Search results for: electrochemical sensing

Authors: S. S. Patil, Sachidanand Kini

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Classification of land use patterns is compelling in complexity and variability of remote sensing imageries data. An imperative research in remote sensing application exploited to mine some of the significant spatially variable factors as land cover and land use from satellite images for remote arid areas in Karnataka State, India. The diverse classification techniques, unsupervised and supervised consisting of maximum likelihood, Mahalanobis distance, and minimum distance are applied in Bellary District in Karnataka State, India for the classification of the raw satellite images. The accuracy evaluations of results are compared visually with the standard maps with ground-truths. We initiated with the maximum likelihood technique that gave the finest results and both minimum distance and Mahalanobis distance methods over valued agriculture land areas. In meanness of mislaid few irrelevant features due to the low resolution of the satellite images, high-quality accord between parameters extracted automatically from the developed maps and field observations was found.

Keywords: Mahalanobis distance, minimum distance, supervised, unsupervised, user classification accuracy, producer's classification accuracy, maximum likelihood, kappa coefficient

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Authors: L. Mentar, O. Baka, A. Azizi

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Zinc oxide as a wide band semiconductor materials, especially nanostructured materials, have potential applications in large-area such as electronics, sensors, photovoltaic cells, photonics, optical devices and optoelectronics due to their unique electrical and optical properties and surface properties. The feasibility of ZnO for these applications is due to the successful synthesis of diverse ZnO nanostructures, including nanorings, nanobows, nanohelixes, nanosprings, nanobelts, nanotubes, nanopropellers, nanodisks, and nanocombs, by different method. Among various synthesis methods, electrochemical deposition represents a simple and inexpensive solution based method for synthesis of semiconductor nanostructures. In this study, the electrodeposition method was used to produce zinc oxide (ZnO) nanostructures on fluorine-doped tin oxide (FTO)-coated conducting glass substrate as TCO from chloride bath. We present a systematic study on the effects of the concentration of chloride anion on the properties of ZnO. The influence of KCl concentrations on the electrodeposition process, morphological, structural and optical properties of ZnO nanostructures was examined. In this research electrochemical deposition of ZnO nanostructures is investigated using conventional electrochemical measurements (cyclic voltammetry and Mott-Schottky), scanning electron microscopy (SEM), and X-ray diffraction (XRD) techniques. The potentials of electrodeposition of ZnO were determined using the cyclic voltammetry. From the Mott-Schottky measurements, the flat-band potential and the donor density for the ZnO nanostructure are determined. SEM images shows different size and morphology of the nanostructures and depends greatly on the KCl concentrations. The morphology of ZnO nanostructures is determined by the corporated action between [Zn(NO3)2] and [Cl-].Very netted hexagonal grains are observed for the nanostructures deposited at 0.1M of KCl. XRD studies revealed that the all deposited films were polycrystalline in nature with wurtzite phase. The electrodeposited thin films are found to have preferred oriented along (002) plane of the wurtzite structure of ZnO with c-axis normal to the substrate surface for sample at different concentrations of KCl. UV-Visible spectra showed a significant optical transmission (~80%), which decreased with low Cl-1 concentrations. The energy band gap values have been estimated to be between 3.52 and 3.80 eV.

Keywords: electrodeposition, ZnO, chloride ions, Mott-Schottky, SEM, XRD

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Authors: Hong Dinh Duong, Jong Il Rhee

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In this study, a ratiometric inorganic phosphate sensor was fabricated by a double layer of the rhodamine 6G-doped nanofibers and the CdSe/ZnS QDs-captured polymer. In which, CdSe/ZnS QDs with emission wavelengths of 595nm were synthesized and ligands on their surface were exchanged with mercaptopropionic acid (MPA). The synthesized MPA-QDs were combined with the mixture of sol-gel of 3-glycidoxypropyl trimethoxysilane (GPTMS), 3-aminopropyltrimethoxysilane (APTMS) and polyurethane (PU) to build a layer for sensing inorganic phosphate. Another sensing layer was of nanofibers doped R6G which were produced from poly(styrene-co-acrylonitrile) by electrospining. The ratio of fluorescence intensities between rhodamin 6G (R6G) and CdSe/ZnS QDs exposed at different phosphate concentrations was used for calculating a linear phosphate concentration range of 0-10mM.

Keywords: nanofiber, QDs, ratiometric phosphate sensor, rhodamine 6G, sol-gel

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Authors: Kwang Chun, John Kemeny

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Light detection and ranging (LiDAR) has been a prevalent remote-sensing technology applied in the geological fields due to its high precision and ease of use. One of the major applications is to use the detailed geometrical information of underground structures as a basis for the generation of a three-dimensional numerical model that can be used in a geotechnical stability analysis such as FEM or DEM. To date, however, straightforward techniques in reconstructing the numerical model from the scanned data of the underground structures have not been well established or tested. In this paper, we propose a comprehensive approach integrating all the various processes, from LiDAR scanning to finite element numerical analysis. The study focuses on converting LiDAR 3D point clouds of geologic structures containing complex surface geometries into a finite element model. This methodology has been applied to Kartchner Caverns in Arizona, where detailed underground and surface point clouds can be used for the analysis of underground stability. Numerical simulations were performed using the finite element code Abaqus and presented by 3D computing visualization solution, ParaView. The results are useful in studying the stability of all types of underground excavations including underground mining and tunneling.

