Unimorph and bimorph piezoelectric energy harvester stimulated by β-emitting radioisotopes: a modeling study

We use energy methods and lumped-element modelling in the analysis and optimization of a miniaturized aluminum nitride based piezoelectric energy harvester which utilizes tritiated silicon as an uninterrupted energy source. Tritiated silicon serves as a radioisotope source which emits energetic β particles that results in an electrostatic force between the radioactive source and collector that traps the emitted particles. The generated electrostatic force will drive the charging and actuating cycles of the piezoelectric cantilever leading to a continuous charge–discharge cycles, thus inducing vibrations in the piezoelectric cantilever. The energy generated from the piezoelectric thin-film is appropriately rectified and stored to provide continuous and uninterrupted electrical power to a low-power devices. The modelled results have been benchmarked against available experimental data for a unimorph piezoelectric harvester with very good agreement. Furthermore, the model was applied to a bimorph piezoelectric harvester, showing that the output power can be doubled in relation to a unimorph design. Moreover, the model accounts for the entire range of design and operating factors such as the ambient medium and associated damping losses, current leakage, and device scaling.     

Optimal energy consuming planning for a home‑based microgrid with mobility constraint of electric vehicles and tractors

This research deals with the energy management problem to minimize the cost of non-renewable energy for a small-scale microgrid with electric vehicles (EV) and electric tractors (ET). The EVs and ETs function as batteries in the power system, while they often have to leave it for their mobility and agricultural work. Each State of Charge (SoC), which is the charge rate of the battery from 0 to 1, and the operating time of ETs are optimized under the assumption that the required electrical energy, the arrival and departure time of EVs, and the working time of ETs are given by users, but they include uncertainties. In this paper, we deal with these uncertainties by constraints for robust energy planning and expected optimization based on scenarios, and show that the scheduling of the SoC assuming the worst case and the optimal home-based power consumption planning that considers the cost of each scenario corresponding to each variation can be obtained. Our proposed method is formulated as a mixed integer linear programming (MILP), and numerical simulations show that the optimal cooperative operation among multiple houses can be obtained and its global optimal or sub-optimal solution can be quickly obtained by using CPLEX.     

Tradeoffs between energy consumption and QoS in mobile grid

Mobile grid, which combines grid and mobile computing, supports mobile users and resources in a seamless and transparent way. However, mobility, QoS support, energy management, and service provisioning pose challenges to mobile grid. The paper presents a tradeoff policy between energy consumption and QoS in the mobile grid environment. Utility function is used to specify each QoS dimension; we formulate the problem of energy and QoS tradeoff by utility optimization. The work is different from the classical energy aware scheduling, which usually takes the consumed energy as the constraints; our utility model regards consumed energy as one of the components of measure of the utility values, which indicates the tradeoff of application satisfaction and consumed energy. It is a more accurate utility model for abstracting the energy characteristics and QoS requirement for mobile users and resources in mobile grid. The paper also proposes a distributed energy–QoS tradeoff algorithm. The performance evaluation of our energy–QoS tradeoff algorithm is evaluated and compared with other energy and deadline constrained scheduling algorithm.     

Improved multi-processor scheduling for?flow time and?energy

Energy usage has been an important concern in recent research on online scheduling. In this paper, we study the tradeoff between flow time and energy (Albers and Fujiwara in ACM Trans. Algorithms 3(4), 2007; Bansal et al. in Proceedings of ACM-SIAM Symposium on Discrete Algorithms, pp. 805–813, 2007b, Bansal et al. in Proceedings of International Colloquium on Automata, Languages and Programming, pp. 409–420, 2008; Lam et al. in Proceedings of European Symposium on Algorithms, pp. 647–659, 2008b) in the multi-processor setting. Our main result is an enhanced analysis of a simple non-migratory online algorithm called CRR (classified round robin) on m≥2 processors, showing that its flow time plus energy is within O(1) times of the optimal non-migratory offline algorithm, when the maximum allowable speed is slightly relaxed. The result still holds even if the comparison is made against the optimal migratory offline algorithm. This improves previous analysis that CRR is O(log P)-competitive where P is the ratio of the maximum job size to the minimum job size.     

The computational energy spectrum of a program as it executes

This paper describes how to interpret a program’s performance in terms of its computational energy spectrum. High spikes in the spectrum correspond to important events during execution, such as cache misses, for example, and their positions show when they happen and how they effect other events. The area under the spectrum measures a program’s size in terms of the computational action norm, a measure of how efficiently it moves through computational phase space. The distance from one program to another is the area between their action curves. The measured energy spectra for a set of real programs executing on real hardware support the conjecture that the best program generates the least action, the Principle of Computational Least Action.     

