Energy Minimization Techniques Research Articles

Performance analysis of cluster based homogeneous sensor network using energy efficient N-policy (EENP) model

A wireless sensor network (WSN) consists of a large number of sensor nodes deployed over a geographical area and have broad applications like environment monitoring, target tracking and surveillance. The unique characteristics of WSNs such as limited bandwidth, computing capacity, data delivery delay and severe energy constraints make their design more challenging. A critical issue in WSN is the limited availability of energy and hence optimizing energy is very important. This paper proposes an energy minimization technique based on queue threshold using N-policy M / M / 1 queueing model of a sensor node in a cluster acting as cluster member (CM) and cluster head (CH). We develop an analytical model of a cluster based sensor network based on queue threshold using N-policy M / M / 1 queueing model. The performance of the proposed model is analysed in terms of average energy consumption and mean delay when the node acts as CM and CH. We also derive the expression for the optimal value of queue threshold (N*) for which the node consumes minimum energy. Results show that the average energy consumption savings is high when the node acts as CH when compared to node acting as CM and the trade-off exist between the average energy consumption and mean delay is explored. We perform simulations and the results obtained show that the simulation results match with the analytical results thus validating the accuracy of the approach.

Thermodynamic optimization of coal-biomass co-gasification process by using non-stoichiometric equilibrium modeling

Co-gasification of coal and biomass improves the gasification process by reducing the amount of tar generated and also produces a low carbon footprint on the environment. In this study, Chemical Equilibrium with Applications (CEA), a non-stoichiometric equilibrium simulation tool, developed by NASA, based on Gibbs free energy minimization technique has been used to study the thermodynamic optimization of coal-biomass co-gasification process. Simulation of the co-gasification process has been done to evaluate the product gases from gasification process for various coal-biomass mixtures at different equivalence ratios and temperatures. The simulation results show that as the gasification temperature increases, CO molar fraction increases for a particular equivalence ratio and reverse is the trend for CO2. Again, the CO molar fraction increases with a decrease in equivalence ratio for all the gasification temperature and reverse in case of CO2. The study also observed that as the percentage of coal increases in the fuel mixture, mole fraction of CO increases at a particular equivalence ratio with the increase in temperature. However, a reverse trend is observed in case of CO2. The mole fraction of H2 decreases with the increase in coal percentage for all gasification temperature for a particular equivalence ratio.

First law energy analysis of thermochemical waste-heat recuperation by steam methane reforming

Thermochemical recuperation of waste flue gas heat may be advantageous for improving energy efficiency of hydrocarbon fuel-consuming furnace. The schematic diagram of thermochemical recuperation (TCR) by steam methane reforming is described. Thermodynamics equilibrium analysis of steam methane reforming (SMR) process has been investigated via Gibbs free energy minimization technique to determine the effects of pressure, inlet steam-to-methane ratio and temperature on TCR efficiency. The energy analysis was carried out for temperature range and steam-to-methane ratio of 600–1300 K and 1–6, respectively, at different pressure of 1–20 bar. The results shown that TCR efficiency can be controlled for maximum energy efficiency by the operating pressure, temperature and various inlet feed stocks. The recuperation rate and heat balance of TCR were analyzed for different waste flue gas temperatures, steam-to-methane ratio at mixture inlet and pressure. For the effective operation of thermochemical recuperation it is necessary to use a pressure of less than 10 bar, because in this case the percentage by volume of non-combustible components in the synthesis gas is minimal. The optimal operation conditions for TCR were determined: steam-to-methane ratio is 2 for flue gas temperature 900–1100 K; steam-to-methane ratio is 1 for the temperature range above 1200 K; optimal pressure is 5–10 bar.

Two-phase fluid induced by N2 in metamorphic rocks

The first quantitative thermodynamic model of two-phase fluid induced by N2 and equilibrated with mineral assemblage in the system SiO2–TiO2–Al2O3–Fe2O3–MnO–MgO–CaO–Na2O–K2O–P2O5–H2O–CO2–N2 (STAFMMCNKPO–HCN) in the conditions of amphibolite facies rocks is proposed. Calculations are performed using the Gibbs free energy minimization technique. The fluid may consist of one phase, either aqueous solution (AS) or fluid with gas-like properties (FG), and also these two fluid phases (AS+FG) may co-exist, depending upon nitrogen content in the system. The values of total nitrogen at which AS co-exists with FG in the fluid were calculated at carbon saturation over a range in pressure and temperature of 3–7kb and 550–650°C. The model is capable of accurately describing various parameters of two fluid phases at each step of nitrogen increment in the system: density, partial pressure and mole fraction of constituents, pH, Eh, concentration of aqueous species. Increments of such an inert component as nitrogen cause the changes in the fluid resulting into subtle quantitative re-distribution of mineral phases in the assemblage plagioclase–biotite–quartz–ilmenite–garnet–apatite–graphite plus minor sillimanite and andalusite.