Keywords: finite element analysis, LiDAR, remote-sensing, scientific visualization, underground stability

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Authors: Bhawesh Kumar, A. P. Krishna

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There are continuous changes upon earth’s surface by a variety of natural and anthropogenic agents cut, carry away and depositing of minerals from land. Running water has higher capacity of erosion than other geomorphologic agents. This research work has been carried out on Ganga River, whose channel is continuously changing under the influence of geomorphic agents and human activities in the surrounding regions. The main focus is to study morphological characteristics and sand dynamics of Ganga River with particular emphasis on bank lines and width changes using remote sensing and GIS techniques. The advance remote sensing data and topographical data were interpreted for obtaining 52 years of changes. For this, remote sensing data of different years (LANDSAT TM 1975, 1988, 1993, ETM 2005 and ETM 2012) and toposheet of SOI for the year 1960 were used as base maps for this study. Sinuosity ratio, braiding index and migratory activity index were also established. It was found to be 1.16 in 1975 and in 1988, 1993, 2005 and 2005 it was 1.09, 1.11, 1.1, 1.09 respectively. The analysis also shows that the minimum value found in 1960 was in reach 1 and maximum value is 4.8806 in 2012 found in reach 4 which suggests creation of number of islands in reach 4 for the year 2012. Migratory activity index (MAI), which is a standardized function of both length and time, was computed for the 8 representative reaches. MAI shows that maximum migration was in 1975-1988 in reach 6 and 7 and minimum migration was in 1993-2005. From the channel change analysis, it was found that the shifting of bank line was cyclic and the river Ganges showed a trend of southward maximum values. The advanced remote sensing data and topographical data helped in obtaining 52 years changes in the river due to various natural and manmade activities like flood, water velocity and excavation, removal of vegetation cover and fertile soil excavation for the various purposes of surrounding regions.

Keywords: braided index, migratory activity index (MAI), Ganga river, river morphology

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Authors: Mohamed A. Baba, Gazy Rodowan, Brigita Abakevičienė, Sigitas Tamulevičius, Bartlomiej Lemieszek, Sebastian Molin, Tomas Tamulevičius

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Solid oxide fuel cells (SOFC) efficiently convert hydrogen to energy without producing any disturbances or contaminants. The core of the cell is electrolyte. For improving the performance of electrolyte-supported cells, it is desirable to extend the available exchange surface area by micro-structuring of the electrolyte with laser-based micromachining. This study investigated the electrochemical performance of cells micro machined using a femtosecond laser. Commercial ceramic SOFC (Elcogen, AS) with a total thickness of 400 μm was structured by 1030 nm wavelength Yb: KGW fs-laser Pharos (Light Conversion) using 100 kHz repetition frequency and 290 fs pulse length light by scanning with the galvanometer scanner (ScanLab) and focused with a f-Theta telecentric lens (SillOptics). The sample height was positioned using a motorized z-stage. The microstructures were formed using a laser spiral trepanning in Ni/YSZ anode supported membrane at the central part of the ceramic piece of 5.5 mm diameter at active area of the cell. All surface was drilled with 275 µm diameter holes spaced by 275 µm. The machining processes were carried out under ambient conditions. The microstructural effects of the femtosecond laser treatment on the electrolyte surface were investigated prior to the electrochemical characterisation using a scanning electron microscope (SEM) Quanta 200 FEG (FEI). The Novo control Alpha-A was used for electrochemical impedance spectroscopy on a symmetrical cell configuration with an excitation amplitude of 25 mV and a frequency range of 1 MHz to 0.1 Hz. The fuel cell characterization of the cell was examined on open flanges test setup by Fiaxell. Using nickel mesh on the anode side and au mesh on the cathode side, the cell was electrically linked. The cell was placed in a Kittec furnace with a Process IDentifier temperature controller. The wires were connected to a Solartron 1260/1287 frequency analyzer for the impedance and current-voltage characterization. In order to determine the impact of the anode's microstructure on the performance of the commercial cells, the acquired results were compared to cells with unstructured anode. Geometrical studies verified that the depth of the -holes increased linearly according to laser energy and scanning times. On the other hand, it reduced as the scanning speed increased. The electrochemical analysis demonstrates that the open circuit voltage OCV values of the two cells are equal. Further, the modified cell's initial slope reduces to 0.209 from 0.253 of the unmodified cell, revealing that the surface modification considerably decreases energy loss. Plus, the maximum power density for the cell with the microstructure and the reference cell respectively, are 1.45 and 1.16 Wcm⁻².

Keywords: electrochemical performance, electrolyte-supported cells, laser micro-structuring, solid oxide fuel cells

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Authors: O. Çomaklı, M. Yazıcı, T. Yetim, A. F. Yetim, A. Çelik

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In this work, TiO₂ films were deposited on Cp-Ti substrates by thermal oxidation, DC plasma oxidation, and by the sol-gel method. Microstructures of uncoated and TiO₂ film coated samples were examined by X-ray diffraction and SEM. Thin oxide film consisting of anatase (A) and rutile (R) TiO₂ structures was observed on the surface of CP-Ti by under three different treatments. Also, the more intense anatase and rutile peaks appeared at samples plasma oxidized at 700˚C. The thicknesses of films were about 1.8 μm at the TiO₂ film coated samples by sol-gel and about 2.7 μm at thermal oxidated samples, while it was measured as 3.9 μm at the plasma oxidated samples. Electrochemical corrosion behaviour of uncoated and coated specimens was mainly carried out by potentiodynamic polarization and electrochemical impedance spectroscopy (EIS) in simulated body fluid (SBF) solution. Results showed that at the plasma oxidated samples exhibited a better resistance property to corrosion than that of other treatments.