Information transmittal,principle of relativity and mass–energy relation

Relativistic transformations and their application to electrodynamics of a weakly accelerated electron considered in [A. Einstein, Zur Elektrodynamik der bewegter Körper, Annalen der Physik, 17 (1905) 891–921] are further analyzed in their relation to the principle of relativity, the concept of mass, and the mass–energy equation. Alternative consideration in dynamics of weakly accelerated electrons demonstrates that the factors in longitudinal $\mu {\beta }^3$ and transverse $\mu {\beta }^2$ masses of an electron with the mass $\mu$ at rest naturally appear in observed accelerations as a result of relativistic transformations, without any deviation from the principle of relativity and the second Newton’s law of motion. As concerns the special relativity in accelerated motion, this allows us to retain the concept of mass as scalar characteristic of an accelerated body. It is argued that “the principle of equivalence of the mass and energy of rest” (Einstein) depends on the speed of the information transmitting signal by which the observation (measurement) is made (synchronization of clocks is achieved), so that relativistic equation $E=m{c}^2$ appears as an image phenomenon which essentially depends on the propagation of light as a measuring signal and on its speed $V=c$ as the critical parameter of Einstein’s relativistic transformations. It is demonstrated that the spherical waves considered by Einstein are distorted in real time, and the fundamental Lorentz invariant is not crisp, but presents a soft interval whose diameter is in the range of 30,000 km for time delays of 0.1 s in transmission of information. The results open new avenues for further research in the theory of relativity and its applications.     

Electrical energy quality: Modeling and H<Superscript>∞</Superscript> control of a three-phase shunt active filter

The main contribution of the paper is the modeling approach used to describe a pure threephase shunt active filter, and the application of the H^∞ control design tool in order to improve the quality of electrical energy. Advanced power electronics devices have widely contributed to the degradation of power quality due to the injection of non-sinusoïdal currents into the utility system. Therefore, it is essential to use an active compensator which can attenuate current harmonics to an acceptable level on the line side of the power source. In this work, a three-phase active filter connected in parallel to a supply system feeding a non-linear load is described, in a complex framework, by a linear multivariable state space representation in order to guarantee that the system is mathematically decoupled and therefore to simplify the controller design. This representation includes a sensor to measure perturbations, and allows one to calculate a linear robust control law. The originality of this paper is that a Linear Matrix Inequality based H^∞ synthesis is performed to design a static state feedback controller with complex-valued parameters. The robustness of this controller with respect to network impedance uncertainties is investigated. Moreover, simulation and experimental results are given to reveal the effectiveness of the synthesized control law.     

The bounded energy optimal control for a class of distributed parameter systems†

The bounded energy optimal control for one-dimensional linear stationary distributed parameter system is solved here. The criterion function is a quadratic functional of the output.

Obtaining the optimal control involves the computation of the solution of a certain non-linear integral equation. The method of solving this integral equation is approximating the kernel of the integral operator by a sequence of degenerate kernels. It is shown that the sequence of approximate solutions of the approximate integral equations converges to the optimal solution; and that the sequence of approximate values of the criterion, converges to the optimal value of the criterion.     

Coverage control in constant flow environments based on a mixed energy–time metric

In this paper, we study a multi-vehicle coverage control problem in constant flow environments while taking into account both energy consumption and traveling time. More specifically, the metric (called the mixed energy–time metric) is a weighted sum of the energy consumption and the traveling time for a vehicle to travel from one point to another in constant flows when using the minimum energy control, and the objective is to find vehicle locations that can minimize the expected mixed energy–time required for the set of vehicles to cover a region. We propose a gradient based control law which is calculated based on refined approximated Voronoi cells (induced by the mixed energy–time metric) and of which the convergence is proved via Hybrid Systems Theory. Simulations show that the refined gradient based control can achieve similar performance as the exact gradient based control.     

Kilowhat? A multidisciplinary approach on the development of a home energy management system

To a consumer, knowing how much energy you use is often a question mark. We get our energy bills and more often than not, they are surprisingly high. The coming of the smart grid and more specifically smart metering provides opportunities to create a better awareness on energy use among consumers. This research presents the user-centric development of a home energy management system. The focus of the research is not specifically on the functionalities per se, rather it lies on the inclusion of the energy end-user in the development process. Throughout the development, end-user research provided valuable input for the development of the system. Large quantitative surveys were alternated with small scale in-depth qualitative research. Each step generated the input for the next step in the research process, resulting in a system with functionalities tailored to the end-users needs and wants.     

Using thermodynamic integration MD simulation to compute relative protein–ligand binding free energy of a GSK3β kinase inhibitor and its analogs

Thermodynamic integration molecular dynamics simulation was used to investigate how TI-MD simulation preforms in reproducing relative protein–ligand binding free energy of a pair of analogous GSK3β kinase inhibitors of available experimental data (see Fig. 1), and to predict the affinity for other analogs. The computation for the pair gave a ΔΔG of 1.0 kcal/mol, which was in reasonably good agreement with the experimental value of −0.1 kcal/mol. The error bar was estimated at 0.5 kcal/mol. Subsequently, we employed the same protocol to proceed with simulations to find analogous inhibitors with a stronger affinity. Four analogs with a substitution at one site inside the binding pocket were the first to be tried, but no significant enhancement in affinity was found. Subsequent simulations for another 7 analogs was focused on substitutions at the benzene ring of another site, which gave two analogs (analogs 9 and 10) with ΔΔG values of −0.6 and −0.8 kcal/mol, respectively. Both analogs had a OH group at the meta position and another OH group at the ortho position at the other side of the benzene ring, as shown in Table 3. To explore further, another 4 analogs with this characteristic were investigated. Three analogs with ΔΔG values of −2.2, −1.7 and −1.2 kcal/mol, respectively, were found. Hydrogen bond analysis suggested that the additional hydrogen bonds of the added OH groups with Gln185 and/or Asn64, which did not appear in the reference inhibitor or as an analog with one substitution only in the examined cases, were the main contributors to an enhanced affinity. A prediction for better inhibitors should interest experimentalists of enzyme and/or cell assays. Analysis of the interactions between GSK3β kinase and the investigated analogs will be useful in the design of GSK3β kinase inhibitors for compounds of this class.     

