Mixing performance of split-and-recombine micromixer with offset inlets

Microsystem Technologies - This study proposes a novel 3D split-and-recombine passive micromixer with offset-inlets. The micromixer is composed of non-aligned inlets and spatially repeating mixing...     

Modeling the role of microstructural parameters in radiative heat transfer through disordered fibrous media

Understanding the influence of microstructural parameters on the rate of heat transfer through a disordered fibrous medium is important for the design and development of heat insulation materials. In this work, by generating virtual 3-D geometries that resemble the internal microstructure of fibrous insulation materials, we simulated the influence of diameter, orientation, and emissivity of the fibers, as well as the media’s porosity and thickness on the radiative heat transmittance. Our simulations are based on a Monte Carlo ray tracing algorithm that we have developed for studying radiative heat flow in 3-D disordered media. The media were assumed to be made up of cylindrical opaque fibers with specular surface. The advantage of our modeling approach is that it does not require any empirical input values, and can directly be used to isolate and study the role of individual microstructural parameters of the media. The major limitation of the model is that it is accurate as long as the fibers can be considered large relative to the wavelength of the incoming rays. Our results indicate that heat flux through a fibrous medium decreases by increasing the packing fraction of the fibers when the thickness and fiber diameter are kept constant. Increasing the fibers’ absorptivity (or emissivity) was observed to decrease the radiation transmittance through the media. Our simulations also revealed that for constant porosity and thickness, the heat flux transmitted across the medium can be reduced by using finer fibers. The steady state temperature profiles across the thicknesses of media with different properties were obtained and found to be independent of the fibers’ emissivity.     

Fabrication of silicon nanowire arrays based solar cell with improved performance

We report fabrication of solar cell (n⁺-p-p⁺ structure) on black silicon substrates consisting of silicon nanowire (SiNW) arrays prepared by Ag induced wet chemical etching process in aqueous HF-AgNO₃ solution. SiNW arrays surface has low reflectivity (<5%) in the entire spectral range (400-1100 nm) of interest for solar cells. The solar cells were fabricated by conventional cell fabrication protocol. Performance of three types of cells, namely cell with SiNW over the entire front surface, cell with SiNW only in the active device area and control cell (on planar surface), has been compared. It was found that cell based on selectively grown shorter length SiNW arrays has the best cell performance.     

Geothermal energy in Turkey: 2008 update

Geological studies indicate that the most important geothermal systems of western Turkey are located in the major grabens of the Menderes Metamorphic Massif, while those that are associated with local volcanism are more common in the central and eastern parts of the country. The present (2008) installed geothermal power generation capacity in Turkey is about 32.65 MWe, while that of direct use projects is around 795 MWt. Eleven major, high-to-medium enthalpy fields in western part of the country have 570 MWe of proven, 905 MWe of probable and 1389 MWe of possible geothermal reserves for power generation. In spite of the complex legal issues related to the development of Turkey's geothermal resources, their use is expected to increase in the future, particularly for electricity generation and for greenhouse heating.     

Neuro-genetic,neuro-imperialism and genetic programing models in predicting ultimate bearing capacity of pile

Prediction of pile-bearing capacity developing artificial intelligence models has been done over the last decade. Such predictive tools can assist geotechnical engineers to easily determine the ultimate pile bearing capacity instead of conducting any difficult field tests. The main aim of this study is to predict the bearing capacity of pile developing several smart models, i.e., neuro-genetic, neuro-imperialism, genetic programing (GP) and artificial neural network (ANN). For this purpose, a number of concrete pile characteristics and its dynamic load test specifications were investigated to select pile cross-sectional area, pile length, pile set, hammer weight and drop height as five input variables which have the most impacts on pile bearing capacity as the single output variable. It should be noted that all the aforementioned parameters were measured by conducting a series of pile driving analyzer tests on precast concrete piles located in Pekanbaru, Indonesia. The recorded data were used to establish a database of 50 test cases. With regard to data modelling, many smart models of neuro-genetic, neuro-imperialism, GP and ANN were developed and then evaluated based on the three most common statistical indices, i.e., root mean squared error (RMSE), coefficient determination (R²) and variance account for (VAF). Based on the simulation results and the computed indices’ values, it is observed that the proposed GP model with training and test RMSE values of 0.041 and 0.040, respectively, performs noticeably better than the proposed neuro-genetic model with RMSE values of 0.042 and 0.040, neuro-imperialism model with RMSE values of 0.045 and 0.059, and ANN model with RMSE values of 0.116 and 0.108 for training and test sets, respectively. Therefore, this GP-based model can provide a new applicable equation to effectively predict the ultimate pile bearing capacity.

