Search results for: three dimensional emission spectral studies

Authors: Yu-Wen Chen, Szu-Wei Huang, Chung-Hsiang Mu, Kelvin Cheng

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This paper developed a data-driven based model to deal with the causality between the Continuous Emission Monitoring System (CEMS, by Environmental Protection Administration, Taiwan) in industrial factories, and the air quality around environment. Compared to the heavy burden of traditional numerical models of regional weather and air pollution simulation, the lightweight burden of the proposed model can provide forecasting hourly with current observations of weather, air pollution and emissions from factories. The observation data are included wind speed, wind direction, relative humidity, temperature and others. The observations can be collected real time from Open APIs of civil IoT Taiwan, which are sourced from 439 weather stations, 10,193 qualitative air stations, 77 national quantitative stations and 140 CEMS quantitative industrial factories. This study completed a causal inference engine and gave an air pollution forecasting for the next 12 hours related to local industrial factories. The outcomes of the pollution forecasting are produced hourly with a grid resolution of 1km*1km on IIoTC (Industrial Internet of Things Cloud) and saved in netCDF4 format. The elaborated procedures to generate forecasts comprise data recalibrating, outlier elimination, Kriging Interpolation and particle tracking and random walk techniques for the mechanisms of diffusion and advection. The solution of these equations reveals the causality between factories emission and the associated air pollution. Further, with the aid of installed real-time flue emission (Total Suspension Emission, TSP) sensors and the mentioned forecasted air pollution map, this study also disclosed the converting mechanism between the TSP and PM2.5/PM10 for different region and industrial characteristics, according to the long-term data observation and calibration. These different time-series qualitative and quantitative data which successfully achieved a causal inference engine in cloud for factory management control in practicable. Once the forecasted air quality for a region is marked as harmful, the correlated factories are notified and asked to suppress its operation and reduces emission in advance.

Keywords: continuous emission monitoring system, total suspension particulates, causal inference, air pollution forecast, IoT

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Authors: Adebayo John Julius, Emmanuel Imoagene

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Mitigating global warming through reducing emission from deforestation and degradation (REDD) has been given increasing attentions in government-to-government negotiations while discussions among decision-makers have been going on, it is important to learn about the perception of local people in relation to REDD because the implementation will affect their lives. A survey was conducted using questionnaires to examine the livelihood and forest dependency of the local people in the vicinity of Onigambari and Ido area. Respondents’ income from forest activities and forest resources are collected. Participation in tourism related activities among the household members was also investigated to measure the potential of this “eco-friendly” income generation activity in the local communities. There was a general indication of reducing slash-and-burn activities with distance from the park and involvement in tourism-related job. Most of the local people were willing to accept compensation as alternative for slash-and-burn activities. The compensation preferred is in various form of development and different level of forest and environmental activities

Keywords: livelihood, emission, deforestation, degradation, local people, southwest Nigeria

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Authors: N. K. Fuloria, S. Fuloria, R. Gupta

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Esterification of p-bromo-m-cresol offered 2-(4-bromo-3-methyl phenoxy)acetate (1), which was hydrazinated to yield 2-(4-bromo-3-methyl phenoxy)aceto hydrazide (2). Compound (2) was reacted with different aromatic aldehydes to yield N-(substituted benzylidiene)-2-(4-bromo-3-methyl phenoxy)acetamide(3a-c). Cyclization of compound (3a-c) with thioglycolic acid yielded 2-(4-bromo-3-methylphenoxy)-N-(4-oxo-2-arylthiazolidin-3-yl) acetamide (4a-c). The newly synthesized compounds were characterized on the basis of spectral studies and evaluated for antibacterial and antifungal activities.

Keywords: imines, thiazolidinone, schiff base, antimicrobial

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Authors: S. Zhuiykov, Z. Wei

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Conformal defect-free two-dimensional (2D) WO₃ and TiO₂ semiconductors have been developed by the atomic layer deposition (ALD) technique on wafer scale with unique approach to the thickness control with precision of ± 10% from the monolayer of nanomaterial (less than 1.0 nm thick) to the nano-layered 2D structures with thickness of ~3.0-7.0 nm. Developed 2D nanostructures exhibited unique, distinguishable properties at nanoscale compare to their thicker counterparts. Specifically, 2D TiO₂-Au bilayer demonstrated improved photocatalytic degradation of palmitic acid under UV and visible light illumination. Improved functional capabilities of 2D semiconductors would be advantageous to various environmental, nano-energy and bio-sensing applications. The ALD-enabled approach is proven to be versatile, scalable and applicable to the broader range of 2D semiconductors.

Keywords: two-dimensional (2D) semiconductors, ALD, WO₃, TiO₂, wafer scale

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Authors: A. Guechi, M. Chegaar

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This study investigates how AlGaAs/GaAs thin film solar cells perform under varying global solar spectrum due to the changes of environmental parameters such as the air mass and the atmospheric turbidity. The solar irradiance striking the solar cell is simulated using the spectral irradiance model SMARTS2 (Simple Model of the Atmospheric Radiative Transfer of Sunshine) for clear skies on the site of Setif (Algeria). The results show a reduction in the short circuit current due to increasing atmospheric turbidity, it is 63.09% under global radiation. However increasing air mass leads to a reduction in the short circuit current of 81.73%.The efficiency decrease with increasing atmospheric turbidity and air mass.

