• Journal of the Korea Fashion and Costume Design Association
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• v.23 no.4
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• pp.39-56
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• 2021

The purpose of this study was to observe the expressive characteristics of Neo-Deconstruction design, examine the expressive characteristics of Neo-Deconstruction design in the collections of Jacquemus, and analyze their internal meanings. For research, observations were made based on the concepts and expressive characteristics of Deconstruction through prior research and literary review, and analysis was conducted focusing on the expressive characteristics of Neo-Deconstruction. The scope of analysis included a total of 605 photographs collected from a total of 17 season collections of Jacquemus from the 2013 S/S to the 2021 S/S season. The results are as follows. First, the Neo-Deconstruction of Jacquemus expresses the youth culture using bright images such as diverse colors and patterns with 'positive playfulness' and pass on positive messages with deconstructive and playful forms, such as exaggeration and reduction and recombination and reconstitution. Second, with tendencies of 'symbolic receptivity', Jacquemus gained inspiration from his own life, memories, and hometown, and attempted to express the street women of places such as southern France, Paris, and Monaco in a number of collections. Also, he proposed designs that can be worn easily by anyone, regardless of gender, and as plus size models began to become more common respect was given to the tastes and preferences of diverse individuals without distinctions based on body type or sexuality. Third, 'geometric simplicity' was generally expressed by pursuing simple and practical fashion with the addition of details, such as geometric forms including stripes or asymmetrical expressions centering around everyday material that is used in clothing. Fourth, with "open communication," Jacquemus constructed his identity by addressing the various needs of consumers based on social network services and continuously sharing his creative ideas with the public. He is gaining popularity in a unique way by responding quickly to the changing atmosphere of society.

• Smart Structures and Systems
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• v.29 no.1
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• pp.195-206
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• 2022

Crack detection is essential for inspection of existing structures and crack segmentation based on deep learning is a significant solution. However, datasets are usually one of the key issues. When building a new dataset for deep learning, laborious and time-consuming annotation of a large number of crack images is an obstacle. The aim of this study is to develop an approach that can automatically select a small portion of the most informative crack images from a large pool in order to annotate them, not to label all crack images. An active learning method with difficulty learning mechanism for crack segmentation tasks is proposed. Experiments are carried out on a crack image dataset of a steel box girder, which contains 500 images of 320×320 size for training, 100 for validation, and 190 for testing. In active learning experiments, the 500 images for training are acted as unlabeled image. The acquisition function in our method is compared with traditional acquisition functions, i.e., Query-By-Committee (QBC), Entropy, and Core-set. Further, comparisons are made on four common segmentation networks: U-Net, DeepLabV3, Feature Pyramid Network (FPN), and PSPNet. The results show that when training occurs with 200 (40%) of the most informative crack images that are selected by our method, the four segmentation networks can achieve 92%-95% of the obtained performance when training takes place with 500 (100%) crack images. The acquisition function in our method shows more accurate measurements of informativeness for unlabeled crack images compared to the four traditional acquisition functions at most active learning stages. Our method can select the most informative images for annotation from many unlabeled crack images automatically and accurately. Additionally, the dataset built after selecting 40% of all crack images can support crack segmentation networks that perform more than 92% when all the images are used.

• Journal of Digital Contents Society
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• v.16 no.4
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• pp.565-573
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• 2015

The development of social media in the 2000s led the unspecified individuals to band together for common interests. Social networking services served as a far-reaching tool for sharing different thoughts and interpretation of the pop culture and helped people build up close relations driven by their common interests for certain works of the pop culture. This Study introduces the TV Series as a case that displays specific patterns of communication between its producer and viewers. Producer Bryan Fuller of the Series as well as key production staffs were quite active on social networking sites with the understanding of what the audience desired and the willingness to sympathize with them, which were eagerly welcomed by the dedicated audience whose number, though, was not big. For the Hannibal production team, SNS was a means for them to just be consumers who appreciate the work instead of solely being the content provider. Their approach is quite different from unilateral marketing approaches employed in the past. Through this case, the Study aims to suggest that social networking sites serve as a powerful medium connecting producers and viewers or as an information hub, and that how interactive contents shall be delivered in the new media environment to be effective.