Keywords: TiO₂, CP-Ti, corrosion properties, thermal oxidation, plasma oxidation, sol-gel

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Authors: Krzysztof Malczewski

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PET is widely applied scanning procedure in medical imaging based research. It delivers measurements of functioning in distinct areas of the human brain while the patient is comfortable, conscious and alert. This article presents the new compression sensing based super-resolution algorithm for improving the image resolution in clinical Positron Emission Tomography (PET) scanners. The issue of motion artifacts is well known in Positron Emission Tomography (PET) studies as its side effect. The PET images are being acquired over a limited period of time. As the patients cannot hold breath during the PET data gathering, spatial blurring and motion artefacts are the usual result. These may lead to wrong diagnosis. It is shown that the presented approach improves PET spatial resolution in cases when Compressed Sensing (CS) sequences are used. Compressed Sensing (CS) aims at signal and images reconstructing from significantly fewer measurements than were traditionally thought necessary. The application of CS to PET has the potential for significant scan time reductions, with visible benefits for patients and health care economics. In this study the goal is to combine super-resolution image enhancement algorithm with CS framework to achieve high resolution PET output. Both methods emphasize on maximizing image sparsity on known sparse transform domain and minimizing fidelity.

Keywords: PET, super-resolution, image reconstruction, pattern recognition

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Authors: Sunghun Jung, Wonkook Kim

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Due to the difficulty of the utilization of satellite and an aircraft, conventional ocean color remote sensing has a disadvantage in that it is difficult to obtain images of desired places at desired times. These disadvantages make it difficult to capture the anomalies such as the occurrence of the red tide which requires immediate observation. It is also difficult to understand the phenomena such as the resuspension-precipitation process of suspended solids and the spread of low-salinity water originating in the coastal areas. For the remote sensing reflectance of seawater, above-water radiometers (AWR) have been used either by carrying portable AWRs on a ship or installing those at fixed observation points on the Ieodo ocean research station, Socheongcho base, and etc. In particular, however, it requires the high cost to measure the remote reflectance in various seawater environments at various times and it is even not possible to measure it at the desired frequency in the desired sea area at the desired time. Also, in case of the stationary observation, it is advantageous that observation data is continuously obtained, but there is the disadvantage that data of various sea areas cannot be obtained. It is possible to instantly capture various marine phenomena occurring on the coast using the unmanned aerial system (UAS) including vertical takeoff and landing (VTOL) type unmanned aerial vehicles (UAV) since it could move and hover at the one location and acquire data of the desired form at a high resolution. To remotely estimate seawater constituents, it is necessary to install an ultra-spectral sensor. Also, to calculate reflected light from the surface of the sea in consideration of the sun’s incident light, a total of three sensors need to be installed on the UAV. The remote sensing reflectance of seawater is the most basic optical property for remotely estimating color components in seawater and we could remotely estimate the chlorophyll concentration, the suspended solids concentration, and the dissolved organic amount. Estimating seawater physics from the remote sensing reflectance requires the algorithm development using the accumulation data of seawater reflectivity under various seawater and atmospheric conditions. The UAS with three AWRs is developed for the remote reflection sensing on the surface of the sea. Throughout the paper, we explain the details of each UAS component, system operation scenarios, and simulation and experiment results. The UAS consists of a UAV, a solar tracker, a transmitter, a ground control station (GCS), three AWRs, and two gimbals.

Keywords: above-water radiometers (AWR), ground control station (GCS), unmanned aerial system (UAS), unmanned aerial vehicle (UAV)

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Authors: Sarono, Hamim Zaky Hadibasyir, dan Ridho Kurniawan

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Estimation of paddy production is one of the areas that can be examined using the techniques of remote sensing and geographic information systems (GIS) in the field of agriculture. The purpose of this research is to know the amount of the paddy production estimation and how remote sensing and geographic information systems (GIS) are able to perform analysis of paddy production estimation in Tegalallang and Payangan Sub district, Bali Province, Indonesia. The method used is the method of land suitability. This method associates a physical parameters which are to be embodied in the smallest unit of a mapping that represents a mapping unit in a particular field and connecting with its field productivity. Analysis of estimated production using standard land suitability from FAO using matching technique. The parameters used to create the land unit is slope (FAO), climate classification (Oldeman), landform (Prapto Suharsono), and soil type. Land use map consist of paddy and non paddy field information obtained from Geo-eye 1 imagery using visual interpretation technique. Landsat image of the Data used for the interpretation of the landform, the classification of the slopes obtained from high point identification with method of interpolation spline, whereas climate data, soil, use secondary data originating from institutions-related institutions. The results of this research indicate Tegallalang and Payangan Districts in known wetland suitability consists of S1 (very suitable) covering an area of 2884,7 ha with the productivity of 5 tons/ha and S2 (suitable) covering an area of 482,9 ha with the productivity of 3 tons/ha. The sum of paddy production estimation as a results in both districts are 31.744, 3 tons in one year.

