A Comparative Study of Consumer Perception of Product Quality: Chinese versus Non-Chinese Products

Product quality is a critical determinant of consumer satisfaction. The demand for a product depends upon the quality that a manufacturer is providing to their consumers. China, which is a growing economic power, exports its manufactured goods to the entire global markets. Chinese goods have been successful to capture market because of its competitive price strategy as compared to the products of other countries. The major problem with the Chinese products is that these are perceived as of relatively inferior quality in comparison to the products of other countries. This study is an attempt to assess the perceptions of customers regarding price and quality aspects of Chinese and non Chinese products. To compare the relative effectiveness of price and quality, the concepts of perceived life and perceived value are used. It is found that the Chinese products are perceived as price effective but the area of product quality requires immediate attention because Chinese products are perceived as of low qualit

Cost Benefits Analysis of Anthelmintic Treatment of Cattle and Buffaloes

A study was carried out to determine the point prevalence of various helminths of cattle and buffalo population of district Toba Tek Singh, Pakistan and economic benefits of deworming with oxyclozanide. Out of 540 fecal samples examined, 205 (37.96%) were found infected with helminths. Significantly higher (OR=2.2; P<0.05) prevalence of helminths was recorded in buffaloes (40%; 112/280) as compared to cattle (35.77%; 93/260). Oesophagostomum, Cooperia, Trichostrongylus, Strongyloide, Ostertagia, Fasciola (F.) hepatica, F. gigantica and Haemonchus contortus were the helminth species identified in the study area. Oxyclozanide medicated buffaloes (E=96.66%) and cattle (E=95.64%) showed a significant decrease in fecal egg counts on day 14 post-treatment. An average daily increase of 0.89 and 0.71 liters of milk along with 0.42 and 0.37% more fat per buffalo and cattle, respectively was observed in oxyclozanide medication. The economic value of reduced production of infected animals was estimated as US$0.47 (Pak Rupees 40) and US$ 0.41 (Pak Rupees 35) per animal per day for cattle and buffaloes, respectively. It can be concluded that single dose of oxyclozanide is effective against all bovine helminths

A Finite-Time Robust Distributed Cooperative Secondary Control Protocol for Droop-Based Islanded AC Microgrids

In this research work, a resilient finite-time consensus-based distributed secondary control protocol is presented for droop-based distributed generating (DG) units of an islanded AC microgrid (MG). Through a multi-agent control structure, the DG units of the microgrid adjust their active power outputs so that they reach an agreed-upon value in a finite time. Concurrently, all the DG units are forced to operate with their frequencies regulated to the reference MG frequency in a finite time, despite time-varying load perturbations. Each DG unit is provided with a hierarchical control architecture, where the primary control is achieved using the droop control method, while the secondary control is established through the proposed distributed control protocol. The communication between DG units takes place over a sparse communication network. The proposed control protocol is robust to both small and sufficiently large communication latencies and it supports the plug-and-play feature of DG units. Different time-domain-based numerical simulations are carried out on a small as well as large microgrid testbenches in Matlab/Simulink and demonstrate the correctness and effectiveness of the proposed distributed control protocol. A comparative study is also presented with the existing distributed control protocol, and it is found that the proposed strategy is superior in its performance

Patients’ receptiveness for medical students during consultation in outpatient department of a teaching hospital

Background: Patients’ attitude towards medical students’ presence during treatment depends on the cultural values of the society. This study was conducted to find out the patients’ receptiveness in our society to be involved in teaching process for medical students during consultation in outpatient department of a teaching hospital. Methods: This cross sectional study conducted in the Out Patient Department (OPD) of surgery at Dow University Hospital over the period of May 2012 to June 2012. Four hundred and eleven patients consented for participation through non probability purposive sampling, in which 279 patients were from morning clinics in the presence of students for clinical teaching, while 132 patients participated through evening clinics of surgery, when students were not present for comparison in specific dimensions of care for patients’ satisfaction. Results: Majority of patients (71%) agrees with the teaching of students during consultation and they feel they are contributed in future doctor’s teaching, only 24% patients disagree. Fifty two percent of disagreed patients reported privacy interference, 34% consultation interference and 43% prolong waiting time due to teaching. Conclusions: Majority of the patients agree to be part of teaching for medical students and this study can be used to assess the educational interventions designed to improve the patient based teaching. Key words: Patients’ satisfaction, patient based teaching, ambulatory teaching

Adaptive Neural Network Q-Learning-Based Full Recurrent Adaptive NeuroFuzzy Nonlinear Control Paradigms for Bidirectional-Interlinking Converter in a Grid-Connected Hybrid AC-DC Microgrid

