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.
For the purpose of utilizing the sawdust having poor combining properties as board raw material and resulting in dimensional instability of board, polypropylene chip (abbreviated below as PP chip) or oriented PP thread was combined with sawdust particle from white meranti(Shorea sp.). The PP chip was prepared from PP thread in length of 0.25, 0.5, 1.0 and 1.5 cm for conventional blending application. Thereafter, the PP chip cut as above was combined with the sawdust particle by 3, 6, 9, 12 and 15% on the weight basis of board. Oriented PP threads were aligned with spacing of 0.5, 1.0 and 1.5cm along transverse direction of board. The physical and mechanical properties on one, two and three layer boards manufactured with the above combining conditions were investigated. The conclusions obtained at this study were summarized as follows: 1. In thickness swelling, all one layer boards combined with PP chips showed lower values than control sawdustboard, and gradually clear decreasing tendendy with the increase of PP chip composition. Two layer board showed higher swelling value than one layer board, but the majority of boards lower values than control sawdustboard. All three layer boards showed lower swelling values than control sawdustboard. 2. In the PP chip and oriented thread combining board, the swelling values of boards combining 0.5cm spacing oriented thread with 1.0 or 1.5cm long PP chip in 12 and 15% by board weight were much lower than the lowest of one or three layer. 3. In specific gravity of 0.51, modulus of rupture of one layer board combined with 3% PP chip showed higher value than control sawdustboard. However, moduli of rupture of the boards with every PP chip composition did not exceed 80kgf/cm2, the low limit value of type 100 board, Korean Industrial Standard KS F 3104 Particleboards. Moduli of rupture of 6%, 1.5cm-long and 3% PP chip combined boards in specific gravity of 0.63 as well as PP chip combined board in specific gravity of 0.72 exceeded 80kgf/
There are only a handful number of research conducted on pattern analysis of corporate distress as compared with research for bankruptcy prediction. The few that exists mainly focus on audited firms because financial data collection is easier for these firms. But in reality, corporate financial distress is a far more common and critical phenomenon for non-audited firms which are mainly comprised of small and medium sized firms. The purpose of this paper is to classify non-audited firms under distress according to their financial ratio using data mining; Self-Organizing Map (SOM). SOM is a type of artificial neural network that is trained using unsupervised learning to produce a lower dimensional discretized representation of the input space of the training samples, called a map. SOM is different from other artificial neural networks as it applies competitive learning as opposed to error-correction learning such as backpropagation with gradient descent, and in the sense that it uses a neighborhood function to preserve the topological properties of the input space. It is one of the popular and successful clustering algorithm. In this study, we classify types of financial distress firms, specially, non-audited firms. In the empirical test, we collect 10 financial ratios of 100 non-audited firms under distress in 2004 for the previous two years (2002 and 2003). Using these financial ratios and the SOM algorithm, five distinct patterns were distinguished. In pattern 1, financial distress was very serious in almost all financial ratios. 12% of the firms are included in these patterns. In pattern 2, financial distress was weak in almost financial ratios. 14% of the firms are included in pattern 2. In pattern 3, growth ratio was the worst among all patterns. It is speculated that the firms of this pattern may be under distress due to severe competition in their industries. Approximately 30% of the firms fell into this group. In pattern 4, the growth ratio was higher than any other pattern but the cash ratio and profitability ratio were not at the level of the growth ratio. It is concluded that the firms of this pattern were under distress in pursuit of expanding their business. About 25% of the firms were in this pattern. Last, pattern 5 encompassed very solvent firms. Perhaps firms of this pattern were distressed due to a bad short-term strategic decision or due to problems with the enterpriser of the firms. Approximately 18% of the firms were under this pattern. This study has the academic and empirical contribution. In the perspectives of the academic contribution, non-audited companies that tend to be easily bankrupt and have the unstructured or easily manipulated financial data are classified by the data mining technology (Self-Organizing Map) rather than big sized audited firms that have the well prepared and reliable financial data. In the perspectives of the empirical one, even though the financial data of the non-audited firms are conducted to analyze, it is useful for find out the first order symptom of financial distress, which makes us to forecast the prediction of bankruptcy of the firms and to manage the early warning and alert signal. These are the academic and empirical contribution of this study. The limitation of this research is to analyze only 100 corporates due to the difficulty of collecting the financial data of the non-audited firms, which make us to be hard to proceed to the analysis by the category or size difference. Also, non-financial qualitative data is crucial for the analysis of bankruptcy. Thus, the non-financial qualitative factor is taken into account for the next study. This study sheds some light on the non-audited small and medium sized firms' distress prediction in the future.