Keywords: production estimation, paddy, remote sensing, geography information system, land suitability

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Authors: Jafar Khan Kasi, Ajab Khan Kasi, Muzamil Bokhari

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Carbon nanotube is one of the most attractive materials for the potential applications of nanotechnology due to its excellent mechanical, thermal, electrical and optical properties. In this paper we report a supercapacitor made of nickel foil electrodes, coated with multiwall carbon nanotubes (MWCNTs) thin film using electrophoretic deposition (EPD) method. Chemical vapor deposition method was used for the growth of MWCNTs and ethanol was used as a hydrocarbon source. High graphitic multiwall carbon nanotube was found at 750 C analyzing by Raman spectroscopy. We observed the electrochemical performance of supercapacitor by cyclic voltammetry. The electrodes of supercapacitor fabricated from MWCNTs exhibit considerably small equivalent series resistance (ESR), and a high specific power density. Electrophoretic deposition is an easy method in fabricating MWCNT electrodes for high performance supercapacitor.

Keywords: carbon nanotube, chemical vapor deposition, catalyst, charge, cyclic voltammetry

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Authors: Klathea Sevilla, Marjorie Remolador, Bryan Baltazar, Imee Saladaga, Loureal Camille Inocencio, Ma. Rosario Concepcion Ang

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The underutilization of biomass resources in the Philippines, combined with its growing population and the rise in fossil fuel prices confirms demand for alternative energy sources. The goal of this paper is to provide a comparison of MODIS-based and Landsat-based agricultural land cover maps when used in the estimation of rice hull’s available energy potential. Biomass resource assessment was done using mathematical models and remote sensing techniques employed in a GIS platform.

Keywords: biomass, geographic information system (GIS), remote sensing, renewable energy

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Authors: Ramon Alberto Paredes Camacho, Li Lu

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Sustainable batteries are possible through the development of cheaper and greener alternatives whose most feasible option is epitomized by Sodium-Ion Batteries (SIB). Na₃V₂(PO₄)₂F₃ (NVPF) an important member of the Na-superionic-conductor (NASICON) materials, has recently been in the spotlight due to its interesting electrochemical properties when used as cathode namely, high specific capacity of 128 mA h g-¹, high energy density of 507 W h Kg-¹, increased working potential at which vanadium redox couples can be activated (with an average value around 3.9 V), and small volume variation of less than 2%. These traits grant NVPF an excellent perspective as a cathode material for the next generation of sodium batteries. Unfortunately, because of its low inherent electrical conductivity and a high energy barrier that impedes the mobilization of all the available Na ions per formula, the overall electrochemical performance suffers substantial degradation, finally obstructing its industrial use. Many approaches have been developed to remediate these issues where nanostructural design, carbon coating, and ion doping are the most effective ones. This investigation is focused on enhancing the electrochemical response of NVPF by doping metal ions in the crystal lattice, substituting vanadium atoms. A facile sol-gel process is employed, with citric acid as the chelator and the carbon source. The optimized conditions circumvent fluorine sublimation, ratifying the material’s purity. One of the reasons behind the large ionic improvement is the attraction of extra Na ions into the crystalline structure due to a charge imbalance produced by the valence of the doped ions (+2), which is lower than the one of vanadium (+3). Superior stability (higher than 90% at a current density of 20C) and capacity retention at an extremely high current density of 50C are demonstrated by our doped NVPF. This material continues to retain high capacity values at low and high temperatures. In addition, full cell NVPF//Hard Carbon shows capacity values and high stability at -20 and 60ºC. Our doping strategy proves to significantly increase the ionic and electronic conductivity of NVPF even at extreme conditions, delivering outstanding electrochemical performance and paving the way for advanced high-potential cathode materials.

Keywords: sodium-ion batteries, cathode materials, NASICON, Na3V2(PO4)2F3, Ion doping

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Authors: Rida Kanwal, Wang Yuhui, Song Weiguo

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Wildfires are one of the most prominent threats to ecosystems, human health, and economic activities, with wind acting as a critical driving factor. This study combines machine learning (ML) and remote sensing (RS) to assess the effects of wind on wildfires in Chongqing Province from August 16-23, 2022. Landsat 8 satellite images were used to estimate the difference normalized burn ratio (dNBR), representing prefire and postfire vegetation conditions. Wind data was analyzed through geographic information system (GIS) mapping. Correlation analysis between wind speed and fire radiative power (FRP) revealed a significant relationship. An autoregressive integrated moving average (ARIMA) model was developed for wind forecasting, and linear regression was applied to determine the effect of wind speed on FRP. The results identified high wind speed as a key factor contributing to the surge in FRP. Wind-rose plots showed winds blowing to the northwest (NW), aligning with the wildfire spread. This model was further validated with data from other provinces across China. This study integrated ML, RS, and GIS to analyze wildfire behavior, providing effective strategies for prediction and management.

Keywords: wildfires, machine learning, remote sensing, wind speed, GIS, wildfire behavior

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Authors: K. Berhanu

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Improper land use results in land degradation and decline in agricultural productivity. Hence, in order to get maximum benefits out of land, proper utilization of its resources is inevitable. The present study was aimed at identifying the landcover changes in the study area in the last 25 years and determines the extent and direction of change that has occurred. The study made use of Landsat TM 1986 and 2011 Remote Sensing Satellite Image for analysis to determine the extent and pattern of rangeland change. The results of the landuse/landcover change detection showed that in the last 25 years, 3 major changes were observed, grassland and open shrub-land resource significantly decreased at a rate of 17.1km2/year and 12 km2/year/, respectively. On the other hand in 25 years dense bushland, open bush land, dense shrubland and cultivated land has shown increment in size at a rate of 0.23km2/year,13.5 km2/year, 6.3 km2/year and 0.2 km2/year, respectively within 25 years. The expansion of unpalatable woody species significantly reduced the rangeland size and availability of grasses. The consequence of the decrease in herbaceous biomass production might result in high risk of food insecurity in the area unless proper interventions are made in time.