The stability of a hybrid AC-DC microgrid depends mainly upon the bidirectional interlinking converter (BIC), which is responsible for power transfer, power balance, voltage solidity, frequency and transients sanity. The varying generation from renewable resources, fluctuating loads, and bidirectional power flow from the utility grid, charging station, super-capacitor, and batteries produce various stability issues on hybrid microgrids, like net active-reactive power flow on the AC-bus, frequency oscillations, total harmonic distortion (THD), and voltage variations. Therefore, the control of BIC between AC and DC buses in grid-connected hybrid microgrid power systems is of great importance for the quality/smooth operation of power flow, power sharing and stability of the whole power system. In literature, various control schemes are suggested, like conventional droop control, communication-based control, model predictive control, etc., each addressing different stability issues of hybrid AC-DC microgrids. However, model dependence, single-point-failure (SPF), communication vulnerability, complex computations, and complicated multilayer structures motivated the authors to develop online adaptive neural network (NN) Q-learning-based full recurrent adaptive neurofuzzy nonlinear control paradigms for BIC in a grid-connected hybrid AC-DC microgrid. The proposed strategies successfully ensure the following: (i) frequency stabilization, (ii) THD reduction, (iii) voltage normalization and (iv) negligible net active-reactive power flow on the AC-bus. Three novel adaptive NN Q-learning-based full recurrent adaptive neurofuzzy nonlinear control paradigms are proposed for PQ-control of BIC in a grid-connected hybrid AC-DC microgrid. The control schemes are based on NN Q-learning and full recurrent adaptive neurofuzzy identifiers. Hybrid adaptive full recurrent Legendre wavelet-based Neural Network Q-learning-based full recurrent adaptive NeuroFuzzy control, Hybrid adaptive full recurrent Mexican hat wavelet-based Neural Network Q-learning-based full recurrent adaptive NeuroFuzzy control, and Hybrid adaptive full recurrent Morlet wavelet-based Neural Network Q-learning-based full recurrent adaptive NeuroFuzzy control are modeled and tested for the control of BIC. The controllers differ from each other, based on variants used in the antecedent part (Gaussian membership function and B-Spline membership function), and consequent part (Legendre wavelet, Mexican hat wavelet, and Morlet wavelet) of the full recurrent adaptive neurofuzzy identifiers. The performance of the proposed control schemes was validated for various quality and stability parameters, using a simulation testbench in MATLAB/Simulink. The simulation results were bench-marked against an aPID controller, and each proposed control scheme, for a simulation time of a complete solar day

Finite-Time Fast Dynamic Terminal Sliding Mode Maximum Power Point Tracking Control Paradigm for Permanent Magnet Synchronous Generator-Based Wind Energy Conversion System

Due to the intermittent nature of wind, there exists a major disparity between the power generation from the wind and the demand of electricity. Hence, a sophisticated maximum power point tracking (MPPT) control paradigm must be formulated for maximizing the power extraction from the wind. This research article focuses on the formulation of a nonlinear fast dynamic terminal sliding mode control (FDTSMC)-based MPPT strategy for optimizing the power extraction from a 3kW, variable speed, fixed-pitch wind energy conversion system equipped with a permanent magnet synchronous generator. The proposed MPPT strategy is compared with the benchmark fast terminal sliding mode control, conventional sliding mode control, feedback linearization control and proportional integral derivative control-based MPPT strategies under a stochastic wind speed profile. The proposed paradigm has been found superior in its tracking performance by converging the output tracking error to zero in a finite time, realizing a high precision performance, offering fast dynamic response, reducing the chattering to a minute level and guaranteeing global robustness. The superior performance and effectiveness of the proposed FDTSMC-based MPPT control paradigm is tested and validated through extensive MATLAB/Simulink simulations

Nonlinear adaptive NeuroFuzzy feedback linearization based MPPT control schemes for photovoltaic system in microgrid.

Renewable energy resources connected to a single utility grid system require highly nonlinear control algorithms to maintain efficient operation concerning power output and stability under varying operating conditions. This research work presents a comparative analysis of different adaptive Feedback Linearization (FBL) embedded Full Recurrent Adaptive NeuroFuzzy (FRANF) control schemes for maximum power point tracking (MPPT) of PV subsystem tied to a smart microgrid hybrid power system (SMG-HPS). The proposed schemes are differentiated based on structure and mathematical functions used in FRANF embedded in the FBL model. The comparative analysis is carried out based on efficiency and performance indexes obtained using the power error between the reference and the tracked power for three cases; a) step change in solar irradiation and temperature, b) partial shading condition (PSC), and c) daily field data. The proposed schemes offer enhanced convergence compared to existing techniques in terms of complexity and stability. The overall performance of all the proposed schemes is evaluated by a spider chart of multivariate comparable parameters. Adaptive PID is used for the comparison of results produced by proposed control schemes. The performance of Mexican hat wavelet-based FRANF embedded FBL is superior to the other proposed schemes as well as to aPID based MPPT scheme. However, all proposed schemes produce better results as compared to conventional MPPT control in all cases. Matlab/Simulink is used to carry out the simulations