Search results for: in-situ atmospheric sensing

Authors: Mahdi Pirmoradian, Olayinka Adigun, Christos Politis

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Cooperative spectrum sensing is a crucial challenge in cognitive radio networks. Cooperative sensing can increase the reliability of spectrum hole detection, optimize sensing time and reduce delay in cooperative networks. In this paper, an efficient central capacity optimization algorithm is proposed to minimize cooperative sensing time in a homogenous sensor network using OR decision rule subject to the detection and false alarm probabilities constraints. The evaluation results reveal significant improvement in the sensing time and normalized capacity of the cognitive sensors.

Keywords: cooperative networks, normalized capacity, sensing time

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Authors: Jossitt Williams Vargas Cruz, Aura Jazmín Pérez Ríos

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The variations of solar dynamics have become a relevant topic of study due to the effects of climate changes generated on the earth. One of the most disconcerting aspects is the variability that the sun has on the climate is the role played by sunspots (extra-atmospheric variable) in the modulation of the Cosmic Rays CR (extra-atmospheric variable). CRs influence the earth's climate by affecting cloud formation (atmospheric variable), and solar cycle influence is associated with the presence of solar storms, and the magnetic activity is greater, resulting in less CR entering the earth's atmosphere. The different methods of climate prediction in Colombia do not take into account the extra-atmospheric variables. Therefore, correlations between atmospheric and extra-atmospheric variables were studied in order to implement a Python code based on neural networks to make the prediction of the extra-atmospheric variable with the highest correlation.

Keywords: correlations, cosmic rays, sun, sunspots and variations.

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Authors: You-Lin Wu, Zong-Xian Wu, Jing-Jenn Lin, Shih-Hung Lin

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In this work, a polysilicon wire (PSW) coated with a mixture of 3-aminopropyltriethoxysilane (r-APTES) and Al2O3 nanoparticles as the sensing membrane prepared with various Al2O3/r-APTES and dispersing agent/r-APTES ratios for pH sensing is studied. The r-APTES and dispersed Al2O3 nanoparticles mixture was directly transferred to PSW surface by solution phase deposition (SPD). It is found that using a mixture of Al2O3 nanoparticles and r-APTES as the sensing membrane help in improving the pH sensing of the PSW sensor and a 5 min SPD deposition time is the best. Dispersing agent is found to be necessary for better pH sensing when preparing the mixture of Al2O3 nanoparticles and r-APTES. The optimum condition for preparing the mixture is found to be Al2O3/r-APTES ratio of 2% and dispersing agent/r-APTES ratio of 0.3%.

Keywords: al2o3 nanoparticles, ph sensing, polysilicon wire sensor, r-aptes

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Authors: Joel F. Campbell, Bing Lin, Michael Obland, Susan Kooi, Tai-Fang Fan, Byron Meadows, Edward Browell, Wayne Erxleben, Doug McGregor, Jeremy Dobler, Sandip Pal, Christopher O'Dell, Ken Davis

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The Active Sensing of CO₂ Emissions over Nights, Days, and Seasons (ASCENDS) CarbonHawk Experiment Simulator (ACES) is a NASA Langley Research Center instrument funded by NASA’s Science Mission Directorate that seeks to advance technologies critical to measuring atmospheric column carbon dioxide (CO₂ ) mixing ratios in support of the NASA ASCENDS mission. The ACES instrument, an Intensity-Modulated Continuous-Wave (IM-CW) lidar, was designed for high-altitude aircraft operations and can be directly applied to space instrumentation to meet the ASCENDS mission requirements. The ACES design demonstrates advanced technologies critical for developing an airborne simulator and spaceborne instrument with lower platform consumption of size, mass, and power, and with improved performance. The Atmospheric Carbon and Transport – America (ACT-America) is an Earth Venture Suborbital -2 (EVS-2) mission sponsored by the Earth Science Division of NASA’s Science Mission Directorate. A major objective is to enhance knowledge of the sources/sinks and transport of atmospheric CO₂ through the application of remote and in situ airborne measurements of CO₂ and other atmospheric properties on spatial and temporal scales. ACT-America consists of five campaigns to measure regional carbon and evaluate transport under various meteorological conditions in three regional areas of the Continental United States. Regional CO₂ distributions of the lower atmosphere were observed from the C-130 aircraft by the Harris Corp. Multi-Frequency Fiber Laser Lidar (MFLL) and the ACES lidar. The airborne lidars provide unique data that complement the more traditional in situ sensors. This presentation shows the applications of CO₂ lidars in support of these science needs.