Keywords: AlGaAs/GaAs, solar cells, environmental parameters, spectral variation, SMARTS

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Authors: Imen Harabi, Hanae Toura, Safa Jemai, Bernabe Mari Soucase

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A promising alternative to traditional Quantum Dots QD materials, which contain toxic heavy elements such as lead and cadmium, sheds light on indium phosphide quantum dots (InP QDs) Owing to improve the quantum yields of photoluminescence and other properties. InP, InP/ZnS core/shell and InP/ZnS/ZnS core/shell/shell Quantum Dots (QDs) were synthetized by the hot injection method. The optical and structural properties of the core InP QDs, InP/ZnS QDs, and InP/ZnS/ZnS QDs have being considered by several techniques such as X-ray diffraction, transmission electron microscopy, optical spectroscopy, and photoluminescence. The average diameter of InP, InP/ZnS, and InP/ZnS/ZnS Quantum Dots (QDs) was varying between 10 nm, 5.4 nm, and 4.10 nm. This experience revealed that the surface morphology of the Quantum Dots has a more regular spherical form with color variation of the QDs in solution. The emission peak of colloidal InP Quantum Dots was around 530 nm, while in InP/ZnS, the emission peak is displayed and located at 598 nm. whilst for InP/ZnS/ZnS is placed at 610 nm. Furthermore, an enhanced PL emission due to a passivation effect in the ZnS-covered InP QDs was obtained. Add the XRD information FWHM of the principal peak of InP QDs was 63 nm, while for InP/ZnS was 41 nm and InP/ZnS/ZnS was 33 nm. The effect of the Zinc stearate precursor concentration on the optical, structural, surface chemical of InP and InP/ZnS and InP/ZnS/ZnS QDs will be discussed.

Keywords: indium phosphide, quantum dot, nanoparticle, core-shell, multishell, luminescence

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Authors: Ebissa Gadissa Kedir, C. S. P. Ojha, K. S. Hari Prasad

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In the present study, the depth-averaged velocity and boundary shear stress in non-prismatic compound channels with three different converging floodplain angles ranging from 1.43ᶱ to 7.59ᶱ have been studied. The analytical solutions were derived by considering acting forces on the channel beds and walls. In the present study, five key parameters, i.e., non-dimensional coefficient, secondary flow term, secondary flow coefficient, friction factor, and dimensionless eddy viscosity, were considered and discussed. An expression for non-dimensional coefficient and integration constants was derived based on the boundary conditions. The model was applied to different data sets of the present experiments and experiments from other sources, respectively, to examine and analyse the influence of floodplain converging angles on depth-averaged velocity and boundary shear stress distributions. The results show that the non-dimensional parameter plays important in portraying the variation of depth-averaged velocity and boundary shear stress distributions with different floodplain converging angles. Thus, the variation of the non-dimensional coefficient needs attention since it affects the secondary flow term and secondary flow coefficient in both the main channel and floodplains. The analysis shows that the depth-averaged velocities are sensitive to a shear stress-dependent model parameter non-dimensional coefficient, and the analytical solutions are well agreed with experimental data when five parameters are included. It is inferred that the developed model may facilitate the interest of others in complex flow modeling.

Keywords: depth-average velocity, converging floodplain angles, non-dimensional coefficient, non-prismatic compound channels

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Authors: Mirabbos Mirkamalov, Zavkiddin Mirtoshev

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The M 1.6 class flare occurred on 6^th of September 2012. Our observations correspond to the active region NOAA 11560 with the heliographic coordinates N04W71. The event took place between 04:00 UT and 04:45 UT, and was close to the solar limb at the western region. The flare temperature correlates with flux peak, increases for a short period (between 04:08 UT and 04:12 UT), rises impulsively, attains a maximum value of about 17 MK at 04:12 UT and gradually decreases after peak value. Around the peak we observe significant emissions of X-ray sources. Flux profiles of the X-ray emission exhibit a progressively faster raise and decline as the higher energy channels are considered.

Keywords: magnetic reconnection, solar atmosphere, solar flare, X-ray emission

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Authors: Naohiro Nakamura

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Analysis methods to accurately estimate the behavior of buildings when earthquakes occur is very important for improving the seismic safety of such buildings. Recently, the use of damping devices has increased significantly and there is a particular need to appropriately evaluate the behavior of buildings with such devices during earthquakes in the design stage. At present, however, the accuracy of the analysis evaluations is not sufficient. One reason is that the accuracy of current analysis methods has not been appropriately verified because there is very limited data on the behavior of actual buildings during earthquakes. Many types of shaking table test of large structures are performed at the '3-Dimensional Full-Scale Earthquake Testing Facility' (nicknamed 'E-Defense') operated by the National Research Institute of Earth Science and Disaster Prevention (NIED). In this study, simulations using 3- dimensional analysis models were conducted on shaking table test of a 5-story steel-frame structure with dampers. The results of the analysis correspond favorably to the test results announced afterward by the committee. However, the suitability of the parameters and models used in the analysis and the influence they had on the responses remain unclear. Hence, we conducted additional analysis and studies on these models and parameters. In this paper, outlines of the test are shown and the utilized analysis model is explained. Next, the analysis results are compared with the test results. Then, the additional analyses, concerning with the hysteresis curve of the dampers and the beam-end stiffness of the frame, are investigated.

