• International journal of advanced smart convergence
• /
• v.10 no.1
• /
• pp.1-11
• /
• 2021

Document page segmentation is an important step in building a quality optical character recognition module. The study examined already existing work on the topic of page segmentation and focused on the development of a segmentation model that has greater functional significance for application in an organization, as well as broad capabilities for managing the quality of the model. The main problems of document segmentation were highlighted, which include a complex background of intersecting objects. As classes for detection, not only classic text, table and figure were selected, but also additional types, such as signature, logo and table without borders (or with partially missing borders). This made it possible to pose a non-trivial task of detecting non-standard document elements. The authors compared existing neural network architectures for object detection based on published research data. The most suitable architecture was RetinaNet. To ensure the possibility of quality control of the model, a method based on neural network modeling using the RetinaNet architecture is proposed. During the study, several models were built, the quality of which was assessed on the test sample using the Mean average Precision metric. The best result among the constructed algorithms was shown by a model that includes four neural networks: the focus of the first neural network on detecting tables and tables without borders, the second - seals and signatures, the third - pictures and logos, and the fourth - text. As a result of the analysis, it was revealed that the approach based on four neural networks showed the best results in accordance with the objectives of the study on the test sample in the context of most classes of detection. The method proposed in the article can be used to recognize other objects. A promising direction in which the analysis can be continued is the segmentation of tables; the areas of the table that differ in function will act as classes: heading, cell with a name, cell with data, empty cell.

• Journal of Biosystems Engineering
• /
• v.27 no.3
• /
• pp.219-226
• /
• 2002

Desorption equilibrium moisture contents of oak mushroom were measured by the static method using salt solutions at flour temperature levels of 35$\^{C}$, 45$\^{C}$, 55$\^{C}$ and 6$\^{C}$ and five relative humidity levels in the range from 11.0% to 90.8%. EMC data were fitted to the modified Henderson, Chung-Pfost, modified Halsey and modified Oswin models using nonlinear regression analysis. Drying tests far oak mushroom were conducted in an experimental dryer equipped with air conditioning unit. The drying test were performed in triplicate at flour air temperatures of 35$\^{C}$, 45$\^{C}$, 55$\^{C}$ and 65$\^{C}$ and three relative humidities of 30%, 50% and 70% respectively. Measured moisture ratio data were fitted to the selected four drying models(Lewis, Page, simplified diffusion and Thompson models) using stepwise multiple regression analysis. The results of comparing root mean square errors for EMC models showed that modified Halsey was the best model, and modified Oswin models could be available far oak mushroom. The results of comparing coefficients of determination and root mean square errors of moisture ratio for four drying models showed that Page model were found to fit adequately to all drying test data with a coefficient of determination of 0.9990 and root mean square error of moisture ratio of 0.00739.

• Food Science of Animal Resources
• /
• v.43 no.2
• /
• pp.305-318
• /
• 2023

This study investigated the protein digestibility of chicken breast and thigh in an in vitro digestion model to determine the better protein sources for the elderly in terms of bioavailability. For this purpose, the biochemical traits of raw muscles and the structural properties of myofibrillar proteins were monitored. The thigh had higher pH, 10% trichloroacetic acid-soluble α-amino groups, and protein carbonyl content than the breast (p<0.05). In the proximate composition, the thigh had higher crude fat and lower crude protein content than the breast (p<0.05). Sodium dodecyl sulfate-polyacrylamide gel electrophoresis (SDS-PAGE) of myofibrillar proteins showed noticeable differences in the band intensities of tropomyosin α-chain and myosin light chain-3 between the thigh and breast. The intrinsic tryptophan fluorescence intensity of myosin was lower in the thigh than in the breast (p<0.05). Moreover, circular dichroism spectroscopy of myosin revealed that the thigh had higher α-helical and lower β-sheet structures than the breast (p<0.05). The cooked muscles were then chopped and digested in the elderly digestion model. The thigh had more α-amino groups than the breast after both gastric and gastrointestinal digestion (p<0.05). SDS-PAGE analysis of the gastric digesta showed that more bands remained in the digesta of the breast than that of the thigh. The content of proteins less than 3 kDa in the gastrointestinal digesta was also higher in the thigh than in the breast (p<0.05). These results reveal that chicken thigh with higher in vitro protein digestibility is a more appropriate protein source for the elderly than chicken breast.

