Congestion Window Scaling Method to Optimize Delay in TCP/IP

Wireless Personal Communications - TCP (Transmission Control Protocol) is a protocol of layer four (Transport Layer), and IP (Internet Protocol) is in the Network Layer (Layer 3) of the OSI Model....     

Introducing a new salty waste for second-generation bioethanol production

We have introduced the discards of turnip juice as a raw material for bioethanol production for the first time. Pretreatment methods, initial biomass loading, and fermentation time were investigated. Supplementation of different kinds of nitrogen sources, mineral salts and agricultural waste hydrolysates were added in the growth medium. The highest bioethanol concentrations and Q_p values were 7.32, 5.34, 1.55 g/L and 0.61, 0.44, 0.05 g/L.h for S. cerevisiae, K. marxianus and P. stipitis, respectively. Furthermore, Y_p/s values were 0.46 g/g, 0.47 g/g, and 0.37 g/g for the three yeasts. Turnip juice discards are promising raw materials for bioethanol production.     

HNMH: A New Hybrid Approach Based on Near Maximum Histogram and LSB Technique for Image Steganography

Wireless Personal Communications - This paper introduces a planar circular split ring resonator (CSRR) coupled to microstrip transmission line (TL) for rotation angle sensing applications....     

Cl2 Adsorption and Desorption over Ordered Mesoporous Carbon Materials as an Indicator for Catalytic Phosgene Formation

The presented work evaluates the implementation of adsorption and desorption experiments with Cl₂ over carbon materials towards the development of more active and stable catalysts for industrial phosgene synthesis. By using a soft templating method as a tool, ordered mesoporous carbon materials with tunable porosity, surface area, and degree of graphitization were synthesized and utilized as model system. The Cl₂ adsorption/desorption properties of these materials were studied and compared to commercial activated carbon. To draw correlations between Cl₂ adsorption/desorption behavior and catalytic performance, the materials were further tested in the phosgene formation in a plug flow reactor. However, the chemical reaction of Cl₂ with carbon during the adsorption/desorption experiment hinders a direct correlation.     

Influence of injection timing on the performance,combustion and emission characteristics of diesel engine powered with tamarind seed biodiesel blend

ABSTRACT

The limitations and ramifications of petroleum fuel on the present environmental society raised the necessity of alternative fuel. The physicochemical properties of biodiesel and its ability to reduce emissions have engaged the attention of researchers to prefer biodiesel as a better alternative fuel. A modification in engine parameters is proven to be one of the best techniques to obtain comparable results with diesel. The following study emphasises TSME 20 (20% Tamarind Seed Methyl Ester with 80% diesel) as an alternative fuel and its performance and emission characteristics are deciphered at different injection timings (19°, 23° and 27° bTDC) at different loads. Focusing on the results obtained at full-load condition, considerable improvement in brake thermal efficiency by 3.18% was noticed with the significant reduction in carbon monoxide, hydrocarbon, oxides of nitrogen and smoke by 17.3%, 57.3%, 31.34% and 8.1%, respectively, at retarded injection timing compared to standard injection timing.     

Landslide susceptibility mapping at Ovacık-Karabük (Turkey) using different artificial neural network models: comparison of training algorithms

This study aims to investigate the performances of different training algorithms used for an artificial neural network (ANN) method to produce landslide susceptibility maps. For this purpose, Ovacık region (southeast of Karabük Province), located in the Western Black Sea Region (Turkey), was selected as the study area. A total of 196 landslides were mapped, and a landslide database was prepared. Topographical elevation, slope angle, aspect, wetness index, lithology, and vegetation index parameters were taken into account for the landslide susceptibility analyses. Two different ANN structures, which were composed of single and double hidden layers, were applied to compare the effects of the ANN. Four different training algorithms, namely batch back-propagation, quick propagation, conjugate gradient descent (CGD), and Levenberg–Marquardt, were used for the training stage of the ANN models. Thus, eight different landslide susceptibility maps were produced for the study area using different ANN structures and algorithms. In order to assess the effects and spatial performances of the considered training algorithms on the ANN models, the relative operating characteristics (ROC) and relation value (r_ij) approaches were used. The susceptibility map produced by CGD1 has the highest AUC (0.817) and r_ij values (0.972). Comparison of the susceptibility maps indicated that CGD training algorithm is the slowest one among the other algorithms, but this algorithm showed the highest performance on the results.

     

A biomedical system based on fuzzy discrete hidden Markov model for the diagnosis of the brain diseases

Because it is a non-invasive, easy to apply and reliable technique, transcranial doppler (TCD) study of the adult intracerebral circulation has increased enormously in the last 10 years. In this study, a biomedical system has been implemented in order to classify the TCD signals recorded from the temporal region of the brain of 82 patients as well as of 24 healthy people. The diseases were investigated cerebral aneurysm, brain hemorrhage, cerebral oedema and brain tumor. The system is composed of feature extraction and classification parts, basically. In the feature extraction stage, the linear predictive coding analysis and cepstral analysis were applied in order to extract the cepstral and delta-cepstral coefficients in frame level as feature vectors. In the classification stage, discrete hidden Markov model (DHMM) based methods were used. In order to avoid loosing information due to vector quantization and to increase the classification performance, a fuzzy approach based similarity was applied to implement the DHMM. The performance of the proposed Fuzzy DHMM (FDHMM) was compared with some methods such as DHMM, artificial neural network (ANN), neuro-fuzzy approaches and obtained better classification performance than these methods.     

The growth and nutrient uptake of invasive vines on contrasting riverbank soils

This study sought to investigate the research question as to whether the growth and nutrient uptake of two invasive vines, Pueraria lobata and Sicyos angulatus, are affected by the heterogeneity of soil characteristics of two riverbank sites with different flooding regimes. Soil, individual ramets of P. lobata and S. angulatus plants were sampled monthly from quadrats set on homogenous stands from two riparian sites along Tama River, Japan for over a year. Soil nutrients, above‐ground (AGB) and below‐ground biomass (BGB), tissue nutrient, and nonstructural carbohydrate contents were estimated, and resource allocations to different organs were calculated. Flooding frequency directly affected the substrate characteristics of the sites; the frequently flooded site had coarser particle and less nutrient content. There were significant differences between the BGB and the AGB of both P. lobata and S. angulatus between the sites. However, the BGB:AGB ratio of these species were statistically similar regardless of the substrate conditions. Although the biomass of S. angulatus were much reduced in coarse habitat, the total amount of nutrient uptake by P. lobata was not affected by habitat the condition. Concentrations of total nitrogen, total phosphorus, and starch in root tissues of S. angulatus were less in frequently inundated soil. The results of this study suggest that inundation frequency directly affects the substrate condition of a riverbank habitat, which in turn affects plant growth, and invasive plant species growing in such habitat respond differently to substrate condition in terms of growth and nutrient uptake.     

Improving the Evaluation of Generator Matrix G by Initial Upper Bound Estimation

STTC （space-time trellis code） can achieve both the diversity and coding gains. To maximize the advantages of STTC, two design criteria for slow Rayleigh fading channels will be used： i.e., the rank and determinant criteria. This paper focuses on the determinant criteria, which involves the evaluation of the generator matrix G. Evaluation is improved by pruning the search process earlier, which is made possible by estimating the initial upper bound prior to the search. In order to reduce the search complexity, the initial upper bound will be calculated at the minimal cycle. Comparatively, it can reduce the search space by 25.8%.