• Journal of the Korean Institute of Intelligent Systems
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• v.26 no.1
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• pp.56-63
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• 2016

In this study, we introduce a design of Fuzzy RBFNNs-based digit recognition system using the incremental-PCA in order to recognize the handwritten digits. The Principal Component Analysis (PCA) is a widely-adopted dimensional reduction algorithm, but it needs high computing overhead for feature extraction in case of using high dimensional images or a large amount of training data. To alleviate such problem, the incremental-PCA is proposed for the computationally efficient processing as well as the incremental learning of high dimensional data in the feature extraction stage. The architecture of Fuzzy Radial Basis Function Neural Networks (RBFNN) consists of three functional modules such as condition, conclusion, and inference part. In the condition part, the input space is partitioned with the use of fuzzy clustering realized by means of the Fuzzy C-Means (FCM) algorithm. Also, it is used instead of gaussian function to consider the characteristic of input data. In the conclusion part, connection weights are used as the extended diverse types in polynomial expression such as constant, linear, quadratic and modified quadratic. Experimental results conducted on the benchmarking MNIST handwritten digit database demonstrate the effectiveness and efficiency of the proposed digit recognition system when compared with other studies.

• International Journal of Highway Engineering
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• v.10 no.4
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• pp.9-18
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• 2008

Curling is caused by the difference in the temperature and humidity by the depth of the slab in Jointed Plain Concrete Pavement. Slab curvature shape and size change due to curling exert a profound influence on the internal stress and roughness of the pavement, affecting structural and functional performance of the pavement. Direct measurement of the slab curvature entails many problems. Many measuring instruments have to be installed at the early-stage of the pavement construction, and the behavior of the slab curvature needs to be measured accurately from the early-stage. Moreover, the cost and technical difficulty are very formidable to measure the slab curvature. This study develops a measurement method for slab curvature in jointed concrete pavement at any given time by applying Power Spectrum Density Analysis and Inverse Fast Fourier Transformation to the profile data, that can be easily obtained at the construction field site. The effectiveness of this developed method is verified by measuring the profile data of the test road of jointed concrete pavement at an inland central expressway by the hour and by examining the result of extracting the slab curvature shape from this profile data. Additionally, the profile data of CRCP(Continuously Reinforced Concrete Pavement) sections on the same expressway were obtained and analyzed at the same time. The validity of the method developed for the slab curvature shape extraction is verified by comparing the result from the analysis of the profile data of CRCP sections with that from the analysis of the prof1Ie data of jointed concrete pavement sections.

• Journal of Periodontal and Implant Science
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• v.31 no.3
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• pp.555-564
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• 2001

The purpose of this study is to evaluate the bioresorbability of Calcium Polyphosphate added with $Na_2O$ and chitosan. Though calcium phosphate ceramics meet some of the needs for bone replacement, they have some limitation of unresorbability and fibrous encapsulation without direct bone apposition during bone remodelling. To solve these problem, we developed a new ceramic, calcium polyphosphate(CPP), and report the biologic response to CPP in extraction sites of beagle dog. Porous CPP granules were prepared by condensation of anhydrous $Ca(H_2PO_4)_2$ to form non-crystalline $Ca(PO_3)_2$. CPP granules added with $Na_2O$ and chitosan were implanted in extraction sockets and histologic observation were performed at 12 weeks later. Histologic observation at 12 weeks revealed that CPP matrix were mingled with and directly apposed to new bone without any intervention of fibrous connective tissue. CPP granules added with chitosan were well adatped without any adverse tissue reaction and resorbed slowly and spontaneously. CPP granules added with $Na_2O$ and chitosan show multinucleated giant cells and osteoblast-like cells around grafted material and newly formed bone. This result revealed that CPP, regardless of its additive component, had a high affinity for bone and had been resorbed slowly. From this results, it was suggested that CPP is promising ceramic as a bone substitute and addition of $Na_2O$ and chitosan help biodegradation. In further study , it will be determined which concentration of $Na_2O$ help biodegradation and the other additive components increase the degradation rate.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.42 no.4 s.304
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• pp.95-102
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• 2005

