Body has been high-lightened as one of the most important theme since the philosophy and the arts are focused on it in the late 20th century. It would be of worth to study the characteristics of contemporary fiber-art works, especially done by Abakanowiz who has been regarded as a dominant pioneer in the contemporary fiber-arts from the viewpoint of inter-grade of the physicals and the mental. This paper, therefore, deals with the Abaknowiz' works in the context of human body and body-signs. Life and works might be classified into 5 stages: first, learning period since her birth in 1930, second, creation period of Abakans, third, remodelling period of Abakans, fourth, composition and dissolution period of Abakans and the last and fifth, new transformation period of Abakans. 'Abakans' through her whole life as an artist have been a plastic language and based ultimately on external human body but in various materials and forms. Abakan as a human-sign uses the past experiences and the texts of the other world in mixed and overlapped forms. Life-size Abakans by Abaknowiz can be easily understood as Abakanowiz herself and her Polish ancestor at the same time. The neuter Abakans with mashed face and obscure body is a expressive figure of coexisting world with opposite concepts like war and ideology, anxiety and freedom, man and woman, and etc. Human body as body-sign is an extensive image has existed since our forefathers and overlapped with the inter textual and the popular images. 'Abakans' that is our world and inner-self at the same time might be a window through which she tries to show what the world is.
Journal of Korean Society of Industrial and Systems Engineering
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v.43
no.3
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pp.29-40
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2020
Korean firms have been vigorously searching and exploring overseas market opportunities through export and overseas investment. As of end of 2019, there were more than 80,000 Korean overseas subsidiaries all over the world. With Korean overseas direct investment increasing recently, it became one of the important issues for overseas investors to be successful in the global market. There are a lot of studies on factors influencing the performance of overseas subsidiaries such as 'firm' and 'country' factors. This study empirically examines subsidiary performance determinants with 'industry architectures' by using a sample of 292 overseas Korean firm subsidiaries. Industry architectures are the stable but evolving sets of rules and roles through which labor is divided within a sector. This article considers how industry architectures shape success in international expansion. Industry architectures differ between countries, are not necessarily technologically determined, shape firms' capabilities and their competitive environment, and constitute a distinct level of analysis. We extract antecedents of related theory and empirically test its impact with a survey of Korean firms expanding in emerging economies. We would say this is the first study which tries to focus on industry architectures with the performance of Korean overseas subsidiaries. We find that separability and similarity of industry architectures across countries and localization of subsidiaries are robust and important predictors of success in international expansion. Our results suggest that industry architectures should be added to firm and country as an intermediate level of analysis that helps explain success in international expansion. While we established a pattern, much more remains to be done. We focus on the success of foreign operations, but we do not consider the broader benefits of going abroad, such as the learning or network effects that accrue at the level of the entire firm. The next obvious question is whether the results would differ in the developed market context. These we leave for future research to consider.
Mobile cellular networks are becoming increasingly complex to manage while classical deployment/optimization techniques and current solutions (i.e., cell densification, acquiring more spectrum, etc.) are cost-ineffective and thus seen as stopgaps. This calls for development of novel approaches that leverage recent advances in storage/memory, context-awareness, edge/cloud computing, and falls into framework of big data. However, the big data by itself is yet another complex phenomena to handle and comes with its notorious 4V: Velocity, voracity, volume, and variety. In this work, we address these issues in optimization of 5G wireless networks via the notion of proactive caching at the base stations. In particular, we investigate the gains of proactive caching in terms of backhaul offloadings and request satisfactions, while tackling the large-amount of available data for content popularity estimation. In order to estimate the content popularity, we first collect users' mobile traffic data from a Turkish telecom operator from several base stations in hours of time interval. Then, an analysis is carried out locally on a big data platformand the gains of proactive caching at the base stations are investigated via numerical simulations. It turns out that several gains are possible depending on the level of available information and storage size. For instance, with 10% of content ratings and 15.4Gbyte of storage size (87%of total catalog size), proactive caching achieves 100% of request satisfaction and offloads 98% of the backhaul when considering 16 base stations.
This study started with the idea that it is necessary to focus on common concepts and ideas among the subjects when conducting integrated education in high school. This is a preliminary study for developing materials that can be taught in mathematics in the context of already learning scientific concepts in high school. For this purpose, Mendel 's law of genetics was studied among the contents of biological subjects which are known to have relatively little connection with mathematics. The more common links between the two subjects are, the better, in order to integrate math and other subjects and develop materials for teaching. Therefore, in this study, we investigated not only the probability domain but also the concept of statistical domain. We have been wondering if there is a more abundant idea to connect between 'Mendel's law' and 'probability and statistics'. Through these anxieties, we could find that concepts such as 'likely equality' and 'permutation and combination' including 'a large number of laws' can be a link between two subjects. Based on this, we were able to develop class materials that correspond to classes. This study is expected to help with research related to development of integrated education support materials, focusing on mathematics.