Keywords: three-dimensional analysis, E-defense, full-scale experimen, vibration control damper

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Authors: Shu Tao

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Based on a global fuel consumption data product (PKU-FUEL-2007) compiled recently and a series of databases for emission factors of various sources, global emission inventories of a number of greenhouse gases and air pollutants, including CO2, CO, SO2, NOx, primary particulate matter (total, PM 10, and PM 2.5), black carbon, organic carbon, mercury, volatile organic carbons, and polycyclic aromatic hydrocarbons, from combustion sources have been developed. The inventories feather high spatial and sectorial resolutions. The spatial resolution of the inventories are 0.1 by 0.1 degree, based on a sub-national disaggregation approach to reduce spatial bias due to uneven distribution of per person fuel consumption within countries. The finely resolved inventories provide critical information for chemical transport modeling and exposure modeling. Emissions from more than 60 sources in energy, industry, agriculture, residential, transportation, and wildfire sectors were quantified in this study. With the detailed sectorial information, the inventories become an important tool for policy makers. For residential sector, a set of models were developed to simulate temporal variation of fuel consumption, consequently pollutant emissions. The models can be used to characterize seasonal as well as inter-annual variations in the emissions in history and to predict future changes. The models can even be used to quantify net change of fuel consumption and pollutant emissions due to climate change. The inventories has been used for model ambient air quality, population exposure, and even health effects. A few examples of the applications are discussed.

Keywords: air pollutants, combustion, emission inventory, sectorial information

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Authors: N. Rajmohan, M. R. Swaminathan

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The performance of a diesel engine depends mainly on mixing of the fuel and air in the combustion chamber. The diesel engine suffers from significant generation of nitric oxide and particulate matter emission due to incomplete combustion. As the fuel is injected directly into the combustion chamber in conventional diesel engines, spatial distributions of air-fuel ratio vary widely from rich to lean in combustion chamber. The NOx is formed in stoichiometric zone and smoke is generated during diffusion combustion period where the combustion rate becomes slower. One of the effective methods to reduce oxides of nitrogen and particulate matter emissions simultaneously is to reduce the intake charge temperature in diesel engines. Therefore, in the present study, the effect of water injection into intake air on performance and emission characteristic of single cylinder CI engine are carried out at different load and constant speed, with variable water to diesel ratio by mass. The water is injected into intake air by an elementary carburetor.

Keywords: engine emission control, oxides of nitrogen, diesel engine, ignition engine

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Authors: K. R. Mohanapriya, D. Geetharamani

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In last few decades, global atmospheric concentrations of green house gases have been frequently increased because of carbon di oxide (CO2) emission from combustion of fossil fuels. This green house gas emission leads to global warming. In order to reduce green house gas emission, cultivation of microalgae has received attention due to their feasibility of CO2 sequestration. Microalgae can grow and multiply in short period because of their photosynthetic simple unicellular structures and can grow using water unsuitable for human consumption with nutrients that are available at low cost. In the present study, freshwater microalgae were isolated from Noyyal river in Coimbatore, Tamil Nadu, India. The isolated strains were screened for CO2 sequestration potential. The efficient isolate namely Klebsormidium sp was subjected to further study. Quantitative determination of CO2 sequestration potential of the isolate under study has been done. The biomass of the isolate thus obtained was subjected to triglyceride and fatty acid analysis to study the potential application of the isolate for biodiesel production.

Keywords: CO2 sequestration, freshwater microalgae, Klebsormidium sp, biodiesel

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Authors: Erick Pruchnicki, Nikhil Padhye

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Plates are important engineering structures which have attracted extensive research since the 19th century. The subject of this work is statical analysis of a linearly elastic homogenous plate under small deformations. A 'thin plate' is a three-dimensional structure comprising of a small transverse dimension with respect to a flat mid-surface. The general aim of any plate theory is to deduce a two-dimensional model, in terms of mid-surface quantities, to approximately and accurately describe the plate's deformation in terms of mid-surface quantities. In recent decades, a common starting point for this purpose is to utilize series expansion of a displacement field across the thickness dimension in terms of the thickness parameter (h). These attempts are mathematically consistent in deriving leading-order plate theories based on certain a priori scaling between the thickness and the applied loads; for example, asymptotic methods which are aimed at generating leading-order two-dimensional variational problems by postulating formal asymptotic expansion of the displacement fields. Such methods rigorously generate a hierarchy of two-dimensional models depending on the order of magnitude of the applied load with respect to the plate-thickness. However, in practice, applied loads are external and thus not directly linked or dependent on the geometry/thickness of the plate; thus, rendering any such model (based on a priori scaling) of limited practical utility. In other words, the main limitation of these approaches is that they do not furnish a single plate model for all orders of applied loads. Following analogy of recent efforts of deploying Fourier-series expansion to study convergence of reduced models, we propose two-dimensional model(s) resulting from truncation of the potential energy and rigorously prove the convergence of these two-dimensional plate models to the parent three-dimensional linear elasticity with increasing truncation order of the potential energy.

