• International Journal of Computer Science & Network Security
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• 제22권4호
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• pp.111-118
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• 2022

This research article presents the work that is related to the application of different machine learning based similarity techniques on religious text for identifying similarities and differences among its various translations. The dataset includes 10 different English translations of verses (Arabic: Ayah) of two Surahs (chapters) namely, Al-Humazah and An-Nasr. The quantitative similarity values for different translations for the same verse were calculated by using the cosine similarity and semantic similarity. The corpus went through two series of experiments: before pre-processing and after pre-processing. In order to determine the performance of machine learning based similarities, human annotated similarities between translations of two Surahs (chapters) namely Al-Humazah and An-Nasr were recorded to construct the ground truth. The average difference between the human annotated similarity and the cosine similarity for Surah (chapter) Al-Humazah was found to be 1.38 per verse (ayah) per pair of translation. After pre-processing, the average difference increased to 2.24. Moreover, the average difference between human annotated similarity and semantic similarity for Surah (chapter) Al-Humazah was found to be 0.09 per verse (Ayah) per pair of translation. After pre-processing, it increased to 0.78. For the Surah (chapter) An-Nasr, before preprocessing, the average difference between human annotated similarity and cosine similarity was found to be 1.93 per verse (Ayah), per pair of translation. And. After pre-processing, the average difference further increased to 2.47. The average difference between the human annotated similarity and the semantic similarity for Surah An-Nasr before preprocessing was found to be 0.93 and after pre-processing, it was reduced to 0.87 per verse (ayah) per pair of translation. The results showed that as expected, the semantic similarity was proven to be better measurement indicator for calculation of the word meaning.

• 한국축산식품학회지
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• 제41권2호
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• pp.173-184
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• 2021

Clean labeling is emerging as an important issue in the food industry, particularly for meat products that contain many food additives. Among synthetic additives, nitrite is the most important additive in the meat processing industry and is related to the development of cured color and flavor, inhibition of oxidation, and control of microbial growth in processed meat products. As an alternative to synthetic nitrite, preconverted nitrite from natural microorganisms has been investigated, and the applications of pre-converted nitrite have been reported. Natural nitrate sources mainly include fruits and vegetables with high nitrate content. Celery juice or powder form have been used widely in various studies. Many types of commercial starter cultures have been developed. S. carnosus is used as a critical nitrate reducing microorganism and lactic acid bacteria or other Staphylococcus species also were used. Pre-converted nitrite has also been compared with synthetic nitrite and studies have been aimed at improving utilization by exploiting the strengths (positive consumer attitude and decreased residual nitrite content) and limiting the weaknesses (remained carcinogenic risk) of pre-converted nitrite. Moreover, as concerns regarding the use of synthetic nitrites increased, research was conducted to meet consumer demands for the use of natural nitrite from raw materials. In this report, we review and discuss various studies in which synthetic nitrite was replaced with natural materials and evaluate pre-converted nitrite technology as a natural curing approach from a clean label perspective in the manufacturing of processed meat products.

• 한국수자원학회논문집
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• 제51권11호
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• pp.1031-1041
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• 2018

본 연구에서는 ANFIS 기반 GloSea5 앙상블 기상전망 개선 기법을 개발하고 평가하였다. 대상유역은 국내 주요 다목적댐인 충주댐 유역을 선정하였으며, 개선 기법은 ANFIS 기반의 전 후처리기법으로 구성된다. 전처리 기법에서 GloSea5의 앙상블 멤버에 가중치를 부여하며(OWM), 후처리 과정에서는 전처리결과를 편의보정 한다(MOS). 평가결과 편의보정된 GloSea5에 비해 예측성능이 개선되었으며, CASE3, CASE1, CASE2 순으로 모의성능이 우수하였다. 전처리 기법은 강수의 변동성이 큰 계절에 개선효과가 우수하였으며, 후처리 기법은 전처리로 개선하지 못한 오차를 줄 일 수 있는 것으로 나타났다. 따라서 본 연구에서 개발한 ANFIS 기반 GloSea5 앙상블 기상전망 개선 기법은 전 후처리 기법을 함께 사용하는 것이 가장 좋으며, 특히 여름철과 같이 강수의 변동성이 큰 계절에 활용성이 높을 것으로 판단된다.