International Journal of Computer Science & Network Security
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v.22
no.9
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pp.287-299
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2022
The article deals with the formation of managerial competence of the future head of preschool education institution by means of information and communication technology as a prerequisite for his ability to act competently and objectively evaluate actions and understand the interaction of forms and content of preschool education. The article aimed to study the effectiveness of information and communication technologies in the formation of managerial competence of the future head of preschool education institution. To achieve the objectives, the methods of comparative and systematic analysis were used to compare different views on the problem under study, namely, the formation of managerial competence of the future head of preschool education institution by means of information and communication technologies. The authors of the article determined that the use of information and communication technologies in the preparation of future heads of preschool educational institutions is of great importance and is an indicator in the structure of managerial competence. The priority directions of the use of various software products for the study of the modern Ukrainian language, methods of teaching the Ukrainian language contribute to the intensification of learning material. It is noted that the current state of development of information technologies and their widespread use in education satisfies the requirements of the objectivity of the assessment obtained the quality of the control process of forming the managerial competence of the future leader in the context of the general problems of pre-school education. It is noted that the means of information and communication technologies play a leading role in creating new educational policies and projects, as they motivate the way of access to knowledge.
Abhishek Subedi;Wen Tang;Tarutal Ghosh Mondal;Rih-Teng Wu;Mohammad R. Jahanshahi
Smart Structures and Systems
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v.31
no.4
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pp.335-349
/
2023
Bridges constantly undergo deterioration and damage, the most common ones being concrete damage and exposed rebar. Periodic inspection of bridges to identify damages can aid in their quick remediation. Likewise, identifying components can provide context for damage assessment and help gauge a bridge's state of interaction with its surroundings. Current inspection techniques rely on manual site visits, which can be time-consuming and costly. More recently, robotic inspection assisted by autonomous data analytics based on Computer Vision (CV) and Artificial Intelligence (AI) has been viewed as a suitable alternative to manual inspection because of its efficiency and accuracy. To aid research in this avenue, this study performs a comparative assessment of different architectures, loss functions, and ensembling strategies for the autonomous segmentation of bridge components and damages. The experiments lead to several interesting discoveries. Nested Reg-UNet architecture is found to outperform five other state-of-the-art architectures in both damage and component segmentation tasks. The architecture is built by combining a Nested UNet style dense configuration with a pretrained RegNet encoder. In terms of the mean Intersection over Union (mIoU) metric, the Nested Reg-UNet architecture provides an improvement of 2.86% on the damage segmentation task and 1.66% on the component segmentation task compared to the state-of-the-art UNet architecture. Furthermore, it is demonstrated that incorporating the Lovasz-Softmax loss function to counter class imbalance can boost performance by 3.44% in the component segmentation task over the most employed alternative, weighted Cross Entropy (wCE). Finally, weighted softmax ensembling is found to be quite effective when used synchronously with the Nested Reg-UNet architecture by providing mIoU improvement of 0.74% in the component segmentation task and 1.14% in the damage segmentation task over a single-architecture baseline. Overall, the best mIoU of 92.50% for the component segmentation task and 84.19% for the damage segmentation task validate the feasibility of these techniques for autonomous bridge component and damage segmentation using RGB images.
Purpose: The objective of this scoping review was to investigate the applicability and performance of various convolutional neural network (CNN) models in tooth numbering on panoramic radiographs, achieved through classification, detection, and segmentation tasks. Materials and Methods: An online search was performed of the PubMed, Science Direct, and Scopus databases. Based on the selection process, 12 studies were included in this review. Results: Eleven studies utilized a CNN model for detection tasks, 5 for classification tasks, and 3 for segmentation tasks in the context of tooth numbering on panoramic radiographs. Most of these studies revealed high performance of various CNN models in automating tooth numbering. However, several studies also highlighted limitations of CNNs, such as the presence of false positives and false negatives in identifying decayed teeth, teeth with crown prosthetics, teeth adjacent to edentulous areas, dental implants, root remnants, wisdom teeth, and root canal-treated teeth. These limitations can be overcome by ensuring both the quality and quantity of datasets, as well as optimizing the CNN architecture. Conclusion: CNNs have demonstrated high performance in automated tooth numbering on panoramic radiographs. Future development of CNN-based models for this purpose should also consider different stages of dentition, such as the primary and mixed dentition stages, as well as the presence of various tooth conditions. Ultimately, an optimized CNN architecture can serve as the foundation for an automated tooth numbering system and for further artificial intelligence research on panoramic radiographs for a variety of purposes.