Keywords: GIS and remote sensing, Dire District, land use/land cover, land sat TM

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Authors: Sofiane Bendoukha, Daniel Moldt, Hayat Bendoukha

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Workflow concepts are essential for the development of remote sensing applications. They can help users to manage and process satellite data and execute scientific experiments on distributed resources. The objective of this paper is to introduce an approach for the specification and the execution of complex scientific workflows in Cloud-like environments. The approach strives to support scientists during the modeling, the deployment and the monitoring of their workflows. This work takes advantage from Petri nets and more pointedly the so-called reference nets formalism, which provides a robust modeling/implementation technique. RENEWGRASS is a tool that we implemented and integrated into the Petri nets editor and simulator RENEW. It provides an easy way to support not experienced scientists during the specification of their workflows. It allows both modeling and enactment of image processing workflows from the remote sensing domain. Our case study is related to the implementation of vegetation indecies. We have implemented the Normalized Differences Vegetation Index (NDVI) workflow. Additionally, we explore the integration possibilities of the Cloud technology as a supplementary layer for the deployment of the current implementation. For this purpose, we discuss migration patterns of data and applications and propose an architecture.

Keywords: cloud computing, scientific workflows, petri nets, RENEWGRASS

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Authors: Sujit Kumar Guchhait, Subir Paul

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One of the major research areas is to find an alternative source of energy to fulfill the energy crisis and environmental problems. The Fuel cell is such kind of energy producing unit. Use of fuel cell to produce renewable energy for commercial purpose is limited by the high cost of Pt based electrode material. Development of high energetic, as well as inexpensive fuel cell electrode materials, is needs of hour to produce clean energy using derive bio-fuel. In this present investigation, inexpensive Cu-Ni-CeO2 electrode material has been synthesized by using pulse current. The surface morphology of the electrode materials is controlled by several deposition parameters to increase the rate of electrochemical oxidation of alcoholic fuel, ethanol. The electrochemical characterization of the developed material was done by Cyclic Voltammetry (CV) and Chronoamperometry (CA) and Electrochemical Impedance Spectroscopy test. It is interesting to find that both these materials have shown high electrocatalytic properties in terms of high exchange current density (I0), low polarization resistance (Rp) and low impedance. It is seen that the addition of CeO2 to Ni-Cu has outperformed Pt as far as high electrocatalytic properties are concerned. The exchange current density on the Cu-Ni-CeO2 electrode surface for ethanol oxidation is about eight times higher than the same on the Pt surface with much lower polarization resistance than the later. The surface morphology of the electrode materials has been revealed by Field Effect Scanning Electron Microscope (FESEM). It is seen that grains are narrow and subspherical with 3D surface containing pores in between two elongated grains. XRD study exhibits the presence of Ni and CeO2 on the Cu surface.

Keywords: electro-catalyst, alcoholic fuel, cyclic voltammetry, potentiodynamic polarization, EIS, XRD, SEM

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Authors: Ionel D. Craiu, Mihai Nedelcu

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Thin-walled cylinders are often used by the offshore industry as columns of floating installations. Based on observed strains, the inverse Finite Element Method (iFEM) may rebuild the deformation of structures. Structural Health Monitoring uses this approach extensively. However, the number of in-situ strain gauges is what determines how accurate it is, and for shell structures with complicated deformation, this number can easily become too high for practical use. Any thin-walled beam member's complicated deformation can be modeled by the Generalized Beam Theory (GBT) as a linear combination of pre-specified cross-section deformation modes. GBT uses bar finite elements as opposed to shell finite elements. This paper proposes an iFEM/GBT formulation for the shape sensing of thin-walled cylinders based on these benefits. This method significantly reduces the number of strain gauges compared to using the traditional inverse-shell finite elements. Using numerical simulations, dent damage detection is achieved by comparing the strain distributions of the undamaged and damaged members. The effect of noise on strain measurements is also investigated.

Keywords: damage detection, generalized beam theory, inverse finite element method, shape sensing

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Authors: Mohammed Al Sulaimani, Hamad Al Manhi