Keywords: CO₂ measurement, IMCW, CW lidar, laser spectroscopy

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Authors: B. Hossen, Y. Helmut

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Soil salinity is a major problem for the coastal region of Bangladesh, which has been increasing for the last four decades. Determination of soil salinity is essential for proper land use planning for agricultural crop production. The aim of the research is to estimate and monitor the soil salinity in the study area. Remote sensing can be an effective tool for detecting soil salinity in data-scarce conditions. In the research, Landsat 8 is used, which required atmospheric and radiometric correction, and nine soil salinity indices are applied to develop a soil salinity map. Ground soil salinity data, i.e., EC value, is collected as a printed map which is then scanned and digitized to develop a point shapefile. Linear regression is made between satellite-based generated map and ground soil salinity data, i.e., EC value. The results show that maximum R² value is found for salinity index SI 7 = G*R/B representing 0.022. This minimal R² value refers that there is a negligible relationship between ground EC value and salinity index generated value. Hence, these indices are not appropriate to assess soil salinity though many studies used those soil salinity indices successfully. Therefore, further research is necessary to formulate a model for determining the soil salinity in the coastal of Bangladesh.

Keywords: soil salinity, EC, Landsat 8, salinity indices, linear regression, remote sensing

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Authors: Tallataf Rasheed, Adnan Rashdi, Ahmad Naeem Akhtar

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The accurate spectrum sensing is a fundamental requirement of dynamic spectrum access for deployment of Cognitive Radio Network (CRN). To acheive this requirement a Reliability factors based Fuzzy Logic (RFL) Scheme for Spectrum Sensing has been proposed in this paper. Cognitive Radio User (CRU) predicts the presence or absence of Primary User (PU) using energy detector and calculates the Reliability factors which are SNR of sensing node, threshold of energy detector and decision difference of each node with other nodes in a cooperative spectrum sensing environment. Then the decision of energy detector is combined with Reliability factors of sensing node using Fuzzy Logic. These Reliability Factors used in RFL Scheme describes the reliability of decision made by a CRU to improve the local spectrum sensing. This Fuzzy combining scheme provides the accuracy of decision made by sensornode. The simulation results have shown that the proposed technique provide better PU detection probability than existing Spectrum Sensing Techniques.

Keywords: cognitive radio, spectrum sensing, energy detector, reliability factors, fuzzy logic

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Authors: Mehtap Çalışkan, Nilüfer Yıldız Varan, Volkan Kaplan

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In this study, the effects of an atmospheric plasma treatment on the durability of water and oil repellent finishes of PET and PET/Spandex fabrics were tested. Fabrics were treated with a low-frequency atmospheric pressure glow discharge. After plasma treatments, the water and oil repellent finishes were applied using pad-dry-cure method. It was observed that plasma treatments improved the durability finish for all fabrics.

Keywords: atmospheric plasma, durable coating, oil repellency, PET/spandex fabrics, water repellency

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Authors: M. Ranjeeth, S. Anuradha

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Spectrum sensing is the main feature of cognitive radio technology. Spectrum sensing gives an idea of detecting the presence of the primary users in a licensed spectrum. In this paper we compare the theoretical results of detection probability of different fading environments like Rayleigh, Rician, Nakagami-m fading channels with the simulation results using energy detection based spectrum sensing. The numerical results are plotted as P_f Vs P_d for different SNR values, fading parameters. It is observed that Nakagami fading channel performance is better than other fading channels by using energy detection in spectrum sensing. A MATLAB simulation test bench has been implemented to know the performance of energy detection in different fading channel environment.

Keywords: spectrum sensing, energy detection, fading channels, probability of detection, probability of false alarm

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Authors: C.W. Kan

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This paper investigates the use of atmospheric pressure plasma for improving the surface hydrophobicity of polyurethane synthetic leather with tetramethylsilane (TMS). The atmospheric pressure plasma treatment with TMS is a single-step process to enhance the hydrophobicity of polyurethane synthetic leather. The hydrophobicity of the treated surface was examined by contact angle measurement. The physical and chemical surface changes were evaluated by scanning electron microscopy (SEM) and infrared spectroscopy (FTIR). The purpose of this paper is to provide learning materials for understanding how to use atmospheric pressure plasma in the textile finishing process to transform a hydrophilic surface to hydrophobic.