• Journal of Internet of Things and Convergence
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• v.8 no.4
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• pp.25-40
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• 2022

This study aimed to understand the increasing number of elder abuses in South Korea, where entry into the super-aged society is imminent, by implementing text mining analysis. Korean Academic journals were obtained from 2004, the establishment year of the senior care agency, to 2021. We performed natural language processing of the titles, keywords, and abstracts and divided them into three segments of periods to identify latent meanings in the data. The results illustrated that the first section included 81 papers, the second 64, and the third 104 respectively, averaging 13.8 annually, which increased its numbers from 2014 until the decrease below the annual average in 2020. Word frequency demonstrated that the common keywords of the entire segments were 'elder abuse,' 'elders,' 'influences,' 'factors,' 'recognition,' 'family,' 'society,' 'prevention plans,' 'experiences,' 'abused elders,' 'abuse prevention,' 'depression,' etc., in consecutive order. TF-IDF indicated that 'influences,' 'recognition,' 'society,' 'prevention plans,' 'abuse prevention,' 'experiences,' 'depression,' etc., were the common keywords of all divisions. Network text analysis displayed that the commonly represented keywords were 'elder abuse,' 'elders,' 'influences,' 'factors,' 'characteristics,' 'recognition,' 'family,' 'prevention plans,' 'society,' 'abuse prevention,' and 'experiences' in the entire sections. concor analysis presented that the first segment consisted of 5 groups, the second 7, and the third 6. We suggest future directions for elder abuse research based on the results.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1993.06a
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• pp.1041-1043
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• 1993

Fuzzy logic based Control Theory has gained much interest in the industrial world, thanks to its ability to formalize and solve in a very natural way many problems that are very difficult to quantify at an analytical level. This paper shows a solution for treating membership function inside hardware circuits. The proposed hardware structure optimizes the memoried size by using particular form of the vectorial representation. The process of memorizing fuzzy sets, i.e. their membership function, has always been one of the more problematic issues for the hardware implementation, due to the quite large memory space that is needed. To simplify such an implementation, it is commonly [1,2,8,9,10,11] used to limit the membership functions either to those having triangular or trapezoidal shape, or pre-definite shape. These kinds of functions are able to cover a large spectrum of applications with a limited usage of memory, since they can be memorized by specifying very few parameters ( ight, base, critical points, etc.). This however results in a loss of computational power due to computation on the medium points. A solution to this problem is obtained by discretizing the universe of discourse U, i.e. by fixing a finite number of points and memorizing the value of the membership functions on such points [3,10,14,15]. Such a solution provides a satisfying computational speed, a very high precision of definitions and gives the users the opportunity to choose membership functions of any shape. However, a significant memory waste can as well be registered. It is indeed possible that for each of the given fuzzy sets many elements of the universe of discourse have a membership value equal to zero. It has also been noticed that almost in all cases common points among fuzzy sets, i.e. points with non null membership values are very few. More specifically, in many applications, for each element u of U, there exists at most three fuzzy sets for which the membership value is ot null [3,5,6,7,12,13]. Our proposal is based on such hypotheses. Moreover, we use a technique that even though it does not restrict the shapes of membership functions, it reduces strongly the computational time for the membership values and optimizes the function memorization. In figure 1 it is represented a term set whose characteristics are common for fuzzy controllers and to which we will refer in the following. The above term set has a universe of discourse with 128 elements (so to have a good resolution), 8 fuzzy sets that describe the term set, 32 levels of discretization for the membership values. Clearly, the number of bits necessary for the given specifications are 5 for 32 truth levels, 3 for 8 membership functions and 7 for 128 levels of resolution. The memory depth is given by the dimension of the universe of the discourse (128 in our case) and it will be represented by the memory rows. The length of a world of memory is defined by: Length = nem (dm(m)＋dm(fm) Where: fm is the maximum number of non null values in every element of the universe of the discourse, dm(m) is the dimension of the values of the membership function m, dm(fm) is the dimension of the word to represent the index of the highest membership function. In our case then Length=24. The memory dimension is therefore 128*24 bits. If we had chosen to memorize all values of the membership functions we would have needed to memorize on each memory row the membership value of each element. Fuzzy sets word dimension is 8*5 bits. Therefore, the dimension of the memory would have been 128*40 bits. Coherently with our hypothesis, in fig. 1 each element of universe of the discourse has a non null membership value on at most three fuzzy sets. Focusing on the elements 32,64,96 of the universe of discourse, they will be memorized as follows: The computation of the rule weights is done by comparing those bits that represent the index of the membership function, with the word of the program memor . The output bus of the Program Memory (μCOD), is given as input a comparator (Combinatory Net). If the index is equal to the bus value then one of the non null weight derives from the rule and it is produced as output, otherwise the output is zero (fig. 2). It is clear, that the memory dimension of the antecedent is in this way reduced since only non null values are memorized. Moreover, the time performance of the system is equivalent to the performance of a system using vectorial memorization of all weights. The dimensioning of the word is influenced by some parameters of the input variable. The most important parameter is the maximum number membership functions (nfm) having a non null value in each element of the universe of discourse. From our study in the field of fuzzy system, we see that typically nfm 3 and there are at most 16 membership function. At any rate, such a value can be increased up to the physical dimensional limit of the antecedent memory. A less important role n the optimization process of the word dimension is played by the number of membership functions defined for each linguistic term. The table below shows the request word dimension as a function of such parameters and compares our proposed method with the method of vectorial memorization[10]. Summing up, the characteristics of our method are: Users are not restricted to membership functions with specific shapes. The number of the fuzzy sets and the resolution of the vertical axis have a very small influence in increasing memory space. Weight computations are done by combinatorial network and therefore the time performance of the system is equivalent to the one of the vectorial method. The number of non null membership values on any element of the universe of discourse is limited. Such a constraint is usually non very restrictive since many controllers obtain a good precision with only three non null weights. The method here briefly described has been adopted by our group in the design of an optimized version of the coprocessor described in [10].