• 복식문화연구
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• 제11권1호
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• pp.66-74
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• 2003

This study is to improve the worst lightfastness of a natural dye. To modify the fiber surface, low temperature oxygen plasma was carried out on silk fabric. The result is followed below after the examination of surface shape, dyeability, color change, UV absorbent influence and lightfastness. 1. When electric discharge outputs are 60W, 80W and 100w, and processing times are 10minutes, 20minutes and 40minutes, the etching effect of surface increased as electric discharge outputs and processing times increased. 2. When examined UV absorbent for 5hours, 10hours, 20hours, 40hours and 80hours, the value changes of E are 1.47, 2.51, 2.91, 3.71, 4.51 and 5.31 in case of Al pre-mordanting/ prasma 80W, 20min./ UVabsorbent 5% (100:1), 2.31, 2.47, 3.84, 3.90, 3.61 and 4.42 in case of Al pre-mordanting/prasma 80W, 20min.1 UV absorbent 5% (o.w.f.). The lightfastness decreased when UV absorbent increased. 3. Dyeability of the samples pre-treated with five different methods was in the following order: plasma processing for 20minutes at 60W/Al pre-mordanting > Al pre-mordanting > plasma processing for 20minutes at 60W > Al after-mordanting. non mordanting Plasma treatment had superior effect on dyeability. 4. When UV absorbent was applied in fabric, the sample under higher electric discharge out puts showed more effective in improving lightfastness.

• International Journal of Computer Science & Network Security
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• 제21권3호
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• pp.206-211
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• 2021

Internet users are increasingly invited to express their opinions on various subjects in social networks, e-commerce sites, news sites, forums, etc. Much of this information, which describes feelings, becomes the subject of study in several areas of research such as: "Sensing opinions and analyzing feelings". It is the process of identifying the polarity of the feelings held in the opinions found in the interactions of Internet users on the web and classifying them as positive, negative, or neutral. In this article, we suggest the implementation of a sentiment analysis tool that has the role of detecting the polarity of opinions from people about COVID-19 extracted from social media (tweeter) in the Arabic language and to know the impact of the pre-processing phase on the opinions classification. The results show gaps in this area of research, first of all, the lack of resources when collecting data. Second, Arabic language is more complexes in pre-processing step, especially the dialects in the pre-treatment phase. But ultimately the results obtained are promising.

• 한국동물위생학회지
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• 제38권1호
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• pp.25-30
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• 2015

Bee venom has been used as to prevent and treat bovine mastitis as natural antimicrobial compounds in some dairy cattle farms in Korea. It is needed to determine the residual of bee venom in milks of dairy cattle treated with bee venom. Since bee venom is not approved as a raw material for animal drugs, the preprocessing method to detect bee venom residual in milk and the tolerance limit for its residue has not been established yet in Korea. Therefore, the purpose of this study was to develop pre-processing method not affecting major component of bee venom for detection of its residue in milks using ultra-high performance liauid chromatography (UHPLC). In addition, bee venom residue was also analyzed in milk samples of dairy cattle treated for mastitis with bee venom using UHPLC with the developed pre-processing method in this study. As a result, melittin, histamin and phospolipase A2, the major components of bee venom, were all detected by UHPLC with the pre-processing method developed in this study. The results of this study suggest that the pre-processing method developed in this study can be useful to detect bee venom residue in dairy cattle milk. We also found that no bee venom residues were detected in milk samples collected from dairy cattle treated with bee venom after 1 and 3 days, respectively.