Keywords: plate theory, Fourier-series expansion, convergence result, Legendre polynomials

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Authors: Jamison Duckworth, Shankarachary Ragi

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Detection and segmentation of wildfire smoke plumes from remote sensing imagery are being pursued as a solution for early fire detection and response. Smoke plume detection can be automated and made robust by the application of artificial intelligence methods. Specifically, in this study, the deep learning approach Mask Region-based Convolutional Neural Network (RCNN) is being proposed to learn smoke patterns across different spectral bands. This method is proposed to separate the smoke regions from the background and return masks placed over the smoke plumes. Multispectral data was acquired using NASA’s Earthdata and WorldView and services and satellite imagery. Due to the use of multispectral bands along with the three visual bands, we show that Mask R-CNN can be applied to distinguish smoke plumes from clouds and other landscape features that resemble smoke.

Keywords: deep learning, mask-RCNN, smoke plumes, spectral bands

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Authors: Petter Eklund, Jonathan Sjölund, Sandra Eriksson, Mats Leijon

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The spoke type rotor can be used to obtain magnetic flux concentration in permanent magnet machines. This allows the air gap magnetic flux density to exceed the remanent flux density of the permanent magnets but gives problems with leakage fluxes in the magnetic circuit. The end leakage flux of one spoke type permanent magnet rotor design is studied through measurements and finite element simulations. The measurements are performed in the end regions of a 12 kW prototype generator for a vertical axis wind turbine. The simulations are made using three dimensional finite elements to calculate the magnetic field distribution in the end regions of the machine. Also two dimensional finite element simulations are performed and the impact of the two dimensional approximation is studied. It is found that the magnetic leakage flux in the end regions of the machine is equal to about 20% of the flux in the permanent magnets. The overestimation of the performance by the two dimensional approximation is quantified and a curve-fitted expression for its behavior is suggested.

Keywords: end effects, end leakage flux, permanent magnet machine, spoke type rotor

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Authors: Sweta Iyer, Nemeshwaree Behary, Jinping Guan, Guoqiang Chen, Vincent Nierstrasz

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Flavin mononucleotide widely known as 'FMN' is a biobased resource derived from riboflavin. The isoalloxazine ring present in the FMN molecule attributes the photoluminescence phenomenon, whereas FMN molecule in the presence of bacterial luciferase enzyme and co-factors such as NADH, long chain aldehyde leads to bioluminescence reaction. In this study, the FMN molecule was treated on cellulosic textile using chromojet technique and the photoluminescence property was characterized using spectroscopy technique. Further, the FMN was used as a substrate along with enzymes and co-factors to treat the non-woven textile, and the bioluminescence property was explored using luminometer equipment. The investigation revealed photoluminescence property on cellulosic textile, and the emission peak was observed at a wavelength around 530 nm with an average corrected spectral intensity of 10×106 CPS/Microamps. In addition, the measurement of nonwoven textile using bioluminescence reaction system exhibited light intensity measured in the form of relative light units (RLU). The study enabled to explore the use of FMN as both photoluminescent and bioluminescent textile. Further investigation would require for stability study of the same to provide an eco-efficient approach to obtain luminescent textile.

Keywords: flavin mononucleotide, photoluminescence, bioluminescence, luminescent textile

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Authors: Danilo López, Edwin Rivas, Fernando Pedraza

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Currently, one of the major challenges in wireless networks is the optimal use of radio spectrum, which is managed inefficiently. One of the solutions to existing problem converges in the use of Cognitive Radio (CR), as an essential parameter so that the use of the available licensed spectrum is possible (by secondary users), well above the usage values that are currently detected; thus allowing the opportunistic use of the channel in the absence of primary users (PU). This article presents the results found when estimating or predicting the future use of a spectral transmission band (from the perspective of the PU) for a chaotic type channel arrival behavior. The time series prediction method (which the PU represents) used is ANFIS (Adaptive Neuro Fuzzy Inference System). The results obtained were compared to those delivered by the RNA (Artificial Neural Network) algorithm. The results show better performance in the characterization (modeling and prediction) with the ANFIS methodology.

Keywords: ANFIS, cognitive radio, prediction primary user, RNA

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Authors: Ali Akyar, Osman Serdar Gedik

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Depth estimation is a challenging computer vision task that involves estimating the distance between objects in a scene and the camera. It predicts how far each pixel in the 2D image is from the capturing point. There are some important Monocular Depth Estimation (MDE) studies that are based on Vision Transformers (ViT). We benchmark three major studies. The first work aims to build a simple and powerful foundation model that deals with any images under any condition. The second work proposes a method by mixing multiple datasets during training and a robust training objective. The third work combines generalization performance and state-of-the-art results on specific datasets. Although there are studies with thermal images too, we wanted to benchmark these three non-thermal, state-of-the-art studies with a hybrid image dataset which is taken by Multi-Spectral Dynamic Imaging (MSX) technology. MSX technology produces detailed thermal images by bringing together the thermal and visual spectrums. Using this technology, our dataset images are not blur and poorly detailed as the normal thermal images. On the other hand, they are not taken at the perfect light conditions as RGB images. We compared three methods under test with our thermal dataset which was not done before. Additionally, we propose an image enhancement deep learning model for thermal data. This model helps extract the features required for monocular depth estimation. The experimental results demonstrate that, after using our proposed model, the performance of these three methods under test increased significantly for thermal image depth prediction.