In this paper, we propose a novel method for monitoring mood trend of Twitter users by analyzing their daily tweets for a long period. Then, to more accurately understand their tweets, we analyze all types of content in tweets, i.e., texts and emoticons, and images, thus develop a multimodal sentiment analysis method. In the proposed method, two single-modal analyses first are performed to extract the users' moods hidden in texts and images: a lexicon-based and learning-based text classifier and a learning-based image classifier. Thereafter, the extracted moods from the respective analyses are combined into a tweet mood and aggregated a daily mood. As a result, the proposed method generates a user daily mood flow graph, which allows us for monitoring the mood trend of users more intuitively. For evaluation, we perform two sets of experiment. First, we collect the data sets of 40,447 data. We evaluate our method via comparing the state-of-the-art techniques. In our experiments, we demonstrate that the proposed multimodal analysis method outperforms other baselines and our own methods using text-based tweets or images only. Furthermore, to evaluate the potential of the proposed method in monitoring users' mood trend, we tested the proposed method with 40 depressive users and 40 normal users. It proves that the proposed method can be effectively used in finding depressed users.
Application developers need effective reuseable methodology to meet rapidly changes and variety of users requirements. Product Line and CBD(Component Based Development) offer the great benefits on quality and productivity for developing the software that is mainly associate with reusable architectures and components in a specific domain and rapidly changing environments. Product line can dynamically focus on the commonality and variety feature model among the products. The product line uses the feature modeling for discovering, analyzing, and mediating interactions between products. Reusable architectures include many variety plans and mechanisms. In case of those architecture are use in product version for a long time, It is very important in architecture product line context for product line design phase. Application developer need to identify the proper location of architecture changing for variety expression. It is lack of specific variety managements to design the product line architecture until nowdays. In this paper, we define various variety types to identify the proper location of architecture changing for variety expression and to design the reusable architecture. We also propose architecture variety on feature model and describe variety expression on component relations. We implemented the web learning system based on the methodology. We finally describe how these methodology may assist in increasing the efficiency, reusability, productivity and quality to develop an application. In the future, we are going to apply the methodology into various domain and suggest international and domestic's standardization.
Purpose - A trading area is very closely related to consumer life. A trading area is a cultural and social space that consumes culture and promotes human relationships as well as an economic space where consumers live their daily lives. In this context, a trading area research should be conducted objectively and empirically because it deals with the activities of consumer's life. The purpose of this study is to identify the intrinsic psychological motivation(push motivation) caused when consumers visit a trading area and to demonstrate how the push motivation for a trading area influence on consumer's flow, satisfaction, revisit intention. Research design, data, and methodology - In order to develop research hypotheses for this study, the development procedures for push motivation scale are as follows; (1) generating initial pool of items based on previous studies, (2) expert judgement to evaluate content and face validity, and (3) assessing convergent and discriminant validity using confirmatory factor analysis. In order to achieve these purposes, online surveys were conducted on frequent or familiar visitors to the trading areas around the Gangnam, Kunkuk University and Hongik University Station. Among the 1,343 questionnaires collected, 1,157 cases were analyzed by using SPSS 22.0 and SmartPLS 3.0 statistical package program, except for 186 responses in which responses were judged to be unfaithful. Results - The push motivation was classified into five sub-dimensions of excitement/stimulus, rest/relaxation, exit/refreshing, knowledge/learning and human relationship promotion as multidimensional and complex factors composed of individual and social-related dimensions. The excitement/stimulus and human relationship promotion of push motivation have positive effects on satisfaction. However, all dimensions of the push motivation have positive effects on flow. And flow has a positive effect on satisfaction and revisit intention. Meanwhile, the mediation test using boostrapping shows that flow plays a full mediating role in the relationship between rest/relaxation, exit/refreshing, knowledge/learning and satisfaction, but a partial mediating rol e between excitement/stimulus, human relationship promotion and satisfaction. Finally, satisfaction plays a partial mediating role between flow and revisit intention. Conclusions - This study shows that the push motivation is multidimensional and compositive depending on the situation of a consumer. In addition, it is found that the human relationship promotion(a social-related motivation) has a much more important effect on flow and satisfaction than other push motivations of individual dimensions. It also shows that satisfaction increases when consumers are being flowed at their visit and degree of revisit intention also grows as satisfaction increases. As implications of this study, a marketer should try to understand consumer's visit motivation at first and then develop factors that increase their flow, satisfaction, revisit intention. It also requires a marketer to approach subjects on a trading area more objectively and empirically based on the psychology and behavior of consumers, in order to establish a proper and efficient strategy on development of a trading area.
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