• Journal of the Korean Geographical Society
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• v.47 no.3
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• pp.440-458
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• 2012

This study analyzed the ignorance and prejudice with regard to African culture, which can be seen at the textbook and class course centering the geography class from 1990's to the present, and reviewed critically the related education and learning effects for mutual understanding. This study results are as follows: First, in the geographic environment contents, the image regarding huge continent, the local image regarding the various physical environments and the geographical importance as the ancient civilization birthplace were not included in the description. Second, the description regarding the African culture and history was focused to the singular African image, so the fixed concept and distorted image has been rooted into the formation of cultural meta-knowledge. Third, the negative sides rather than positive development and the past backward facts rather than changed status have been emphasized in the description regarding African resources and industry as well, so only the region surrounded with the various problems including poverty and the image as underdeveloped country have been rooted into the description. Now, real Africa view, an image for a variety of attractive and vibrant Africa rather than the same culture and characteristics of African must be learned in text books.

• Journal of Internet Computing and Services
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• v.16 no.3
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• pp.21-32
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• 2015

Since spatio-temporal local features for video representation have become an important issue of modeless bottom-up approaches in action recognition, various methods for feature extraction and description have been proposed in many papers. In particular, BoF(bag of features) has been promised coherent recognition results. The most important part for BoF is how to represent dynamic information of actions in videos. Most of existing BoF methods consider the video as a spatio-temporal volume and describe neighboring 3D interest points as complex volumetric patches. To simplify these complex 3D methods, this paper proposes a novel method that builds BoF representation as a way to learn 2D interest points directly from video data. The basic idea of proposed method is to gather feature points not only from 2D xy spatial planes of traditional frames, but from the 2D time axis called spatio-temporal frame as well. Such spatial-temporal features are able to capture dynamic information from the action videos and are well-suited to recognize human actions without need of 3D extensions for the feature descriptors. The spatio-temporal BoF approach using SIFT and SURF feature descriptors obtains good recognition rates on a well-known actions recognition dataset. Compared with more sophisticated scheme of 3D based HoG/HoF descriptors, proposed method is easier to compute and simpler to understand.

• Journal of the Korean association of regional geographers
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• v.8 no.2
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• pp.170-183
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• 2002

Recently it is supposed to be a shift to regional geography. To understand the emergence of the new regional geography, It must be remarked that the progress of capitalist production and consumption change our conceptional apparatus such as representation of space. Region is one of the important mode of representations of space and time. In the Fordist capitalism of 20th century, development is regarded as diffusion of capitalist expansion of western worlds. State must support capitalist growth through regional policies which include constructing of infrastructure and regionalization of spatial division of labour. The regional development theories contributed as ideology and policy tools for state intervention. The region was simply one of the most logical classification tools of organizing geographical informations. In the theories of regional development, the concept of region was reduced to the formal unit of classification. As the transition from Fordism to flexible accumulation, the region is again acquiring its 'identity' and 'authenticity'. In this tendency of the revival of region, it is expected that good achievement could be made in the field of regional geography through relevant research methods. It is also believed one of the available means are historical approaches to the cultural and ecological regions. The historical approaches to cultural and ecological regions are not only correspondent with cultural development strategies of local governments, but also could convey regional identities through both narrativization of place and aestheticization of landscape.

• KIPS Transactions on Software and Data Engineering
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• v.12 no.12
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• pp.519-524
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• 2023

In hashing-based image retrieval, the hash code of a manipulated image is different from the original image, making it difficult to search for the same image. This paper proposes and evaluates a self-supervised deephashing model that generates perceptual hash codes from feature information such as texture, shape, and color of images. The comparison models are autoencoder-based variational inference models, but the encoder is designed with a fully connected layer, convolutional neural network, and transformer modules. The proposed model is a variational inference model that includes a SimAM module of extracting geometric patterns and positional relationships within images. The SimAM module can learn latent vectors highlighting objects or local regions through an energy function using the activation values of neurons and surrounding neurons. The proposed method is a representation learning model that can generate low-dimensional latent vectors from high-dimensional input images, and the latent vectors are binarized into distinguishable hash code. From the experimental results on public datasets such as CIFAR-10, ImageNet, and NUS-WIDE, the proposed model is superior to the comparative model and analyzed to have equivalent performance to the supervised learning-based deephashing model. The proposed model can be used in application systems that require low-dimensional representation of images, such as image search or copyright image determination.

