• The Journal of Society for e-Business Studies
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• v.14 no.4
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• pp.267-286
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• 2009

Most companies in automobile part industry need a SCM (Supply Chain Management) system under the cooperation with suppliers for assembling a automobile. Automobile part industry has a industry feature of hierarchical structure like 1st, 2nd, 3rd vendors. Recently, new cases to implement RFID (Radio Frequency Identification) technology appear in various areas required for integrated information system. Especially, supply chain environment in automobile part industry turns toward ubiquitous computing environment. Most companies in automobile part industry are interested in implementing RFID-based supply chain management system, which makes them shorten the business process, share the transaction information, and enhance the collaborative relationship between trading partners. This paper intends to implement RFID technology in the physical distribution area of automobile part industry such as warehousing, delivering, inventory management. The purpose of this paper is to improve the collaborative relationship of supply chain network using RFID applied to u-SCM system in ubiquitous computing environment. The contribution of this paper is to suggest a new system approach to transform existing business process into new business process through designing and implementing a RFID based SCM system using UML techniques.

• Applied Chemistry for Engineering
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• v.5 no.3
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• pp.537-546
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• 1994

The physical characteristics of polymer modified asphalt depend on many parameters, such as, the polymer nature, polymer content and the asphalt properties. The objective of this study is to investigate the temperature susceptibility of polymer modified asphalt. The asphalts employed in this study were two different grades : a soft(200/300) grade and a hard(85/100) grade. And chlorinated polyethylene of two different characteristics were used : plastomer(Tyrin 2552) and elastomer(Tyrin CM0730). Temperature susceptibility of asphalt is a fundamental feature for characterizing asphalt and modified asphalt. It can be quantified by the penetration index(PI) and pen-vis number(PVN). These indices were obtained from the measurements of penetration and viscosity of the asphalt samples. For both of asphalts, the addition of the polymers increases the value of PI and PVN. Plastomer modified asphalt shows higher value of PI and PVN than elastomer modified asphalt. Soft grade shows more temperature susceptibility than hard grade at elevated temperatures.

• Journal of the Korean Wood Science and Technology
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• v.40 no.6
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• pp.445-453
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• 2012

In this study the effects of particle size and water content on the yields and physical/chemical properties of pyrolytic products were investigated through fast-pyrolysis of yellow poplar. Water content was critical parameters influencing the properties of bio-oil. The yields of bio-oil were increased with decreasing water content. However, the yield of pyrolytic product was not clearly influenced by feedstock's particle size. The water content, pH and HHV (Higher Heating Value) of bio-oil were measured to 20~30%, 2.2~2.4 and 16.6~18.5MJ/kg, respectively. The water content of feedstock was clearly influenced to water content of bio-oil. In terms of bio-char, HHV of them were measured to 26.2~30.1 MJ/kg with high content of carbon over 80%.

• The Bulletin of The Korean Astronomical Society
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• v.35 no.1
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• pp.68.1-68.1
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• 2010

We focus on two Galactic molecular clouds that are located in wholly different environments and both are observed by FIMS instrument onboard STSAT-1. The Draco cloud is known as a translucent molecular cloud at high Galactic latitude. The FUV spectra show important ionic lines of C IV, Si IV+O IV], Si II* and Al II, indicating the existence of hot and warm interstellar gases in the region. The enhanced C IV emission inside the Draco cloud region is attributable to the turbulent mixing of the interacting cold and warm/hot media, which is supported by the detection of the O III] emission line and the $H{\alpha}$ feature in this region. The Si II* emission covers the remainder of the region outside the Draco cloud, in agreement with previous observations of Galactic halos. Additionally, the H2 fluorescent map is consistent with the morphology of the atomic neutral hydrogen and dust emission of the Draco cloud. In the Aquila Rift region near Galactic plane, FIMS observed that the FUV continuum emission from the core of the Aquila Rift suffers heavy dust extinction. The entire field is divided into three sub-regions that are known as the- "halo," "diffuse," and "star-forming" regions. The "diffuse" and "star-forming" regions show various prominent H2 fluorescent emission lines, while the "halo" region indicates the general ubiquitous characteristics of H2. The CLOUD model and the FUV line ratio are included here to investigate the physical conditions of each sub-region. Finally, the development of an infrared imaging system known as the MIRIS instrument onboard STSAT-3 is briefly introduced. It can be used in WIM studies through $Pa{\alpha}$ observations.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.45 no.6
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• pp.154-161
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• 2008