Keywords: Learning materials, atmospheric pressure plasma treatment, hydrophobic, hydrophilic, surface

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Authors: Kostas Philippopoulos, Chris G. Tzanis, Despina Deligiorgi

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Climate change adaptation requires the exploitation of renewable energy sources such as wind. However, climate variability can affect the regional wind energy potential and consequently the available wind power production. The goal of the research project is to examine the impact of atmospheric circulation on wind energy production over Greece. In the context of synoptic climatology, the proposed novel methodology employs Self-Organizing Maps for grouping and classifying the atmospheric circulation and nationally-aggregated capacity factor time series for a 30-year period. The results indicate the critical effect of atmospheric circulation on the national aggregated wind energy production values and therefore address the issue of optimum distribution of wind farms for a specific region.

Keywords: wind energy, atmospheric circulation, capacity factor, self-organizing maps

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Authors: Cam Nguyen

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Rapid, accurate, and safe sensing and imaging of physical quantities or structures finds many applications and is of significant interest to society. Sensing and imaging using radio-frequency (RF) techniques, particularly, has gone through significant development and subsequently established itself as a unique territory in the sensing world. RF sensing and imaging has played a critical role in providing us many sensing and imaging abilities beyond our human capabilities, benefiting both civilian and military applications - for example, from sensing abnormal conditions underneath some structures’ surfaces to detection and classification of concealed items, hidden activities, and buried objects. We present the developments of several sensing and imaging systems implementing RF technologies like ultra-wide band (UWB), synthetic-pulse, and interferometry. These systems are fabricated completely using RF integrated circuits. The UWB impulse system operates over multiple pulse durations from 450 to 1170 ps with 5.5-GHz RF bandwidth. It performs well through tests of various samples, demonstrating its usefulness for subsurface sensing. The synthetic-pulse system operating from 0.6 to 5.6 GHz can assess accurately subsurface structures. The synthetic-pulse system operating from 29.72-37.7 GHz demonstrates abilities for various surface and near-surface sensing such as profile mapping, liquid-level monitoring, and anti-personnel mine locating. The interferometric system operating at 35.6 GHz demonstrates its multi-functional capability for measurement of displacements and slow velocities. These RF sensors are attractive and useful for various surface and subsurface sensing applications. This paper was made possible by NPRP grant # 6-241-2-102 from the Qatar National Research Fund (a member of Qatar Foundation). The statements made herein are solely the responsibility of the authors.

Keywords: RF sensors, radars, surface sensing, subsurface sensing

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Authors: Satyendra Mourya, Jyoti Jaiswal, Gaurav Malik, Brijesh Kumar, Ramesh Chandra

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Present work describes the fabrication and sensing characteristics of the Pd-Pt decorated nanostructured silicon carbide (SiC) thin films on anodized porous silicon (PSi) substrate by RF magnetron sputtering. The gas sensing performance of Pd-Pt/SiC/PSi sensing electrode towards H2 gas under low (10–400 ppm) detection limit and high operating temperature regime (25–600 °C) were studied in detail. The chemiresistive sensor exhibited high selectivity, good sensing response, fast response/recovery time with excellent stability towards H2 at high temperature. The selectivity measurement of the sensing electrode was done towards different oxidizing and reducing gases and proposed sensing mechanism discussed in detail. Therefore, the investigated Pd-Pt/SiC/PSi structure may be a highly sensitive and selective hydrogen gas sensing electrode for deployment in extreme environment applications.

Keywords: RF Sputtering, silicon carbide, porous silicon, hydrogen gas sensor

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Authors: Elena Castillo-López, Raúl Pereda, Julio Manuel de Luis, Rubén Pérez, Felipe Piña

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Sediments are an important source of accumulation of toxic contaminants within the aquatic environment. Bioassays are a powerful tool for the study of sediments in relation to their toxicity, but they can be expensive. This article presents a methodology to estimate the main physical property of intertidal sediments in coastal zones: heavy metals concentration. This study, which was developed in the Bay of Santander (Spain), applies classical and robust statistic to CASI-2 hyperspectral images to estimate heavy metals presence and ecotoxicity (TOC). Simultaneous fieldwork (radiometric and chemical sampling) allowed an appropriate atmospheric correction to CASI-2 images.