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With the development of Remote Sensing technology, the resolution of optical Remote Sensing images has greatly improved, and images have become largely available. Numerous detectors have been developed for detecting different types of objects. In the past few years, Remote Sensing has benefited a lot from deep learning, particularly Deep Convolution Neural Networks (CNNs). Deep learning holds great promise to fulfill the challenging needs of Remote Sensing and solving various problems within different fields and applications. The use of Unmanned Aerial Systems in acquiring Aerial Photos has become highly used and preferred by most organizations to support their activities because of their high resolution and accuracy, which make the identification and detection of very small features much easier than Satellite Images. And this has opened an extreme era of Deep Learning in different applications not only in feature extraction and prediction but also in analysis. This work addresses the capacity of Machine Learning and Deep Learning in detecting and extracting Oil Leaks from Flowlines (Onshore) using High-Resolution Aerial Photos which have been acquired by UAS fixed with RGB Sensor to support early detection of these leaks and prevent the company from the leak’s losses and the most important thing environmental damage. Here, there are two different approaches and different methods of DL have been demonstrated. The first approach focuses on detecting the Oil Leaks from the RAW Aerial Photos (not processed) using a Deep Learning called Single Shoot Detector (SSD). The model draws bounding boxes around the leaks, and the results were extremely good. The second approach focuses on detecting the Oil Leaks from the Ortho-mosaiced Images (Georeferenced Images) by developing three Deep Learning Models using (MaskRCNN, U-Net and PSP-Net Classifier). Then, post-processing is performed to combine the results of these three Deep Learning Models to achieve a better detection result and improved accuracy. Although there is a relatively small amount of datasets available for training purposes, the Trained DL Models have shown good results in extracting the extent of the Oil Leaks and obtaining excellent and accurate detection.

Keywords: GIS, remote sensing, oil leak detection, machine learning, aerial photos, unmanned aerial systems

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Authors: Navpreet Kaur, Himkusha Thakur, Nirmal Prabhakar

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One of the most publicized and controversial issue in crop production is the use of agrichemicals- also known as pesticides. This is evident in many reports that Organophosphate (OP) insecticides, among the broad range of pesticides are mainly involved in acute and chronic poisoning cases. Therefore, detection of OPs is very necessary for health protection, food and environmental safety. In our study, a nanocomposite of poly (3,4 ethylenedioxythiophene) (PEDOT) and multi-walled carbon nanotubes (MWCNTs) has been deposited electrochemically onto the surface of fluorine doped tin oxide sheets (FTO) for the analysis of malathion OP. The -COOH functionalization of MWCNTs has been done for the covalent binding with amino groups of AChE enzyme. The use of PEDOT-MWCNT films exhibited an excellent conductivity, enables fast transfer kinetics and provided a favourable biocompatible microenvironment for AChE, for the significant malathion OP detection. The prepared PEDOT-MWCNT/FTO and AChE/PEDOT-MWCNT/FTO nano-biosensors were characterized by Fourier transform infrared spectrometry (FTIR), Field emission-scanning electron microscopy (FE-SEM) and electrochemical studies. Electrochemical studies were done using Cyclic Voltammetry (CV) or Differential Pulse Voltammetry (DPV) and Electrochemical Impedance Spectroscopy (EIS). Various optimization studies were done for different parameters including pH (7.5), AChE concentration (50 mU), substrate concentration (0.3 mM) and inhibition time (10 min). The detection limit for malathion OP was calculated to be 1 fM within the linear range 1 fM to 1 µM. The activity of inhibited AChE enzyme was restored to 98% of its original value by 2-pyridine aldoxime methiodide (2-PAM) (5 mM) treatment for 11 min. The oxime 2-PAM is able to remove malathion from the active site of AChE by means of trans-esterification reaction. The storage stability and reusability of the prepared nano-biosensor is observed to be 30 days and seven times, respectively. The application of the developed nano-biosensor has also been evaluated for spiked lettuce sample. Recoveries of malathion from the spiked lettuce sample ranged between 96-98%. The low detection limit obtained by the developed nano-biosensor made them reliable, sensitive and a low cost process.

Keywords: PEDOT-MWCNT, malathion, organophosphates, acetylcholinesterase, nano-biosensor, oxime (2-PAM)

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Authors: Maxim Panov, Evgenia Khairullina, Sergey Ermakov, Oleg Gundobin, Vladimir Kochemirovsky

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The continuous in situ laser-induced catalysis proceeding via generation and growth of nano-sized copper particles was discussed. Also, the simple and lost-cost method for manufacturing of microstructural copper electrodes was proposed. The electrochemical properties of these electrodes were studied by cyclic voltammetry and impedance spectroscopy. The surface of the deposited copper structures (electrodes) was investigated by X-ray photoelectron spectroscopy and atomic force microscopy. These microstructures are highly conductive and porous with a dispersion of pore size ranging from 50 nm to 50 μm. An analytical response of the fabricated copper electrode is 30 times higher than those observed for a pure bulk copper with similar geometric parameters. A study of sensory characteristics for hydrogen peroxide determination showed that the value of Faraday current at the fabricated copper electrode is 2-2.5 orders of magnitude higher than for etalon one.

Keywords: laser-induced deposition, electrochemical electrodes, non-enzymatic sensors, copper

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Authors: Ming-Jong Tsai, T. M. Wu, R. C. Chu

Abstract:

The purpose of this study is to develop an Advanced linear calibration Technique for air flow sensing by using CTA-based Hot wire Anemometry. It contains a host PC with Human Machine Interface, a wind tunnel, a wind speed controller, an automatic data acquisition module, and nonlinear calibration model. To improve the fitting error by using single fitting polynomial, this study proposes a Multiple three-order Polynomial Fitting Method (MPFM) for fitting the non-linear output of a CTA-based Hot wire Anemometry. The CTA-based anemometer with built-in fitting parameters is installed in the wind tunnel, and the wind speed is controlled by the PC-based controller. The Hot-Wire anemometer's thermistor resistance change is converted into a voltage signal or temperature differences, and then sent to the PC through a DAQ card. After completion measurements of original signal, the Multiple polynomial mathematical coefficients can be automatically calculated, and then sent into the micro-processor in the Hot-Wire anemometer. Finally, the corrected Hot-Wire anemometer is verified for the linearity, the repeatability, error percentage, and the system outputs quality control reports.

