• Korean Journal of Plant Resources
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• v.12 no.4
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• pp.324-339
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• 1999

Morphological reinvestigation, external characters and discriminant functional analysis(44 qualitative characters) were examined on 6 taxa of Korean Ophelia, including 5 taxa distributed in south Korea, and one taxon considered to be the variation type of Ophelia wilfordi in order to clarify the limit of intersection and interspecies. And to establish the taxonomic position. One taxon distributed in north Korea was included in the description of species by observation of herbarium specimen of the University of Tokyo in Japan. The two sections were successfully distinguished by internal structure of ovary, morphology of nectary, number of corolla lobe and calyx lobe, and species were also distinguished by morphology of cauline leaf, and color and spot of corolla, respectively. The variation type of Ophelia wilfordi was not distinguished with other species except for absent or present of purple spot in corolla lobe. The results of the discriminal functional analysis indicated that characters of corolla were the most important qualitative characters to distinguish the Ophelia taxa, and morphology of seed and seed coat was useful characters to distinguish taxa higher than species. Therefore the difficult problems of identification of species were successfully solved, and the taxonomic position in intrageneric level was clarified on Korean Ophelia.

• Cross-Cultural Studies
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• v.37
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• pp.51-79
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• 2014

Seriously depressed by the failure in the first performance of his own drama ${\ll}$The Government Inspector${\gg}$, N. Gogol sought out a space, Italy, which is obviously a turning point for the writer. Here in Italy, the writer could be able to explore an essential foundation for the national identity as well as self-identification of Russian traditional culture, all of which have already been epitomized in the Renaissance period in Italy. The city Rome itself provided Gogol with its grandness and harmonious perfectness, influencing something 'spiritual being' upon the writer. The work under discussion, "Rome," is thus created through these literary circumstances. Though it is made under the different title as "Annuntiata" and it delivers a love story between lovers, the story lines gradually turned into a fiction about the city, Rome. In comparison with city Paris, Gogol himself presents a negative view of the French metropolitan, saying that it is nothing but a by-product of the 19th century civilization. Interestingly enough, Rome for Gogol is totally different; it is the place of sublimity, that is a locus of harmonious, holy, and eternal city. Likewise, this pattern can be said of another description on the two contradictory cities: Paris and Rome. Again, Gogol fully pictures the city Paris as centripetal and Rome as centrifugal, in which the main protagonist makes the reader indulge in his own world. Throughout the story the writer tells us a transformation experienced by his character, and the work ends with an open denouement. Like Jerusalem, Rome is the city of resurrection for Gogol. Yet, this kind of possibility of transformation in the story is exposed to the hero, and it arguably depends on the extent to which he explores the readiness for encountering of 'eternity' in this "eternal city."

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.4
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• pp.1765-1794
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• 2019

Genetic Programming (GP) is an intelligence technique whereby computer programs are encoded as a set of genes which are evolved utilizing a Genetic Algorithm (GA). In other words, the GP employs novel optimization techniques to modify computer programs; imitating the way humans develop programs by progressively re-writing them for solving problems automatically. Trial programs are frequently altered in the search for obtaining superior solutions due to the base is GA. These are evolutionary search techniques inspired by biological evolution such as mutation, reproduction, natural selection, recombination, and survival of the fittest. The power of GAs is being represented by an advancing range of applications; vector processing, quantum computing, VLSI circuit layout, and so on. But one of the most significant uses of GAs is the automatic generation of programs. Technically, the GP solves problems automatically without having to tell the computer specifically how to process it. To meet this requirement, the GP utilizes GAs to a "population" of trial programs, traditionally encoded in memory as tree-structures. Trial programs are estimated using a "fitness function" and the suited solutions picked for re-evaluation and modification such that this sequence is replicated until a "correct" program is generated. GP has represented its power by modifying a simple program for categorizing news stories, executing optical character recognition, medical signal filters, and for target identification, etc. This paper reviews existing literature regarding the GPs and their applications in different scientific fields and aims to provide an easy understanding of various types of GPs for beginners.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.21 no.1
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• pp.85-91
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• 2011

