• Korean Chemical Engineering Research
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• v.58 no.3
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• pp.346-355
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• 2020

This study proposed a new optimization-based decision model for an enterprise resource planning and production scheduling of a pharmaceutical intermediates manufacturing plant. To do this work, we first define the inflow and outflow information as well as the model structure, and develop an optimization model to minimize the production time (i.e., makespan) using a mixed integer linear programing (MILP). The unique feature of the proposed model is that the optimal process scheduling is established based on real-time resource logistics information using a radio frequency identification (RFID) technology, thereby theoretically requiring no material inventories. essential information for process operation, such as the required amount of raw materials and estimated arrival timing to manufacturing plant, is used as logistics constraints in the optimization model to yield the optimal manufacturing scheduling to satisfy final production demands. We illustrated the capability of the proposed decision model by applying the optimization model to two scheduling problems in a real pharmaceutical intermediates manufacturing process. As a result, the optimal production schedule and raw materials order timing were identified to minimize the makespan while satisfying all the product demands.

• KSCI Review
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• v.14 no.2
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• pp.159-164
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• 2006

MES(Manufacturing Execution System) is a control system which supports basic activities(scheduling, working process and qualify management, etc) to execute working on the shop floor. As especially MES is a system to decrease the gap between production planning and operating, it executes functions that make decision between management and labor using real-time data. MES for real-time information processing requires certain conditions such as data modeling of RFID, which has recently attracted attentions, and monitoring of each product unit from manufacture to sales. However, in the middle of processing the unit with a RFID tag, transponders(readers) can't often read the tag due to reader's malfunctions, intentional damages, loss and the circumstantial effects; for that reason, users are unable to confirm the location of the product unit. In this case, users cannot avoid tracing the path of units with uncertain clues. In this paper, we suggest that the unique MES based on RFID and Bayesian Network can immediately track the product unit, and show how to evaluate it.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2016.05a
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• pp.89-90
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• 2016

Anomalous propagation echo is a kind of abnormal radar signal occurred by irregularly refracted radar beam caused by temperature or humidity. The echo frequently appears in ground-based weather radar. In order to improve accuracy of weather forecasting, it is important to analyze radar data precisely. Therefore, there are several ongoing researches about identifying the anomalous propagation echo all over the world. This paper conducts researches about a classification method which can distinguish anomalous propagation echo in the radar data using naive Bayes classifier and unique attributes of the echo such as reflectivity, altitude, and so on. It is confirmed that the fine classification results are derived by verifying the suggested naive Bayes classifier using actual appearance cases of the echo.

• International Journal of Computer Science & Network Security
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• v.24 no.6
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• pp.8-16
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• 2024

Communication with the deaf has always been crucial. Deaf and hard-of-hearing persons can now express their thoughts and opinions to teachers through sign language, which has become a universal language and a very effective tool. This helps to improve their education. This facilitates and simplifies the referral procedure between them and the teachers. There are various bodily movements used in sign language, including those of arms, legs, and face. Pure expressiveness, proximity, and shared interests are examples of nonverbal physical communication that is distinct from gestures that convey a particular message. The meanings of gestures vary depending on your social or cultural background and are quite unique. Sign language prediction recognition is a highly popular and Research is ongoing in this area, and the SVM has shown value. Research in a number of fields where SVMs struggle has encouraged the development of numerous applications, such as SVM for enormous data sets, SVM for multi-classification, and SVM for unbalanced data sets.Without a precise diagnosis of the signs, right control measures cannot be applied when they are needed. One of the methods that is frequently utilized for the identification and categorization of sign languages is image processing. African Buffalo Optimization using Support Vector Machine (ABO+SVM) classification technology is used in this work to help identify and categorize peoples' sign languages. Segmentation by K-means clustering is used to first identify the sign region, after which color and texture features are extracted. The accuracy, sensitivity, Precision, specificity, and F1-score of the proposed system African Buffalo Optimization using Support Vector Machine (ABOSVM) are validated against the existing classifiers SVM, CNN, and PSO+ANN.

