• Journal of the korean society of oceanography
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• v.34 no.4
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• pp.207-213
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• 1999

Sediment physical properties (compressional wave velocity, grain density, dry bulk density, and wet bulk density) are correlated to the paleoenvironmental parameters (coarse fraction, oxygen isotope, and planktonic foraminifera fragmentation) to reveal the possible interrelationship in the latest Quaternary sediments of the Ulleung Basin, the East Sea of Korea. Laboratory determinations of physical properties and paleoenvironmental parameters have been conducted on four piston core sediments. There are slight differences in the physical properties between glacial and interglacial period sediment sections. This is due to the large fraction of coarse grains of volcanic and terrigenous sediments relative to carbonate sediments. However, dry bulk density as an indicator of carbonate abundance in pelagic environment shows higher values at the lower part of cores, reflecting deeper CCD in the glacial period. Changes in velocity also relatively parallel to those in sediment coarse fraction, number of planktonic foraminifera, and wet bulk density. Therefore, we suggest that high-resolution physical properties may be used as a valuable tool for paleoenvironmental interpretation in the Ulleung Basin.

• International Journal of Industrial Entomology and Biomaterials
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• v.22 no.1
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• pp.11-15
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• 2011

Impact of pruning date, shoot age and weather parameters on the severity and development of grey leaf spot (Pseudocercospora mori) of mulberry was studied. The disease severity (%) increased with increase in shoot age irrespective of pruning date. Maximum disease severity was observed in plants pruned during second week of October and minimum in plants pruned during last week of December. Significant (P<0.05) influence of date of pruning, shoot age and their interaction was observed on the severity of the disease. Apparent infection rate (r) was significantly higher during plant growth period from day-48 to day-55. Average apparent rate was higher in plants pruned during first week of September and least in plants pruned during third and fourth week of December. Multiple regression analysis revealed contribution of various combinations of weather parameters on the disease severity. A linear prediction model [$Y=66.05+(-1.39)x_1+(-0.219)x_4$] with significant $R^2$ was developed for prediction of the disease under natural epiphytotic condition.

• Journal of Electrical Engineering and Technology
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• v.7 no.1
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• pp.109-114
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• 2012

In this paper, we utilize training strategy of hidden Markov model (HMM) to use in versatile issues such as classification of time-series sequential data such as electric transient disturbance problem in power system. For this, an automatic means of optimizing HMMs would be highly desirable, but it raises important issues: model interpretation and complexity control. With this in mind, we explore the possibility of using genetic algorithm (GA) and harmony search (HS) algorithm for optimizing the HMM. GA is flexible to allow incorporating other methods, such as Baum-Welch, within their cycle. Furthermore, operators that alter the structure of HMMs can be designed to simple structures. HS algorithm with parameter-setting free technique is proper for optimizing the parameters of HMM. HS algorithm is flexible so as to allow the elimination of requiring tedious parameter assigning efforts. In this paper, a sequential data analysis simulation is illustrated, and the optimized-HMMs are evaluated. The optimized HMM was capable of classifying a sequential data set for testing compared with the normal HMM.

• International Journal of Automotive Technology
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• v.6 no.2
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• pp.95-105
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• 2005

Diesel engines have low specific fuel consumption, but high particulate emissions, mainly soot. Diesel soot is suspected to have significant effects on the health of living beings and might also affect global warming. Hence stringent measures have been put in place in a number of countries and will be even stronger in the near future. Diesel engines require either advanced integrated exhaust after treatment systems or modified engine models to meet the statutory norms. Experimental analysis to study the emission characteristics is a time consuming affair. In such situations, the real picture of engine control can be obtained by the modeling of trend prediction. In this article, an effort has been made to predict emissions smoke and NO$_{x}$ using cylinder combustion derived parameters and diesel particulate filter data, with artificial neural network techniques in MATLAB environment. The model is based on three layer neural network with a back propagation learning algorithm. The training and test data of emissions were collected from experimental set up in the laboratory for different loads. The network is trained to predict the values of emission with training values. Regression analysis between test and predicted value from neural network shows least error. This approach helps in the reduction of the experimentation required to determine the smoke and NO$_{x}$ for the catalyst coated filters.