Experiments were carried out to evaluate the standard gravity in determining potential kernel size and to determine the effective sampling way by analyzing intra - and inter - plant variations for some source and sink characters using eleven semi-dwarf indica and three japonica cultivars including four semi-dwarf indica nearisogenic lines. Also, additional experiments were conducted to understand yearly variation and variety x year interaction effects for ten characters related to source and sink and to characterize the varietal difference of pre- and post-heading self-competition employing three parental varieties and their F
Internet commerce has been growing at a rapid pace for the last decade. Many firms try to reach wider consumer markets by adding the Internet channel to the existing traditional channels. Despite the various benefits of the Internet channel, a significant number of firms failed in managing the new type of channel. Previous studies could not cleary explain these conflicting results associated with the Internet channel. One of the major reasons is most of the previous studies conducted analyses under a specific market condition and claimed that as the impact of Internet channel introduction. Therefore, their results are strongly influenced by the specific market settings. However, firms face various market conditions in the real worlddensity and disutility of using the Internet. The purpose of this study is to investigate the impact of various market environments on a firm's optimal channel strategy by employing a flexible game theory model. We capture various market conditions with consumer density and disutility of using the Internet.
Since the Industrial Revolution, which made the mass production and mass distribution of standardized goods possible, machine-made (manufactured) products have accounted for the majority of the market. However, in recent years, the phenomenon of purchasing even more expensive handmade products has become a noticeable trend as consumers have started to acknowledge the value of handmade products, such as the craftsman's commitment, belief in their quality and scarcity, and the sense of self-esteem from having them,. Consumer interest in these handmade products has shown explosive growth and has been coupled with the recent development of three-dimensional (3D) printing technologies. Etsy.com is the world's largest online handmade platform. It is no different from any other online platform; it provides an online market where buyers and sellers virtually meet to share information and transact business. However, Etsy.com is different in that shops within this platform only deal with handmade products in a variety of categories, ranging from jewelry to toys. Since its establishment in 2005, despite being limited to handmade products, Etsy.com has enjoyed rapid growth in membership, transaction volume, and revenue. Most recently in April 2015, it raised funds through an initial public offering (IPO) of more than 1.8 billion USD, which demonstrates the huge potential of online handmade platforms. After the success of Etsy.com, various types of online handmade platforms such as Handmade at Amazon, ArtFire, DaWanda, and Craft is ART have emerged and are now competing with each other, at the same time, which has increased the size of the market. According to Deloitte's 2015 holiday survey on which types of gifts the respondents plan to buy during the holiday season, about 16% of U.S. consumers chose "homemade or craft items (e.g., Etsy purchase)," which was the same rate as those for the computer game and shoes categories. This indicates that consumer interests in online handmade platforms will continue to rise in the future. However, this high interest in the market for handmade products and their platforms has not yet led to academic research. Most extant studies have only focused on machine-made products and intelligent services for them. This indicates a lack of studies on handmade products and their intelligent services on virtual platforms. Therefore, this study used signaling theory and prior research on the effects of sellers' characteristics on their performance (e.g., total sales and price premiums) in the buyer-seller relationship to identify the key influencing e-Image factors (e.g., reputation, size, information sharing, and length of relationship). Then, their impacts on the performance of shops within the online handmade platform were empirically examined; the dataset was collected from Etsy.com through the application of web harvesting technology. The results from the structural equation modeling revealed that the reputation, size, and information sharing have significant effects on the total sales, while the reputation and length of relationship influence price premiums. This study extended the online platform research into online handmade platform research by identifying key influencing e-Image factors on within-platform shop's total sales and price premiums based on signaling theory and then performed a statistical investigation. These findings are expected to be a stepping stone for future studies on intelligent online handmade services as well as handmade products themselves. Furthermore, the findings of the study provide online handmade platform operators with practical guidelines on how to implement intelligent online handmade services. They should also help shop managers build their marketing strategies in a more specific and effective manner by suggesting key influencing e-Image factors. The results of this study should contribute to the vitalization of intelligent online handmade services by providing clues on how to maximize within-platform shops' total sales and price premiums.