The technique, which is able to detect and recognize characters in videos such as a movie or TV drama, can be used for applications which are database management of a general user's facial images for the suppliers of PVR(personal video recorder), mobile phones, and multimedia, etc. In this paper, we propose a face detection algorithm. It searches the character through cast indexing when the scene is changed in video. It is consisted of three stages. The first step is the detection-step of the scene change after producing a paused image. The second step is the face detection-step using color information. The final step is the detection-step which detects its features by the facial boundary. According to the experimental result, it has detected faces in different conditions successfully and more advanced than the existing other one that are using only color information.

• Journal of the Korean Society for information Management
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• v.39 no.3
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• pp.311-336
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• 2022

This study analyzed the contents of Goodreads review data, which is a social cataloging service with the participation of book users around the world, to identify the preference factors that affect book users' book recommendations in the library information service environment. To understand user preferences from a more detailed point of view, sub-datasets for each rating group, each book, and each user were constructed in the sample selection process. Stratified sampling was also performed based on the result of topic modeling of review text data to include various topics. As a result, a total of 90 preference factors belonging to 7 categories('Content', 'Character', 'Writing', 'Reading', 'Author', 'Story', 'Form') were identified. Also, the general preference factors revealed according to the ratings, as well as the patterns of preference factors revealed in books and users with clear likes and dislikes were identified. The results of this study are expected to contribute to more sophisticated recommendations in future recommendation systems by identifying specific aspects of user preference factors.

• Journal of the Korea Society of Computer and Information
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• v.14 no.7
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• pp.25-32
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• 2009

In this paper, we propose a new handwriting verification method using pattern analysis in off-line environments. The proposed method first segments character regions in a document and extracts effective features from the segmented regions. It then estimates the similarity between the extracted non-linear features and reference ones by using dynamic time warping and principal component analysis. Our handwriting verification method extracts handwriting features effectively and enables the verification of handwriting with various lengths of features as well as ones of short patterns. The experimental results show that our method outperforms others in terms as accuracy. We expect that the proposed method will automate the manual handwriting verification tasks and provide much objectivity on handwriting identification.

• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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• v.6 no.6
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• pp.103-110
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• 2016

The recent frequent cases of damage due to leakage of medical data and the privacy of medical patients is increasing day by day. The government says the Privacy Rule regulations established for these victims, such as prevention. Medical data guidelines can be seen 'national medical privacy guidelines' is only released. When replacing the image data between the institutions it has been included in the image file (JPG, JPEG, TIFF) there is exchange of data in common formats such as being made when the file is leaked to an external file there is a risk that the exposure key identification information of the patient. This medial image file has no protection such as encryption, This this paper, introduces a masking technique using a mosaic technique encrypting the image file contains the application to optical character recognition techniques. We propose pseudonymization technique of personal information in the image data.

• Journal of Information Processing Systems
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• v.19 no.3
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• pp.289-301
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• 2023

Due to the development and dissemination of modern technology, anyone can easily communicate using services such as social network service (SNS) through a personal computer (PC) or smartphone. The development of these technologies has caused many beneficial effects. At the same time, bad effects also occurred, one of which was the spam problem. Spam refers to unwanted or rejected information received by unspecified users. The continuous exposure of such information to service users creates inconvenience in the user's use of the service, and if filtering is not performed correctly, the quality of service deteriorates. Recently, spammers are creating more malicious spam by distorting the image of spam text so that optical character recognition (OCR)-based spam filters cannot easily detect it. Fortunately, the level of transformation of image spam circulated on social media is not serious yet. However, in the mail system, spammers (the person who sends spam) showed various modifications to the spam image for neutralizing OCR, and therefore, the same situation can happen with spam images on social media. Spammers have been shown to interfere with OCR reading through geometric transformations such as image distortion, noise addition, and blurring. Various techniques have been studied to filter image spam, but at the same time, methods of interfering with image spam identification using obfuscated images are also continuously developing. In this paper, we propose a deep learning-based spam image detection model to improve the existing OCR-based spam image detection performance and compensate for vulnerabilities. The proposed model extracts text features and image features from the image using four sub-models. First, the OCR-based text model extracts the text-related features, whether the image contains spam words, and the word embedding vector from the input image. Then, the convolution neural network-based image model extracts image obfuscation and image feature vectors from the input image. The extracted feature is determined whether it is a spam image by the final spam image classifier. As a result of evaluating the F1-score of the proposed model, the performance was about 14 points higher than the OCR-based spam image detection performance.

