Effectiveness of appropriately trained nurses in preoperative assessment: randomised controlled equivalence/non-inferiority trial

Objective To determine whether preoperative assessments carried out by appropriately trained nurses are inferior in quality to those carried out by preregistration house officers. Design Randomised controlled equivalence/non-inferiority trial. Setting Four NHS hospitals in three trusts. Three of the four were teaching hospitals. Participants All patients attending for assessment before general anaesthesia for general, vascular, urological, or breast surgery between April 1998 and March 1999. Intervention Assessment by one of three appropriately trained nurses or by one of several preregistration house officers. Main outcome measures History taken, physical examination, and investigations ordered. Measures evaluated by a specialist registrar in anaesthetics and placed in four categories: correct, overassessment, underassessment not affecting management, and underassessment possibly affecting management (primary outcome). Results 1907 patients were randomised, and 1874 completed the study; 926 were assessed by house officers and 948 by nurses. Overall 121/948 (13%) assessments carried out by nurses were judged to have possibly affected management compared with 138/926 (15%) of those performed by house officers. Nurses were judged to be non-inferior to house officers in assessment, although there was variation among them in terms of the quality of history taking. The house officers ordered considerably more unnecessary tests than the nurses (218/926 (24%) v 129/948 (14%). Conclusions There is no reason to inhibit the development of nurse led preoperative assessment provided that the nurses involved receive adequate training. However, house officers will continue to require experience in preoperative assessment

Optimal Array size for Multiuser MIMO

This paper investigates the optimal number of antennas at a base station, in contrast to what has been accepted in the past: that increasing the number of antennas at base station always enhances performance. In this study, we show that increasing the number of antennas does not always improve the desired performance. Additionally, such increase in antennas consumes more power in transmission and adds to the computation complexity, which in turn needs more time and is more difficult to implement. The optimum number of antennas has been evaluated using simulations. The simulation results show that the optimal ratio equals to 1.2 times the number of active users in each time frame

Maximum Power Point Tracking for Photovoltaic System by Using Fuzzy Neural Network

The electrical energy from the sun can be extracted using solar photovoltaic (PV) modules. This energy can be maximized if the connected load resistance matches that of the PV panel. In search of the optimum matching between the PV and the load resistance, the maximum power point tracking (MPPT) technique offers considerable potential. This paper aims to show how the modelling process of an efficient PV system with a DC load can be achieved using a fuzzy neural network (FNN) controller. This is applied via an innovative methodology, which senses the irradiance and temperature of the PV panel and produces an optimal value of duty ration for the boost converter to obtain the MPPT. The coefficients of this controller have been refined based upon previous data sets using the irradiance and temperature. A gradient descent algorithm is employed to improve the parameters of the FNN controller to achieve an optimal response. The validity of the PV system using the MPPT technique based on the FNN controller is further demonstrated via a series of experimental tests at different ambient conditions. The simulation results show how the MPPT technique based on the FNN controller is more effective in maintaining the optimal power values compared with conventional techniques

Reconfigurable Wilkinson power divider with unity to 8dB output power differences using one varactor diode

A novel reconfigurable equal to unequal Wilkinson power divider is presented. The proposed power divider adopts coupled microstrip line technique to implement a high impedance section to have unequal output power ratio. A varactor diode is placed between the coupled lines to achieve reconfigurability by changing the reverse biasing voltage on the varactor diode. This enables equal to 8 dB power division ratios between the output ports. A wide range of biasing voltage is used to achieve the smooth power division ratio. A prototype hardware is designed, fabricated and measured to validate the proposed approach. In the equal power division ratio scenario, the measured performance shows a bandwidth of 600 MHz at 5.4 GHz centre frequency. A higher bandwidth of 750 MHz is obtained in the case of unequal power division ratios

An indoor path loss prediction model using wall correction factors for wireless local area network and 5G indoor networks

A modified indoor path loss prediction model is presented, namely, effective wall loss model. The modified model is compared to other indoor path loss prediction models using simulation data and real-time measurements. Different operating frequencies and antenna polarizations are considered to verify the observations. In the simulation part, effective wall loss model shows the best performance among other models as it outperforms 2 times the dual-slope model, which is the second best performance. Similar observations were recorded from the experimental results. Linear attenuation and one-slope models have similar behavior, the two models parameters show dependency on operating frequency and antenna polarization

Current technologies and location based services

This paper examines the benefits and drawbacks of these services, reviewing differences in infrastructure, power requirements, sensing devices, and other factors. Technologies covered include Radio Frequency Identification, GSM, GPS, A-GPS, Smart Antennas, Distributed Antenna Systems, Localization by Cell-ID, Localization by Prediction (Dead Reckoning method), Angle of Arrival (AOA), Localization by Finger Printing, Localization by Time of Arrival (TOA), Localization by Observed Time Difference of Arrival (TDOA), and Hybrid Localization-based AOA-TOA