Energy Map Research Articles

CNN-LSTM Hybrid model based human action recognition with skeletal representation using joint movements based energy maps

CNN-LSTM Hybrid model based human action recognition with skeletal representation using joint movements based energy maps

Hot Deformation Behaviors and Intrinsic Hot Workability Map of Ti-12Mo-4Zr-5Sn Alloy Based on Physical Model and Polar Reciprocity Model

The hot compression tests of Ti-12Mo-4Zr-5Sn alloy were tested on the thermo-mechanical simulator of Gleeble-3500 under isothermal and constant strain rate. We studied this alloy’s behavior during thermal deformation at the conditions of T = 670~820 °C, ε ˙ = 0.001~10 s−1, and deformation degree 70%. The rheological stress curves of the alloy were modified, the characteristics of the rheological stress curves were analyzed, and the activation energy map of hot deformation was established. A physical constitutive model of the alloy based on strain compensation was established, which has taken the relationship between Young’s modulus and self-diffusion coefficient and temperature into account. Moreover, the intrinsic hot workability ξ map of the alloy was established based on the polar reciprocity model. The results show that this alloy’s rheological stress will descend when the temperature of deformation rises and grow when the strain rate increases, and has negative sensitivity of temperature and positive sensitivity of strain rate. According to the error calculation, the physical constitutive model’s correlation coefficient is 0.9910 and the average relative error is 3.97%, which has good accuracy. Through the analysis of the microstructures of the instability zone and the stability zone, it was found that the instability mode of the instability zone was dominated by the local flow, and the deformation mechanism of the stability zone was dominated by the dynamic recrystallization. The optimum processing parameters of the alloy known from ξ map and metallographic structure are the following: T = 790~820 °C and ε ˙ = 0.001~0.01 s−1.

Green Synthesis of CuO nanoparticles via Plectranthus amboinicus leaves extract with its characterization on structural, morphological, and biological properties

Synthetic synthesis of nanoparticles is harmful to human and environment due to pollution. The use of harmful chemicals in synthetic method has avoided in the biosynthesis. To overcome the hurdles in synthesis of nanoparticles, the biogenic synthesis of CuO nanoparticles has been done with Plectranthus amboinicus leaf extracts. The biosynthesis provides the enhanced efficiency compared to synthetic methods. It establishes the environmentally friendly and pollution-free approach. The powder X-ray diffraction (XRD) pattern exhibited a crystalline nature with the crystallite size in 20–35 nm. The Fourier-Transform InfraRed (FTIR) spectrum explicated the Cu and O metal oxide bonds. The UV–visible analysis emphasized the stability of CuO nanoparticles with the inference of the Surface Plasmon Resonance band at 398 nm. The photoluminescence study displayed the bluish–green emission nature peak at 491 nm. The particle size analyzer manifested the synthesized CuO nanoparticles majority in 5–40 nm. The field-emission scanning electron micrographs (FESEM) and high-resolution transmission electron micrographs (HRTEM) exposed the spherical, circular-shaped nanoparticles with size in 5–30 nm range. The energy dispersive X-ray diffraction (EDAX) spectrum and mapping proved the CuO nanoparticles formation. The antimicrobial activity reported the potent nature of formed CuO nanoparticles on bacteria and fungi. The antioxidant activity identified the effective free-radical scavenging activity nature at 95% in 80 μg/mL and IC50 value at 40.10 μg/mL concentration. The anti-inflammatory activity assessed the efficient nature of CuO nanoparticles in protein denaturation of Egg albumin at 92% in 500 μg/mL and IC50 value at 243.08 μg/mL concentration. The anti-diabetic activity established the effective inhibition on α-Amylase at 94% in 500 μg/mL and IC50 value at 317.19 μg/mL concentration. The anti-larvicidal activity manifested the potent inhibition on Anopheles subpictus mosquito larvae within 24 h in 100 ppm concentration and which exhibited low LC50 value.

Building Energy-Cost Maps From Aerial Images and Ground Robot Measurements With Semi-Supervised Deep Learning

Planning energy-efficient paths is an important capability in many robotics applications. Obtaining an energy-cost map for a given environment enables planning such paths between any given pair of locations within the environment. However, efficiently building an energy map is challenging, especially for large environments. Some of the prior work uses physics-based laws (friction and gravity force) to model energy costs across environments. These methods work well for uniform surfaces, but they do not generalize well to uneven terrains. In this letter, we present a method to address this mapping problem in a data-driven fashion for the cases where an aerial image of the environment can be obtained. To efficiently build an energy-cost map, we train a neural network that learns to predict the complete energy maps by combining aerial images and sparse ground robot energy-consumption measurements. Field experiments are performed to validate our results. We show that our method can efficiently build an energy-cost map accurately even across different types of ground robots.