Keywords: monocular depth estimation, thermal dataset, benchmarking, vision transformers

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Authors: Nikhat Nawaz, S. Srinivasulu, P. Kesava Rao

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Feature extraction plays an important role in many remote sensing applications. Automatic extraction of water bodies is of great significance in many remote sensing applications like change detection, image retrieval etc. This paper presents a procedure for automatic extraction of water information from remote sensing images. The algorithm uses the relative location of R-colour component of the chromaticity diagram. This method is then integrated with the effectiveness of the spatial scale transformation of whole method. The whole method is based on water index fitted from spectral library. Experimental results demonstrate the improved accuracy and effectiveness of the integrated method for automatic extraction of water bodies.

Keywords: feature extraction, remote sensing, image retrieval, chromaticity, water index, spectral library, integrated method

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Authors: Kishor Chandra Kandpal, Amit Kumar

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The Indian Himalaya region harbours approximately 1748 plants of medicinal importance, and as per International Union for Conservation of Nature (IUCN), the 112 plant species among these are threatened and endangered. To ease the pressure on these plants, the government of India is encouraging its in-situ cultivation. The Saussurea costus, Valeriana jatamansi, and Picrorhiza kurroa have also been prioritized for large scale cultivation owing to their market demand, conservation value and medicinal properties. These species are found from 1000 m to 4000 m elevation ranges in the Indian Himalaya. Identification of these plants in the field requires taxonomic skills, which is one of the major bottleneck in the conservation and management of these plants. In recent years, Hyperspectral remote sensing techniques have been precisely used for the discrimination of plant species with the help of their unique spectral signatures. In this background, a spectral library of the above 03 medicinal plants was prepared by collecting the spectral data using a handheld spectroradiometer (325 to 1075 nm) from farmer’s fields of Himachal Pradesh and Uttarakhand states of Indian Himalaya. The Random forest (RF) model was implied on the spectral data for the classification of the medicinal plants. The 80:20 standard split ratio was followed for training and validation of the RF model, which resulted in training accuracy of 84.39 % (kappa coefficient = 0.72) and testing accuracy of 85.29 % (kappa coefficient = 0.77). This RF classifier has identified green (555 to 598 nm), red (605 nm), and near-infrared (725 to 840 nm) wavelength regions suitable for the discrimination of these species. The findings of this study have provided a technique for rapid and onsite identification of the above medicinal plants in the field. This will also be a key input for the classification of hyperspectral remote sensing images for mapping of these species in farmer’s field on a regional scale. This is a pioneer study in the Indian Himalaya region for medicinal plants in which the applicability of hyperspectral remote sensing has been explored.

Keywords: himalaya, hyperspectral remote sensing, machine learning; medicinal plants, random forests

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Authors: Endalkachew Abebe Kebede, Bojin Bojinov, Andon Vasilev Andonov, Orhan Dengiz

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Remote sensing has a potential application in assessing and monitoring the plants' biophysical properties using the spectral responses of plants and soils within the electromagnetic spectrum. However, only a few reports compare the performance of different remote sensing sensors against in-situ field spectral measurement. The current study assessed the potential applications of open data source satellite images (Sentinel 2 and Landsat 9) in estimating the biophysical properties of the wheat crop on a study farm found in the village of OvchaMogila. A Landsat 9 (30 m resolution) and Sentinel-2 (10 m resolution) satellite images with less than 10% cloud cover have been extracted from the open data sources for the period of December 2021 to April 2022. An Unmanned Aerial Vehicle (UAV) has been used to capture the spectral response of plant leaves. In addition, SpectraVue 710s Leaf Spectrometer was used to measure the spectral response of the crop in April at five different locations within the same field. The ten most common vegetation indices have been selected and calculated based on the reflectance wavelength range of remote sensing tools used. The soil samples have been collected in eight different locations within the farm plot. The different physicochemical properties of the soil (pH, texture, N, P₂O₅, and K₂O) have been analyzed in the laboratory. The finer resolution images from the UAV and the Leaf Spectrometer have been used to validate the satellite images. The performance of different sensors has been compared based on the measured leaf spectral response and the extracted vegetation indices using the five sampling points. A scatter plot with the coefficient of determination (R2) and Root Mean Square Error (RMSE) and the correlation (r) matrix prepared using the corr and heatmap python libraries have been used for comparing the performance of Sentinel 2 and Landsat 9 VIs compared to the drone and SpectraVue 710s spectrophotometer. The soil analysis revealed the study farm plot is slightly alkaline (8.4 to 8.52). The soil texture of the study farm is dominantly Clay and Clay Loam.The vegetation indices (VIs) increased linearly with the growth of the plant. Both the scatter plot and the correlation matrix showed that Sentinel 2 vegetation indices have a relatively better correlation with the vegetation indices of the Buteo dronecompared to the Landsat 9. The Landsat 9 vegetation indices somewhat align better with the leaf spectrometer. Generally, the Sentinel 2 showed a better performance than the Landsat 9. Further study with enough field spectral sampling and repeated UAV imaging is required to improve the quality of the current study.

