• Journal of KIISE:Software and Applications
• /
• v.27 no.1
• /
• pp.13-23
• /
• 2000

As software becomes more complicated and large-scaled, user's demands become more varied and his expectation levels about software products are raised. Therefore it is very important that a software engineer analyzes user's requirements precisely and applies it effectively in the development step. This paper presents a requirements analysis system that reduces and revises errors of requirements specifications analysis effectively. As this system measures the similarity among requirements documents and sentences, it assists users in analyzing the dependency among requirements specifications and finding the traceability, redundancy, inconsistency and incompleteness among requirements sentences. It also extracts sentences that contain ambiguous words. Indexing method for the similarity measurement combines sliding window model and dependency structure model. This method can complement each model's weeknesses. This paper verifies the efficiency of similarity measure techniques through experiments and presents a proccess of the requirements specifications analysis using the embodied system.

• Korean Journal of Remote Sensing
• /
• v.22 no.4
• /
• pp.275-284
• /
• 2006

The noise sources of a Hyperion image are mainly due to the atmospheric effects, the sensor's instrumental errors, and A/D conversion. Though uncalibrated, overlapping, and all deep water absorption bands generally are removed, there still exist noisy bands. The visual inspection for selecting clean and stable processing bands is a simple practice, but is a manual, inefficient, and subjective process. In this paper, we propose that the extrema ratio be used for noise estimation and unsupervised band selection. The extrema ratio was compared with existing SNR and entropy measures. First, Gaussian, salt and pepper, and Speckle noises were added to ALI (Advanced Land Imager) images with relatively low noises, and the relation of noise level and those measures was explored. Second, the unsupervised band selection was performed through the EM (Expectation-Maximization) algorithm of the measures which were extracted from a Hyperion images. The Hyperion data were classified into 5 categories according to the image quality by visual inspection, and used as the reference data. The experimental result showed that the extrema ratio could be used effectively for band selection of Hyperion images.

• Korean Journal of Remote Sensing
• /
• v.33 no.5_1
• /
• pp.455-467
• /
• 2017

When performing target detection using hyperspectral imagery, a feature extraction process is necessary to solve the problem of redundancy of adjacent spectral bands and the problem of a large amount of calculation due to high dimensional data. This study proposes a new band selection method using the $L_{2,1}$-norm regression model to apply the feature selection technique in the machine learning field to the hyperspectral band selection. In order to analyze the performance of the proposed band selection technique, we collected the hyperspectral imagery and these were used to analyze the performance of target detection with band selection. The Adaptive Cosine Estimator (ACE) detection performance is maintained or improved when the number of bands is reduced from 164 to about 30 to 40 bands in the 350 nm to 2500 nm wavelength band. Experimental results show that the proposed band selection technique extracts bands that are effective for detection in hyperspectral images and can reduce the size of the data without reducing the performance, which can help improve the processing speed of real-time target detection system in the future.

• Korean Journal of Microbiology
• /
• v.39 no.1
• /
• pp.36-39
• /
• 2003

The rapid and reliable 16S rDNA multiplex polymerase chain reaction (PCR) assay was established to characterize bacterial etiologies of middle ear effusion. These etiologies included Haemophilus influenzae, Moraxella catarrhalis and Streptococcus pneumonia, which were detected in middle-ear effusion (MEE) samples taken from patient with otitis media. A total of 39 MEE samples were aspirated from 26 patients. DNA was extracted from MEE samples, and PCR was done with DNA extracts by using the common primers, which is localized at C4 region in the 16S rDNA gene of all bacterial species, and species-specific primers: (i) Haemophilus-specific primer, (ii) Moraxella- specific primer, and (iii) Streptococcus-specific primer. Among 39 samples tested, 24 (61.5%) were positive for H. influenzae, 10 (25.6%) were positive for M. catarrhalis, 3(7.7%) were positive for S. pneumonia, and 11 (28%) were negative for 165 rDNA multiplex PCR reaction. Nine samples (28.6%) exhibited a mixed infection and were positive for both H. infuenzae and M. catarrhalis. We suggested that 16S rDNA multiplex PCR is a useful method to identify rapidly for rapid identification of the pathogenic bacteria and characterization of bacterial etiologies of middle ear effusion.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.21 no.11
• /
• pp.420-426
• /
• 2020

