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Objectives Radiation dose variation within and among Computed Tomography (CT) centres is commonly reported. This work systematically reviewed published articles on adult Diagnostic Reference Levels (DRLs) for the brain, chest and abdomen to determine the causes and extent of variation. A systematic literature search and review was performed in selected databases containing leading journals in radiography, radiology and medical physics using carefully defined search terms related to CT and DRLs. The quality of the included articles was determined using the Effective Public Health Practise Project tool for quantitative studies. Key findings The 54 articles reviewed include: 45 studies using human data, 8 studies using phantom data, and one study with both human and phantom data. The main comparator in between studies was the dose indices used in reporting DRLs. DRL variations of up to a factor of 2 for the same procedure were noted in phantom studies, and up to a factor of 3 in human studies. Sources of variation include the type of scanner, the age of the scanner, differences in protocols, variations in patients, as well as variations in study design. Different combinations of dose indices were reported: volume computed tomography dose index (CTDIvol) and dose length product (DLP) (59%); DLP only (11%); weighted computed tomography dose index (CTDIw) and DLP (9%); CTDIvol only (7%); CTDIvol, DLP and effective dose (ED) (6%); CTDIw only (4%); CTDIvol, DLP and size specific dose estimate (SSDE) (1%) and CTDIw, CTDIvol and DLP (1%). The use of different dose indices limited dose comparison between studies. Conclusion The study noted a 2–3 fold variation in DRLs between studies for the same procedure. The causes of variation are reported and include study design, scanner technology and the use of different dose indices. Implications for practice There is a need for standardisation of CT DRLs in line with the International Commission on Radiological Protection recommendations to reduce dose variation and facilitate dose comparison.

The improvement of the robustness of the performance of electrical machines in presence of neglected features, such as manufacturing tolerances and deviations in material properties and parameters, is increasingly demanded. The available optimization procedures do not account for manufacturing tolerances, leaving the decision process incomplete. The article proposes a methodology for the selection of the more robust design towards manufacturing tolerances among the best candidates, detected by an optimization procedure. Statistical tools for tolerance analysis and worst-case analysis are discussed and adopted for the scope. The proposed methodology is used to select a robust design with respect to torque ripple deviations due to geometric tolerances in the laminations of a Synchronous Reluctance Motor with fluid shaped barriers. The statistical performance analysis and the worst-case analysis provide an estimation of the performance deterioration in the presence of the tolerances in the manufacturing process.

Attitude control for CubeSats and small satellites has been widely researched. Nonetheless, most of the literature is based on simulations, with limited availability of actual implementation results. This article tries to fill this gap by highlighting implementation difficulties and proposing appropriate workable solutions. The difficulty of direct reaction wheel (RW) torque feedback for attitude control of a 1p PocketQube (PQ) pico-satellite is noted and addressed. A simple control strategy implementable on a microcontroller is then proposed, showing how direct RW torque control can be achieved through angular velocity measurement without using derivative feedback. A linear quadratic Gaussian controller with integral action in quaternion formulation is used for attitude control, and a reference input boundary caused by the use of the standard integral action scheme is highlighted. A simple solution is then proposed, showing how using the error quaternion removes this boundary. An extended Kalman filter in quaternion formulation is used for attitude determination by fusing data from three sensors, namely, a magnetometer, solar cells, and a gyroscope. An accelerometer is used in place of the solar cells for simplified laboratory testing. Magnetometer error due to surrounding interference is addressed through calibration. A string-suspended model of the UoMBSat-1 PocketQube pico-satellite is used for attitude control testing. Preliminary single-axis tests are performed using a PID controller to determine the satellite parameters and actuators verification. The proposed linear quadratic Gaussian controller is then tested and validated experimentally in the laboratory setting.

This paper presents a preliminary sizing procedure for a fluid shaped rotor of a Synchronous Reluctance motor and the design refinement by an optimization step. Starting from the definition of the fluid shaped barrier based on the Joukosky equation and on the analogy between the magnetic and mechanical equations, the preliminary design can be defined. The method uses the same approach of the other rotor shapes accurately changed to match the features of the fluid shaped rotor. This procedure is applied to a case study where the stator core is already defined. After the definition of the preliminary design a further optimization is carried out which involves an optimization algorithm linked to the Finite Element analysis. The preliminary and the optimized designs are then compared and discussed.

Traffic conditions in signalized junctions are highly dynamic and may be subject to abrupt changes due to unanticipated traffic incidents or network obstructions. These abrupt changing conditions are represented as different regimes or modes where each mode is represented by its own distinct model, forming a set of multiple models. At any instance in time, only one model of the set has the potential of representing the physical system dynamics at that time. However the dynamics may arbitrarily jump over to a different regime when an abnormal condition arises. Furthermore, it might be impossible to identify these models a priori. Hence, a multiple model approach is developed to self-detect these abrupt changes, identify which member of the set best represents the actual system and automatically self-configure and add a new model to the set when a previously unmodelled regime arises. This approach makes use of a real-time joint (dual) estimation algorithm to estimate traffic state variables such as queue lengths and traffic flow, as well as model parameters such as turning ratios, saturation flow values and noise covariance resulting from unmodelled dynamics and measurement errors. The proposed algorithm is validated through simulations on signalized 3-arm and 4-arm junctions with typical day-to-day traffic conditions including several network irregularities occuring at different times of the day such as arm closures as a result of traffic incidents. This work is aimed to form part of adaptive control loops for traffic light systems that are able to autonomously adjust to changing traffic conditions so as to ensure efficient vehicle flows.