• 한국멀티미디어학회논문지
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• 제21권3호
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• pp.391-399
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• 2018

In this paper, we construct and compare various guitar chord classification systems using perceptron neural network and convolutional neural network without pre-processing other than Fourier transform to identify the optimal chord classification system. Conventional guitar chord classification schemes use, for better feature extraction, computationally demanding pre-processing techniques such as stochastic analysis employing a hidden markov model or an acoustic data filtering and hence are burdensome for real-time chord classifications. For this reason, we construct various perceptron neural networks and convolutional neural networks that use only Fourier tranform for data pre-processing and compare them with dataset obtained by playing an electric guitar. According to our comparison, convolutional neural networks provide optimal performance considering both chord classification acurracy and fast processing time. In particular, convolutional neural networks exhibit robust performance even when only small fraction of low frequency components of the data are used.

• KCI Concrete Journal
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• 제12권2호
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• pp.3-10
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• 2000

A computer program, named NEO-PCBRG, for the analysis and design of prestressed con-crete(PSC) bridges was developed using the finite element method. NEO-PCBRG can predict the response of PSC bridges throughout the various stages of construction and service. NEO-PCBRG has both pre- and post-processing capabilities. Pre-processing refers to all the neces- sary steps required to prepare a virtual prototype, more commonly termed a varied model for analysis. Post-processing here stands for the step in which the results from the analysis are reviewed and interpreted. In order to allow for the easy and convenient execution of the entire procedure, NEO-PCBRG was developed using computer graphics in the Visual Basic pro- gramming language. In conclusion, this study presents a new software architecture for analy-sis using the user-oriented design technique.

• 동아시아식생활학회지
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• 제22권6호
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• pp.860-867
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• 2012

Codonopsis lanceolata serves as, an appetizing health food for its, characteristic flavor, taste, and texture:however, it requires a long and complicated cooking process. Therefore, this study conducted pre-processing procedures to improve the cooking process and Codonopsis lanceolata more easily. For processing efficiency, freezing and blanching were efficient for peeling and the rate of peel disuse. In addition the freezing process, effectively reduced the time spent in beating raw material. In the salinity test, freezing and blanching quickly increased salinity over 28 days. As the result of SEM cross-section tests showed that frozen Codonopsis lanceolata become porous, it's assumed that seasoning permeates into this cross-section efficiently. As the appearance of Deodeok-gui as significant differences according to the pre-processing methods, this study examined pre-processing methods(time spent in peeling, rate of peel disuse, time spent in beating out material, salinity, moisture content, texture, and the color) of Codonopsis lanceolata. After testing Deodeok-gui, it was found that freezing is effective, not only for process efficiency and cooking time reduction, but also for improving its qualities.

• 농업과학연구
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• 제42권1호
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• pp.53-61
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• 2015

Development of highly efficient and energy-saving tractors has been one of the issues in agricultural machinery. For design of such tractors, measurement and analysis of load on major power transmission parts of the tractors are the most important pre-requisite tasks. Objective of this study was to perform pre-processing procedures before effective analysis of load data of agricultural tractors (30, 75, and 82 kW) during major field operations such as plow tillage, rotary tillage, baling, bale wrapping, and to select the suitable pre-processing method for the analysis. A load measurement systems, equipped in the tractors, were consisted of strain-gauge, encoder, hydraulic pressure, and radar speed sensors to measure torque and rotational speed levels of transmission input shaft, PTO shaft, and driving axle shafts, pressure of the hydraulic inlet line, and travel speed, respectively. The entire sensor data were collected at a 200-Hz rate. Plow tillage, rotary tillage, baling, wrapping, and loader operations were selected as major field operations of agricultural tractors. Same or different farm works and driving levels were set differently for each of the load measuring experiment. Before load data analysis, pre-processing procedures such as outlier removal, low-pass filtering, and data division were performed. Data beyond the scope of the measuring range of the sensors and the operating range of the power transmission parts were removed. Considering engine and PTO rotational speeds, frequency components greater than 90, 60, and 60 Hz cut off frequencies were low-pass filtered for plow tillage, rotary tillage, and baler operations, respectively. Measured load data were divided into five parts: driving, working, implement up, implement down, and turning. Results of the study would provide useful information for load characteristics of tractors on major field operations.