An Approach for the Retrieval of Land Surface Temperature from the Industrial Area Using Landsat-8 Thermal Infrared Sensors

The thermal imagine provides data with synoptic coverage for investigating thermal information from hot sources for detecting, mapping energy loss from the industrial area. This study attempts to retrieved heat loss from the industrial area using Landsat-8 TIRS experimented at an industrial area of Pasir Gudang, Peninsular Malaysia, the main objective is to investigate the sensitivity of Landsat-8 TIR for detecting industrial thermal energy within the various range of targets of different temperatures. An estimated heat map with absolute surface temperature values is the final output. Apart of the pre-processing of Landsat-8 TIRS data, data are processed for the retrieval of land surface temperature, then subjected to a downscaling process to final 30 x 30 m pixels, hence enable to merge with all Landsat-8 bands for visualization and validation of results. The split window algorithm (SWA) is used for the temperature retrieval from band 10 and 11, with other driven parameters. The Multiple Adaptive Regression Splines (MARS) model for spatial downscaling was adopted in this study. The generated thermal energy map was then validated over selected targets in the field and compared to corresponding downscaled MODIS LST product (MODIS11A2). TIR bands applied with SWA generated 13.7°C temperature dynamic range from 22.35˜51.36° C in comparison with MODIS LST product values range from 27.17 ˜ 37.65°C). Results indicated good agreement between the generated thermal energy map with the in-situ validations (RMSE=0.43 °C). It is therefore concluded that derived Land surface temperature map derived is suitable for study industrial thermal environment at 1:50,000 ˜ 100,000 scales, adequately to be used for environmental impact assessment.

Implementation of Nighttime Radiance Threshold Class for Green Zone Energy Mapping

Bali is the most excellent tourism resort through precious supporting facility. The structure creates with art that inspires from culture and blends with environment. The original concept is not much usable energy for conditioner and light. Modern and comport facilities are more attractive now. Electricity supply becomes issue. It is important to control uses of excessive energy that emitted carbon and cost. This paper presents results of radiance threshold method that can be used as a system to monitor above issue. The variability of light sources aspects that deplete energy had defined. Development of business support tourism privately is a key of this case. For sustainable of energy, a mutual agreement among stakeholder is urgency. Areas that define as class criteria spread widely, mostly at Kuta and Nusadua city. Development of moderate class light is key to understand spatial-temporal of dynamical many aspects that relate to urban cycles. Nocturnal light trend spread up to northern part of island. Notice for stakeholder to attention of diminishes green space. Long-term dynamical trend of nocturnal light requires inter calibration between nighttime satellite mission. The nonlinearity relationship of those data pays attentions to many factors. Possibility of model function approved a power model. Linearity validation results shows agreement.

Aeroelastic response of an airfoil to gusts: Prediction and control strategies from computed energy maps

A method to predict the aeroelastic pitch response of an airfoil to gusts is presented. The prediction is based on energy maps generated by high-fidelity fluid dynamic simulations of the airfoil with prescribed pitch oscillations. The energy maps quantify the exchange of energy between the pitching airfoil and the flow, and serve as manifolds over which the dynamical states of aeroelastic airfoil system grow, decay and attain stationary states. This method allows us to study the full nonlinear response of the system to large gusts, and predict the growth and saturation of aeroelastic pitch instabilities. We also show that the manifold topology in these maps can be used to make informed modifications to the system parameters in order to control the response to gusts.

Body mass, mercury exposure, biochemistry and untargeted metabolomics of incubating common eiders (Somateria mollissima) in three Baltic colonies