• Smart Structures and Systems
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• v.28 no.6
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• pp.799-810
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• 2021

When monitoring the structural integrity of a bridge using data collected through accelerometers, identifying the profile of the load exerted on the bridge from the vehicles passing over it becomes a crucial task. In this study, the speed and location of vehicles on the deck of a bridge is reconfigured using real-time video to implicitly associate the load applied to the bridge with the response from the bridge sensors to develop an image-based deep learning network model. Instead of directly measuring the load that a moving vehicle exerts on the bridge, the intention in the proposed method is to replace the correlation between the movement of vehicles from CCTV images and the corresponding response by the bridge with a neural network model. Given the framework of an input-output-based system identification, CCTV images secured from the bridge and the acceleration measurements from a cantilevered beam are combined during the process of training the neural network model. Since in reality, structural damage cannot be induced in a bridge, the focus of the study is on identifying local changes in parameters by adding mass to a cantilevered beam in the laboratory. The study successfully identified the change in the material parameters in the beam by using the deep-learning neural network model. Also, the method correctly predicted the acceleration response of the beam. The proposed approach can be extended to the structural health monitoring of actual bridges, and its sensitivity to damage can also be improved through optimization of the network training.

• Structural Engineering and Mechanics
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• v.81 no.5
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• pp.575-589
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• 2022

In order to enhance the greenness in the strain-hardening composites and to reduce the high cost of typical polyvinyl alcohol fiber reinforced engineered cementitious composite (PVA-ECC), an affordable strain-hardening composite with green binder content has been proposed. For optimizing the strain-hardening behavior of cementitious composites, this paper investigates the effects of polypropylene fibers on the first cracking strength, fracture properties, and micromechanical parameters of cementitious composites. For this purpose, digital image correlation (DIC) technique was utilized to monitor crack propagation. In addition, to have an in-depth understanding of fiber/matrix interaction, scanning electron microscope (SEM) analysis was used. To understand the effect of fibers on the strain hardening behavior of cementitious composites, ten mixes were designed with the variables of fiber length and volume. To investigate the micromechanical parameters from fracture tests on notched beam specimens, a novel technique has been suggested. In this regard, mechanical and fracture tests were carried out, and the results have been discussed utilizing both fracture and micromechanical concepts. This study shows that the fiber length and volume have optimal values; therefore, using fibers without considering the optimal values has negative effects on the strain-hardening behavior of cementitious composites.

• Asian Pacific Journal of Cancer Prevention
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• v.16 no.5
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• pp.1913-1917
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• 2015

Background: Oesophageal squamous cell carcinoma (ESCC) is endemic in the Eastern Anatolian region of Turkey. The present study was performed to identify risk factors for ESCC that specifically reflect the demography and nutritional habits of individuals living in this region. Materials and Methods: The following parameters were compared in 208 ESCC patients and 200 control individuals in the Eastern Anatolian region: age, sex, place of living, socioeconomic level, education level, smoking, alcohol intake, nutritional habits, and food preservation methods. Results: The mean age of ESCC patients was 56.2 years, and 87 (41.8%) were 65 years-old or older. The ratio of women to men in the patient group was 1.39/1. ESCC patients consumed significantly less fruit and yellow or green vegetables and more hot black tea, 'boiled yellow butter', and mouldy cheese than did control individuals. Residence in rural areas, smoking, and cooking food by burning animal manure were also significantly associated with ESCC. Conclusions: The consumption of boiled yellow butter and mouldy cheese, which are specific to the Eastern Anatolian region, and the use of animal manure for food preparation were identified as risk factors in this region. Further studies are required to potentially identify the carcinogenic substances that promote the development of ESCC in this region.