In this paper, a novel method is proposed using color and pattern information for recognizing some emotions included in a fertile. Here we use 10 Kobayashi emotion to represent emotions. - { romantic, clear, natural, casual, elegant chic, dynamic, classic, dandy, modem } The proposed system is composed of feature extraction and classification. To transform the subjective emotions as physical visual features, we extract representative colors and Patterns from textile. Here, the representative color prototypes are extracted by color quantization method, and patterns exacted by wavelet transform followed by statistical analysis. These exacted features are given as input to the neural network (NN)-based classifiers, which decides whether or not a textile had the corresponding emotion. When assessing the effectiveness of the proposed system with 389 textiles collected from various application domains such as interior, fashion, and artificial ones. The results showed that the proposed method has the precision of 100% and the recall of 99%, thereby it can be used in various textile industries.

• Women's Health Nursing
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• v.7 no.4
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• pp.631-641
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• 2001

This study is to investigate women have pre menstruation discomfort, The period of this research was almost one month (from 25, August 2001 to 25, October 2001). The PAF (Premenstrual assessment form), which was made by Park, Myonng-Wha, used for this study. The confidence rate is Crombach's $\alpha$= .9773. Correcting research papers are analyzed by SPSS 7.5 program and normal feature of the subject is divided by frequency, percentage, mean, standard deviation, t-test and ANOVA. The results of this study are as follows; 1. The average age of the subjects is 26.47 age. 220 subjects(44.6%) have gastroenteric trouble like, enteritis, stomachache, laxity. 278 subjects usually have caffeine drink in routine life. 123 subjects(24.9%) have controlled their diet. The average age of the first plowing is 13.55 ages and distribution is between 10 years and 20 years. The average of the uncomfortable point is 2.84. The way to reduce the uncomfortable feeling on the menstruation is taking relax time. 2. All subjects have experienced pre menstruation discomfort, even the degree uncomfortable feeling is different. Through eighteenth categories on the research papers, average point 2.21 were calculated and many subjects have fatigue ($2.89{\pm}1.0614$) and normal physical uncomfortable ($2.84{\pm}1.0633$) and undercurrent water symptom and unsuitability ($2.45{\pm}0.9857$). 3. According to the result of this study, that shows statistical difference; age (F=2.56. p=.037). marriage (t=2.60, p=.009) the number of children(t=2.83, p=.005), stress level(F=13.03, p=.000) job(F=3.91, p=.020). monthly income(t=2.14. p=.032) uncomfortable degree on the menstruation (F=19.121, p=.000), use of contraceptive appliance or pill(t=-2.20, p=.043), schooling (F=3.30, p=.038). Further research is need to understand pie menstruation discomforts, the variables associated with them. And nursing intervention has to considered in program to reduces of pre-menstruation discomforts.

• Asian Pacific Journal of Cancer Prevention
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• v.16 no.14
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• pp.5669-5673
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• 2015

Background: Breast cancer is the most prevalent kind of cancer among women in Iran. Regarding the importance of cancer prevention and considerable variation of breast cancer incidence in different parts of the country, it is necessary to recognize regions with high incidence of breast cancer and evaluate the role of potential risk factors by use of advanced statistical models. The present study focussed on incidence of breast cancer in Iran at the province level and also explored the impact of some prominent covariates using Bayesian models. Materials and Methods: All patients diagnosed with breast cancer in Iran from 2005 to 2008 were included in the study. Smoking, fruit and vegetable intake, physical activity, obesity and the Human Development Index (HDI), measured at the province level, were considered as potential modulating factors. Gamma-Poisson, log normal and BYM models were used to estimate the relative risk of breast cancer in this ecological investigation with and without adjustment for the covariates. Results: The unadjusted BYM model had the best fit among applied models. Without adjustment, Isfahan, Yazd, and Tehran had the highest incidences and Sistan- Baluchestan and Chaharmahal-Bakhtiari had the lowest. With the adjusted model, Khorasan-Razavi, Lorestan and Hamedan had the highest and Ardebil and Kohgiluyeh-Boyerahmad the lowest incidences. A significantly direct association was found between breast cancer incidence and HDI. Conclusions: BYM model has better fit, because it contains parameters that allow including effects from neighbors. Since HDI is a significant variable, it is also recommended that HDI should be considered in future investigations. This study showed that Yazd, Isfahan and Tehran provinces feature the highest crude incidences of breast cancer.