• Journal of Biosystems Engineering
• /
• v.21 no.1
• /
• pp.72-83
• /
• 1996

This study was performed to find out drying characteristics and develop drying model for the design of an efficient dryer or drying system of garlic. The basic model which describes drying phenomenon of garlic was first established. A series of drying test were conducted with two varieties of garlic(Uiseong, Namdo) at 9-different drying conditions (drying temperatures ; $40^{\circ}C$, $50^{\circ}C$, $60^{\circ}C$, relative humidities ; 20%, 35%, 50%) and statistical analysis was made to fit the data with exponential equation, approximated diffusion equation, page equation, thompson equation and wang equation, respectively. In this test, the effects of drying air temperature and relative humidity on the drying rate were undertaken. Finally, new drying model based on these experimental results was developed to describe the drying characteristics of garlic. Also, the volatile components of garlic extracts were investigated. For experiment both Uisoeng and Namdo garlic were dried by heated-air-drying, followed by ether extraction. The extracts were analysed by Gas chromatography/Mass spectrometer.

• Journal of Korea Society of Digital Industry and Information Management
• /
• v.12 no.4
• /
• pp.71-79
• /
• 2016

This study proposes a performance model of a shared bus multi-processor system and analyzes the effect of input/output types on system performance and overload of shared resources. This system performance model reflects the memory reference time in relation to the effect of input/output types on shared resources and the input/output processing time in relation to the input/output processor, disk buffer, and device standby places. In addition, it demonstrates the contribution of input/output types to system performance for comprehensive analysis of system performance. As the concept of workload in the probability theory and the presented model are utilized, the result of operating and analyzing the model in various conditions of processor capability, cache miss ratio, page fault ratio, disk buffer hit ratio (input/output processor and controller), memory access time, and input/output block size. A simulation is conducted to verify the analysis result.

• Journal of KIISE:Computer Systems and Theory
• /
• v.27 no.7
• /
• pp.639-649
• /
• 2000

In the relational database systems, the join operation is one of the most time-consuming query operations. Many parallel join algorithms have been developed to reduce the execution time. Multiple hash join algorithm using allocation tree is one of most efficient ones. However, it may have some delay on the processing each node of allocation tree, which is occurred in tuple-probing phase by the difference between one page reading time of outer relation and the processing time of already read one. In this paper, to solve the performance degrading problem by the delay, we develop a join algorithm using the concept of 'synchronization of page execution time' for multiple hash joins. We reduce the processing time of each nodes in the allocation tree and improve the total system performance. In addition, we analyze the performance by building the analytical cost model and verify the validity of it by various performance comparison with previous method.

• Korean Journal of Microbiology
• /
• v.46 no.1
• /
• pp.96-103
• /
• 2010

Oligosaccharyltransferase (OTase) catalyzes the transfer of a lipid-linked oligosaccharide (LLO) to the nascent polypeptide. Most eukaryotes have an OTase composed of a multisubunit protein complex. However, the kinetoplastid Leishmania major and the bacterium Campylobacter jejuni have only a single subunit for OTase activity, Stt3p and PglB, respectively. In this study, a new in vitro assay for OTase was developed by using a fluorescent peptide containing N-glycosylation sequon, Asn-Xaa-Thr/Ser, where Xaa can be any amino acid residue except Pro. L. major Stt3p and C. jejuni PglB as a model OTase enzyme demonstrated the formation of glycopeptides from a fluorescent peptide through OTase activities. For separation and measurement of the glycopeptides produced by the OTases, Tricine-SDS-PAGE, a lectin column and fluorospectrophotometer, and HPLC were applied. Comparison of these assay methods for analyzing a fluorescent glycopeptide showed HPLC analysis is the best method for separation of glycopeptides and nonglycosylated peptides as well as for quantify the peptides than other methods.