Keywords: landsat 9, leaf spectrometer, sentinel 2, UAV

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Authors: Geetika Barman, B. S. Daya Sagar

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In this article, we proposed a pixel-wise classification of hyperspectral images using a mathematical morphology operator-based distance metric called “dilation distance” and “erosion distance”. This method involves measuring the spatial distance between the spectral features of a hyperspectral image across the bands. The key concept of the proposed approach is that the “dilation distance” is the maximum distance a pixel can be moved without changing its classification, whereas the “erosion distance” is the maximum distance that a pixel can be moved before changing its classification. The spectral signature of the hyperspectral image carries unique class information and shape for each class. This article demonstrates how easily the dilation and erosion distance can measure spatial distance compared to other approaches. This property is used to calculate the spatial distance between hyperspectral image feature vectors across the bands. The dissimilarity matrix is then constructed using both measures extracted from the feature spaces. The measured distance metric is used to distinguish between the spectral features of various classes and precisely distinguish between each class. This is illustrated using both toy data and real datasets. Furthermore, we investigated the role of flat vs. non-flat structuring elements in capturing the spatial features of each class in the hyperspectral image. In order to validate, we compared the proposed approach to other existing methods and demonstrated empirically that mathematical operator-based distance metric classification provided competitive results and outperformed some of them.

Keywords: dilation distance, erosion distance, hyperspectral image classification, mathematical morphology

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Authors: Thomas L. McCullough, John D. Hague, Marylesa M. Howard, Matthew K. Kiser, Michael A. Mazur, Lance K. McLean, Johanna L. Turk

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Radiological search and mapping depends on the successful recognition of anomalies in large data sets which contain varied and dynamic backgrounds. We present a new algorithmic approach for real-time anomaly detection which is resistant to common detector imperfections, avoids the limitations of a source template library and provides immediate, and easily interpretable, user feedback. This algorithm is based on a continuous wavelet transform for variance reduction and evaluates the deviation between a foreground measurement and a local background expectation using methods from linear algebra. We also present a technique for recognizing and visualizing spectrally similar clusters of data. This technique uses Laplacian Eigenmap Manifold Learning to perform dimensional reduction which preserves the geometric "closeness" of the data while maintaining sensitivity to outlying data. We illustrate the utility of both techniques on real-world data sets.

Keywords: radiological search, radiological mapping, radioactivity, radiation protection

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Authors: Leonid Zhukov, Dmytro Petrenko

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Optical thermometry has no alternative in many cases of industrial most effective continuous temperature control. Classical optical thermometry technologies can be used on available for pyrometers controlled objects with stable radiation characteristics and transmissivity of the intermediate medium. Without using temperature corrections, it is possible in the case of a “black” body for energy pyrometry and the cases of “black” and “grey” bodies for spectral ratio pyrometry or with using corrections – for any colored bodies. Consequently, with increasing the number of operating waves, optical thermometry possibilities to reduce methodical errors significantly expand. That is why, in recent 25-30 years, research works have been reoriented on more perfect spectral (multicolor) thermometry technologies. There are two physical material substances, i.e., substance (controlled object) and electromagnetic field (thermal radiation), to be operated in optical thermometry. Heat is transferred by radiation; therefore, radiation has the energy, entropy, and temperature. Optical thermometry was originating simultaneously with the developing of thermal radiation theory when the concept and the term "radiation temperature" was not used, and therefore concepts and terms "conditional temperatures" or "pseudo temperature" of controlled objects were introduced. They do not correspond to the physical sense and definitions of temperature in thermodynamics, molecular-kinetic theory, and statistical physics. Launched by the scientific thermometric society, discussion about the possibilities of temperature measurements of objects, including colored bodies, using the temperatures of their radiation is not finished. Are the information about controlled objects transferred by their radiation enough for temperature measurements? The positive and negative answers on this fundamental question divided experts into two opposite camps. Recent achievements of spectral thermometry develop events in her favour and don’t leave any hope for skeptics. This article presents the results of investigations and developments in the field of spectral thermometry carried out by the authors in the Department of Thermometry and Physics-Chemical Investigations. The authors have many-year’s of experience in the field of modern optical thermometry technologies. Innovative technologies of optical continuous temperature control have been developed: symmetric-wave, two-color compensative, and based on obtained nonlinearity equation of spectral emissivity distribution linear, two-range, and parabolic. Тhe technologies are based on direct measurements of physically substantiated and proposed by Prof. L. Zhukov, radiation temperatures with the next calculation of the controlled object temperature using this radiation temperatures and corresponding mathematical models. Тhe technologies significantly increase metrological characteristics of continuous contactless and light-guide temperature control in energy, metallurgical, ceramic, glassy, and other productions. For example, under the same conditions, the methodical errors of proposed technologies are less than the errors of known spectral and classical technologies in 2 and 3-13 times, respectively. Innovative technologies provide quality products obtaining at the lowest possible resource-including energy costs. More than 600 publications have been published on the completed developments, including more than 100 domestic patents, as well as 34 patents in Australia, Bulgaria, Germany, France, Canada, the USA, Sweden, and Japan. The developments have been implemented in the enterprises of USA, as well as Western Europe and Asia, including Germany and Japan.