Keywords: remote sensing, intertidal sediment, airborne sensors, heavy metals, eTOCoxicity, robust statistic, estimation

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Authors: Sumaira Hafeez, Saira Akram

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Albeit the populace in metropolitan regions on the planet develops each year, the urban communities battling to adapt to the expanded metropolitan movement grow at different rates. Land Surface Temperature and other atmospheric parameters of the area of not really settled using Landsat pictures more than 10 years isolated. The LULC types were moreover arranged using managed gathering techniques. Quick urbanization is changing the current examples of Land Use Land Cover (LULC) all around the world, which is thusly expanding the Land Surface Temperature (LST) other atmospheric parameters in numerous districts. Present review was centered around assessing the current and recreating the future LULC and Land Surface Temperature patterns in the elevated climate of lower Himalayan district of Pakistan. Past examples of LULC and Land Surface Temperature were distinguished through the multi-unearthly Landsat satellite pictures during the 1995–2019 information period. The future forecasts were made for the year 2030 to work out LULC and LST changes separately, utilizing their previous examples. The review presumes that the reliably extending encroachment of the city's as of late advanced provincial regions over the totally open have went with an overall warming of the district's typical. Meteorological parameters over the earlier ten years and that permitting the land to lie void for a significant long time resulting to clearing the country fields for future metropolitan improvement is a preparation that has lamentable natural effects.

Keywords: surface urban heat island, land surface temperature, urban climate change, spatial analysis of meterological and atmospheric science

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Authors: Amir H. Alavi, Kaveh Barri, Qianyun Zhang

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This study presents a new generation of lightweight and mechanically tunable structural composites with sensing and energy harvesting functionalities. This goal is achieved by integrating metamaterial and triboelectric energy harvesting concepts. Proof-of-concept polymeric beam prototypes are fabricated using 3D printing methods based on the proposed concept. Experiments and theoretical analyses are conducted to quantitatively investigate the mechanical and electrical properties of the designed multifunctional beams. The results show that these integrated structural elements can serve as nanogenerators and distributed sensing mediums without a need to incorporating any external sensing modules and electronics. The feasibility of design self-sensing and self-powering structural elements at multiscale for next generation infrastructure systems is further discussed.

Keywords: multifunctional structures, composites, metamaterial, triboelectric nanogenerator, sensors, structural health monitoring, energy harvesting

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Authors: Andrew Hall, Paul Clarkson

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Climate change is predicted to increase the number of extreme weather events intensifying the strain on Railway Earthworks. This paper describes the use of Distributed Rayleigh Sensing to monitor low frequency activity on a vulnerable earthworks sectionprone to landslides alongside a railway line in Northern Spain. The vulnerable slope is instrumented with conventional slope stability sensors allowing an assessment to be conducted of the application of Distributed Rayleigh Sensing as an earthwork condition monitoring tool to enhance the resilience of railway networks.

Keywords: condition monitoring, railway earthworks, distributed rayleigh sensing, climate change

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Authors: Luis Gimeno, Rosmeri da Rocha, Raquel Nieto, Tercio Ambrizzi, Alex Ramos, Anita Drumond

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The transport of moisture from oceanic sources to the continents represents the atmospheric branch of the water cycle, forming the connection between evaporation from the ocean and precipitation over the continents. In this regard two large scale dynamical/meteorological structures appear to play a key role, namely Low Level Jet (LLJ) systems and Atmospheric Rivers (ARs). The former are particularly important in tropical and subtropical regions; the latter is mostly confined to extratropical regions. A key question relates to the anomalies in the transport of moisture observed during natural hazards related to extremes of precipitation (i.e., drought or wet spells). In this study we will be focused on these two major atmospheric moisture transport mechanisms (LLJs and ARs) and its role in precipitation extreme events (droughts and wet spells) in the Amazonia paying particular attention to i) intensification (decreasing) of moisture transport by them and its role in wet spells (droughts), and ii) changes in their positions and occurrence with associated flooding and wet spells.