The purpose of this study is to investigate the psychological reaction to the image of the worship space in the church buildings and to quantify its contribution of the stimulation elements causing such reaction, and finally to suggest basic data for realizing emotional worship space of the church architecture. For this, 143 christians were surveyed to analyze the relationship between 23 emotional expressions extracted from the worship space and 32 images of the worship space. The combined data was described with the two dimensional dispersion using the quantification theory III. The analysis found out that 'simplicity-complexity' of the image consisted of the horizontal axis (the x-axis) and 'creativity' of the image the vertical axis(the y-axis). In addition, to extract the causal relationship between the value of emotional reaction and its stimulation elements quantitatively, the author indicated 4 emotional word groups such as simple, sublime for x-axis and typical creative for y-axis based on its similarity by the cluster analysis, The quantification theory I was also used with total value of equivalent emotional words as the standard variance and the emotional stimulation elements of the worship space as the independent variance. 9 specific examples of the emotional stimulation elements were selected including colors and shapes of the wall and the ceiling, shapes and finish of the floor materials, window shapes, and the use of the symbolic elements. Furthermore, 31 subcategories were also chosen to analyse their contribution on the emotional reaction. As a result, the color and finish of the wall found to be the most effective element on the subjects' emotional reaction, while the symbolic elements and the color of the wall found to be the least effective. It is estimated that the present study would be helpful to increase the emotional satisfaction of the users and to approach a spatial design through satisfying the types and purposes of the space.
It was to study as a following-research of "A Case Study on Center of Gravity(COG) Analysis when Performing Uchimata(inner thigh reaping throw) by Posture and Voluntary Resistance Levels(VRL) of Uke in Judo[I]". The purpose of this study was to analyze the COG variables when performing uchimata(inner thigh reaping throw) by two postures and voluntary resistance levels(VRL) of uke(reciver) in Judo. The subjects, who were one male judoka(YH) for 1992 Barcelona Olympic Games Olympian(silver medalist), and one male trainee; Y.I.University representative member (SDK), and were filmed on two S-VHS 16mm video cameras(60fields/sec.) through 3-dimensional motion analysis methods, that postures of uke were shizenhontai (straight natural posture) and jigohontai(straight defensive posture), VRL of uke were 0% and 100%, respectively. The kinematical variable was COG variable, distance of COG, and distance of resultant COG between uke and tori(the thrower), velocity and acceleration of COG. The data of this study collection were digitized by SIMI Motion Program computed the mean values and the standard deviation calculated for each variables. When performing uchinmata according to each posture and VRL of uke and classifying. From the data analysis and discussion, the conclusions were as follows : 1. Displacement of COG Subject YH, COG was the highest in kuzushi(balance -breaking), vertical COG was low when following in tsukuri(positioning; set-up), kake(application; execution), and COG was pattern of same character each postures and resistance, respectively. Subject SDK, COG was low from kumikata(engagement positioning) to kake, and COG was that each postures and resistance were same patterns, respectively. Subject YH, SDK, each individual, postures and resistance, vertical COG was the lowest in kake phase, when performing. 2. Distance of COG between uke and tori The distance of COG between uke and tori when performing, subject YH was
To investigate the actual conditions of smoking in middle and high school students in Chinan County, I used a sturctured questionnaire for 1,579 students attending twelve middle-high schools from December 1, 1998 to December 20, 1998. I collected and data correlated the using an
The propriety between suppliers and demanders in geometric design is very important. Although the final purpose of constructing roads is to concern about the driver s comfort, unfortunately, it has not been considered so far. We've considered the regularity and quickness in considering driver's comfort but there should be considered the safety for the accident as well. If drivers are appeared to be more speeding than designer's intention, there will be needed some supplements to increase the safety rate for the roads. Even if both an upward and downward section are supposed to exist at the same time for solid geometry of the roads like this, it is true that the recent design for the 3-D solid geometry section has been done as flat 2-D and the minimum plane curve radius and the maximum cant have been decided just by calculating without considering operating speed between an upward and downward section at the same point. In this investigation, thus, I'd like to calculate the safety of the cant by considering the speed features of the solid geometry for the first lane of four lane rural roads. To begin with, we investigated the driving speed of the car, which is not been influenced by a preceding car to analyze the influence