The Baltic/Wadden Sea Flyway of common eiders has declined over the past three decades. Multiple factors such as contaminant exposure, global warming, hunting, white-tailed eagle predation, decreased agricultural eutrophication and infectious diseases have been suggested to explain the decline. We collected information on body mass, mercury (Hg) concentration, biochemistry and untargeted metabolomics of incubating birds in two colonies in the Danish Straits (Hov Røn, n = 100; Agersø, n = 29) and in one colony in the Baltic proper (Christiansø, n = 23) to look into their metabolisms and energy balance. Body mass was available from early and late incubation for Hov Røn and Christiansø, showing a significant decline (25–30%) in both colonies with late body mass at Christiansø being the lowest. Whole blood concentrations of total mercury Hg were significantly higher in birds at Christiansø in the east compared to Hov Røn in the west. All birds in the three colonies had Hg concentrations in the range of ≤1.0 μg/g ww, which indicates that the risk of effects on reproduction is in the no to low risk category for wild birds. Among the biochemical measures, glucose, fructosamine, amylase, albumin and protein decreased significantly from early to late incubation at Hov Røn and Christiansø, reflecting long-term fastening as supported by the decline in body mass. Untargeted metabolomics performed on Christiansø eiders revealed presence of 8,433 plasma metabolites. Of these, 3,179 metabolites changed significantly (log2-fold change ≥1, p ≤ 0.05) from the early to late incubation. For example, smaller peptides and vitamin B2 (riboflavin) were significantly down-regulated while 11-deoxycorticosterone and palmitoylcarnitine were significantly upregulated. These results show that cumulative stress including fasting during incubation affect the eiders’ biochemical profile and energy metabolism and that this may be most pronounced for the Christiansø colony in the Baltic proper. This amplify the events of temperature increases and food web changes caused by global warming that eventually accelerate the loss in body weight. Future studies should examine the relationship between body condition, temperature and reproductive outcomes and include mapping of food web contaminant, energy and nutrient content to better understand, manage and conserve the populations.

Microstructural and morphological development of eggshell powder and flyash-based geopolymers

The microstructural and morphological development of eggshell powder (ESP) and flyash (FA)-based geopolymer, prepared using alkaline liquid activator which is a mixture of sodium silicate and sodium hydroxide solution, was investigated. Various synthesis parameters for geopolymer were adopted to study the microstructural changes viz. precursor combination (70% ESP and 30% FA, 50% ESP and 50% FA, 30% ESP and 70% FA), activator ratio (Na2SiO3/NaOH–0.5, 1, and 2) and curing temperature (25, 50, and 80 °C). Morphological features and structural characterization of raw precursor materials were analyzed using an X-ray diffractometer (XRD), X-ray fluorescent (XRF), and Scanning electron microscopy (SEM) techniques. The process of geopolymerization was explicated using SEM with an energy dispersive X-ray spectrometer (SEM-EDX) and mapping. Increase in curing temperature altered the morphology of ESP-FA geopolymer. Curing of samples at the lower temperature resulted in unreacted precursor particles, whereas curing at the higher temperature resulted in the porous structure. Formation of Nan–(–Si–O–Al–O–Si–O–Si–O–)n– was confirmed in the optimum geopolymer as Si/Al and Na/Al ratios were found greater than 1. The co-existence of calcium silicate hydrate (C-S-H) gel with the main geopolymeric gel and its bonding with the remaining unreacted precursor particles have also been confirmed.

A novel heuristic based energy efficient routing strategy in wireless sensor network

Wireless Sensor Network (WSN) is used in many applications for different roles, such as monitoring, data transmitting, information gathering, and so on. However, managing energy in WSN is a critical task. To end this issue several clustering and heuristic strategies were constructed still, a suitable solution is not found. So the current research proposed a novel African Buffalo based Two Tier Data Dissemination (AB-TTDD) strategy to monitor the energy drained node in an earlier stage before the data transmission. The fitness function of African Buffalo model is utilized to recognize the harmful and energy drained nodes in an earlier stage. Furthermore, a novel Temporary Energy Mapping Algorithm (TEMA) is developed to maintain the route by creating the reference node instead of energy drained node. This novel proposed mechanism has reduced the packet flow ratio and power consumption in a high manner. At the same time, it enhanced the energy intensity of sensor hubs by mounting its lifetime and affording the reroute. Subsequently, the capability of the proposed strategy is validated with the recent research works and achieved better performance by reducing energy consumption and packet drop ratio.

Optical frequency and phase information-based fusion approach for image rotation symmetry detection.

Detecting an object using rotation symmetry property is widely applicable as most artificial objects have this property. However, current known techniques often fail due to using single symmetry energy. To tackle this problem, this paper proposes a novel method which consists of two steps: 1) Based on an optical image, two independent symmetry energies are extracted from the optical frequency space (RSS - Rotation Symmetry Strength) and phase space (SSD - Symmetry Shape Density). And, an optimized symmetry-energy-based fusion algorithm is creatively applied to these two energies to achieve a more comprehensive reflection of symmetry information. 2) In the fused symmetry energy map, the local region detection algorithm is used to realize the detection of multi-scale symmetry targets. Compared with known methods, the proposed method can get more multiple-scale (skewed, small-scale, and regular) rotation symmetry centers, and can significantly boost the performance of detecting symmetry properties with better accuracy. Experimental results confirm the performance of the proposed method, which is superior to the state-of-the-art methods.