• International Journal of Industrial Entomology and Biomaterials
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• v.8 no.1
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• pp.67-71
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• 2004

Ten improved mulberry varieties (Vl, C1730, C2016, C2017, Anantha, RFS-175, Thallaghatapura, Vishala, S1 and S1635) were evaluated through enzyme assay and estimation of soluble protein content followed by regression analysis, grown under irrigated conditions in the alluvial soils of Gangetic plains of West Bengal in India for five successive crops in a year, The nitrate reductase (EC No. 1.6.6.1) activity (NRA, $\mu$mol N $O_2$- $h^{-1}$ $g^{-1}$ fr, wt.), total soluble protein (mg $g^{-1}$ fr, wt.) was estimated which showed to vary significantly in the tested varieties. In addition to these, the other parameters like unit leaf fresh and dry weight (g), moisture ％, unit leaf area ($\textrm{cm}^2$), specific leaf weight (g c $m^{-2}$ ), total soluble sugar (mg $g^{-1}$ fr, wt.), leaf yield/plant (kg), shoot yield/plant (kg) and net photosynthetic rate (NPR, $\mu$㏖ $m^{2}$ $s^{-1}$ ) were also studied which showed to vary significantly in tested varieties. Among them, S1635, haying higher NRA (13.25 $\mu$㏖ N $O_2$- $h^{-l}$ $g^{-1}$ fr, wt.), total soluble protein (39.63mg $g^{-1}$ fr, wt.), NPR(16.66 $\mu$㏖ $m^{-2}$ $s^{-1}$ ), total soluble sugar (48.44 mg $g^{-1}$ fr. wt.), leaf yield/plant (0.689 kg) and shoot yield/plant (1.135 kg) showed its superiority over other tested varieties. Regression and correlation coefficients were analysed, and a strong positive correlation was found between NRA ＆ total soluble protein, NRA ＆ NPR, NRA ＆ total soluble sugar, NRA af unit leaf weight, NRA ＆ specific leaf weight, NRA ＆ leaf yield/plant, NRA ＆ shoot yield/plant, NPR ＆ leaf yield and NPR ＆ specific leaf weight.t.

• Archives of design research
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• v.16 no.2
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• pp.121-130
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• 2003

The diffusion expressive power means the flexibility of which creative power test spheres(fluency, originality) by Torrance is ability making the considerations, thoughts and concepts to the meaningful symbolic change. This study is willing to develop and improve program toward the diffusion expressive power and is to testify training effect of the students are majoring design with the object. The training programs composed of six levels which is based on the theory of Eskild Tjalve. And the parameters of each levels are element, function, number, arrangement, form geometric, size and have to practice 2 weeks at once by 12 weeks. For successful measuring the effective results of this study, 40 undergraduate junior students in the department of design are grouped to excercise with experimental pilot group and regulated group. The standard type of creative paper is used to evaluate the results of student's training. This study give proof that creative power of the experimental pilot and under training group is higher than the regulated and under comparison group at in the conclusion.

• International Journal of Industrial Entomology and Biomaterials
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• v.7 no.1
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• pp.59-63
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• 2003

In the present study, hybrid vigour in terms of heterosis and over dominance of newly evolved bivoltine hybrids and their reciprocals raised from the promising newly evolved bivoltine breeds were calculated for the important parameters like pupation, cocoon yield, cocoon weight, shell weight, shell ratio, raw silk percentage, filament length and neatness. Through there was no significant difference among the hybrids for the characters pupation, cocoon yield and cocoon weight, the magnitude of heterosis and over dominance were varied significantly for these characters. However, significant differences were observed between new hybrids and control hybrid for the characters like cocoon shell weight, cocoon shell ratio, filament length and raw silk percentage. The results indicate that majority of new hybrids have shown higher heterosis and over dominance than control hybrid. The data also indicate that highest mean heterosis of all new hybrids was recorded for cocoon yield followed by filament length. Whereas highest mean over dominance was recorded for cocoon yield followed by cocoon weight. Negative mean heterosis and over dominance were recorded for the trait cocoon shell ratio. Based on the results, the importance of three hybrids viz., CSR2 ${\times}$ CSR4, CSR2 ${\times}$ CSR5 and CSR3 ${\times}$ CSR6 and their reciprocals (CSR4 ${\times}$ CSR2, CSR5 ${\times}$ CSR2 and CSR6 ${\times}$ CSR3) which exhibited significant heterosis and over dominance, for commercial exploitation was discussed.