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Auxetic materials expand in at least one dimension, when stretched longitudinally i.e. they have negative Poisson's ratio. Development of 2D woven auxetic fabrics (AF) is a new approach to develop mechanically stable auxetic textile structures. However, the mechanical response of such emerging structure is still not studied in detail yet, therefore different mechanical properties of 2D woven AF are compared with conventional non-auxetic fabric (NAF). AF was developed by orienting yarns in auxetic honey-comb (AHC) geometry and auxeticity is induced due to such orientation of yarns. AF was developed using conventional (non-auxetic) materials; cotton yarn and elastane cotton yarn in warp and weft dimension respectively, using air jet loom. Structure and auxeticity of AF were analyzed using a digital microscope and its different mechanical properties (tensile strength, tear strength, bursting strength, cut resistance, and puncture resistance) were studied. AF showed superior mechanical properties with a lower initial modulus, which is beneficial for different protective textiles applications like cut resistance gloves, blast resistant curtains, and puncture tolerant elastomeric composites.
The application of mathematical analysis to the study of wireless ad hoc networks has met with limited success due to the complexity of mobility, traffic models and the dynamic topology. A scenario based universal mobile telecommunications system (UMTS) time division duplex (TDD) opportunistic cellular system with an ad hoc behaviour that operates over UMTS frequency division duplex (FDD) licensed cellular network is considered. In this paper, we present a new routing metric which overall improves system performance in terms of interference and routing which operate in an ad hoc network in an opportunistic manner. Therefore we develop a simulation tool that addresses the goal of analysis and assessment of UMTS TDD opportunistic radio system with ad hoc behavior in coexistence with a UMTS FDD primary cellular networks.
In this research, a novel method based on Canonical Correlation Analysis (CCA) and Artificial Neural Network (ANN) to detect epileptic seizures from EEG signals is proposed. CCA was applied on EEG signals and feature vectors corresponding to Eigen values were extracted. These Eigen values were fed as input to Artificial Neural Network (ANN)'s widely explored model Multilayer Perceptron Neural Networks (MLPNNs) for classification between occurrence of non-epileptic seizures and epileptic seizures. The extracted Eigen values using CCA proved to be a better epileptic seizures detector and provide average classification accuracy, sensitivity and specificity as 92.583%, 93.25% and 91% respectively.
Facies control on selective dolomitization and its impact on reservoir heterogeneities in the Samana Suk Formation (middle Jurassic), Southern Hazara Basin (NW Himalaya, Pakistan): an outcrop analogue
This studied rocks form part of the southern Hazara basin in the NW Himalayan Fold and Thrust belt, Pakistan. Thick inner to mid ramp carbonate platform deposits of Samana Suk Formation (Bajocian–Callovian) mostly composed of medium to thick bedded limestone with occasional dolostone beds are exposed in various localities. In the present studies, attempt has been made to understand degree of diagenetic alterations (i.e., dolomitization) within various limestone facies due to fluid-rock interaction phenomenon, and its impact on the reservoir behavior of altered rocks based on field investigations, petrographic studies, stable isotope signatures and porosity/permeability analysis. Field observations revealed various limestone types (oolitic, burrowed, fossiliferous, micritic and sandy), whereas dolomite occurs as completely replacive phase (Dol-I), and partially replacive patchy bodies (Dol-II) respectively. Petrographic studies showed various limestone and dolomite facies, which include: (i) Grainstone facies (bioclastic grainstone, peloidal grainstone, ooidal grainstone and pel-bioclastic grainstone), (ii) Packstone facies (bioclastic packstone and peloidal packstone), (iii) Wackestone facies (bioclastic wackestone), (iv) Mudstone facies (lime mudstone, and (v) Dolomite facies (coarse crystalline strata-bound Dol-I, and fine crystalline patchy Dol-II) respectively. O/C isotope analysis revealed that Dol-I shows signatures of δ18O (–5.84 to –3.91‰ V-PDB), and δ13C (+0.6 to +2.37‰ V-PDB) are within the limit of the carbonate marine seawater signatures, hence originated from sea-water or modified sea-water, whereas Dol-II exhibited depleted δ18O values (–6.88 to –5.87‰ V-PDB) and slightly depleted δ13C signatures (+0.968 to +1.85‰ V-PDB), indicating high temperature dolomitizing fluids. During early stage of marine diagenesis, which resulted in the cementation of pores within the grainstone-packstone facies, whereas mudstone-wackestone facies remained unaltered due to low porosity and permeability. Late stage dolomitization caused partial to complete alteration of mudstone-wackestone facies, in contrast grainstone-packstone facies are not affected by dolomitizing fluids due to the fact that the pore network of these coarser facies had already been occluded by the preceding marine cementation event. Porosity and permeability analyses revealed relatively high porosity values (4–8%) and permeability values (11.5 mD) in the dolomitized facies, whereas unaltered limestone facies showed considerably low porosity/permeability values (> 1%). In conclusion, less porous/permeable fine-grained facies evolved into more porous and permeable units due to the interaction of dolomitizing fluids of hydrothermal origin, which confirms that the original sedimentary texture of rock has implications on the selectivity of any diagenetic alteration.
We present a simple and efficient management scheme for gain control of EDFA by using standardized network management protocol (Simple Network Management Protocol) and operating the optical amplifier in a link-control scheme. We have demonstrated the proposed scheme by using SNMP Simulator and optical simulation software package.