In this paper, we propose a user friendly object-based image retrieval system using the interaction between cortex and hippocampus. Most existing ways of queries in content-based image retrieval rely on query by example or query by sketch. But these methods of queries are not adequate to needs of people's various queries because they are not easy for people to use and restrict. We propose a method of automatic color object extraction using CSB tree map(Color and Spatial based Binary をn map). Extracted objects were transformed to bit stream representing information such as color, size and location by region labelling algorithm and they are learned by the hippocampal neural network using the interplay between cortex and hippocampus. The cells of exciting at peculiar features in brain generate the special sign when people recognize some patterns. The existing neural networks treat each attribute of features evenly. Proposed hippocampal neural network makes an adaptive fast content-based image retrieval system using excitatory learning method that forwards important features to long-term memories and inhibitory teaming method that forwards unimportant features to short-term memories controlled by impression.

• Journal of the Institute of Electronics and Information Engineers
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• v.53 no.3
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• pp.114-123
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• 2016

The effective feature extraction method for unmanned aerial vehicle (UAV) detection is proposed and verified in this paper. The UAV engine sound is harmonic complex tone whose frequency ratio is integer and its variation is continuous in time. Using these characteristic, we propose the feature vector composed of a mean and standard deviation of difference value between fundamental frequency with 1st overtone as well as mean variation of their frequency. It was revealed by simulation that the suggested feature vector has excellent discrimination in target signal identification from various interfering signals including frequency variation with time. By comparing Fisher scores, three features based on frequency show outstanding discrimination of measured UAV signals with low signal to noise ratio (SNR). Detection performance with simulated interference signal is compared by MFCC by using ELM classifier and the suggested feature vector shows 37.6% of performance improvement As the SNR increases with time, the proposed feature can detect the target signal ahead of MFCC that needs 4.5 dB higher signal power to detect the target.

• The Journal of Society for e-Business Studies
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• v.23 no.3
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• pp.33-49
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• 2018

The importance of convergence activities among business is increasing due to the necessity of designing and developing new products to satisfy various customers' needs. In particular, decision makers such as CEOs are required to participate in networks between entrepreneurs for being connected with valuable convergence partners. Moreover, it is important for entrepreneurs not only to make a large number of network connections, but also to understand the networking relationship with entrepreneurs with similar topic information. However, there is a difficult limit in collecting the topic information that can show the lack of current status of business and the technology and characteristics of entrepreneur in industry sector. In this paper, we solve these problems through the topic extraction method and analyze the business network in three aspects. Specifically, there are C, S, T-Layer models, and each model analyzes amount of entrepreneurs relationship, network centrality, and topic similarity. As a result of experiments using real data, entrepreneur need to activate network by connecting high centrality entrepreneur when the corporate relationship is low. In addition, we confirmed through experiments that there is a need to activate the topic-based network when topic similarity is low between entrepreneurs.

• The Journal of the Convergence on Culture Technology
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• v.7 no.1
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• pp.291-299
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• 2021

In 2019, SUV sales surpassed sedans in the domestic sales market with phenomenal domestic sales. The strength of SUVs around the world is expected to continue in the future. South Korea's K-company aggressively launched small SUVs in the SUV market. Its simple lineup is recognized as a brand image, not as a SUV. It is time to evaluate this. Therefore, it influences the purchasing decisions of potential customers and buyers of small SUVs through the evaluation of design images of small SUVs in Korea. Rather than the functional properties of the SUV model, it is purchased by emotional characteristics, brand symbolism, and image. Subconsciousness of the purchasing psychology of the end consumer was used by metaphor extraction techniques. Customers wanted to study the evaluation of small SUV design images that fit their needs. We wanted to see if consumers who intend to purchase or purchase small SUVs in Korea had a connection with the image of design of small SUVs in Korea. The conclusion of the study was extracted through ZMET, a metaphor extraction technique, with the latent consciousness of the primary ambiguous message from the consumer's feeling and representation of the image. Therefore, based on the results of this study, we hope that the images presented in SUVs in the future will be used as a design guide in the development of small SUVs to influence customer thinking and behavior.