Keywords: droughts, wet spells, amazonia, LLJs, atmospheric rivers

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Authors: Jun Su Park, Byung Kwan Oh, Jin Woo Hwang, Yousok Kim, Hyo Seon Park

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For the structural safety, the maximum stress calculated from the stress distribution of a structure is widely used. The stress distribution can be estimated by deformed shape of the structure obtained from measurement. Although the estimation of stress is strongly affected by the location and number of sensing points, most studies have conducted the stress estimation without reasonable basis on sensing plan such as the location and number of sensors. In this paper, an optimal sensing technique for estimating the stress distribution is proposed. This technique proposes the optimal location and number of sensing points for a 2-D frame structure while minimizing the error of stress distribution between analytical model and estimation by cubic smoothing splines using genetic algorithm. To verify the proposed method, the optimal sensor measurement technique is applied to simulation tests on 2-D steel frame structure. The simulation tests are performed under various loading scenarios. Through those tests, the optimal sensing plan for the structure is suggested and verified.

Keywords: genetic algorithm, optimal sensing, optimizing sensor placements, steel frame structure

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Authors: Min-ju Kwon, Chae-won Kim, Jeong-yun Seo, Hee-guk Chae, Yong-seo Koo

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In this paper, we presented the LDO (low-dropout) regulator which enhanced the PSRR by applying the constant current source generation technique through the BGR (Band Gap Reference) to form the noise sensing circuit. The current source through the BGR has a constant current value even if the applied voltage varies. Then, the noise sensing circuit, which is composed of the current source through the BGR, operated between the error amplifier and the pass transistor gate of the LDO regulator. As a result, the LDO regulator has a PSRR of -68.2 dB at 1k Hz, -45.85 dB at 1 MHz and -45 dB at 10 MHz. the other performance of the proposed LDO was maintained at the same level of the conventional LDO regulator.

Keywords: LDO regulator, noise sensing circuit, current reference, pass transistor

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Authors: Spoorthi Srupad

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Environmental Impact Assessment (EIA) stands as a critical engineering application facilitated by Earth Resources and Environmental Remote Sensing. Employing advanced technologies, this process enables a systematic evaluation of potential environmental impacts arising from engineering projects. Remote sensing techniques, including satellite imagery and geographic information systems (GIS), play a pivotal role in providing comprehensive data for assessing changes in land cover, vegetation, water bodies, and air quality. This abstract delves into the significance of EIA in engineering, emphasizing its role in ensuring sustainable and environmentally responsible practices. The integration of remote sensing technologies enhances the accuracy and efficiency of impact assessments, contributing to informed decision-making and the mitigation of adverse environmental consequences associated with engineering endeavors.

Keywords: environmental impact assessment, engineering applications, sustainability, environmental monitoring, remote sensing, geographic information systems, environmental management

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Authors: Yilei Song, Linlin Tian, Ning Zhao

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Turbulence energetics and structures in the wake of large-scale wind turbines under the stably-stratified atmospheric boundary layer (SABL) can be complicated due to the presence of low-level jets (LLJs), a region of higher wind speeds than the geostrophic wind speed. With a modified one-k-equation, eddy viscosity model specified for atmospheric flows as the sub-grid scale (SGS) model, a realistic atmospheric state of the stable ABL is well reproduced by large-eddy simulation (LES) techniques. Corresponding to the precursor stably stratification, the detailed wake properties of a standard 5-MW wind turbine represented as an actuator line model are provided. An engineering model is proposed for wake prediction based on the simulation statistics and gets validated. Results confirm that the proposed wake model can provide good predictions for wind turbines under the SABL.

Keywords: large-eddy simulation, stably-stratified atmospheric boundary layer, wake model, wind turbine wake

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Authors: Sikander Nawaz Khan

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Natural disasters like flood, earthquake, cyclone, volcanic eruption and others are causing immense losses to the property and lives every year. Current status and actual loss information of natural hazards can be determined and also prediction for next probable disasters can be made using different remote sensing and mapping technologies. Global Positioning System (GPS) calculates the exact position of damage. It can also communicate with wireless sensor nodes embedded in potentially dangerous places. GPS provide precise and accurate locations and other related information like speed, track, direction and distance of target object to emergency responders. Remote Sensing facilitates to map damages without having physical contact with target area. Now with the addition of more remote sensing satellites and other advancements, early warning system is used very efficiently. Remote sensing is being used both at local and global scale. High Resolution Satellite Imagery (HRSI), airborne remote sensing and space-borne remote sensing is playing vital role in disaster management. Early on Geographic Information System (GIS) was used to collect, arrange, and map the spatial information but now it has capability to analyze spatial data. This analytical ability of GIS is the main cause of its adaption by different emergency services providers like police and ambulance service. Full potential of these so called 3S technologies cannot be used in alone. Integration of GPS and other remote sensing techniques with GIS has pointed new horizons in modeling of earth science activities. Many remote sensing cases including Asian Ocean Tsunami in 2004, Mount Mangart landslides and Pakistan-India earthquake in 2005 are described in this paper.