     

Bit Rate Reduction in Cloud Gaming Using Object Detection Technique

The past two decades witnessed a broad-increase in web technology and on-line gaming. Enhancing the broadband confinements is viewed as one of the most significant variables that prompted new gaming technology. The immense utilization of web applications and games additionally prompted growth in the handled devices and moving the limited gaming experience from user devices to online cloud servers. As internet capabilities are enhanced new ways of gaming are being used to improve the gaming experience. In cloud-based video gaming, game engines are hosted in cloud gaming data centers, and compressed gaming scenes are rendered to the players over the internet with updated controls. In such systems, the task of transferring games and video compression imposes huge computational complexity is required on cloud servers. The basic problems in cloud gaming in particular are high encoding time, latency, and low frame rates which require a new methodology for a better solution. To improve the bandwidth issue in cloud games, the compression of video sequences requires an alternative mechanism to improve gaming adaption without input delay. In this paper, the proposed improved methodology is used for automatic unnecessary scene detection, scene removing and bit rate reduction using an adaptive algorithm for object detection in a game scene. As a result, simulations showed without much impact on the players’ quality experience, the selective object encoding method and object adaption technique decrease the network latency issue, reduce the game streaming bitrate at a remarkable scale on different games. The proposed algorithm was evaluated for three video game scenes. In this paper, achieved 14.6% decrease in encoding and 45.6% decrease in bit rate for the first video game scene.     

Near-infrared spectroscopy coupled chemometric algorithms for prediction of antioxidant activity of black goji berries (<Emphasis Type="Italic">Lycium ruthenicum</Emphasis> Murr.)

In this study, near-infrared (NIR) spectroscopy coupled with partial least-squares (PLS) regression and various efficient variable selection algorithms, synergy interval-PLS (Si-PLS), backward interval PLS (Bi-PLS) and genetic algorithm-PLS (GA-PLS) were applied comparatively for the prediction of antioxidant activity in black wolfberry (BW). The eight assays were used for quantification of antioxidant content. The developed models were assessed using correlation coefficients (R²) of the calibration (Cal.) and prediction (Pre.); root mean square error of prediction, RMSEP; standard Error of Cross-Validation, RMSECV and residual predictive deviation, RPD. The performance of the built model greatly improved by the application of Si-PLS, Bi-PLS and GA-PLS compared with full spectrum PLS. The R² values determined for calibration and prediction set ranged from 0.8479 to 0.9696 and 0.8401 to 0.9638, respectively. These findings revealed that NIR spectroscopy combined with chemometric algorithms can be used for quantification of antioxidant activity in BW samples.     

Rayleigh backscattering minimization in single fiber colorless WDM-PON using intensity remodulation technique

The performance of colorless wavelength-division multiplexed passive optical network(WDM-PON) systems suffers from the transmission impairments mainly due to Rayleigh backscattering(RB).In this paper,we propose and demonstrate a single fiber colorless WDM-PON which enhances the tolerance to RB induced noise.The high extinction ratio in both return-to-zero(RZ)-shaped differential phase shift keying(DPSK) downstream(DS) data signal and intensity-remodulated upstream(US) data signal helps to improve the tolerance to RB induced noise.Simulation results show that downstream and upstream signals can achieve error-free performance at 10 Gbit/s with negligible penalty and improve the tolerance to RB induced noise over 25 km standard single-mode fiber.     

Chitosan-Based Smart Polymeric Hydrogels and Their Prospective Applications in Biomedicine

With increasing scientific research, knowledge, and socioeconomic awareness, research, and industrial communities are now much more interested in biopolymers-based composite materials with multifaceted functionalities. Biopolymers are easily obtainable, economical, non-hazardous, and abundant. Several natural and synthetic polymers have been used to prepare hydrogels, microbeads, and microfibers for controlled drug release. Due to marvelous properties, chitosan has been widely explored for medical and pharmaceutical applications. In recent years, considerable attention has been paid to the chitosan-based hydrogels for biomedical applications, especially for transplantation, and for improving interfacial interactions for the living tissues. Hydrogels can be synthesized by co-polymerization, condensation, and cross-linking. This review spotlights recent advances in physicochemical characteristics, modification strategies, and smart blended hydrogels for an array of biomedical and pharmaceutical applications. The whole discussion reveals that among all the biopolymers, chitosan is the finest carrier for biomedical applications.