of the geometrical structure by using Nc-97. Secondly, we statistically analyzed the driving features of the solid geometry after comparing the 6 sections, that is, measuring the driving speed feature at 12 points and combining the influence of the vertical geometry and plane geometry to the driving speed of the plane curve which was researched before. Finally, we estimated the value of cant which considers the driving speed not by using it which has applied uniformly without considering it properly, though there were some differences between a designed speed and driving speed through the result of the basic statistical analysis but by introducing the new safety rate rule, a notion of shows the channel structures analyzed in this study. Before the Internet channel is introduced, a monopoly manufacturer sells its products through an independent physical store. From this structure, the manufacturer could introduce its own Internet channel (MI). The independent physical store could also introduce its own Internet channel and coordinate it with the existing physical store (RI). An independent Internet retailer such as Amazon could enter this market (II). In this case, two types of independent retailers compete with each other. In this model, consumers are uniformly distributed on the two dimensional space. Consumer heterogeneity is captured by a consumer's geographical location (ci) and his disutility of using the Internet channel ( shows various market conditions captured by the two consumer heterogeneities. (a) illustrates a market with symmetric consumer distributions. The model captures explicitly the asymmetric distributions of consumer disutility in a market as well. In a market like that is represented in (c), the average consumer disutility of using an Internet store is relatively smaller than that of using a physical store. For example, this case represents the market in which 1) the product is suitable for Internet transactions (e.g., books) or 2) the level of E-Commerce readiness is high such as in Denmark or Finland. On the other hand, the average consumer disutility when using an Internet store is relatively greater than that of using a physical store in a market like summarizes the various scenarios of consumer distributions analyzed in this study. The range for disutility of using the Internet (
summarizes the analysis results. As the average travel cost in a market decreases while the average disutility of Internet use remains the same, average retail price, total quantity sold, physical store profit, monopoly manufacturer profit, and thus, total channel profit increase. On the other hand, the quantity sold through the Internet and the profit of the Internet store decrease with a decreasing average travel cost relative to the average disutility of Internet use. We find that a channel that has an advantage over the other kind of channel serves a larger portion of the market. In a market with a high average travel cost, in which the Internet store has a relative advantage over the physical store, for example, the Internet store becomes a mass-retailer serving a larger portion of the market. This result implies that the Internet becomes a more significant distribution channel in those markets characterized by greater geographical dispersion of buyers, or as consumers become more proficient in Internet usage. The results indicate that the degree of price discrimination also varies depending on the distribution of consumer disutility in a market. The manufacturer in a market in which the average travel cost is higher than the average disutility of using the Internet has a stronger incentive for price discrimination than the manufacturer in a market where the average travel cost is relatively lower. We also find that the manufacturer has a stronger incentive to maintain a high price level when the average travel cost in a market is relatively low. Additionally, the retail competition effect due to Internet channel introduction strengthens as average travel cost in a market decreases. This result indicates that a manufacturer's channel power relative to that of the independent physical retailer becomes stronger with a decreasing average travel cost. This implication is counter-intuitive, because it is widely believed that the negative impact of Internet channel introduction on a competing physical retailer is more significant in a market like Russia, where consumers are more geographically dispersed, than in a market like Hong Kong, that has a condensed geographic distribution of consumers.
A Study on the Buyer's Decision Making Models for Introducing Intelligent Online Handmade Services
(지능형 온라인 핸드메이드 서비스 도입을 위한 구매자 의사결정모형에 관한 연구)
A Study on the Emotional Reaction to the Interior Design - Focusing on the Worship Space in the Church Buildings -
(실내공간 구성요소에 의한 감성반응 연구 - 기독교 예배공간 강단부를 중심으로 -)
A Case Study on Center of Gravity Analysis when Performing Uchimata by Posture and Voluntary Resistance Levels of Uke in Judo[ll]
(유도 허벅다리걸기 기술발휘 시 받기의 자세와 저항수준에 따른 중심변인 분석 사례연구[II])
A Study on the Actual Conditions of Smoking in Middle and High School Students in One Region
(일 지역 중·고등학생의 흡연실태)
Estimation of the Superelevation Safety Factor Considering Operating Speed at 3-Dimensional Alignment
(입체선형의 주행속도를 고려한 편경사 안전율 산정에 관한 연구)
이메일무단수집거부
이용약관
제 1 장 총칙
제 2 장 이용계약의 체결
제 3 장 계약 당사자의 의무
제 4 장 서비스의 이용
제 5 장 계약 해지 및 이용 제한
제 6 장 손해배상 및 기타사항
Detail Search
Image Search
(β)