Dynamic and Leakage Power-Composition Profile Driven Co-Synthesis for Energy and Cost Reduction

Recent research has shown that combining dynamic voltage scaling (DVS) and adaptive body bias (ABB) techniques achieve the highest reduction in embedded systems energy dissipation [1]. In this paper we show that it is possible to produce comparable energy saving to that obtained using combined DVS and ABB techniques but with reduced hardware cost achieved by employing processing elements (PEs) with separate DVS or ABB capability. A co-synthesis methodology which is aware of tasks’ power-composition profile (the ratio of the dynamic power to the leakage power) is presented. The methodology selects voltage scaling capabilities (DVS, ABB, or combined DVS and ABB) for the PEs, maps, schedules, and voltage scales applications given as task graphs with timing constraints, aiming to dynamic and leakage energy reduction at low hardware cost. We conduct detailed experiments, including a real-life example, to demonstrate the effectiveness of our methodology. We demonstrate that it is possible to produce designs that contain PEs with only DVS or ABB technique but have energy dissipation that are only 4.4% higher when compared with the same designs that employ PEs with combined DVS and ABB capabilities

3D UAV Trajectory and Communication Design for Simultaneous Uplink and Downlink Transmission

In this paper, we investigate the unmanned aerial vehicle (UAV)-Aided simultaneous uplink and downlink transmission networks, where one UAV acting as a disseminator is connected to multiple access points (AP), and the other UAV acting as a base station (BS) collects data from numerous sensor nodes (SNs). The goal of this paper is to maximize the system throughput by jointly optimizing the 3D UAV trajectory, communication scheduling, and UAV-AP/SN transmit power. We first consider a special case where the UAV-BS and UAV-AP trajectories are pre-determined. Although the resulting problem is an integer and non-convex optimization problem, a globally optimal solution is obtained by applying the polyblock outer approximation (POA) method based on the problem's hidden monotonic structure. Subsequently, for the general case considering the 3D UAV trajectory optimization, an efficient iterative algorithm is proposed to alternately optimize the divided sub-problems based on the successive convex approximation (SCA) technique. Numerical results demonstrate that the proposed design is able to achieve significant system throughput gain over the benchmarks. In addition, the SCA-based method can achieve nearly the same performance as the POA-based method with much lower computational complexity

High-Torque-Density Low-Cost Magnetic Gear Utilizing Hybrid Magnets and Advanced Materials

Two major challenges of existing high-performance magnetic gears are: (i) High content of rare-earth permanent magnets which results in high cost as well as price fluctuation; (ii) Conflict between mechanical and electromagnetic performances, especially in the design of highspeed rotor. A magnetic gear using a blend of magnet types, i.e NdFeB, or Dy-free NdFeB and ferrites, is proposed in this paper. The goal is to bring down the cost while retaining comparable torque-transducing performance to a baseline magnetic gear only using rare-earth NdFeB magnets. A variety of topologies based on different combinations of magnet types and geometric shapes have been studied and compared. In addition, the potential impact of using an advanced dual-phase material is evaluated. The goal is to eliminate the well-known tradeoff between rotor mechanical integrity and PM flux leakage

Throughput Maximization for UAV-Aided Backscatter Communication Networks

This paper investigates unmanned aerial vehicle (UAV)-aided backscatter communication (BackCom) networks, where the UAV is leveraged to help the backscatter device (BD) forward signals to the receiver. Based on the presence or absence of a direct link between BD and receiver, two protocols, namely transmit-backscatter (TB) protocol and transmit-backscatter-relay (TBR) protocol, are proposed to utilize the UAV to assist the BD. In particular, we formulate the system throughput maximization problems for the two protocols by jointly optimizing the time allocation, reflection coefficient and UAV trajectory. Different static/dynamic circuit power consumption models for the two protocols are analyzed. The resulting optimization problems are shown to be non-convex, which are challenging to solve. We first consider the dynamic circuit power consumption model, and decompose the original problems into three sub-problems, namely time allocation optimization with fixed UAV trajectory and reflection coefficient, reflection coefficient optimization with fixed UAV trajectory and time allocation, and UAV trajectory optimization with fixed reflection coefficient and time allocation. Then, an efficient iterative algorithm is proposed for both protocols by leveraging the block coordinate descent method and successive convex approximation (SCA) techniques. In addition, for the static circuit power consumption model, we obtain the optimal time allocation with a given reflection coefficient and UAV trajectory and the optimal reflection coefficient with low computational complexity by using the Lagrangian dual method. Simulation results show that the proposed protocols are able to achieve significant throughput gains over the compared benchmarks

K-means based cluster analysis of residential smart meter measurements

A clustering module based on the k-means cluster analysis method was developed. Smart meter based residential load profiles were used to validate the clustering module. Several case studies were implemented using daily and segmented load profiles of individual and aggregated smart meters. Simulation results defined in terms of the relationship between the clustering ratio and the segmentation time window reveal that the minimum clustering ratio is obtained for the shortest time window of segmentation. Results also show that a small number of clusters is recommended for highly correlated load profiles

Implementation of an effective time-saving two-stage methodology for microstructural characterization of cemented carbides

Linear intercept on scanning electron microscopy micrographs is the most commonly used measurement method to determine carbide grain size and contiguity in WC–Co cemented carbides (hardmetals). However, it involves manual time-consuming measurements and is critically dependent on the quality of the micrographs as well as on the identification and definition of grain boundaries. In this study a two-stage methodology for microstructural characterization of hardmetals is presented. First, a digital semi-automatic image analysis procedure for grain size determination of the carbide phase is presented. It involves an experimental assessment of grain size on processed images corresponding to a series of WC–Co and WC–Ni cemented carbide grades with different microstructural characteristics. Obtained results are then compared to the values obtained by means of the linear intercept technique. A good correlation between the mean grain sizes determined following both measurement techniques was attained. Based on experimental findings, a series of empirical relations were found to correlate grain size distributions obtained following both methods. Second, an empirical relation for estimating carbide contiguity in WC–Co cemented carbides is proposed. This relation considers simultaneously the influence of the binder content and the experimentally determined mean grain size on contiguity. The proposed equation for contiguity estimation is based on extensive data collection from open literature. An excellent agreement was attained between contiguity values estimated from such equation and those obtained using the linear intercept technique. This validates the two-stage procedure as an effective time-saving methodology for microstructural characterization of WC–Co cemented carbides.Peer ReviewedPostprint (author's final draft