Search results for: sensing range

Authors: Ouerchefani Dalel, Mahdhaoui Basma

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Land use change is one of the important factors needed to evaluate later on the impact of human actions on land degradation. This work present the application of a methodology based on remote sensing for evaluation land use change in an arid region of Tunisia. This methodology uses Landsat TM and ETM+ images to produce land use maps by supervised classification based on ground truth region of interests. This study showed that it was possible to rely on radiometric values of the pixels to define each land use class in the field. It was also possible to generate 3 land use classes of the same study area between 1988 and 2011.

Keywords: land use, change, remote sensing, GIS

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Authors: Arpan Kumar Nayak, Debabrata Pradhan

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A simple, single-step and one-pot hydrothermal method was employed to synthesize WO₃-SnO₂ mixed nanostructured metal oxides at 200°C in 12h. The SnO₂ nanoparticles were found to be uniformly decorated on the WO₃ nanoplates. Though it is widely known that noble metals such as Pt, Pd doping or decoration on metal oxides improve the sensing response and sensitivity, we varied the SnO₂ concentration in the WO₃-SnO₂ mixed oxide and demonstrated their performance in ammonia, ethanol and acetone sensing. The sensing performance of WO₃-(x)SnO₂ [x = 0.27, 0.54, 1.08] mixed nanostructured oxides was found to be not only superior to that of pristine oxides but also higher/better than that of reported noble metal-based sensors. The sensing properties (selectivity, limit of detection, response and recovery times) are measured as a function of operating temperature (150-350°C). In particular, the gas selectivity is found to be highly temperature-dependent with optimum performance obtained at 200°C, 300°C and 350°C for ammonia, ethanol, and acetone, respectively. The present results on cost effective WO₃-SnO₂ sensors can find potential application in human breath analysis by noninvasive detection.

Keywords: gas sensing, mixed oxides, nanoplates, ammonia, ethanol, acetone

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Authors: Chyuan Haur Kao, Hsiang Chen, Yu Sheng Tsai, Chen Hao Hung, Yu Shan Lee

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Dielectric electrolyte-insulator-semiconductor sensing membranes-based biosensors have been intensively investigated because of their simple fabrication, low cost, and fast response. However, to enhance their sensing performance, it is worthwhile to explore alternative materials, distinct processes, and novel treatments. An ISFET can be viewed as a variation of MOSFET with the dielectric oxide layer as the sensing membrane. Then, modulation on the work function of the gate caused by electrolytes in various ion concentrations could be used to calculate the ion concentrations. Recently, owing to the advancement of CMOS technology, some high dielectric materials substrates as the sensing membranes of electrolyte-insulator-semiconductor (EIS) structures. The EIS with a stacked-layer of SiO₂ layer between the sensing membrane and the silicon substrate exhibited a high pH sensitivity and good long-term stability. IGZO is a wide-bandgap (~3.15eV) semiconductor of the III-VI semiconductor group with several preferable properties, including good transparency, high electron mobility, wide band gap, and comparable with CMOS technology. IGZO was sputtered by reactive radio frequency (RF) on a p-type silicon wafer with various gas ratios of Ar:O₂ and was treated with rapid thermal annealing in O₂ ambient. The sensing performance, including sensitivity, hysteresis, and drift rate was measured and XRD, XPS, and AFM analyses were also used to study the material properties of the IGZO membrane. Moreover, IGZO was used as a sensing membrane in dielectric EIS bio-sensor structures. In addition to traditional pH sensing capability, detection for concentrations of Na+, K+, urea, glucose, and creatinine was performed. Moreover, post rapid thermal annealing (RTA) treatment was confirmed to improve the material properties and enhance the multi-analyte sensing capability for various ions or chemicals in solutions. In this study, the IGZO sensing membrane with annealing in O₂ ambient exhibited a higher sensitivity, higher linearity, higher H+ selectivity, lower hysteresis voltage and lower drift rate. Results indicate that the IGZO dielectric sensing membrane on the EIS structure is promising for future bio-medical device applications.