An Efficient Computational Approach for the Detection of MR Brain Tissues in the Presence of Noise and Intensity Inhomogeneity

The automatic detection of brain tissues such as White Matter (WM), Gray Matter (GM), and Cerebrospinal Fluid (CSF) from the MR images of the brain using segmentation is of immense interest for the early detection and diagnosing various brain-related diseases. MR imaging technology is one of the best and most reliable ways of studying the brain. Segmentation of MR images is a challenging task due to various artifacts such as noise, intensity inhomogeneity, partial volume effects and elemental texture of the image. This work proposes a region based, efficient and modern energy minimization process called as Anisotropic Multiplicative Intrinsic Component Optimization (AMICO) for the brain image segmentation in the presence of noise and intensity inhomogeneity to separate different tissues. This algorithm uses an efficient Anisotropic diffusion filter to decrease the noise. The denoised image gets segmented after the correction of intensity inhomogeneity by the MICO algorithm. The algorithm decomposes the MR brain image as two multiplicative intrinsic components, called as the component of the true image which represents the physical properties of the brain tissue and the component of bias field that is related to intensity inhomogeneity. By optimizing the values of these two components using an efficient energy minimization technique, correction of intensity inhomogeneity and segmentation of the tissues can be achieved simultaneously. Performance evaluation and the comparison with some existing methods have validated the remarkable performance of AMICO in terms of efficiency of segmentation of brain images in the presence of noise and intensity inhomogeneity.

Speeding Up Micromagnetic Simulation by Energy Minimization With Interpolation of Magnetostatic Field

An energy minimization technique with interpolation of magnetostatic field for micromagnetic simulation is proposed. This interpolation method reduces the number of evaluations of the magnetostatic field, which is the most time-consuming process in micromagnetic simulation. The interpolation does not change the M-H curves of the multigrain permanent magnets. The simulation results show that the present method accelerates micromagnetic simulation by a factor of up to 43 compared to the integration of the Landau-Lifshitz-Gilbert equation while maintaining the accuracy of the coercivity estimation.

Increasing the energy efficiency of microcontroller platforms with low-design margin co-processors

Reducing the energy consumption in low cost, performance-constrained microcontroller units (MCU’s) cannot be achieved with complex energy minimization techniques (i.e. fine-grained DVFS, Thermal Management, etc), due to their high overheads. To this end, we propose an energy-efficient, multi-core architecture combining two homogeneous cores with different design margins. One is a performance-guaranteed core, also called Heavy Core (HC), fabricated with a worst-case design margin. The other is a low-power core, called Light Core (LC), which has only a typical-corner design margin. Post-silicon measurements show that the Light core has a 30% lower power density compared to the Heavy core, with only a small loss in reliability. Furthermore, we derive the energy-optimal workload distribution and propose a runtime environment for Heavy/Light MCU platforms. The runtime decreases the overall energy by exploiting available parallelism to minimize the platform’s active time. Results show that, depending on the core to peripherals power-ratio and the Light core’s operating frequency, the expected energy savings range from 10 to 20%.

Energy Efficiency for Clustered Heterogeneous Multicores

Heterogeneous multicore systems clustered in multiple Voltage Frequency Islands (VFIs) are the next-generation solution for power and energy efficient computing systems. Due to the heterogeneity, the power consumption and execution time of a task changes not only with Dynamic Voltage and Frequency Scaling (DVFS), but also according to the task-to-island assignment, presenting major challenges for power management and energy minimization techniques. This paper focuses on energy minimization of periodic real-time tasks (or performance-constrained tasks) on such systems, in which the cores in an island are homogeneous and share the same voltage and frequency, but different islands have different types and numbers of cores and can be executed at other voltages and frequencies. We present an efficient algorithm to minimize the total energy consumption while satisfying the timing constraints of all tasks. Our technique consists of the coordinated selection of the voltage and frequency levels for each island, together with a task partitioning strategy that considers the energy consumption of the task executing on different islands and at different frequencies, as well as the impact of the frequency and the underlying core architecture to the resulting execution time. Every task is then mapped to the most energy efficient island for the selected voltage and frequency levels, and to a core inside the island such that the workloads of the cores in a VFI are balanced. We experimentally evaluate our technique and compare it to state-of-the-art solutions, resulting in average in 25 percent less energy consumption (and up to 87 percent for some cases), while guaranteeing that all tasks meet their deadlines.