• Journal of Intelligence and Information Systems
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• v.19 no.4
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• pp.55-79
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• 2013

In this paper, we propose a hybrid genetic algorithm (HGA) approach to effectively solve the reverse logistics network with centralized centers (RLNCC). For the proposed HGA approach, genetic algorithm (GA) is used as a main algorithm. For implementing GA, a new bit-string representation scheme using 0 and 1 values is suggested, which can easily make initial population of GA. As genetic operators, the elitist strategy in enlarged sampling space developed by Gen and Chang (1997), a new two-point crossover operator, and a new random mutation operator are used for selection, crossover and mutation, respectively. For hybrid concept of GA, an iterative hill climbing method (IHCM) developed by Michalewicz (1994) is inserted into HGA search loop. The IHCM is one of local search techniques and precisely explores the space converged by GA search. The RLNCC is composed of collection centers, remanufacturing centers, redistribution centers, and secondary markets in reverse logistics networks. Of the centers and secondary markets, only one collection center, remanufacturing center, redistribution center, and secondary market should be opened in reverse logistics networks. Some assumptions are considered for effectively implementing the RLNCC The RLNCC is represented by a mixed integer programming (MIP) model using indexes, parameters and decision variables. The objective function of the MIP model is to minimize the total cost which is consisted of transportation cost, fixed cost, and handling cost. The transportation cost is obtained by transporting the returned products between each centers and secondary markets. The fixed cost is calculated by opening or closing decision at each center and secondary markets. That is, if there are three collection centers (the opening costs of collection center 1 2, and 3 are 10.5, 12.1, 8.9, respectively), and the collection center 1 is opened and the remainders are all closed, then the fixed cost is 10.5. The handling cost means the cost of treating the products returned from customers at each center and secondary markets which are opened at each RLNCC stage. The RLNCC is solved by the proposed HGA approach. In numerical experiment, the proposed HGA and a conventional competing approach is compared with each other using various measures of performance. For the conventional competing approach, the GA approach by Yun (2013) is used. The GA approach has not any local search technique such as the IHCM proposed the HGA approach. As measures of performance, CPU time, optimal solution, and optimal setting are used. Two types of the RLNCC with different numbers of customers, collection centers, remanufacturing centers, redistribution centers and secondary markets are presented for comparing the performances of the HGA and GA approaches. The MIP models using the two types of the RLNCC are programmed by Visual Basic Version 6.0, and the computer implementing environment is the IBM compatible PC with 3.06Ghz CPU speed and 1GB RAM on Windows XP. The parameters used in the HGA and GA approaches are that the total number of generations is 10,000, population size 20, crossover rate 0.5, mutation rate 0.1, and the search range for the IHCM is 2.0. Total 20 iterations are made for eliminating the randomness of the searches of the HGA and GA approaches. With performance comparisons, network representations by opening/closing decision, and convergence processes using two types of the RLNCCs, the experimental result shows that the HGA has significantly better performance in terms of the optimal solution than the GA, though the GA is slightly quicker than the HGA in terms of the CPU time. Finally, it has been proved that the proposed HGA approach is more efficient than conventional GA approach in two types of the RLNCC since the former has a GA search process as well as a local search process for additional search scheme, while the latter has a GA search process alone. For a future study, much more large-sized RLNCCs will be tested for robustness of our approach.

• Journal of the Korean Institute of Landscape Architecture
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• v.47 no.1
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• pp.57-75
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• 2019