Keywords: flow rate sensing, hot wire, constant temperature anemometry (CTA), linear calibration, multiple three-order polynomial fitting method (MPFM), temperature compensation

Procedia PDF Downloads 416

Authors: Tingwei Shu, Dong Zhou, Chengjun Guo

Abstract:

Semantic communication is an emerging form of communication that realize intelligent communication by extracting semantic information of data at the source and transmitting it, and recovering the data at the receiving end. It can effectively solve the problem of data transmission under the situation of large data volume, low SNR and restricted bandwidth. With the development of Deep Learning, semantic communication further matures and is gradually applied in the fields of the Internet of Things, Uumanned Air Vehicle cluster communication, remote sensing scenarios, etc. We propose an improved semantic communication system for the situation where the data volume is huge and the spectrum resources are limited during the transmission of remote sensing images. At the transmitting, we need to extract the semantic information of remote sensing images, but there are some problems. The traditional semantic communication system based on Convolutional Neural Network cannot take into account the global semantic information and local semantic information of the image, which results in less-than-ideal image recovery at the receiving end. Therefore, we adopt the improved vision-Transformer-based structure as the semantic encoder instead of the mainstream one using CNN to extract the image semantic features. In this paper, we first perform pre-processing operations on remote sensing images to improve the resolution of the images in order to obtain images with more semantic information. We use wavelet transform to decompose the image into high-frequency and low-frequency components, perform bilinear interpolation on the high-frequency components and bicubic interpolation on the low-frequency components, and finally perform wavelet inverse transform to obtain the preprocessed image. We adopt the improved Vision-Transformer structure as the semantic coder to extract and transmit the semantic information of remote sensing images. The Vision-Transformer structure can better train the huge data volume and extract better image semantic features, and adopt the multi-layer self-attention mechanism to better capture the correlation between semantic features and reduce redundant features. Secondly, to improve the coding efficiency, we reduce the quadratic complexity of the self-attentive mechanism itself to linear so as to improve the image data processing speed of the model. We conducted experimental simulations on the RSOD dataset and compared the designed system with a semantic communication system based on CNN and image coding methods such as BGP and JPEG to verify that the method can effectively alleviate the problem of excessive data volume and improve the performance of image data communication.

Keywords: semantic communication, transformer, wavelet transform, data processing

Procedia PDF Downloads 78

Authors: M. Mominul Haque, Danny KY. Wong

Abstract:

In this paper, we will demonstrate the feasibility of selectively removing the azo dye, Acid Red 1, in the presence of a second dye, Indigo Carmine, at conducting polypyrrole films. A long-term goal of this work is to develop an efficient and effective electrochemical treatment of textile effluents that does not yield any toxic by-products. Specifically, pyrrole was initially electrochemically oxidised in the presence of Acid Red 1 to prepare an Acid Red 1-entrapped polypyrrole film. Next, the Acid Red 1 entrapped film was electrochemically reduced to expel the dye from the film. The film was then ready for use in removing the dye in an Acid Red 1 solution. The entrapment efficiency of the film was then studied by spectroscopically determining the change in the absorbance of the dye solution. These experiments were repeated using Indigo Carmine or a mixture of Acid Red 1 and Indigo Carmine, in place of Acid Red 1. Therefore, this has given rise to an environmentally friendly treatment method for textile effluents. In our work, we have also studied the characteristics of Acid Red 1- and Indigo Carmine-entrapped polypyrrole films by scanning electron microscopy, X-ray diffraction and Fourier transfer infrared spectroscopy.

Keywords: azo dye, electrochemical treatment, polypyrrole, Acid Red 1

Procedia PDF Downloads 407

Authors: Desplanches Maxime

Abstract:

Accurate estimation of the remaining useful life of lithium-ion batteries for electronic devices is crucial. Data-driven methodologies encounter challenges related to data volume and acquisition protocols, particularly in capturing a comprehensive range of aging indicators. To address these limitations, we propose a hybrid approach that integrates an electrochemical model with state-of-the-art data analysis techniques, yielding a comprehensive database. Our methodology involves infusing an aging phenomenon into a Newman model, leading to the creation of an extensive database capturing various aging states based on non-destructive parameters. This database serves as a robust foundation for subsequent analysis. Leveraging advanced data analysis techniques, notably principal component analysis and t-Distributed Stochastic Neighbor Embedding, we extract pivotal information from the data. This information is harnessed to construct a regression function using either random forest or support vector machine algorithms. The resulting predictor demonstrates a 5% error margin in estimating remaining battery life, providing actionable insights for optimizing usage. Furthermore, the database was built from the Newman model calibrated for aging and performance using data from a European project called Teesmat. The model was then initialized numerous times with different aging values, for instance, with varying thicknesses of SEI (Solid Electrolyte Interphase). This comprehensive approach ensures a thorough exploration of battery aging dynamics, enhancing the accuracy and reliability of our predictive model. Of particular importance is our reliance on the database generated through the integration of the electrochemical model. This database serves as a crucial asset in advancing our understanding of aging states. Beyond its capability for precise remaining life predictions, this database-driven approach offers valuable insights for optimizing battery usage and adapting the predictor to various scenarios. This underscores the practical significance of our method in facilitating better decision-making regarding lithium-ion battery management.