Keywords: disaster mitigation, GIS, GPS, remote sensing

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Authors: Spoorthi Sripad

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Rapid advancements in LiDAR (Light Detection and Ranging) technology, coupled with the synergy of remote sensing, have revolutionized Earth observation methodologies. This paper delves into the transformative impact of integrated LiDAR and remote sensing systems. Focusing on miniaturization, cost reduction, and improved resolution, the study explores the evolving landscape of terrestrial and aquatic environmental monitoring. The integration of multi-wavelength and dual-mode LiDAR systems, alongside collaborative efforts with other remote sensing technologies, presents a comprehensive approach. The paper highlights the pivotal role of LiDAR in environmental assessment, urban planning, and infrastructure development. As the amalgamation of LiDAR and remote sensing reshapes Earth observation, this research anticipates a paradigm shift in our understanding of dynamic planetary processes.

Keywords: LiDAR, remote sensing, earth observation, advancements, integration, environmental monitoring, multi-wavelength, dual-mode, technology, urban planning, infrastructure, resolution, miniaturization

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Authors: Shivani A. Singh, Pravin S. More

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In the present inspection, we indicate the falsification of Fe-doped graphene nanoparticles by modified Hummers method. Structural and physiochemical properties of the resulting pallets were explored with the help of ultraviolet-visible spectroscopy (UV-Vis), Fourier transform infrared spectroscopy (FTIR), X-ray powder diffraction (XRD) and scanning electron microscopy (SEM), Photoluminescence spectroscopy (PL) for graphene sample exhibits absorption peaks ~248nm. Pure graphene shows PL peak at 348 nm. After doping of Fe with graphene the PL peak shifted from 348 nm to 332 nm. The oxidation degree, i.e. the relative amount of oxygen functional groups was estimated from the relative intensities of the oxygen related bands (ORB) in the FTIR measurements. These analyses show that this modified material can be useful for gas sensing applications and to be used in diverse areas.

Keywords: chemical doping, graphene, gas sensing, sensing

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Authors: Deepa Das, Susmita Das

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Cognitive Radio (CR) is an emerging technology to combat the spectrum scarcity issues. This is achieved by consistently sensing the spectrum, and detecting the under-utilized frequency bands without causing undue interference to the primary user (PU). In soft decision fusion (SDF) based cooperative spectrum sensing, various evolutionary algorithms have been discussed, which optimize the weight coefficient vector for maximizing the detection performance. In this paper, we propose the hybrid invasive weed optimization and particle swarm optimization (IWO/PSO) algorithm as a fast and global optimization method, which improves the detection probability with a lesser sensing time. Then, the efficiency of this algorithm is compared with the standard invasive weed optimization (IWO), particle swarm optimization (PSO), genetic algorithm (GA) and other conventional SDF based methods on the basis of convergence and detection probability.

Keywords: cognitive radio, spectrum sensing, soft decision fusion, GA, PSO, IWO, hybrid IWO/PSO

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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: Maryam Kiani

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The self-sensing capability opens up new possibilities for structural health monitoring, offering real-time information on the condition and performance of constructions. The synthesis and characterization of these functional 2D material geopolymers will be explored in this study. Various fabrication techniques, including mixing, dispersion, and coating methods, will be employed to ensure uniform distribution and integration of the 2D materials within the geopolymers. The resulting composite materials will be evaluated for their mechanical strength, electrical conductivity, and sensing capabilities through rigorous testing and analysis. The potential applications of these self-sensing geopolymers are vast. They can be used in infrastructure projects, such as bridges, tunnels, and buildings, to provide continuous monitoring and early detection of structural damage or degradation. This proactive approach to maintenance and safety can significantly improve the lifespan and efficiency of constructions, ultimately reducing maintenance costs and enhancing overall sustainability. In conclusion, the development of functional 2D material geopolymers as self-sensing materials presents an exciting advancement in the construction industry. By integrating these innovative materials into structures, we can create a new generation of intelligent, self-monitoring constructions that can adapt and respond to their environment.