Chemical exergy of electrochemical cell anolytes of cupric/cuprous chlorides

In this paper, the chemical exergy of the anolyte in the copper–chlorine water splitting cycle of hydrogen production is analyzed for relevant speciation. The speciation refers to the anolyte composition in terms of concentration of various ionic and neutral species at thermodynamic equilibrium within the electrolyte. The anolyte is the electrolyte circulated through the anode of the hydrogen-generating electrochemical cell. It is a strong aqueous electrolyte formed of hydrochloric acid, cupric chloride and cuprous chloride. The anolyte forms a complex speciation due to its high ionic strength. This makes the chemical exergy difficult to calculate as it is dependent on the anolyte speciation in actual conditions. Chemical exergy is an important parameter for system analysis and assessment according to the second law of thermodynamics. The results include an extended anolyte speciation range of copper II fractions from zero to 10% in 10 molal HCl and 2 molal CuCl constraints. A Gibbs energy minimization technique is formulated and examined for standard temperature. The most relevant ionic species in these conditions is CuCl32−(aq) whereas the copper anions are assumed negligible. The chemical exergy of anolyte varies in a narrow range with an average of 14.09 MJ/mol. The ionic species which contributes most to the anolyte Gibbs free energy of formation and thus to the chemical exergy is the dissociated hydrochloric acid followed by copper I ion CuCl32−(aq).

Identification of hydrothermal alteration zones of the Baogutu porphyry copper deposits in northwest China using ASTER data

Remote sensing technology plays a vital role in the initial stages of ore deposits exploration, with special significance in arid and semiarid regions. Advanced spaceborne thermal emission and reflection radiometer (ASTER) creates opportunities for geologists and many researchers to study the extraction of hydrothermal alterations of the porphyry copper and epithermal gold deposits. ASTER data were used to map distribution of hydrothermal alteration of deposits in the Baogutu region which is located in western Junggar, Xinjiang, China, including Baogutu II and Baogutu V deposits. Band ratio logical operator (BRLO), principal component analysis (PCA), mixture-tuned matched-filtering (MTMF), and constrained energy minimization (CEM) techniques were used for detailed hydrothermal alteration mapping. The alteration zones were identified using BRLO and PCA. The minerals subject to alteration were extracted by MTMF and CEM. The results were validated through field observation, spectral measurements, and petrographic studies. By comparing the extraction results and accuracy rates of four methods, CEM boasts the highest accuracy and identifies the altered minerals corresponding to three types of alterations at accuracy of over 80%. The identifying result of CEM method indicates that the prospect areas that were located in the southeast part of the Baogutu II rocks and in the southwest part of the Baogutu V rocks are valuable for further exploration.

Joint Head Pose/Soft Label Estimation for Human Recognition In-The-Wild.

Soft biometrics have been emerging to complement other traits and are particularly useful for poor quality data. In this paper, we propose an efficient algorithm to estimate human head poses and to infer soft biometric labels based on the 3D morphology of the human head. Starting by considering a set of pose hypotheses, we use a learning set of head shapes synthesized from anthropometric surveys to derive a set of 3D head centroids that constitutes a metric space. Next, representing queries by sets of 2D head landmarks, we use projective geometry techniques to rank efficiently the joint 3D head centroids/pose hypotheses according to their likelihood of matching each query. The rationale is that the most likely hypotheses are sufficiently close to the query, so a good solution can be found by convex energy minimization techniques. Once a solution has been found, the 3D head centroid and the query are assumed to have similar morphology, yielding the soft label. Our experiments point toward the usefulness of the proposed solution, which can improve the effectiveness of face recognizers and can also be used as a privacy-preserving solution for biometric recognition in public environments.