Evaluations of biosynthesized Ag nanoparticles via Allium Sativum flower extract in biological applications

The eco-friendly phytomediated synthesis of Ag nanoparticles provides better efficient applications than synthetic methods. Ag nanoparticles are considered by researchers due to its specific properties. The phytochemical analysis of Allium Sativum flower extract provides the phytochemicals exist in it. Due to this, the efficient eco-friendly synthesis of Ag nanoparticles via Allium Sativum flower extract has performed. The X-ray diffraction pattern exposes the crystalline nature with the mean crystallite size at 25 nm. The Fourier Transform Infra-Red spectrum displays the phytochemicals involved in the synthesis. The UV–Visible spectrum illustrates the formation of Ag nanoparticles with SPR band at 436 nm. The particle size analyzer demonstrates the size of formed Ag particles in 20–35 nm. The morphological, elemental and structural analyzes demonstrate the formation of spherical shaped Ag nanoparticles. The formation of Ag nanoparticles was confirmed by the appearance of Ag peak in Energy Dispersive X-ray Diffraction spectrum and mapping study. The antimicrobial activity explains the effective antimicrobial effect on human pathogens. The antioxidant activity reports the efficient scavenging property of synthesized Ag nanoparticles. The anti-inflammatory activity reveals the potential ability of protein denaturation on bovine serum albumin. The anti-diabetic activity exhibits much inhibition on α-Amylase. The anticancer activity reports the effective inhibition of synthesized Ag nanoparticles on human MCF-7 breast cancer cells.

Mapping of Least ρ-Dirichlet Energy between Doubly Connected Riemann Surfaces

In this note, we consider the mappings $$h:h:\mathbb{X}\rightarrow\mathbb{Y}$$ between doubly connected Riemann surfaces having least ρ-Dirichlet energy. For a pair of doubly connected Riemann surfaces, in which $$\mathbb{X}$$ has finite conformai modulus, we establish the following principle: A mapping h in the class$${\overline H _2}\left(\mathbb{X}{,}\mathbb{Y}\right)$$of strong limits of homeomorphisms in Sobolev space$${\mathbb{W}^{1,2}}\left(\mathbb{X}{,}\mathbb{Y}\right)$$is ρ-energy-minimal if and only if its Hopf-differential is analytic in$$\mathbb{X}$$and real along$$\partial\mathbb{X}$$. It improves and extends the result of Iwaniec et al. (see Theorem 1.4 in [Arch. Ration. Mech. Anal., 209, 401–453 (2013)]). Furthermore, we give an application of the principle. Any ρ-energy minimal diffeomorphism is ρ-harmonic, however, we give a $$1/{\left| w \right|^2}$$-harmonic diffemorphism which is not $$1/{\left| w \right|^2}$$-energy minimal diffeomorphism. At last, we investigate the necessary and sufficient conditions for the existence of $$1/{\left| w \right|^2}$$-harmonic mapping from doubly connected domain Ω to the circular annulus A(1, R).

First principles Heisenberg models of 2D magnetic materials: the importance of quantum corrections to the exchange coupling

Magnetic materials are typically described in terms of the Heisenberg model, which provides an accurate account of thermodynamic properties when combined with first principles calculations. This approach is usually based on an energy mapping between density functional theory and a classical Heisenberg model. However, for two-dimensional systems the eigenenergies of the Heisenberg model may differ significantly from the classical approximation, which leads to modified expressions for exchange parameters. Here we demonstrate that density functional theory yields local magnetic moments that are in accordance with strongly correlated anti-ferromagnetic eigenstates of the Heisenberg Hamiltonian. This implies that density functional theory provides a description of these states that conforms with the quantum mechanical eigenstates of the model. We then provide expressions for exchange parameters based on a proper eigenstate mapping to the Heisenberg model and find that they may be reduced by up to 17% compared to a classical analysis. Finally, we calculate the corrections to critical temperature for magnetic ordering for a previously predicted set of two-dimensional ferromagnetic insulators and find that the inclusion of quantum effects may reduce the predictions of critical temperatures by up to 7%. The effect is, however, predicted to be much higher for spin-1/2 systems, which are not included in the predictions of critical temperatures.

