INVESTIGATION OF CAPACITY GAINS IN MIMO CORRELATED RICIAN FADING CHANNELS SYSTEMS

This paper investigate the effect of Rician fading and correlation on the capacity and diversity of MIMO channels. The use of antenna arrays at both sides of the wireless communication link (MIMO systems) can increase channel capacity provided the propagation medium is rich scattering or Rayleigh fading and the antenna arrays at both sides are uncorrelated. However, the presence of line-of-sight (LOS) component and correlation of real world wireless channels may affect the system performance. Along with that we also investigate power distribution methods for higher capacity gains and effect of CSI at the transmitter on the capacity for range of SNR. Our investigation follows capacity gain as function of number of antennas and signal-to-noise (SNR) power ratio Block and frequency nonselective Rician fading channel is assumed, and the effect of Rician factor (L) and the correlation parameter (ρ) on the capacity and diversity gains of MIMO channels are found. Inde

Impact of FLAMM scoring on cesarean section rate in previous one lower segment cesarean section patient

Background: The aim of this study was to evaluate the impact of Flamm scoring for Successful VBAC (vaginal birth after cesarean) and Failed TOLAC (Emergency cesarean section) in case of previous one lower segment cesarean delivery.Methods: This is prospective observation study. Out of 150, 111 patients gave consent for TOLAC. 111 patients with previous one caesarean section with gestational weeks between 37 to 40 weeks with spontaneous onset of labour admitted in labour room of Obstetrics and Gynecology Department in Sola Civil Hospital over a period of 1 year from April 2014 to April 2015.Results: In the present study, 111 (74%) patients had undergone TOLAC trial. Out of 111, 77(69.36%) patients had successful VBAC whereas 34 (30.63%) had emergency cesarean. Among the successful VBAC, 7 patients had assisted vaginal delivery to cut short the second stage in prolonged labour. 26% patients refused to give consent for TOLAC from total number of patients in this study. Mean FLAMM score for Successful VBAC was 5.35 (95% CI, 3.9 to 6.7) compared to Failed TOLAC (EME CS) was 3.62 (95% CI, 3.27 to 4.57) Chances of success of TOLAC was increased with increasing FLAMM score according to this study.Conclusions: Application of FLAMM scoring gives fare judgment of successful vaginal birth in TOLAC. So FLAMM scoring can be applied in each previous one lower segment cesarean section patient undergoing TOLAC without increasing morbidity. Practice of protocol of applying FLAMM score and monitoring by partogram will reduce the rate of cesarean section in previous one lower segment cesarean section patient

Relook at Aileron to Rudder Interconnect

The implementation of interconnect gain from aileron to rudder surface on the majority of the aircraftis to decrease sideslip which is generated because of adverse yaw with the movement of control stick in lateral axis and also enhances the turning rate performance.The Aileron to Rudder Interconnect (ARI)involves significant part to decouple the Dutch roll oscillations from roll rate response to aileron command. ARI is feed-forward gain whichis susceptible to aircraft system uncertainty. Incorrect ARI gain can lead to side slip buildup which can cause aircraft to depart in case of fault scenarios. Four systematic ARI design methods are proposed. One of the proposed methods which use the norm of ARI transfer function at roll damping frequency is suitable for online reconfiguration of control law. The reconfiguration of ARI gain is illustratedwith the simulation responses of fault scenario case of aileron surface damage

Translational science in chronic tendinopathies

Chronic tendinopathies involve majority of patients in clinical practice of orthopaedic surgeons and sports physicians. Translational medicine confers an emerging medical advance efficiently towards the clinician directly from scientists which may be used as a targeted therapy. The main objective of translational research from “bench to bedside” is to test novel inventions in humans. Our purpose in this article to understand the translational medicine approach for chronic tendinopathies in clinical aspects. Translational research in chronic tendinopathies is required certainly due to plenty of reasons. Newer advances and targeted approach to these tendon disorders may curtail the further degenerative process. It aids in earlier diagnosis and prevention of morbidity, early occupancy of occupational activity, lack of economical as well as recreational failure. Pre-disease level activity is ultimate goal of any therapy. Tendon pathophysiology is constantly evolving researched topic in both biochemical as well as molecular aspect. The basic fundamental understanding of complex process of tendon healing and regeneration is necessary for formulating a newer guideline. The cornerstone of treatment of tendinopathies is still non-operative management. Physical therapy, better pain control, NSAIDS are still primary choice for these conditions. Various biological therapy whenever used one should combined them with other appropriate options to obtain an optimum outcome