The effect of CO2 and N2 on phase relations, fluid composition, and quartz solubility in amphibolite facies metamorphic rocks

Phase equilibria in the system SiO2–TiO2–Al2O3–Fe2O3–MnO–MgO–CaO–Na2O–K2O–P2O5–H2O–CO2–N2 are calculated to illustrate phase relations in amphibolite facies metasediments over a wide range of X[H2O–CO2–N2] conditions at 600 °C and 4.4 kb. Calculations are performed using the Gibbs free energy minimization technique. Results are presented in plots showing stable mineral assemblages as a function of total carbon in the system at varying water (\(a_{{{\text{H}}_{2} {\text{O}}}}\) = 1) content in the presence/absence of N2 in the fluid. The calculations indicate that the typical assemblage plagioclase—quartz—biotite—ilmenite—garnet—apatite is restricted to the rocks with CO2 saturation and \(X_{{{\text{H}}_{ 2} {\text{O}}}}\) higher than 60% in the fluid. Significant decrease in \(X_{{{\text{CO}}_{2} }}\) favors the stability of muscovite rather than garnet, whereas the decrease in \(X_{{{\text{H}}_{ 2} {\text{O}}}}\) leads to the stability of microcline over all range of \(X_{{{\text{CO}}_{2} }}\). This paper also presents the composition and parameters (pH, Eh) of the fluid equilibrated with mineral assemblage. It is shown that the presence of low concentrations of N2 causes the fluid to consist of two phases when an aqueous supercritical solution (AS) coexists with a supercritical fluid with gas-like properties (SF). At high concentration of N2, the fluid consists of SF alone; in the absence of nitrogen, the fluid consists of AS alone. The solubility of monomer SiO20 and dimer Si2O40 decreases with increasing CO2 and after CO2 saturation point is held constant. The magnitude of the silica solubility at CO2 saturation depends upon the water content in AS. The effect of nitrogen on quartz solubility has been demonstrated to be negligible.

Atomistic simulations of symmetrical low-angle [100] (01l) tilt boundaries in SrTiO3

The structural properties of symmetrical low-angle [100] (01l) tilt grain boundaries in the perovskite oxide SrTiO3 were investigated by empirical pair potentials and energy minimisation techniques. Thirteen interfaces with misorientation angles varying between θ = 3° and θ = 22.6° were studied in both stoichiometric and oxygen deficient forms. Examination of the relaxed simulation cells indicated that all the studied grain boundaries consisted of some combination of two different types of dislocation core. The structures of the two types of dislocation core remain unchanged at low misorientation angles but become increasingly distorted at the highest angles examined. Simple rules were derived to predict the type, arrangement and alignment of the dislocations at a given interface.

Comparative analysis of multiple target tracking methods

Many applications such as intelligent transportation, video surveillance, robotics of computer vision mainly depend on task of multiple object tracking. It includes the process of detection, classifications and tracking. The main focus of the study is to develop an efficient and effective multiple target tracking methods to solve the issues of illumination changes, occlusions and affinity matching. Accordingly, the various multiple target tracking methods are tested and evaluated using the metrics on publicly available datasets from which it is obvious that the outcome of the global energy minimization and optimization techniques is comparatively better than any other existing techniques in all aspects. This comparative study work will also help in better understanding of the problem, knowledge of the methods and experimental evaluation skill for further research works.

Teaching the Concept of Gibbs Energy Minimization through Its Application to Phase-Equilibrium Calculation

Robust and fast methods for chemical or multiphase equilibrium calculation are routinely needed by chemical-process engineers working on sizing or simulation aspects. Yet, while industrial applications essentially require calculation tools capable of discriminating between stable and nonstable states and converging to nontrivial solutions, students are often introduced to the simplest and less efficient equilibrium-calculation methods. In this article, the Gibbs energy minimization technique is presented as a robust alternative way to perform phase-equilibrium calculations and is applied to the determination of 2-fluid phase equilibria in low-pressure binary systems. It is carefully explained how the combination of this technique with an efficient quasi-global minimization method makes it possible to derive a robust PT-flash algorithm. In the frame of project-based learning devoted to develop a tool for building complex phase diagrams, this approach was successfully tested with a group of 100 students.

Automated detection and classification of nuclei in PAX5 and H&E-stained tissue sections of follicular lymphoma

In this paper, we propose a novel framework for the detection and classification of centroblasts (CB) in follicular lymphoma (FL) tissue samples stained with PAX5 and H&E stains and sliced at 1 \(\upmu \)m thickness level. By employing PAX5 immunohistochemistry, we facilitate the segmentation of nuclei, while the use of H&E stain enables us to extract textural information related to histological characteristics used by pathologists in the diagnosis of FL grading. For the segmentation of nuclei in PAX5-stained images, we initially apply an energy minimization technique based on graph cuts and then we propose a novel algorithm for the separation of overlapped nuclei inspired by the clustering of large-scale visual vocabularies. The morphological characteristics of nuclei extracted from PAX5-stained images are combined with a number of textural characteristics identified in H&E images through a Bayesian network classifier, which aims to model pathologists’ knowledge used in FL grading. Experimental results have already shown the great potential of the proposed methodology providing an average F-score of \(94.56\,\%\).