• Knowledge Management Research
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• v.22 no.2
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• pp.145-165
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• 2021

As of late December 2019, the spread of COVID-19 pandemic began which put the entire world in panic. In order to overcome the crisis and minimize any subsequent damage, the government as well as its affiliated institutions must maximize effects of pre-existing policy support and introduce a holistic response plan that can reflect this changing situation- which is why it is crucial to analyze social topics and people's interests. This study investigates people's major thoughts, attitudes and topics surrounding COVID-19 pandemic through the use of social media and big data. In order to collect public opinion, this study segmented time period according to government countermeasures. All data were collected through NAVER blog from 31 December 2019 to 12 December 2020. This research applied TF-IDF keyword extraction and LDA topic modeling as text-mining techniques. As a result, eight major issues related to COVID-19 have been derived, and based on these keywords, this research presented policy strategies. The significance of this study is that it provides a baseline data for Korean government authorities in providing appropriate countermeasures that can satisfy needs of people in the midst of COVID-19 pandemic.

• The Journal of Korea Assosiation for Disability and Oral Health
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• v.7 no.1
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• pp.25-28
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• 2011

Autism is a developmental, neuropsychiatric disorder that begins in early childhood. A patient with autism seen in the dental office frequently may have many complications. Therefore, it may be needed to consider modified or alternative therapy for dental care of autistic patients. This is the case of a 16-year old boy who have autism. He came to the department of the pediatric dentistry, Yonsei University Dental Hospital, for evaluation and treatment of dentigerous cyst associated with impacted teeth(#33,34,35). Under daily hospitalization and general anesthesia, the cyst was enucleated with surgical extraction of #34 and autotransplantation of #33,35. And during the periodic dental followup, apexification of #33,35 was performed for periapical lesion and root maturity. At 2 year 6 months follow- up, now, bony healing was completed and there are some complications like external resorption of #33 and space loss of #34 area. Generally, the marsupialization has been widely recommended for treatment of dentigerous cyst. However, in this case, there is a little possibility of spontaneous eruption after marsupialization considering of patient's age, location and angulation of the impacted tooth, root maturity. And there is necessity to choose the treatment that has low recurrence risk and needs short-term follow-up for autism. Above all, poor oral hygiene and lack of cooperation for decompression treatment is a matter of primary consideration. Consequently, enucleation of the cyst was chosen for the final treatment plan in this case. It is important to consider the conditions that affect the eruption of a dentigerous cyst-associated tooth to predict the successful eruption and special health care needs of the patient when the treatment plan is settled.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.29 no.6
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• pp.621-629
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• 2011

According to the development of technologies for generating the 3D spatial information, the needs for producing and updating the precise 3D objects with LoD 4 level are increased. On the other hand, the needs for real-time updating of 2D digital maps are expanded, based on the execution of various GIS projects. These 2D informations can be extracted from precisely constructed 3D spatial information, to do this the feasibility studies on extraction of the 2D information from the 3D spatial information is needed. In this study, 3D objects are modeled using multi-oblique images, and the objects are stereo-plotted using digital airborne images, as well. Then the two data sets are compared and analyzed. The results show that the accuracy assessments fulfill the 1/1,000 digital map accuracy standard of regulations for photogrametric surveying of National Geographic Information Institute, but the shapes and the areas of building objects are different between two data sets because of the portrayal standards. Consequently, researchers can conclude that it is possible to generate the building layer of large scale topographic map using multi-oblique images, but additional researches is needed to resolve the problems on differences of the portrayal standards.