Keywords: emissivity, radiation temperature, object temperature, spectral thermometry

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Authors: Abdulrahman Abdulrahman, Abir Abdulrahman

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Free over-fall is an instrument for measuring discharge in open channels by measuring end depth. A comprehensive researchers investigated theoretically and experimentally brink phenomenon with various approaches for different cross-sectional shapes. Anderson's method, based on Boussinq's approximation and energy approach was used to derive a pressure distribution factor at end depth. Applying the one-dimensional momentum equation and the principles of limit slope analysis, a relevant analytical solution may be derived for brink depth ratio (EDR) in prismatic rectangular channel. Also relationships between end depth ratio and slope ratio for a given non-dimensional normal or critical depth with upstream supercritical flow regime are presented. Simple indirect procedure is used to estimate the end depth discharge ratio (EDD) for subcritical and supercritical flow using measured end depth. The comparison of this analysis with all previous theoretical and experimental studies showed an excellent agreement.

Keywords: analytical solution, brink depth, end depth, flow measurement, free over fall, hydraulics, rectangular channel

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Authors: Isara Muangthai, Lin Sue Jane

Abstract:

Electricity is vital to every country’s economy in the world. For Thailand, the electricity generation sector plays an important role in the economic system, and it is the largest source of CO2 emissions. The aim of this paper is to use the decomposition analysis to investigate the key factors contributing to the changes of CO2 emissions from the electricity sector. The decomposition analysis has been widely used to identify and assess the contributors to the changes in emission trends. Our study adopted the Divisia index decomposition to identify the key factors affecting the evolution of CO2 emissions from Thailand’s thermal power sector during 2000-2011. The change of CO2 emissions were decomposed into five factors, including: Emission coefficient, heat rate, fuel intensity, electricity intensity, and economic growth. Results have shown that CO2 emission in Thailand’s thermal power sector increased 29,173 thousand tons during 2000-2011. Economic growth was found to be the primary factor for increasing CO2 emissions, while the electricity intensity played a dominant role in decreasing CO2 emissions. The increasing effect of economic growth was up to 55,924 million tons of CO2 emissions because the growth and development of the economy relied on a large electricity supply. On the other hand, the shifting of fuel structure towards a lower-carbon content resulted in CO2 emission decline. Since the CO2 emissions released from Thailand’s electricity generation are rapidly increasing, the Thailand government will be required to implement a CO2 reduction plan in the future. In order to cope with the impact of CO2 emissions related to the power sector and to achieve sustainable development, this study suggests that Thailand’s government should focus on restructuring the fuel supply in power generation towards low carbon fuels by promoting the use of renewable energy for electricity, improving the efficiency of electricity use by reducing electricity transmission and the distribution of line losses, implementing energy conservation strategies by enhancing the purchase of energy-saving products, substituting the new power plant technology in the old power plants, promoting a shift of economic structure towards less energy-intensive services and orienting Thailand’s power industry towards low carbon electricity generation.

Keywords: co2 emission, decomposition analysis, electricity generation, energy consumption

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Authors: Tibor Ajtai, Noémi Utry, Máté Pintér, Tomi Smausz, Zoltán Kónya, Béla Hopp, Gábor Szabó, Zoltán Bozóki

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Characterization of spectral responses of light absorbing carbonaceous particulate matter (LAC) is of great importance in both modelling its climate effect and interpreting remote sensing measurement data. The residential or domestic combustion of coal is one of the dominant LAC constituent. According to some related assessments the residential coal burning account for roughly half of anthropogenic BC emitted from fossil fuel burning. Despite of its significance in climate the comprehensive investigation of optical properties of residential coal aerosol is really limited in the literature. There are many reason of that starting from the difficulties associated with the controlled burning conditions of the fuel, through the lack of detailed supplementary proximate and ultimate chemical analysis enforced, the interpretation of the measured optical data, ending with many analytical and methodological difficulties regarding the in-situ measurement of coal aerosol spectral responses. Since the gas matrix of ambient can significantly mask the physicochemical characteristics of the generated coal aerosol the accurate and controlled generation of residential coal particulates is one of the most actual issues in this research area. Most of the laboratory imitation of residential coal combustion is simply based on coal burning in stove with ambient air support allowing one to measure only the apparent spectral feature of the particulates. However, the recently introduced methodology based on a laser ablation of solid coal target opens up novel possibilities to model the real combustion procedure under well controlled laboratory conditions and makes the investigation of the inherent optical properties also possible. Most of the methodology for spectral characterization of LAC is based on transmission measurement made of filter accumulated aerosol or deduced indirectly from parallel measurements of scattering and extinction coefficient using free floating sampling. In the former one the accuracy while in the latter one the sensitivity are liming the applicability of this approaches. Although the scientific community are at the common platform that aerosol-phase PhotoAcoustic Spectroscopy (PAS) is the only method for precise and accurate determination of light absorption by LAC, the PAS based instrumentation for spectral characterization of absorption has only been recently introduced. In this study, the investigation of the inherent, spectral features of laser generated and chemically characterized residential coal aerosols are demonstrated. The experimental set-up and its characteristic for residential coal aerosol generation are introduced here. The optical absorption and the scattering coefficients as well as their wavelength dependency are determined by our state-of-the-art multi wavelength PAS instrument (4λ-PAS) and multi wavelength cosinus sensor (Aurora 3000). The quantified wavelength dependency (AAE and SAE) are deduced from the measured data. Finally, some correlation between the proximate and ultimate chemical as well as the measured or deduced optical parameters are also revealed.