Dense Projection Tomography on the Triangular Tiling

In this paper, we consider the binary tomography reconstruction problem. A new ap- proach is proposed what exploits a possibility provided by the natural structure of the triangular grid, which is not available in the case of the classical square grid. In contrast to the square grid, in the case of the triangular grid information need for the reconstruction of the unknown image is increasing when not only one, but two projections are used by lanes. In this way, the number of 4 andr shaped pixels per lane can be determined. We propose this type of projection approach and call it dense projections. The reconstruction is based on three projection directions by the lane directions of the grid (they are analogous to row and column directions on the square grid). Our algorithm is deterministic and uses energy minimization technique to find (near) optimal solution in a reasonable time. The experimental evaluation of the new method, using regular hexagon shaped test images, is given. Comparison with reconstructions based on the square grid is also considered.

Doping effect on the structural properties of Cu1−x(Ni, Zn, Al and Fe)xO samples (0

In this work, the effect of insertion of transition metal, TM (=Ni, Zn, Al and Fe), ions in Cu1−xTMxO samples (0<x<0.10) prepared via co-precipitation method is studied through experimental and computational methods. The analyses of X-ray diffraction (XRD) patterns using Rietveld refinement show that i) at x=0, all samples present a monoclinic crystal system with space group C2/c and ii) for increasing the TM-doping, Ni and Zn-doped samples show a small amount of spurious phases for concentrations above x=0.05. Based on these results, a defect disorder study for using atomistic computational simulations which is based on the lattice energy minimization technique is employed to predict the location of the dopant ions in the structure. In agreement with XRD data, our computational results indicate that the trivalent (Al and Fe ions) are more favorable to be incorporated into CuO matrix than the divalent (Ni and Zn ions).

New spiral state and skyrmion lattice in 3D model of chiral magnets

We present the phase diagram of magnetic states for films of isotropic chiral magnets (ChMs) calculated as function of applied magnetic field and thickness of the film. We have found a novel magnetic state driven by the natural confinement of the crystal, localized at the surface and stacked on top of the conical bulk phase. This magnetic surface state has a three-dimensional (3D) chiral spin-texture described by the superposition of helical and cycloidal spin spirals. This surface state exists for a large range of applied magnetic fields and for any film thickness beyond a critical one. We also identified the whole thickness and field range for which the skyrmion lattice becomes the ground state of the system. Below a certain critical thickness the surface state and bulk conical phase are suppressed in favor of the skyrmion lattice. Unraveling of those phases and the construction of the phase diagram became possible using advanced computational techniques for direct energy minimization applied to a basic 3D model for ChMs. Presented results provide a comprehensive theoretical description for those effects already observed in experiments on thin films of ChMs, predict new effects important for applications and open perspectives for experimental studies of such systems.

A Size-Dependent Thermodynamic Model for Coke Crystallites: The Carbon-Sulfur System Up to 2500 K (2227 °C)

A model is presented for the development of the thermodynamic functions of enthalpy, entropy, and Gibbs energy for the elements carbon and sulfur in coke crystallites. The crystallites of various degrees of graphitization may be described by crystallite length L a and crystallite height L c. This carbon/sulfur model has been developed using concepts similar to those in the carbon/hydrogen model for coke crystallites. The major model parameters are derived from reported thermodynamic properties. Approximately 75 pct of the model parameters for the carbon/hydrogen and carbon/sulfur system are parameters common to both systems. The resulting crystallite size (L a) constrained in the carbon/sulfur phase diagram, computed by a Gibbs energy minimization technique, is presented for 1 atm and temperatures between 1500 K and 2500 K (1227 °C and 2227 °C). A very good agreement is obtained between the predicted thermal desulfurization of petroleum cokes and critically assessed experimental data. The removal of sulfur from coke crystallites is predicted to occur mostly between 1600 K and 1850 K (1327 °C and 1577 °C) at 1 atm, depending on the L a value. The precision in the predictive calculations and the transferability of the model parameters are two aspects that tend to support the usefulness and the theoretical basis of the entire approach.