Keywords: 2D materials, geopolymers, electrical properties, self-sensing

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Authors: Ping-Ping Zhang, Hui-Zhang, Xu-Hui Sun

Abstract:

Highly-uniform In2O3/CuO bilayer and multilayer porous thin films were successfully fabricated using self-assembled soft template and simple sputtering deposition technique. The sensor based on the In2O3/CuO bilayer porous thin film shows obviously improved sensing performance to ethanol at the lower working temperature, compared to single layer counterpart sensors. The response of In2O3/CuO bilayer sensors exhibits nearly 3 and 5 times higher than those of the single layer In2O3 and CuO porous film sensors over the same ethanol concentration, respectively. The sensing mechanism based on p-n hetero-junction, which contributed to the enhanced sensing performance was also experimentally confirmed by a control experiment which the SiO2 insulation layer was inserted between the In2O3 and CuO layers to break the p-n junction. In addition, the sensing performance can be further enhanced by increasing the number of In2O3/CuO junction layers. The facile process can be easily extended to the fabrication of other semiconductor oxide gas sensors for practical sensing applications.

Keywords: gas sensor, multilayer porous thin films, In2O3/CuO, p-n junction

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Authors: Amritansh Agarwal, Tejaswi Agarwal

Abstract:

Forest ecosystem plays very important role in the global carbon cycle. It stores about 80% of all above ground and 40% of all below ground terrestrial organic carbon. There is much interest in the extent of tropical forests and their rates of deforestation for two reasons: greenhouse gas contributions and the impact of profoundly negative biodiversity. Deforestation has many ecological, social and economic consequences, one of which is the loss of biological diversity. The rapid deployment of remote sensing (RS) satellites and development of RS analysis techniques in the past three decades have provided a reliable, effective, and practical way to characterize terrestrial ecosystem properties. Global estimates of tropical deforestation vary widely and range from 50,000 to 170,000 km2 /yr Recent FAO tropical deforestation estimates for 1990–1995 cite 116,756km2 / yr globally. Remote Sensing can prove to be a very useful tool in monitoring of forests and associated deforestation to a sufficient level of accuracy without the need of physically surveying the forest areas as many of them are physically inaccessible. The methodology for the assessment of forest cover using digital image processing (ERDAS) has been followed. The satellite data for the study was procured from USGS website in the digital format. While procuring the satellite data, care was taken to ensure that the data was cloud and aerosol free by making using of FLAASH atmospheric correction technique. The Normalized Difference Vegetation Index (NDVI) has been used as a numerical indicator of the reduction in ground biomass. NDVI = (near I.R - Red)/ (near I.R + Red). After calculating the NDVI variations and associated mean we have analysed the change in ground biomass. Through this paper we have tried to indicate the rate of deforestation over a given period of time by comparing the forest cover at different time intervals. With the help of remote sensing and GIS techniques it is clearly shows that the total forest cover is continuously degrading and transforming into various land use/land cover category.

Keywords: remote sensing, deforestation, supervised classification, NDVI change detection

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Authors: Z. O. Apotiola, J. F. Fashakin

Abstract:

A study was conducted to investigate the storage stability of Mr Chef and Annapurna salts. The salts were bought from Mile 12 market in Lagos State and were stored for a period of six months. The stability of the iodine content was then investigated by storing some at ambient temperature (24-30oC) and some at atmospheric temperature (21-35 oC), and from each storage condition, a sample each was taken every month to analyze for the iodine and moisture contents. The result shows that there was a significant difference between Mr Chef and the standard and Annapurna and the standard. The iodine content of Mr Chef stored at ambient and atmospheric temperature decreases progressively from 48.70±0.00-37.00±0.00 and 47.60±0.00-11.60±0.00 respectively. And that of Annapurna at both ambient and atmospheric temperature also decreases progressively from 47.60±0.00-36.60±0.00 and 47.60±0.00-10.60±0.00 respectively. Also, the moisture content of both salts at the zero month to the sixth month both at room temperature and atmospheric temperature increases from 1.11±0.00-1.70±0.00 and 1.11±0.00-2.40±0.00 respectively. The results of the heavy metals shows that only Copper, Zinc and Cobalt were detected at the first and the sixth month in both Mr Chef and Annapurna which ranges from 0.15±0.00-0.38±0.00 and 0.18±0.00 - 3.50±0.00 respectively. Hence, the stability of iodine in salt is influenced by the storage conditions it is subjected to and the length of time it is been stored.

Keywords: salt, iodine, stability, ambient, atmospheric temperature

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