• Journal of the Korean GEO-environmental Society
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• v.15 no.6
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• pp.57-65
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• 2014

Recently, Construction business is changing from on the ground to underground space because of deficit of developing space, creation of green space and of incremental of land compensation expenses. Meanwhile, 3D Topographic, Marine and Cadastral maps need to have Spatial Interrelation. Also, understanding of the information is also needed. Spatial information object registration system is impossible to contact and understanding intelligence mutually because the former one is managed as automatic ID system. Therefore, 3D Object information ID System of underground space is managed based on Object Identifier. Construction of Spatial information integration ID System is required and it will offer Division Code (Ground, Index, Underground) and depth information. We are defined and classified Under Spatial Information in this paper. Moreover, we developed the integration ID System based on UFID for cadastral information Construction. We supposed underground spatial information DB Construction and a developed the way of exploiting 3D cadastral information system through the study. The research result will be the base data of Standard ID system, DB Construction and system Development of National spatial data which is considered together with spatial interrelation.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.40 no.2
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• pp.91-108
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• 2022

In most cases, optical images have been used as training data of DL (Deep Learning) models for object detection, recognition, identification, classification, semantic segmentation, and instance segmentation. However, properties of 3D objects in the real-world could not be fully explored with 2D images. One of the major sources of the 3D geospatial information is DSM (Digital Surface Model). In this matter, characteristic information derived from DSM would be effective to analyze 3D terrain features. Especially, man-made objects such as buildings having geometrically unique shape could be described by geometric elements that are obtained from 3D geospatial data. The background and motivation of this paper were drawn from concept of the intrinsic image that is involved in high-level visual information processing. This paper aims to extract buildings after classifying terrain features by training DL model with DSM-derived information including slope, aspect, and SRI (Shaded Relief Image). The experiments were carried out using DSM and label dataset provided by ISPRS (International Society for Photogrammetry and Remote Sensing) for CNN-based SegNet model. In particular, experiments focus on combining multi-source information to improve training performance and synergistic effect of the DL model. The results demonstrate that buildings were effectively classified and extracted by the proposed approach.

• Korean Journal of Veterinary Research
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• v.42 no.3
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• pp.363-370
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• 2002

For the development of diagnostic polymerase chain reaction (PCR) to fungal infection by dermatophytes Trichophyton and Microsporum, detection of the fungal DNA by PCR and analysis of the DNA pattern were undertaken in the present study. A total of 15 strains were tested and those consisted of 3 reference strains and 12 isolates such as: reference strains of T mentagrophytes (downy type, ATCC 9533), T rubrum (IFO 6204) and M gypseum (ATCC 9083), and each isolate of T mentogrophytes (powdery type), T mentagrophytes (granular type), T mentogrophytes (purple-red type), T rubrum, T raubitschekii, T tonsurans, T equinum, T ajelloi, T verrucosum, M cookei, M nanum and M gypseum. The DNA were purely isolated from all strains of Trichophyton spp. and Microsporum spp. by a simple method partly consisted of disruption of fungal cells by lyophilization and grinding and extraction of fungal DNA without phenol treatment which is a routine procedure in DNA isolation. For the detection of fungal DNAs, optimal condition of PCR was determined as preheating once at $94^{\circ}C$ for 5 min, 35 cycles of denaturation at $94^{\circ}C$ for 1 min, annealing at $38^{\circ}C$ for 1 min and polymerization at $72^{\circ}C$ for 2 min, and 1 cycle of final extension at $72^{\circ}C$ for 5 min. In PCR using arbitrary primers AP-1 (5' ACCCGACCTG3') and AP-2 (5' ACGGGCCAGT3'), DNAs in various numbers and sizes were detected from different species of Trichophyton and Microsporum, while DNAs in similar size were also detected in all strains of Trichophyton spp. and Microsporum spp. There were unique DNAs observed from certain dermatophytes by AP-1 such as 1,900 bases in T rubrum, 950 and 1,100 bases in T raubitscheldi, 2,100 bases in T equinum, 400 bases in T verrucosum and 1,150 bases in M gypseum. The unique DNAs were also observed by AP-2 such as 1,200 bases in T ajelloi, 250 bases in T verrucosum, 1,150 bases in M cookei and 2,000 bases in M nanum. The results indicated that PCR can detect a specific DNA from certain Trychophyton and Microsporum spp, which can be the information for further development of diagoomc PCR to dennatophytes.

