• The Journal of the Acoustical Society of Korea
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• v.14 no.6
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• pp.62-67
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• 1995

In this paper, the features extraction of reflected ultrasonic signals from various type of defects existing in Al metal has been studied by digital signal processing. Since the reflected signals from various type of the defects are ambiguous in features distinction from effects of noise, Wiener filtering using AR (auto-regressive) technique and least-absolute-values norm method has been used in features extraction and comparison of signals. In this experiment, three types of the defect in aluminum specimen have been considered: a flat cut, an angular cut, a circular hole. And the reflected signal have been measured by pulse-echo methods. In the result of digital signal processing of the reflected signal, it has been found that the features extraction method have been effective for classification of the reflected signals from various defects.

• Proceedings of the Korea Information Processing Society Conference
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• 2022.05a
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• pp.346-348
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• 2022

Media Contents Recommendation Web Service (service name 'mobodra') is a web service that analyzes media types and genre tastes for each user and recommends content accordingly. Users select some of the works randomly provided on the web when signing up for membership and analyze their tastes based on this. Based on this analysis, preferred content for each user is recommended. In this paper, we implement a content recommendation algorithm through item-based collaborative filtering. When the user's activity data or preference is re-examined, the above process is executed again to update the user's taste.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.10a
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• pp.404-406
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• 2021

In modern society, artificial intelligence and automation are being applied in various fields due to the development of the 4th industrial revolution and IoT technology. In particular, systems with a high proportion of image processing, such as automated processes, intelligent CCTV, medical industry, robots, and drones, are susceptible to external factors noise. In this paper, we propose a digital filter based on noise estimation and weights to reconstruct an image in a complex noise environment. The proposed algorithm classifies the types of noise using noise judgment, and determines the noise level of the filtering mask to switch the filtering process to obtain the final output. In order to verify the performance of the proposed algorithm, simulation was conducted, compared with the existing filter algorithm, and the results were analyzed.

• Journal of the Korean Association of Geographic Information Studies
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• v.27 no.2
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• pp.78-95
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• 2024

For the establishment and comparison of environmental plans across various domains, considering climate change and urban issues, it is crucial to build spatial data at the regional scale classified with consistent criteria. This study mapping the Local Climate Zone (LCZ) of Changwon City, where active climate and environmental research is being conducted, using the protocol suggested by the World Urban Database and Access Portal Tools (WUDAPT). Additionally, to address the fragmentation issue where some grids are classified with different climate characteristics despite being in regions with homogeneous climate traits, a filtering technique was applied, and the LCZ classification characteristics were compared according to the filtering radius. Using satellite images, ground reference data, and the supervised classification machine learning technique Random Forest, classification maps without filtering and with filtering radii of 1, 2, and 3 were produced, and their accuracies were compared. Furthermore, to compare the LCZ classification characteristics according to building types in urban areas, an urban form index used in GIS-based classification methodology was created and compared with the ranges suggested in previous studies. As a result, the overall accuracy was highest when the filtering radius was 1. When comparing the urban form index, the differences between LCZ types were minimal, and most satisfied the ranges of previous studies. However, the study identified a limitation in reflecting the height information of buildings, and it is believed that adding data to complement this would yield results with higher accuracy. The findings of this study can be used as reference material for creating fundamental spatial data for environmental research related to urban climates in South Korea.

• Journal of Korean Society of Occupational and Environmental Hygiene
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• v.25 no.4
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• pp.542-553
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• 2015

Objectives: Many types of dust collector are used for industrial ventilation, with the most common types being the cylinder bag filter system, rectangular bag filter system and cylinder type cartridge filter system. The cylinder type cartridge bag filter, which has more filtering area than other types of bag filter, can increase the pulse time and extend the useful life of the filter. This can save operational costs and installation area. Materials: This study used cylinder type cartridge bag filter equipment and tested the impact of vibration level and filter pressure with different pulse jet cleaning conditions. The final, cleaning efficiency was calculated through input dust mass and cleaning dust mass Conclusions: Two optimum cleaning condition groups were found. The first condition group was $3kgf/cm^2$ pulse pressure, 15 cm pulse distance, 0.2 s pulse time with an H-10 type nozzle. The second condition group was $3kgf/cm^2$ pulse pressure, 15 cm pulse distance, 0.3 s pulse time with an H-10 type nozzle.

• Journal of the Korean Institute of Landscape Architecture
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• v.45 no.4
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• pp.131-142
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• 2017

This study aims to create a Local Climate Zone(LCZ) map of Seoul by using World Urban Database and Access Portal Tools(WUDAPT) protocol, and to analyze the characteristics of the Seoul LCZs. For this purpose, training samples of 17 LCZ types were collected by using Landsat images and Google Earth. LCZ Classification and Filtering were performed by SAGA GIS. An ArcGIS was used to analyze the characteristics of each LCZ type. The characteristics of the LCZ types were analyzed by focusing on building surface fraction ratio, impervious surface fraction ratio, pervious surface fraction ratio, building stories and air temperature. The results show that one filtering was found to be most appropriate. While Yangcheongu and Yeongdeungpogu with the higher annual and maximum mean air temperature than other areas have the higher rate of LCZ 3(compact low-rise) and LCZ 4(open high-rise), Jongnogu, Eunpyeonggu, Nowongu and Gwanakgu with the lower value have the higher rate of LCZ A(Dence trees). The values of building surface fraction ratio, impervious surface fraction ratio and building stories of each LCZ were included in the range of WUDAPT for most LCZs. However, the values of pervious surface fraction ratio were out of the range, in particular, in the LCZs 4~6 and 9~10. This study shows the usability and applicability of the WUDAPT methodology and its climate zone classification used in many countries as a basic data for the landscape planning and policy to improve the thermal environment in urban areas.