• Asian Pacific Journal of Cancer Prevention
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• v.17 no.4
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• pp.1833-1835
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• 2016

Background: Multiple myeloma (MM) is an acquired clonal B-cell malignancy which primarily affects elderly individuals with an annual incidence of approximately 1% of all malignancies. Our aim is to study demographic and clinicopathological features of adult Pakistani MM patients at presentation. Materials and Methods: This single centre retrospective study extended from January 2010 to December 2014. Data were retrieved from the patients' maintained records on predetermined performa. Results: Overall, 61 patients were diagnosed at our institution with MM during the study period. There were 43 males and 18 females. Age ranged between 34 and 81 years with a mean of $56.1{\pm}12.8$ and a median of 57 years. The male to female ratio was ~2:1. Common presenting complaints included fatigue (81.9%), backache (80.3%) and bone pain (67.2%). Physical findings revealed pallor (44.2%) as a presenting clinical feature. The mean hemoglobin value was $8.9{\pm}1.7g/dl$ with a mean MCV of $85.3{\pm}11.0fl$. Severe anemia with hemoglobin <8.5 gm/dl was seen in 40.9%. The mean total leukocyte count was $8.9{\pm}8.2{\times}10^9/l$, the ANC was $5.0{\pm}3.1{\times}10^9/l$ and the mean platelet count was $188.4{\pm}150.6{\times}10^9/l$. Conclusions: MM in Pakistani patients is seen in a relatively young population with male preponderance. The majority of patients present with symptomatic anemia and backache to seek medical attention. However, clinico-pathological features appear comparable to the published literature.

• The Transactions of the Korea Information Processing Society
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• v.6 no.8
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• pp.2031-2041
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• 1999

In this paper, we present the HVIS (Hybrid Video Information System) which bolsters up meaning retrieval of all the various users by integrating feature-based retrieval and annotation-based retrieval of unformatted formed and massive video data. HVIS divides a set of video into video document, sequence, scene and object to model the metadata and suggests the Two layered Hybrid Object-oriented Metadata Model(THOMM) which is composed of raw-data layer for physical video stream, metadata layer to support annotation-based retrieval, content-based retrieval, and similarity retrieval. Grounded on this model, we presents the video query language which make the annotation-based query, content-based query and similar query possible and Video Query Processor to process the query and query processing algorithm. Specially, We present the similarity expression to appear degree of similarity which considers interesting of user. The proposed system is implemented with Visual C++, ActiveX and ORACLE.

• Journal of KIISE:Software and Applications
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• v.26 no.10
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• pp.1143-1155
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• 1999

셀룰러 방식의 이동통신 시스템에서 전파의 유효신호 도달범위를 예측하기 위해서는 전파전파 모델을 이용한 예측기법이 주로 사용된다. 그러나, 전파과정에서 주변 지형지물에 의해 발생하는 전파손실은 매우 복잡한 비선형적인 특성을 가지며 수식으로는 정확한 표현이 불가능하다. 본 논문에서는 신경회로망의 함수 근사화 능력을 이용하여 전파손실 예측모델을 생성하는 방법을 제안한다. 즉, 전파손실을 송수신 안테나간의 거리, 송신안테나의 특성, 장애물 투과영향, 회절특성, 도로, 수면에 의한 영향 등과 같은 전파환경 변수들의 함수로 가정하고, 신경회로망 학습을 통하여 함수를 근사화한다. 전파환경 변수들이 신경회로망 입력으로 사용되기 위해서는 3차원 지형도와 벡터지도를 이용하여 전파의 반사, 회절, 산란 등의 물리적인 특성이 고려된 특징 추출을 통해 정량적인 수치들을 계산한다. 이와 같이 얻어진 훈련데이타를 이용한 신경회로망 학습을 통해 전파손실 모델을 완성한다. 이 모델을 이용하여 서울 도심 지역의 실제 서비스 환경에 대한 타 모델과의 비교실험결과를 통해 제안하는 모델의 우수성을 보인다.Abstract In cellular mobile communication systems, wave propagation models are used in most cases to predict cell coverage. The amount of propagation loss induced by the obstacles in the propagation path, however, is a highly non-linear function, which cannot be easily represented mathematically. In this paper, we introduce the method of producing propagation loss prediction models by function approximation using neural networks. In this method, we assume the propagation loss is a function of the relevant parameters such as the distance from the base station antenna, the specification of the transmitter antenna, obstacle profile, diffraction effect, road, and water effect. The values of these parameters are produced from the field measurement data, 3D digital terrain maps, and vector maps as its inputs by a feature extraction process, which takes into account the physical characteristics of electromagnetic waves such as reflection, diffraction and scattering. The values produced are used as the input to the neural network, which are then trained to become the propagation loss prediction model. In the experimental study, we obtain a considerable amount of improvement over COST-231 model in the prediction accuracy using this model.