• Journal of Plant Biotechnology
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• v.38 no.2
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• pp.162-168
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• 2011

High salinity is a common stress condition that adversely affects plant growth and crop production. In response to various environmental stresses, plants activate a number of defense genes that function to increase the tolerance. To isolate Arabidopsis genes that are involved in abiotic stress responses, we carried out genetic screening using various mutant lines. Among them, the blh8 ($\b{B}$EL1-$\b{L}$ike $\b{H}$omeodomain $\underline{8}$) mutant specifically shows chlorotic phenotypes to ionic (specifically, $Na^+$ and $K^+$) stresses, but no differences in root growth. In addition, BLH8 is related to plant development and abiotic stress as predicted by a Graphical Gaussian Model (GGM) network program. It implies that BLH8 functions as a putative transcription factor related to abiotic stress responses. Collectively, our results show that gene network analysis is a useful tool for isolating genes involved in stress adaptation in plants.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.43 no.7 s.349
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• pp.60-71
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• 2006

Group key agreement protocols are designed to allow a group of parties communicating over a public network to securely and efficiently establish a common secret key, Over the years, a number of solutions to the group key agreement protocol have been proposed with varying degrees of complexity, and the research relating to group key agreement to securely communicate among a group of members in integrated wired and wireless networks has been recently proceeded. Both features of wired computing machines with the high-performance and those of wireless devices with the low-power are considered to design a group key agreement protocol suited for integrated wired and wireless networks. Especially, it is important to reduce computational costs of mobile devices which have the limited system resources. In this paper, we present an efficient group key agreement scheme which minimizes the computational costs of mobile devices and is well suited for this network environment and prove its security.