Keywords: absorption, scattering, residential coal, aerosol generation by laser ablation

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Authors: ChunLoon Cha, HoYeon Lee, SangSoon Hwang

Abstract:

Mild combustion is characterized with its distinguished features, such as suppressed pollutant emission, homogeneous temperature distribution, reduced noise and thermal stress. However, most studies for MILD combustion have been focused on gas phase fuel. Therefore further study on MILD combustion using liquid fuel is needed for the application to liquid fueled gas turbine especially. In this work, we will focus on numerical simulation of the effects of diluent gas velocity on the formation of liquid fuel MILD combustion used in gas turbine area. A series of numerical simulations using Ansys fluent 18.2 have been carried out in order to investigate the detail effect of the flow field in the furnace on the formation of MILD combustion. The operating conditions were fixed at relatively lower heat intensity of 1.28 MW/m³ atm and various global equivalence ratios were changed. The results show that the local high temperature region was decreased and the flame temperature was uniformly distributed due to high velocity of diluted burnt gas. The increasing of diluted burnt gas velocity can be controlled by open ratio of adapter size. It was found that the maximum temperature became lower than 1800K and the average temperature was lower than 1500K that thermal NO formation was suppressed.

Keywords: MILD combustion, spray combustion, liquid fuel, diluent gas velocity, low NOx emission

Procedia PDF Downloads 231

Authors: Snezana Lazic, Zarko Gacevic, Mark Holmes, Ekaterina Chernysheva, Marcus Müller, Peter Veit, Frank Bertram, Juergen Christen, Yasuhiko Arakawa, Enrique Calleja

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The study reports how the pencil-like morphology of a homoepitaxially grown GaN nanowire can be exploited for the fabrication of a thin conformal InGaN nanoshell, hosting nonpolar, semipolar and polar single photon sources (SPSs). All three SPS types exhibit narrow emission lines (FWHM~0.35 - 2 meV) and high degrees of linear optical polarization (P > 70%) in the low-temperature micro-photoluminescence (µ-PL) experiments and are characterized by a pronounced antibunching in the photon correlation measurements (gcorrected(2)(0) < 0.3). The quantum-dot-like exciton localization centers induced by compositional fluctuations within the InGaN nanoshell are identified as the driving mechanism for the single photon emission. As confirmed by the low-temperature transmission electron microscopy combined with cathodoluminescence (TEM-CL) study, the crystal region (i.e. non-polar m-, semi-polar r- and polar c-facets) hosting the single photon emitters strongly affects their emission wavelength, which ranges from ultra-violet for the non-polar to visible for the polar SPSs. The photon emission lifetime is also found to be facet-dependent and varies from sub-nanosecond time scales for the non- and semi-polar SPSs to a few nanoseconds for the polar ones. These differences are mainly attributed to facet-dependent indium content and electric field distribution across the hosting InGaN nanoshell. The hereby reported pencil-like InGaN nanoshell is the first single nanostructure able to host all three types of single photon emitters and is thus a promising building block for tunable quantum light devices integrated into future photonic and optoelectronic circuits.

Keywords: GaN nanowire, InGaN nanoshell, linear polarization, nonpolar, semipolar, polar quantum dots, single-photon sources

Procedia PDF Downloads 392

Authors: Zong-Xian Qiu, Ta-Wui Cheng, Wei-Hao Lee, Yung-Chin Ding

Abstract:

The greenhouse effect is an important issue since it has been responsible for global warming. Carbon dioxide plays an important part of role in the greenhouse effect. Therefore, human has the responsibility for reducing CO₂ emissions in their daily operations. Except iron making and power plants, another major CO₂ production industry is cement industry. According to the statistics by EPA of Taiwan, production 1 ton of Portland cement will produce 520.29 kg of CO₂. There are over 7.8 million tons of CO₂ produced annually. Thus, trying to development low CO₂ emission green concrete is an important issue, and it can reduce CO₂ emission problems in Taiwan. The purpose of this study is trying to use marble wastes and slag as the raw materials to fabricate geopolymer green concrete. The result shows the marble based geopolymer green concrete have good workability and the compressive strength after curing for 28 days and 365 days can be reached 44MPa and 53MPa in indoor environment, 28MPa and 40.43MPa in outdoor environment. The acid resistance test shows the geopolymer green concrete have good resistance for chemical attack. The coefficient of permeability of geopolymer green concrete is better than Portland concrete. By comparing with Portland cement products, the marble based geopolymer not only reduce CO₂ emission problems but also provides great performance in practices. According to the experiment results shown that geopolymer concrete has great potential for further engineering development in the future, the new material could be expected to replace the Portland cement products in the future days.

Keywords: marble, slag, geopolymer, green concrete, CO₂ emission

Procedia PDF Downloads 138