Keywords: Li-ion battery, aging, diagnostics, data analysis, prediction, machine learning, electrochemical model, regression

Procedia PDF Downloads 69

Authors: Fikre Belay Tekulu

Abstract:

The Adigrat town lies in the Tigray region of Ethiopia. This region is mountainous and experiences a semiarid type of climate. Most of the rainfall occurs in four months of the year, which are June to September. During this season, flood is a common natural disaster, especially in urban areas. In this paper, an attempt is made to identify flood-prone areas in Adigrat town using Boolean logic with GIS and remote sensing techniques. Three parameters were incorporated as land use type, elevation, and slope. Boolean logic was used as land use equal to buildup land, elevation less than 2430 m, and slope less than 5 degrees. As a result, 0.575 km² was identified severely affected by floods during the rainy season.

Keywords: flood, GIS, hydrology, Adigrat

Procedia PDF Downloads 141

Authors: Xiang Jianhong, Wang Cong, Wang Linyu

Abstract:

With the rise of medical IoT technologies, Wireless body area networks (WBANs) can collect fetal electrocardiogram (FECG) signals to support telemedicine analysis. The compressed sensing (CS)-based WBANs system can avoid the sampling of a large amount of redundant information and reduce the complexity and computing time of data processing, but the existing algorithms have poor signal compression and reconstruction performance. In this paper, a Joint block multi-orthogonal least squares (JBMOLS) algorithm is proposed. We apply the FECG signal to the Joint block sparse model (JBSM), and a comparative study of sparse transformation and measurement matrices is carried out. A FECG signal compression transmission mode based on Rbio5.5 wavelet, Bernoulli measurement matrix, and JBMOLS algorithm is proposed to improve the compression and reconstruction performance of FECG signal by CS-based WBANs. Experimental results show that the compression ratio (CR) required for accurate reconstruction of this transmission mode is increased by nearly 10%, and the runtime is saved by about 30%.

Keywords: telemedicine, fetal ECG, compressed sensing, joint sparse reconstruction, block sparse signal

Procedia PDF Downloads 127

Authors: Zohreh Derikvand, Hadis Cheraghi, Azadeh Azadbakht, Vaclav Eigner, Michal Dusek

Abstract:

Two new one and two dimensional metal organic coordination polymers of Cu(II), [Cu(3-nph)2(H2O)2pz]n (1) and Ag(I), {[Ag(3-nph)pz].H2O}n (2) with pyrazine (pz) and 3- nitrophthalic acid (3-nph) have been synthesized and characterized by elemental analysis, spectral (IR, UV-Vis), thermal (TG/DTG) analysis and single crystal X-ray diffraction. We used these compounds to preparation modified electrode with Au/Pt nanosparticles in order to investigation electrochemistry and electrocatalysis activities. The surface structure and composition of the sensor were characterized by scanning electron microscopy (SEM). The Ag(I) coordination polymer shows a 2D layer structure constructed from dinuclear silver (I) building blocks in which two crystallographically Ag+ ions are connected to each other by a covalent bond. The pyrazine ligands adopt μ2 bridging modes, linking the metal centers into a one and two -dimensional coordination framework in 1 and 2. The two AgI cations are surrounded by pyrazine and 3-nitrophthalate mono anions and indicate distorted tetrahedral geometry. In the crystal structures of Ag(I) complex there are non-classical hydrogen bonding arrangements, C–O•••π and π–π stacking interactions. In Cu(II) coordination polymer, the coordination geometry around Cu(II) atom is a distorted octahedron. Interestingly, the structural analysis illustrates that the strong and weak hydrogen bond accompanied with C–H•••π and C–O•••π stacking interactions assemble the crystal structure of 1 and 2 into fascinating 3D supramolecular architecture.

Keywords: 3-nithrophethalic acid, crystal structure, coordination polymer, electrocatalysis

Procedia PDF Downloads 319

Authors: Kaveh Shahi, Helmi Z. M. Shafri, Ebrahim Taherzadeh

Abstract:

In remote sensing, shadow causes problems in many applications such as change detection and classification. It is caused by objects which are elevated, thus can directly affect the accuracy of information. For these reasons, it is very important to detect shadows particularly in urban high spatial resolution imagery which created a significant problem. This paper focuses on automatic shadow detection based on a new spectral index for multispectral imagery known as Shadow Detection Index (SDI). The new spectral index was tested on different areas of World-View 2 images and the results demonstrated that the new spectral index has a massive potential to extract shadows effectively and automatically.

Keywords: spectral index, shadow detection, remote sensing images, World-View 2

Procedia PDF Downloads 538

Authors: Vishnu Pratap Singh Kirar

Abstract:

The main aim of the communication system is to achieve maximum performance. In cognitive radio, any user or transceiver have the ability to sense best suitable channel, while the channel is not in use. It means an unlicensed user can share the spectrum of licensed user without any interference. Though the spectrum sensing consumes a large amount of energy and it can reduce by applying various artificial intelligent methods for determining proper spectrum holes. It also increases the efficiency of Cognitive Radio Network (CRN). In this survey paper, we discuss the use of different learning models and implementation of Artificial Neural Network (ANN) to increase the learning and decision-making capacity of CRN without affecting bandwidth, cost and signal rate.

Keywords: artificial neural network, cognitive radio, cognitive radio networks, back propagation, spectrum sensing

Procedia PDF Downloads 609