Using information systems to improve energy efficiency: Do smart meters make a difference?

The large-scale generation of electricity is a major contributor to increasing levels of greenhouse gas emissions, putting pressure on the industry to reduce its environmental impacts. Electricity utility companies are looking to two strategies to help make this happen: the smart grid and demand-side management. Viewing the challenge from an IS perspective, this study attempts to answer the question: do smart grid information systems and technologies make a difference in utilities’ efforts to promote energy efficiency? Drawing on organizational information processing theory and extending it by integrating the concept of information waste, two competing hypotheses are developed and tested using hierarchical regression and data from 543 U.S. electricity utilities. The model, incorporating four levels of metering devices, is found to explain a high portion of the variance in energy efficiency effects of demand-side management programs. This suggests that there are IS-enabled information processing capacities within smart meters that have a significant influence on utilities’ EDM effectiveness. However, the results also point to the potential for both positive and negative effects. Implications of these findings for practice and future research directions are discussed.     

Improving performance and energy efficiency of embedded processors via post-fabrication instruction set customization

Encapsulating critical computation subgraphs as application-specific instruction set extensions is an effective technique to enhance the performance and energy efficiency of embedded processors. However, the addition of custom functional units to the base processor is required to support the execution of custom instructions. Although automated tools have been developed to reduce the long design time needed to produce a new extensible processor for each application, short time-to-market, significant non-recurring engineering and design costs are issues. To address these concerns, we introduce an adaptive extensible processor in which custom instructions are generated and added after chip-fabrication. To support this feature, custom functional units (CFUs) are replaced by a reconfigurable functional unit (RFU). The proposed RFU is based on a matrix of functional units which is multi-cycle with the capability of conditional execution. To generate more effective custom instructions, they are extended over basic blocks and hence, multiple-exits custom instruction and intuition behind it are introduced. Conditional execution capability has been added to the RFU to support the multi-exit feature of custom instructions. Because the proposed RFU has limitations on hardware resources (i.e., connections and processing elements), an integrated mapping-temporal partitioning framework is proposed to guarantee that the generated custom instructions can be mapped on the RFU (mappable custom instructions). Experimental results show that multi-exit custom instructions enhance the performance and energy efficiency by an average of 32% and 3% compared to custom instructions limited to one basic block, respectively. A maximum speedup of 4.9, compared to a single-issue embedded processor, and an average speedup of 1.9 was achieved on MiBench benchmark suite. The maximum and average energy saving are 56% and 22%, respectively. These performance and energy efficiency are obtained at the cost of 30% area overhead.     

Modeling and Analysis of a Trajectory-Based Stability

I.INTRODUCTION Recently,many emergency cases took places all over the world,such as the outbreaks of the plague named severe acute respiratory syndrome(SARS)[1]and the electrical network blackout in California[2]etc.In these large area catastrophic events,we don’t know the exact spreading mechanisms of the SARS virus or the exact electrical network faults in time;instead,all the on-line data of the practical systems are available.In the past decades,a lot of studies were made in the a…     

Order-α weighted information energy

We first give an expression for the amount of information supplied by a probabilistic experiment, whose elementary events are characterized by both their probabilities and some qualitative weights. This measure is called “order-α weighted information energy”, and it is a generalization of the weighted information energy given by Theodorescu and studied extensively by Pardo. Some properties and an axiomatic treatment of the measure are given.     

Method of predicting the position of the energy center of the image of a laser beam using a parallel–hierarchical network

This paper presents a prediction method using a parallel–hierarchical (PH) network and hyperbolic smoothing of empirical data. The average prediction error is 0.55% for the developed method and 1.62% for neural networks; therefore, this method is more efficient as applied to real-time systems than traditional neural networks due to the use of the PH network and hyperbolic smoothing in implementing the operation of predicting the positions of energy centers of laser beam spot images for optical communication systems.     

ε-Entropy and Fractal Dimension of a State for a Gaussian Measure

Kolmogorov introduced the concept of -entropy to analyze information in classical continuous systems. The fractal dimension of a geometric set was introduced by Mandelbrot as a new criterion to analyze the geometric complexity of the set. The -entropy and the fractal dimension of a state in a general quantum system were introduced by one of the present authors (MO) in order to characterize chaotic properties of general states.In this paper, we show that -entropy of a state includes Kolmogorov's -entropy, and that the fractal dimension of a state describes fractal structure of Gaussian measures.