The purpose and main points of the ROK-US Navy were analyzed from various angles using the big data technology Word Cloud for efficient sea trials. First, a comparison of words extracted through keyword cleansing in the ROK-US Navy sea trial showed that the ROK Navy conducted a single equipment test, and the US Navy conducted an integrated test run focusing on the system. Second, an analysis of the ROK-US Navy sea trials showed that approximately 66.6% were analyzed as similar items, of which more than two items were 112 items Approximately 44% of the 252 items of the ROK Navy sea trials overlapped, and that 89 items (35% of the total) could be reduced when integrated into the US Navy sea trials. A ship is a complex system in which multiple equipment operates simultaneously. The focus on checking the functions and performance of individual equipment, such as the ROK Navy's sea trials, will increase the sea trial period because of the excessive number of sea trial targets. In addition, the budget required will inevitably increase due to an increase in schedule and evaluation costs. In the future, further research will be needed to achieve more efficient and accurate sea trials through integrated system evaluations, such as the U.S. Navy sea trials.

• Journal of Intelligence and Information Systems
• /
• v.15 no.2
• /
• pp.33-48
• /
• 2009

Capsule endoscopy is one of the most remarkable inventions in last ten years. Causing less pain for patients, diagnosis for entire digestive system has been considered as a most convenience method over a normal endoscope. However, it is known that the diagnosis process typically requires very long inspection time for clinical experts because of considerably many duplicate images of same areas in human digestive system due to uncontrollable movement of a capsule endoscope. In this paper, we propose a method for clinical diagnosticians to get highly valuable information from capsule-endoscopy video. Our software system consists of three global maps, such as movement map, characteristic map, and brightness map, in temporal domain for entire sequence of the input video. The movement map can be used for effectively removing duplicated adjacent images. The characteristic and brightness maps provide frame content analyses that can be quickly used for segmenting regions or locating some features(such as blood) in the stream. Our experiments show the results of four patients having different health conditions. The result maps clearly capture the movements and characteristics from the image frames. Our method may help the diagnosticians quickly search the locations of lesion, bleeding, or some other interesting areas.

• Journal of Internet Computing and Services
• /
• v.22 no.2
• /
• pp.89-107
• /
• 2021

This paper explores the empirically analyzes the competitive nature of the five social media by analyzing the proper SNS service such as Facebook, Instagram, YouTube, Pinterest, and Twitter. In this study, we surveyed the use and satisfaction of social media for SNS users by using the proper theory. A total of 224 users were selected for analysis. Based on the results of the questionnaire, factor analysis was carried out to extract common factors such as relationship, sociality, convenience, daily life, and entertainment. As a result of the research using proper analysis, Facebook showed the widest narrowness in sociality (.627) and convenience (.636) in the first place, and YouTube showed the lowest in daily life (.670) and entertainment (.615) In the relationship (.520), the Instagram was the widest. In terms of five factors, Facebook and YouTube have the greatest overlap in relationship (1.826) and sociality (2.696), while Pinterest and Twitter are the most common in daily life (1.937) and entertainment (2.263) There is redundancy, and for convenience (2.583), YouTube and Twitter have the most redundancy. Facebook, Instagram, and YouTube have a competitive advantage over Pinterest in terms of relationships, sociality, convenience, routine, and entertainment, and are competitive across all factors except Facebook, Instagram, and YouTube Twitter It is possible to confirm that it is superior.