• The Journal of the Korea Contents Association
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• v.13 no.4
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• pp.1-7
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• 2013

A personalized recommendation system is a recommendation system that recommends goods to users' taste by using an automated information filtering technology. A collaborative filtering method in this technology is a method that discriminates certain types, which represent similar patterns. Thus, it is possible to estimate the pain strength based on the data of the patients who have the past similar types and extract related conditions according to the similarity in classified patients. A representative method using the Pearson correlation coefficient for extracting the similarity weight may represent inexact results as the sample data is small according to the amount of data. Also, it has a disadvantage that it is not possible to fast draw results due to the increase in calculations as a square scale as the sample data is large. In this paper, the excellency of the intelligence pain nursing intervention u-health system implemented by comparing the scale and similarity group of the sample data for extracting significant data is verified through the evaluation of MAE and Raking scoring. Based on the results of this verification, it is possible to present basic data and guidelines of the pain of patients recognized by nurses and that leads to improve the welfare of patients.

• Food Science and Preservation
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• v.24 no.4
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• pp.510-516
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• 2017

This study was performed to analyze the content of 6 different fusel oils in 9 types of liquor distributed in domestic market. GC-FID method was employed for quantifying fusel oil (1-propanol, iso-butanol, 1-butanol, 2-butanol, iso-amyl alcohol, active amyl alcohol) levels in 260 liquor samples of liquor. Relative standard deviations (%) of intra-and interday measurements were under 1.56 and 2.44%, respectively, while recovery rates (%) were 98.22-105.26% and 98.53-107.15%, respectively. Pretreatment method (filtering and centrifugation) of Takju did not affect analytic results. The average of total fusel oil contents in Yakju (39 types) and fruit wines (30 types) were 497.6 and 151.9 mg/L, showing Yakju contains more fusel oils than Takju or fruit wines. In fruit wines, iso-amyl alcohol was the major fusel oil component (at 6.8-249.0 mg/L). The highest content of fusel oil was found in foreign brandy, whereas the diluted Soju did not contain fusel oils. However, the average of total fusel oil contents was high at 764.5 mg/L in the three types of distilled Soju and iso-amyl alcohol content ranged from 114.2 to 421.0 mg/L. Domestic and foreign beers were similar in terms of their fusel oil compositions and contents. In conclusion, excluding the diluted Soju, the contents of total fusel oils ranged from 114.8 to 1447.3 mg/L in the monitored liquors.

• Journal of Broadcast Engineering
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• v.13 no.4
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• pp.452-462
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• 2008

In this paper, we address issues associated with the real-time implementation of the MPEG-1/2 Layer-II (or MUSICAM) and MPEG-4 ER-BSAC decoders for Digital Multimedia Broadcasting (DMB) on TMS320C64x+ that is a fixed-point DSP processor with a clock speed of 330 MHz. To achieve the real-time requirement, they should be optimized in different steps as follows. First of all, a C-code level optimization is performed by sharing the memory, adjusting data types, and unrolling loops. Next, an algorithm level optimization is carried out such as the reconfiguration of bitstream reading, the modification of synthesis filtering, and the rearrangement of the window coefficients for synthesis filtering. In addition, the C-code of a synthesis filtering module of the MPEG-1/2 Layer-II decoder is rewritten by using the linear assembly programming technique. This is because the synthesis filtering module requires the most processing time among all processing modules of the decoder. In order to show how the real-time implementation works, we obtain the percentage of the processing time for decoding and calculate a RMS value between the decoded audio signals by the reference MPEG decoder and its DSP version implemented in this paper. As a result, it is shown that the percentages of the processing time for the MPEG-1/2 Layer-II and MPEG-4 ER-BSAC decoders occupy less than 3% and 11% of the DSP clock cycles, respectively, and the RMS values of the MPEG-1/2 Layer-II and MPEG-4 ER-BSAC decoders implemented in this paper all satisfy the criterion of -77.01 dB which is defined by the MPEG standards.

• Journal of the Korean Data and Information Science Society
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• v.24 no.4
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• pp.803-813
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• 2013

The purchase of items in e-commerce is a little bit different from that of items in off-line. The recommendation of items in off-line is conducted by salespersons' recommendation, However, the item recommendation in e-commerce cannot be recommended by salespersons, and so different types of methods can be recommended in e-commerce. Recommender system is a method which recommends items in e-commerce. Preferences of customers who want to purchase new items can be predicted by the preferences of customers purchasing existing items. In the recommender system, the items with estimated high preferences can be recommended to customers. The algorithm of collaborative filtering is used in recommender system of e-commerce, and the list of recommended items is made by estimated values, and then the list is recommended to customers. The dataset used in this research are 100k dataset and 1 million dataset in Movielens dataset. Similar results in two dataset are deducted for generalization. To suggest a new algorithm, distribution features of estimated values are analyzed by the existing algorithm and transformed algorithm. In addition, respondent'distribution features are analyzed respectively. To improve the collaborative filtering algorithm in neighborhood recommender system, a new algorithm method is suggested on the basis of existing algorithm and transformed algorithm.