Image resizing with minimum distortion

Displays became cheap and were combined with many devices, like camera, mobile, and so on…, so there has been an increased interest on resizing methods to make the image suitable and fill any screen size. Common and known methods like cropping or resampling can cause undesirable effects such as: losses in information or distortion in perception. Recently, content-aware image resizing methods have been proposed to get rid of these problems and produce exceptional results. Seam-carving produced by Avidan and Shamir has gained attention as an effective solution. This paper discussed about this method and used it to resize (minimize and maximize) four colored images vertically and horizontally respectively, and maintained the main features of the images by deleting or repeating only the uninfluenced features. The energy map was calculated that described the basic and influential details of the image using energy function. But instead of gradient function (as in Avidan and Shamir) entropy function was used to compute the energy of the images. A vertical or a horizontal seam of pixels with minimum energy values was either deleted or inserted to resize the image. Good results were obtained especially when the image contains spaces within its details. The work was programmed using Matlab2018a.

Connected component analysis integrated edge based technique for automatic vehicular license plate recognition framework

Automatic vehicle license plate recognition (AVLPR) aims at extracting the region that contains the information of vehicle license number out of an image data and then identifying the characters apart from the human intervention. This study proposed an effective AVLPR framework where detection, segmentation and recognition of various shaped license plates have been focused. For both proper visual perception and computational processing, a pre-processing technique including grey-scaling conversion combined with close arithmetic-based dilation has been defined. Both vertical and horizontal edge densities have been enumerated by kernel matrices which enable robustness in detecting various shaped and sized license plates. For better detection of candidate region, the vertical and horizontal energy mapping features combined with Gaussian smoothing filter have been used to enable detection of license plates from both high definition and lower resolution images under various illumination conditions and crowded background. For ensuring a better character segmentation rate which is the prerequisite for higher recognition rate, a blob assessment method has been defined integrated with connected component analysis. With 400 vehicle images having varying pixels, the proposed algorithm achieves 96.5, 95.6 and 94.4% accuracy, respectively, in identifying, segmenting and recognising the plate number.

A GIS-Based Methodology for Speedy Energy Efficiency Mapping: A Case Study in Bologna

The paper reports a methodology developed to map energy consumption of the building stock at the urban scale on a GIS environment. Energy consumption has been investigated, focusing on the shift from the individual building scale to the district one with the purpose of identifying larger homogenous energy use areas for addressing policies and plans to improve the quality and the performance levels at the city scale. The urban planning zoning concept was extended to the energy issue to include the energy behavior of each zone that depends on the performance of its individual buildings. The methodology generates GIS maps providing a district scale visualization of energy consumption according to shared criteria. A case study in Bologna city (Italy) is provided. In the specific case, the last update of Emilia-Romagna regional urban planning regulation required a mapping action regarding energy efficiency of homogeneous urban portions defined by the General Urban Plan. The main achieved results are (a) a methodology to identify homogeneous areas for analyzing energy consumption; (b) an updated energy map of Bologna Municipality.

Surface Energy Mapping of Modified Silica Using IGC Technique at Finite Dilution.

The reinforcing silica filler, which can be more than 40% of an elastomer composite, plays a key role to achieve the desired mechanical properties in elastomer vulcanizates. However, the highly hydrophilic nature of silica surface causes silica particle aggregation. It remained a challenge for many tire manufacturers when using silica-filled elastomer compounds. Here, the silica surface energy changes when the surface is modified with coupling or noncoupling silanes; coupling silanes can covalently bond the silica to the elastomers. The surface energy of silica was determined using inverse gas chromatography (IGC) at finite dilution (FD-IGC) and found to be reduced by up to 50% when the silica surface was silanized. The spatial distribution of silica aggregates within the tire matrix is determined by transmission electron microscopy (TEM) and a direct correlation between aggregate size (silica microdispersion) and work of cohesion from IGC is reported, highlighting surface energy and work of cohesion being excellent indicators of the degree of dispersion of silica aggregates.

Iris center localization using energy map synthesis based on gradient and isophote

Iris center localization using energy map synthesis based on gradient and isophote

Polyaniline supercapacitor electrode and carbon fiber graphene oxide: Electroactive properties at the charging limit

Electroactive materials have presented increasingly relevant application potentials as energy storage, because of the use of 5G technologies, artificial intelligence, IoT and batteries for electric vehicles. The objective of this work was to evaluate their electroactive properties in different potential applications and to test the electrode charge limit for energy storage devices. Structural carbon fiber composite materials coated by electrochemical synthesis of polyaniline with graphene oxide were obtained. The electrodes were characterized by GCD (with and without cutoff), FEG, FTIR, Raman, CV, EIS and 4 probes. The electrodes can be classified with supercapacitive properties according to the Ragone Diagram and applied to different potential variations reaching a charging limit (potential limit that stores the largest amount of charge). Mapping of specific power and energy during cycling reveals that the GO electrode confers structural stability to the PANI and maintains the material’s electroactive properties elevated over 500 cycles.