• Genomics & Informatics
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• v.14 no.4
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• pp.255-264
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• 2016

The plethora of genome sequence information of bacteria in recent times has ushered in many novel strategies for antibacterial drug discovery and facilitated medical science to take up the challenge of the increasing resistance of pathogenic bacteria to current antibiotics. In this study, we adopted subtractive genomics approach to analyze the whole genome sequence of the Fusobacterium nucleatum, a human oral pathogen having association with colorectal cancer. Our study divulged 1,499 proteins of F. nucleatum, which have no homolog's in human genome. These proteins were subjected to screening further by using the Database of Essential Genes (DEG) that resulted in the identification of 32 vitally important proteins for the bacterium. Subsequent analysis of the identified pivotal proteins, using the Kyoto Encyclopedia of Genes and Genomes (KEGG) Automated Annotation Server (KAAS) resulted in sorting 3 key enzymes of F. nucleatum that may be good candidates as potential drug targets, since they are unique for the bacterium and absent in humans. In addition, we have demonstrated the three dimensional structure of these three proteins. Finally, determination of ligand binding sites of the 2 key proteins as well as screening for functional inhibitors that best fitted with the ligands sites were conducted to discover effective novel therapeutic compounds against F. nucleatum.

• The Journal of the Korea Contents Association
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• v.15 no.8
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• pp.9-17
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• 2015

One of RFID features is that each RFID tag has a unique identifying code. Logistic System utilizes RFID tag as location tracing, understanding stock or etc. On the other hand, there is a problem of overall lower recognition rate by getting the information of non-mobility tags with no need for reading. To solve this problem, we trace and analyze variation of moving and moveless RFID tag sensitivity by the hour. In analyzed data, we verify that tag sensitivity of mobile RFID is gradually increase while non-mobility tag has same intensity value. In order to detect mobile tag, we generate a function using Matlab with analyzed data and separate moving tags from non-mobility tags by software. As a result, we can confirm that non-mobility tags are detected by software and recognition rate of RFID tag is improved by separating moveless tag.

• Proceedings of the Plant Resources Society of Korea Conference
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• 2018.10a
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• pp.64-64
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• 2018

The genus Cenchrus (Poaceae), containing ca. 97 species, is distributed throughout Australia, Africa and Indian sub-continent and which was introduced to the United States and Mexico for use in improved pasture. In Korea, especially Daecheong Island, it is one of the most hazardous invasive plant, which causes serious environmental threats, biodiversity damages and physically negative impact on humans and animals. It can cause serious damage to farms, fields and white sand beaches. However, the chloroplast (cp) genome sequences and information of Cenchrus longispinus have been not addressed, so we provide the complete cp genome of Cenchrus longispinus using next-generation sequencing technology. The size of cp genomes of this Daecheong Island species (Cenchrus longispinus) is 137,144 bp, and it shows a typical quadripartite structure. Consisting of the large single copy (LSC; 80,223 bp), small single copy (SSC; 12,449 bp), separated by a pair of inverted repeats (IRs; 22,236 bp). This cp genome contains 75 unique genes, 4 rRNA coding genes, 33 tRNA coding genes and 21 duplicated in the IR regions, with the gene content and organization are similar to other Poaceae cp genomes. Our comparative analysis identified four cpDNA regions (rpl16, rbcL, ndhH and ndhF) from three Cenchrus species, two Setaria species and one Pennisetum species which may be useful for molecular identification.