• Convergence Security Journal
• /
• v.23 no.1
• /
• pp.19-25
• /
• 2023

The current network environment provides a real-time interactive service from an initial one-way information prov ision service. Depending on the form of web-based information sharing, it is possible to provide various knowledge a nd services between users. However, in this web-based real-time information sharing environment, cases of damage by illegal attackers who exploit network vulnerabilities are increasing rapidly. In particular, for attackers who attempt a phishing attack, a link to the corresponding web page is induced after actively generating a forged web page to a user who needs a specific web page service. In this paper, we analyze whether users directly and actively forge a sp ecific site rather than a passive server-based detection method. For this purpose, it is possible to prevent leakage of important personal information of general users by detecting a disguised webpage of an attacker who induces illegal webpage access using traceback information

• Journal of the Korea Society of Computer and Information
• /
• v.29 no.2
• /
• pp.21-30
• /
• 2024

This research aims to design a system capable of generating real web pages based on deep learning and big data, in three stages. First, a classification system was established based on the industry type and functionality of e-commerce websites. Second, the types of components of web pages were systematically categorized. Third, the entire web page auto-generation system, applicable for deep learning, was designed. By re-engineering the deep learning model, which was trained with actual industrial data, to analyze and automatically generate existing websites, a directly usable solution for the field was proposed. This research is expected to contribute technically and policy-wise to the field of generative AI-based complete website creation and industrial sectors.

• Journal of Intelligence and Information Systems
• /
• v.23 no.1
• /
• pp.127-141
• /
• 2017

Advances in Internet technologies and the proliferation of mobile devices enabled consumers to approach a wide range of goods and services, while causing an adverse effect that they have hard time reaching their congenial items even if they devote much time to searching for them. Accordingly, businesses are using the recommender systems to provide tools for consumers to find the desired items more easily. Association Rule Mining (ARM) technology is advantageous to recommender systems in that ARM provides intuitive form of a rule with interestingness measures (support, confidence, and lift) describing the relationship between items. Given an item, its relevant items can be distinguished with the help of the measures that show the strength of relationship between items. Based on the strength, the most pertinent items can be chosen among other items and exposed to a given item's web page. However, the diversity of the measures may confuse which items are more recommendable. Given two rules, for example, one rule's support and confidence may not be concurrently superior to the other rule's. Such discrepancy of the measures in distinguishing one rule's superiority from other rules may cause difficulty in selecting proper items for recommendation. In addition, in an online environment where a web page or mobile screen can provide a limited number of recommendations that attract consumer interest, the prudent selection of items to be included in the list of recommendations is very important. The exposure of items of little interest may lead consumers to ignore the recommendations. Then, such consumers will possibly not pay attention to other forms of marketing activities. Therefore, the measures should be aligned with the probability of consumer's acceptance of recommendations. For this reason, this study proposes a model-based approach to combine those measures into one unified measure that can consistently determine the ranking of recommended items. A regression model was designed to describe how well the measures (independent variables; i.e., support, confidence, and lift) explain consumer's acceptance of recommendations (dependent variables, hit rate of recommended items). The model is intuitive to understand and easy to use in that the equation consists of the commonly used measures for ARM and can be used in the estimation of hit rates. The experiment using transaction data from one of the Korea's largest online shopping malls was conducted to show that the proposed model can improve the hit rates of recommendations. From the top of the list to 13th place, recommended items in the higher rakings from the proposed model show the higher hit rates than those from the competitive model's. The result shows that the proposed model's performance is superior to the competitive model's in online recommendation environment. In a web page, consumers are provided around ten recommendations with which the proposed model outperforms. Moreover, a mobile device cannot expose many items simultaneously due to its limited screen size. Therefore, the result shows that the newly devised recommendation technique is suitable for the mobile recommender systems. While this study has been conducted to cover the cross-selling in online shopping malls that handle merchandise, the proposed method can be expected to be applied in various situations under which association rules apply. For example, this model can be applied to medical diagnostic systems that predict candidate diseases from a patient's symptoms. To increase the efficiency of the model, additional variables will need to be considered for the elaboration of the model in future studies. For example, price can be a good candidate for an explanatory variable because it has a major impact on consumer purchase decisions. If the prices of recommended items are much higher than the items in which a consumer is interested, the consumer may hesitate to accept the recommendations.