• Fisheries and Aquatic Sciences
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• v.26 no.9
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• pp.569-581
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• 2023

The morphology and genetic identification of Rasbora lateristriata and Rasbora argyrotaenia between cultivated and wild populations has never been reported. This study compares morphology and cytochrome c oxidase (COI) genes between farmed and wild stock Rasbora spp. in Java and Sumatra island, Indonesia. We analyzed the truss network measurement (TNM) characters of 80 fish using discriminant function analysis statistical tests. DNA was extracted from muscle tissue of 24 fish specimens, which was then followed by polymerase chain reaction, sequencing, phylogenetic analysis, fixation index analysis, and statistical analysis of haplotype networks. Basic Local Alignment Search Tool analysis validated the following species: R. lateristriata and R. argyrotaenia from farming (Jogjakarta); Rasbora agryotaenia (Purworejo), R. lateristriata (Purworejo and Malang), Rasbora dusonensis (Palembang), and Rasbora einthovenii (Riau) from natural resources. Based on TNM characters, Rasbora spp. were divided into four groups, referring to four distinct characters in the middle of the body. The phylogenetic tree is divided into five clades. The genetic distance between R. argyrotaenia (Jogjakarta) and R. lateristriata (Malang) populations (0.66) was significantly different (p < 0.05). R. lateristriata (Purworejo) has the highest nucleotide diversity (0.43). R. argyrotaenia from Jogjakarta and Purworejo shared the same haplotype. The pattern of gene flow among them results from the two populations' close geographic proximity and environmental effects. R. argyrotaenia had low genetic diversity, therefore, increasing heterozygosity in cultivated populations is necessary to avoid inbreeding. Otherwise, R. lateristriata (Purworejo) had a greater gene variety that could be used to develop breeding. In conclusion, the middle body parts are a distinguishing morphometric character of Rasbora spp., and the COI gene is more heterozygous in the wild population than in farmed fish, therefore, enrichment of genetic variation is required for sustainable Rasbora fish farming.

• International Journal of Computer Science & Network Security
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• v.24 no.3
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• pp.125-134
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• 2024

The novel coronavirus 2019 is called COVID-19 has outspread swiftly worldwide. An early diagnosis is more important to control its quick spread. Medical imaging mechanics, chest calculated tomography or chest X-ray, are playing a vital character in the identification and testing of COVID-19 in this present epidemic. Chest X-ray is cost effective method for Covid-19 detection however the manual process of x-ray analysis is time consuming given that the number of infected individuals keep growing rapidly. For this reason, it is very important to develop an automated COVID-19 detection process to control this pandemic. In this study, we address the task of automatic detection of Covid-19 by using a popular deep learning model namely the VGG19 model. We used 1300 healthy and 1300 confirmed COVID-19 chest X-ray images in this experiment. We performed three experiments by freezing different blocks and layers of VGG19 and finally, we used a machine learning classifier SVM for detecting COVID-19. In every experiment, we used a five-fold cross-validation method to train and validated the model and finally achieved 98.1% overall classification accuracy. Experimental results show that our proposed method using the deep learning-based VGG19 model can be used as a tool to aid radiologists and play a crucial role in the timely diagnosis of Covid-19.