Soundscapes have the potential to help people experience the historical background and cultural traditions by the scenery of a local area and to be used as a cultural and tourism resource. This concept was first explained in detail by M. Schafer and has been developed as a new way of experiencing landscapes using various senses. This research studied the soundscape of Kyodong Island, the so-called "Island of Peace" and designed new cultural acoustic content for education and tourism. Kyodong Island is located right below the Northern Limit Line and the whole island is in the Civilian Controlled Area. The political and economic status of the island has been changed dynamically by the Korean War and the division of the country. These days, the island needs to realize the vision of the "Island of Peace" in a more creative way using local resources, including its "cold war landscape" and the natural scenery of the region. This research applied the concept of a soundscape to document the island, and to reproduce it in an artistic way. A workshop was conducted to learn concepts and techniques of soundscapes with a sound artist. Listening, recording, conducting interviews, and literature research was used to study the soundscape of the island. After that, this research reconstructed the soundscape of the island through a soundscape composition. The main theme of the composition story was the "Hope and Wish for the Harmony and Peace" to show the vision of the "Island of Peace". The initial sub-theme for the introduction part was "First Encounter with Kyodong Island" arranging the representative soundscape, which could be the first impression of the region. The second sub-theme was "War and Tension" using several soundscapes as a metaphor for the tragedy of the Korean War. The third sub-theme was "Everyday Life of Kyodong Island" which described the energy of the present day, after the wounds of the war have healed. The final sub-theme was "Harmony and Peace" using traditional music and keynote sounds of the region as a reminder of the peaceful past, before the war. The recording files were documented as two types of sound maps. One was a two-dimensional map to show the soundscapes from one point of view, and the other used the online application called "Sound Around You". The final artwork was displayed at an exhibition and uploaded on YouTube to be shared publicly. Through this project, we discovered the potential of soundscapes as a medium to preserve the history and local identity, as well as presenting a new vision. The artwork will be exhibited at historically and culturally meaningful places on the Island to utilize the underused places as local tourist attractions and educational resources.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.39 no.2
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• pp.82-90
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• 2002

BDD have become widely used for various CAD applications because Boolean functions can be represented uniquely and compactly by using BDD. The size of the BDD representation for a function is very sensitive to the choice of orderings on the input variable. Therefore, it is very important to find a good variable ordering which minimize the size of the BDD. Since finding an optimal ordering is NP-complete, several heuristic algorithms have been proposed to find good variable orderings. In this paper, we propose a variable ordering algorithm, Faster-${\mu}$0, based on the ${\mu}$0(microcanonical optimization). In the Faster-${\mu}$0 algorithm, the initialization phase is replaced with a shifting phase to produce better solutions in a fast local search. We find values for algorithm parameters experimentally and the proposed algorithm has been experimented on well known benchmark circuits and shows superior performance compared to various existing algorithms.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.42 no.5 s.305
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• pp.19-26
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• 2005

In this paper, a new method for obtaining three-dimensional shape of an object by measuring relative blur between images using wavelet analysis has been described. Most of the previous methods use inverse filtering to determine the measure of defocus. These methods suffer from some fundamental problems like inaccuracies in finding the frequency domain representation, windowing effects, and border effects. Besides these deficiencies, a filter, such as Laplacian of Gaussian, that produces an aggregate estimate of defocus for an unknown texture, can not lead to accurate depth estimates because of the non-stationary nature of images. We propose a new depth from defocus (DFD) method using wavelet analysis that is capable of performing both the local analysis and the windowing technique with variable-sized regions for non-stationary images with complex textural properties. We show that normalized image ratio of wavelet power by Parseval's theorem is closely related to blur parameter and depth. Experimental results have been presented demonstrating that our DFD method is faster in speed and gives more precise shape estimates than previous DFD techniques for both synthetic and real scenes.

• Journal of the Korean Geographical Society
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• v.43 no.6
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• pp.873-893
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• 2008

This article focuses on reviewing place branding theories as a major toolkit of 'soft regional development'. Place branding provides sophisticate methodologies to strengthen city and regional image and identity. For effective place marketing practices, four of useful place branding tools are suggested. They include the methodology of place identity development, brand leadership system in local governance, construction of city brand architecture, and evaluation model for city brand equity. A process model is suggested for systematically organizing the diverse tools of place marketing and branding. The model is expected to be used as a framework of strategical soft regional development and planning. The place branding process model is to be an important theoretical and methodological basement of postmodern urban and regional development on which creativity, symbol and signs are more emphasized. More in-depth theoretical and empirical studies are needed. Geographical tradition and knowledge can play important roles in this inter-disciplinary process.

• Journal of the Korea Institute of Building Construction
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• v.17 no.4
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• pp.369-375
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• 2017

This study suggests PSO(Particle Swarm Optimization) algorithm that optimizes the snowplow route allocation and the location of the snow control material storage to improve the efficiency in snow removal works. The modified PSO algorithm for improving the search capacity is proposed, and this study suggests the solution representation, the parameter setting, and the fitness function for the given optimization problems. Computational experiments in real-world case are carried out to justify the proposed method and compared with the traditional PSO algorithms. The results show that the proposed algorithms can find the better solution than the traditional PSO algorithms by searching for the wider solution space without falling into the local optima. The finding of this study is efficiently employed to solve the optimization of the snowplow route allocation by minimizing the workload of each snowplow to search the location of the snow control material storage as well.