Thermophysiological Comfort by PA6/TiO2 Nanocomposite Yarns

Thermophysiological comfort is one of the most important factors for people to choose desirable gar-ments, which can be evaluated via measuring permeability of body heat and sweat. In this paper the water vapor permeability of nanocomposite nylon 6 fabrics produced from melt spun nanocomposite yarns with different TiO2 nanoparticle concentrations have been investigated. Results from measuring water vapor permeability at different environment temperatures for 4 h. indicated that sample with 0.4 wt% of TiO2 nanoparticle can provide fabric with maximum comfort properties. At low temperature 27.5% decline of permeability as compared to pure fabric causes this sample to protect body from cool weather through pre-venting loss of body heat. By increasing temperature from 12 to 35 oC water vapor permeability enhance-ment of nanocomposite improved about 99% as compared to pure one. Consequently nanocomposite with suitable nanoparticle content can provide more comfortable fabrics in different temperatures and applica-tions. When you are citing the document, use the following link http://essuir.sumdu.edu.ua/handle/123456789/3560

Abrasion Resistance of Ag/SiO2/PA6 Nanocomposite Fabrics

In recent decades, polymeric nanocomposites have been widely used in chemical, automobile and aero industries due to their low weight and smoothness. Abrasion resistance is a vital property in variable ap-plications of polymeric composites. Here, to investigate the wear resistance of nylon 6 nanocomposite fab-rics, melt spun yarns were filled with different concentrations of Ag/SiO2 nanoparticles and the wear prop-erties of weft knitted nanocomposite and pure samples were evaluated. Results disclosed that the wear re-sistance of composite fabrics containing nano-particles increased considerably in comparison to pure one. Therefore, nanoparticles can play an important role in improving the nanocomposite wear resistance. When you are citing the document, use the following link http://essuir.sumdu.edu.ua/handle/123456789/3563

Amylose Content and Grain Length of New Rice Transgressive Variants Derived from a Cross Between O. rufipogon and Malaysian Rice Cultivar MR219

Amylose content is one of the important grain quality properties of rice. A total of 10 new rice genotypes (BC2F7 generation) derived from a cross between O. rufipogon Griff. accession IRGC105491 and O. sativa subspecies indica cv. MR219 with high yield were evaluated for amylose content in three environments in Peninsular Malaysia. One of the parents, a popular high yielding Malaysian rice cultivar MR219 was used as a check. Based on the average amylose content across the environments, the genotype G13 showed significantly (p < 0.05) different amylose content (23.88 %) in comparison to other genotypes. Two genotypes G13 (25.7%) and G15 (25.6%) were higher than MR219 (25.1%) in terms of amylose content in Sungai Besar environment. There was a positive (r2=0.018) but no significant correlation between amylose content and grain length

Design and Optimization of Low-Specific Speed Centrifugal Pump

Centrifugal pumps find applications in a wide range of industries, such as rocketry, oil and gas, petroleum, etc. A main property used to characterize the design of pumps is the specific speed, which relates the flow properties of the pump at its operating point. Pumps in the low-specific speed range have been of particular interest. These are characterized by the high head value (representative of mechanical energy) produced at a relatively low flow rate. A lower flow rate reduces the power requirements required to operate the shaft that rotates the impeller. However, the design of such pumps presents many challenges. Most of the existing design methodologies are developed for pumps in a normal specific speed range--low specific-speed pumps fall out of this range. These methods, when applied for the design of low-specific speed pumps, can result in dimensions that are not physically realizable. The work done herein combines empirical relations based on experimental measurements and theory for the optimal design of a low-specific speed pump. This is done by delineating a baseline design for the design flow rate of 253 USGPM based on these relations and then optimizing the baseline design based on its performance features obtained using numerical simulations. Each design was simulated with both a tangential diffuser and an axial diffuser to assess the impact of these diffuser options on performance characteristics

Enhanced Clustering Algorithms For Gray-Scale Image Segmentation

The clustering algorithms are widely used as an unsupervised method for image segmentation in medical diagnosis, satellite imaging and biometric systems. The algorithms are chosen since they are easy to be implemented, required low computational time and less sensitive to noise and artifacts. However, in some cases the conventional clustering algorithms introduce over-segmentation problems and unable to preserve the region of interest (i.e. objects)

How Much Output should be Produced by the Firm? An Analysis

In this study, the main objective of the firm is to determine output and price level; we have taken the time series data of the firm and have applied the ordinary least square technique. We find out the equilibrium point of the firm where marginal revenue is equal to marginal cost and at that point firm earn the maximum profit and we also determine the price level of the firm. The output level that the firm should produce would be of 3922 units, at this point its total cost is 1131611, total revenue is 1115890, marginal revenue is 308.6689, marginal cost is 308.6702 and optimal price is 284.5206. Keywords: Price and Output Determination, Empirical Study, MR = M

Automatic Extraction of Buildings in an Urban Region

There are currently several automatic building extraction methods introduced in the literature, but none of them are capable to completely extract portions of a building that are below a pre-defined building minimum height threshold. This paper proposes a systematic method which analyzes the height differences between the extracted adjacent planes above and below the height threshold as well as the planes' connectivity, thereby, extracting all portions belonging to buildings more completely. In general, the height difference between the edges of the adjacent planes above and below the height threshold that belong to the same building is more uniform. In addition, the extracted planes below the height threshold that belong to a building and their adjacent ground planes also have a clear height difference. The proposed method incorporates such information to achieve better performance in building extraction. We have compared our proposed method to a current state-of-the-art building extraction method qualitatively and quantitatively. Our experimental results show that our proposed method successfully recovers portions of a building below the height threshold, thereby achieving relatively higher average completeness (an improvement of 1.14%) and quality (an improvement of 0.93%)

An improved building detection in complex sites using the LIDAR height variation and point density

In this paper, the height variation in LIDAR (Light Detection And Ranging) point cloud data and point density are analyzed to remove the false building detection in highly vegetation and hilly sites. In general, the LIDAR points in a tree area have higher height variations than those in a building area. Moreover, the density of points having similar height values is lower in a tree area than in a building area. The proposed method uses such information as an improvement to a current state-of-the-art building detection method. The qualitative and object-based quantitative analyzes have been performed to verify the effectiveness of the proposed building detection method as compared with a current method. The analysis shows that proposed building detection method successfully reduces false building detection (i.e. trees in high complex sites of Australia and Germany), and the average correctness and quality have been improved by 6.36% and 6.16% respectively

A new building mask using the gradient of heights for automatic building extraction

A number of building detection methods have been proposed in the literature. However, they are not effective in detecting small buildings (typically, 50 m(2)) and buildings with transparent roof due to the way area thresholds and ground points are used. This paper proposes a new building mask to overcome these limitations and enables detection of buildings not only with transparent roof materials but also which are small in size. The proposed building detection method transforms the non-ground height information into an intensity image and then analyses the gradient information in the image. It uses a small area threshold of 1 m2 and, thereby, is able to detect small buildings such as garden sheds. The use of non-ground points allows analyses of the gradient on all types of roof materials and, thus, the method is also able to detect buildings with transparent roofs. Our experimental results show that the proposed method can successfully extract buildings even when their roofs are small and/or transparent, thereby, achieving relatively higher average completeness and quality