Machine learning assisted metamaterial‑based reconfigurable antenna for low‑cost portable electronic devices

Antenna design has evolved from bulkier to small portable designs but there is a need for smarter antenna design using machine learning algorithms that can meet today’s high growing demand for smart and fast devices. Here in this research, main focus is on developing smart antenna design using machine learning applicable in 5G mobile applications and portable Wi-Fi, Wi-MAX, and WLAN applications. Our design is based on the metamaterial concept where the patch is truncated and etched with a split ring resonator (SRR). The high gain requirement is met by adding metamaterial superstrates having thin wires (TW) and SRRs. The reconfigurability is achieved by adding three PIN diode switches. Multiple designs have been observed by adding superstrate layers ranging from one layer to four layers with interchanging TWs and SRRs. The TW metamaterial superstrate design with two layers is giving the best performance in gain, bandwidth, and the number of bands. The design is optimized by changing the path’s physical parameters. To shrink simulation time, Extra Tree Regression based machine learning model is used to learn the behavior of the antenna and predict the reflectance value for a wide range of frequencies. Experimental results prove that the use of the Extra Tree Regression based model for simulation of antenna design can cut the simulation time, resource requirements by 80%

PERFORMANCE ANALYSIS OF PILOT-AIDED MIMO-OFDM LTE DOWNLINK SYSTEM USING HYBRID LS-LMMSE TECHNIQUE

ABSTRACT This paper focuses on the channel estimation in OFDM system and it implemented by using pilot type channel estimation by hybrid LS-LMMSE. A LTE system is basically MIMO-OFDM system, where a cyclic prefix is inserted at the beginning of each OFDM symbol in order to suppress both inter-carrier interference (ICI) and inter symbol interference (ISI). The inserted CP is usually longer or equal to the channel length but in some cases, the CP can be shorter. In case of LS and LMMSE channel estimation technique, simulation results shows that LMMSE performs better than LS estimator where cyclic prefix is equal to or longer than the channel length. In other case, LMMSE gives better performance than LS only for low SNR values and for high SNR value, LS gives better performance. Therefore, a hybrid LS-LMMSE channel estimation technique is to reduce the effect of the channel length on system. Simulation results for hybrid system shows its true efficiency and specially for the case where the channel length exceeds the cyclic prefix length

Ultra-broadband and polarization-insensitive metasurface absorber with behavior prediction using machine learning

The solar spectrum energy absorption is very important for designing any solar absorber. The need for absorbing visible, infrared, and ultraviolet regions is increasing as most of the absorbers absorb visible regions. We propose a metasurface solar absorber based on Ge2Sb2Te5 (GST) substrate which increases the absorption in visible, infrared and ultraviolet regions. GST is a phase-changing material having two different phases amorphous (aGST) and crystalline (cGST). The absorber is also analyzed using machine learning algorithm to predict the absorption values for different wavelengths. The solar absorber is showing an ultra-broadband response covering a 0.2–1.5 µm wavelength. The absorption analysis for ultra-violet, visible, and near-infrared regions for aGST and cGST is presented. The absorption of aGST design is better compared to cGST design. Furthermore, the design is showing polarization insensitiveness. Experiments are performed to check the K-Nearest Neighbors (KNN)-Regressor model’s prediction efficiency for predicting missing/intermediate wavelengths values of absorption. Different values of K and test scenarios; C-30, C-50 are used to evaluate regressor models using adjusted R2 Score as an evaluation metric. It is detected from the experimental results that, high prediction proficiency (more than 0.9 adjusted R2score) can be accomplished using a lower value of K in KNN-Regressor model. The design results are optimized for geometrical parameters like substrate thickness, metasurface thickness, and ground plane thickness. The proposed metasurface solar absorber is absorbing ultraviolet, visible, and near-infrared regions which will be used in solar thermal energy applications