occasion of 190 Years of the Asiatic Museum, held at the Hermitage Museum. Published in 2018 by the Shanghai Chinese Classics Publishing House in collaboration with the Hermitage Museum, Kuche Art Relics Collected in Russia introduces the Hermitage's collection of artifacts from the Kuche (or Kucha) region. While the book focuses exclusively on artifacts excavated from the Kuche area, it also includes valuable on-site photos and sketches from the Russian expeditions, thus helping to enhance readers' overall understanding of the characteristics of Kuche art within the Buddhist art of Central Asia. The book was compiled by Dr. Kira Samosyuk, senior curator of the Oriental Department of the Hermitage Museum, who also wrote the main article and the artifact descriptions. Dr. Samosyuk is an internationally renowned scholar of Central Asian Buddhist art, with a particular expertise in the art of Khara-Khoto and Xi-yu. In her article "The Art of the Kuche Buddhist Temples," Dr. Samosyuk provides an overview of Russia's Silk Road expeditions, before introducing the historical development of Kuche in the Buddhist era and the aspects of Buddhism transmitted to Kuche. She describes the murals and clay sculptures in the Buddhist grottoes, giving important details on their themes and issues with estimating their dates, and also explains how the temples operated as places of worship. In conclusion, Dr. Samosyuk argues that the Kuche region, while continuously engaging with various peoples in China and the nomadic world, developed its own independent Buddhist culture incorporating elements of Gandara, Hellenistic, Persian, and Chinese art and culture. Finally, she states that the culture of the Kuche region had a profound influence not only on the Tarim Basin, but also on the Buddhist grottoes of Dunhuang and the central region of China. A considerable portion of Dr. Samosyuk's article addresses efforts to estimate the date of the grottoes in the Kuche region. After citing various scholars' views on the dates of the murals, she argues that the Kizil grottoes likely began prior to the fifth century, which is at least 100 years earlier than most current estimates. This conclusion is reached by comparing the iconography of the armor depicted in the murals with related materials excavated from the surrounding area (such as items of Sogdian art). However, efforts to date the Buddhist grottoes of Kuche must take many factors into consideration, such as the geological characteristics of the caves, the themes and styles of the Buddhist paintings, the types of pigments used, and the clothing, hairstyles, and ornamentation of the depicted figures. Moreover, such interdisciplinary data must be studied within the context of Kuche's relations with nearby cultures. Scientific methods such as radiocarbon dating could also be applied for supplementary materials. The preface of Kuche Art Relics Collected in Russia reveals that the catalog is the first volume covering the Hermitage Museum's collection of Kuche art, and that the next volume in the series will cover a large collection of mural fragments that were taken from Berlin during World War II. For many years, the whereabouts of these mural fragments were unknown to both the public and academia, but after restoration, the fragments were recently re-introduced to the public as part of the museum's permanent exhibition. We look forward to the next publication that focuses on these mural fragments, and also to future catalogs introducing the artifacts of Turpan and Khotan. Currently, fragments of the murals from the Kuche grottoes are scattered among various countries, including Russia, Germany, and Korea. With the publication of this catalog, it seems like an opportune time to publish a comprehensive catalog on the murals of the Kuche region, which represent a compelling mixture of East-West culture that reflects the overall characteristics of the region. A catalog that includes both the remaining murals of the Kizil grottoes and the fragments from different parts of the world could greatly enhance our understanding of the murals' original state. Such a book would hopefully include a more detailed and interdisciplinary discussion of the artifacts and murals, including scientific analyses of the pigments and other materials from the perspective of conservation science. With the ongoing rapid development in western China, the grotto murals are facing a serious crisis related to climate change and overcrowding in the oasis city of Xinjiang. To overcome this challenge, the cultural communities of China and other countries that possess advanced technology for conservation and restoration must begin working together to protect and restore the murals of the Silk Road grottoes. Moreover, centers for conservation science should be established to foster human resources and collect information. Compiling the data of Russian expeditions related to the grottoes of Kuche (among the results of Western archaeological surveys of the Silk Road in the early twentieth century), Kuche Art Relics Collected in Russia represents an important contribution to research on Kuche's Buddhist art and the Silk Road, which will only be enhanced by a future volume introducing the mural fragments from Germany. As the new authoritative source for academic research on the artworks and artifacts of the Kuche region, the book also lays the groundwork for new directions for future studies on the Silk Road. Finally, the book is also quite significant for employing a new editing system that improves its academic clarity and convenience. In conclusion, Dr. Kira Samosyuk, who planned the publication, deserves tremendous praise for taking the research of Silk Road art to new heights.