• Journal of the Korea Society for Simulation
• /
• v.19 no.1
• /
• pp.143-151
• /
• 2010

Fingerprint classification is a step to increase the efficiency of an 1:N fingerprint recognition system and plays a role to reduce the matching time of fingerprint and to increase accuracy of recognition. It is difficult to classify fingerprints, because the ridge pattern of each fingerprint class has an overlapping characteristic with more than one class, fingerprint images may include a lot of noise and an input condition is an exceptional case. In this paper, we propose a novel approach to design a stochastic model and to accomplish fingerprint classification using a directional characteristic of fingerprints for an effective classification of various qualities. We compute the directional value by searching a fingerprint ridge pixel by pixel and extract a directional characteristic by merging a computed directional value by fixed pixels unit. The modified Markov model of each fingerprint class is generated using Markov model which is a stochastic information extraction and a recognition method by extracted directional characteristic. The weight list of classification model of each class is decided by analyzing the state transition matrixes of the generated Markov model of each class and the optimized value which improves the performance of fingerprint classification using GA (Genetic Algorithm) is estimated. The performance of the optimized classification model by GA is superior to the model before the optimization by the experiment result of applying the fingerprint database of various qualities to the optimized model by GA. And the proposed method effectively achieved fingerprint classification to exceptional input conditions because this approach is independent of the existence and nonexistence of singular points by the result of analyzing the fingerprint database which is used to the experiments.

• Journal of the Korean Institute of Traditional Landscape Architecture
• /
• v.32 no.3
• /
• pp.10-20
• /
• 2014

The purpose of this study is to define criteria for landscape restoration of palace gardens. The case study on Gyeongbokgung and Changdeokgung was used not only to evaluate effectiveness of the criteria, but also to propose solutions to issues of current restoration process of both palace gardens. Following three pairs of different concepts were chosen as criteria to determine on the original form: Diachrony vs. Synchrony, Originality vs. Contemporary Characteristics, and Invariance vs. Deformability. Gyeongbokgung has been restored based on its contemporary characteristics of Year 1888 and the main focus is on its architectural features rather than both architecture and landscape. However, in-depth complementary work on landscape restoration is necessary to restore its originality in Year 1395 such as analyzing photos of Gyeongbokgung taken in modern era. In case of Changdeokgung, we analyzed separately by region or landmark such as Jondeok-Pavilion(尊德亭), Yeonkyung-Hall(演慶堂), and Okryu-Stream(玉流川). Original form of Jondeok-Pavilion Area was changed in 1884. Since diachronic invariance that lasted for 240 years is more important criterion than its contemporary characteristics, it should be restored as how it was painted in Donggwoldo(東闕圖). In Yeonkyung-Hall Area, both original characteristics at the time of Hyomyung Crown Prince and contemporary characteristics of Emperor Kojong Era appear. Therefore, different solution is required for such area to be restored appropriately. Starting from era of King Injo(1636), diachrony and invariance of Okryu-Stream Area were continued throughout the era of King Sukjong and King Jeongjo(1800). It is more than 250 years before Okryu-Stream Area was altered under the rule of Emperor Kojong in 1884. In fact, alterations made to Okryu-Stream Area after 1884 doesn't hold much significance. Therefore, water landscape of Okryu-Stream Area, which was altered in the era of Emperor Kojong, needs to be restored based on Donggwoldo.

• Journal of the Korean Society of Radiology
• /
• v.16 no.4
• /
• pp.453-462
• /
• 2022

In this paper, the artificial intelligence (AI) technology used in the medical image analysis field was analyzed through a literature review. Literature searches were conducted on PubMed, ResearchGate, Google and Cochrane Review using the key word. Through literature search, 114 abstracts were searched, and 98 abstracts were reviewed, excluding 16 duplicates. In the reviewed literature, AI is applied in classification, localization, disease detection, disease segmentation, and fit degree of registration images. In machine learning (ML), prior feature extraction and inputting the extracted feature values into the neural network have disappeared. Instead, it appears that the neural network is changing to a deep learning (DL) method with multiple hidden layers. The reason is thought to be that feature extraction is processed in the DL process due to the increase in the amount of memory of the computer, the improvement of the calculation speed, and the construction of big data. In order to apply the analysis of medical images using AI to medical care, the role of physicians is important. Physicians must be able to interpret and analyze the predictions of AI algorithms. Additional medical education and professional development for existing physicians is needed to understand AI. Also, it seems that a revised curriculum for learners in medical school is needed.