• Journal of Biomedical Engineering Research
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• v.29 no.1
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• pp.32-39
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• 2008

This paper reports on a realtime OS based master-slave configuration robot control system for laparoscopic surgery robot which enables telesurgery and overcomes shortcomings with conventional laparoscopic surgery. Surgery robot system requires control system that can process large volume information such as medical image data and video signal from endoscope in real-time manner, as well as precisely control the robot with high reliability. To meet the complex requirements, the use of high-level real-time OS (Operating System) in surgery robot controller is a must, which is as common as in many of modem robot controllers that adopt real-time OS as a base system software on which specific functional modules are implemened for more reliable and stable system. The control system consists of joint controllers, host controllers, and user interface units. The robot features a compact slave robot with 5 DOF (Degree-Of-Freedom) expanding the workspace of each tool and increasing the number of tools operating simultaneously. Each master, slave and Gill (Graphical User Interface) host runs a dedicated RTOS (Real-time OS), RTLinux-Pro (FSMLabs Inc., U.S.A.) on which functional modules such as motion control, communication, video signal integration and etc, are implemented, and all the hosts are in a gigabit Ethernet network for inter-host communication. Each master and slave controller set has a dedicated CAN (Controller Area Network) channel for control and monitoring signal communication with the joint controllers. Total 4 pairs of the master/slave manipulators as current are controlled by one host controller. The system showed satisfactory performance in both position control precision and master-slave motion synchronization in both bench test and animal experiment, and is now under further development for better safety and control fidelity for clinically applicable prototype.

• Journal of Intelligence and Information Systems
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• v.18 no.1
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• pp.91-107
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• 2012

As the Internet becomes more popular, many people use it to communicate. With the increasing number of personal homepages, blogs, and social network services, people often expose their personal information online. Although the necessity of those services cannot be denied, we should be concerned about the negative aspects such as personal information leakage. Because it is impossible to review all of the past records posted by all of the people, an automatic personal information detection method is strongly required. This study proposes a method to detect or classify online documents that contain personal information by analyzing features that are common to personal information related documents and learning that information based on the Na$\ddot{i}$ve Bayes algorithm. To select the document classification algorithm, the Na$\ddot{i}$ve Bayes classification algorithm was compared with the Vector Space classification algorithm. The result showed that Na$\ddot{i}$ve Bayes reveals more excellent precision, recall, F-measure, and accuracy than Vector Space does. However, the measurement level of the Na$\ddot{i}$ve Bayes classification algorithm is still insufficient to apply to the real world. Lewis, a learning algorithm researcher, states that it is important to improve the quality of category features while applying learning algorithms to some specific domain. He proposes a way to incrementally add features that are dependent on related documents and in a step-wise manner. In another experiment, the algorithm learns the additional dependent features thereby reducing the noise of the features. As a result, the latter experiment shows better performance in terms of measurement than the former experiment does.

• International Journal of Computer Science & Network Security
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• v.21 no.12spc
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• pp.459-462
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• 2021

The article examines the main problems of land market formation in Ukraine. The article is devoted to the study of problems and prospects of land market introduction after the abolition of the ban on alienation. The advantages and disadvantages of lifting the moratorium on the purchase and sale of agricultural land are highlighted. The experience of such European countries as France, Germany, Latvia, Romania and Poland in regulating the market of agricultural lands is analyzed. The historical stages of market formation, features of state policy in this area are considered. The authors found that in these countries the market for agricultural land is well developed and works effectively, which has positive consequences for the economy of these countries. After analyzing the experience, we identified common elements of an effective mechanism for regulating the land market in European countries, which can be implemented in Ukraine. It is emphasized that after the opening of the land market it is necessary to prevent the concentration of a large number of agricultural lands in the hands of one person or close persons and it is necessary to create an effective supervisory body, whose main functions will be supervising sales prevention of speculation in the land market. Emphasis is placed on the need to improve legislation in the field of land, organizational and informational conditions for land reform. The Law of Ukraine "On Amendments to Certain Legislative Acts of Ukraine Concerning the Circulation of Agricultural Land" was analyzed, the adoption of which put an end to the systematic extension of the moratorium on the sale of agricultural land. The positive aspects of such reservations are noted, such as the gradual introduction of the land market, quantitative restrictions, the lower limit of the value equivalent, which can not be less than the normative monetary value. At the same time, the problem is that the lack of an imperative norm on termination of the lease agreement in case of refusal of the lessee to purchase such land at a price not lower than expert assessment, will negatively affect its price formation and actually make the landlord hostage.