Keywords: dielectric sensing membrane, IGZO, hydrogen ion, plasma, rapid thermal annealing

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Authors: Gherbi Nabil

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Detection of ground targets in SAR radar images is an important area for radar information processing. In the literature, various algorithms have been discussed in this context. However, most of them are of low robustness and accuracy. To this end, we discuss target detection in SAR images based on compressive sensing. Firstly, traditional SAR image target detection algorithms are discussed, and their limitations are highlighted. Secondly, a compressive sensing method is proposed based on the sparsity of SAR images. Next, the detection problem is solved using Multiple Measurements Vector configuration. Furthermore, a robust Alternating Direction Method of Multipliers (ADMM) is developed to solve the optimization problem. Finally, the detection results obtained using raw complex data are presented. Experimental results on real SAR images have verified the effectiveness of the proposed algorithm.

Keywords: compressive sensing, raw complex data, synthetic aperture radar, ADMM

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Authors: H. Bakhshi, E. Khayyamian

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Cognitive radios have been recognized as one of the most promising technologies dealing with the scarcity of the radio spectrum. In cognitive radio systems, secondary users are allowed to utilize the frequency bands of primary users when the bands are idle. Hence, how to accurately detect the idle frequency bands has attracted many researchers’ interest. Detection performance is sensitive toward noise power and gain fluctuation. Since signal to noise ratio (SNR) between primary user and secondary users are not the same and change over the time, SNR and noise power estimation is essential. In this paper, we present a cooperative spectrum sensing algorithm using SNR estimation to improve detection performance in the real situation.

Keywords: cognitive radio, cooperative spectrum sensing, energy detection, SNR estimation, spectrum sensing, rayleigh fading channel

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Authors: Zheng DianXun, Cheng Bo, Lin Hetong

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This paper focuses on the orbit avoidance strategies of optical remote sensing satellite. The optical remote sensing satellite, moving along the Sun-synchronous orbit, is equipped with laser warning equipment to alert CCD camera from laser attacks. There are three ways to protect the CCD camera: closing the camera cover, satellite attitude maneuver and satellite orbit avoidance. In order to enhance the safety of optical remote sensing satellite in orbit, this paper explores the strategy of satellite avoidance. The avoidance strategy is expressed as the evasion of pre-determined target points in the orbital coordinates of virtual satellite. The so-called virtual satellite is a passive vehicle which superposes the satellite at the initial stage of avoidance. The target points share the consistent cycle time and the same semi-major axis with the virtual satellite, which ensures the properties of the satellite’s Sun-synchronous orbit remain unchanged. Moreover, to further strengthen the avoidance capability of satellite, it can perform multi-target-points avoid maneuvers. On occasions of fulfilling the satellite orbit tasks, the orbit can be restored back to virtual satellite through orbit maneuvers. Thereinto, the avoid maneuvers adopts pulse guidance. And the fuel consumption is also optimized. The avoidance strategy discussed in this article is applicable to optical remote sensing satellite when it is encountered with hostile attack of space-based laser anti-satellite.

Keywords: optical remote sensing satellite, satellite avoidance, virtual satellite, avoid target-point, avoid maneuver

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Authors: Juan Heredia, Naci Dilekli

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The Ecuadorian Rainforest has been polluted for almost 60 years with little to no regard to oversight, law, or regulations. The consequences have been vast environmental damage such as pollution and deforestation, as well as sickness and the death of many people and animals. The aim of this paper is to quantify and localize the polluted zones, which something that has not been conducted and is the first step for remediation. To approach this problem, multi-spectral Remote Sensing imagery was utilized using a novel algorithm developed for this study, based on four normalized indices available in the literature. The algorithm classifies the pixels in polluted or healthy ones. The results of this study include a new algorithm for pixel classification and quantification of the polluted area in the selected image. Those results were finally validated by ground control points found in the literature. The main conclusion of this work is that using hyperspectral images, it is possible to identify polluted vegetation. The future work is environmental remediation, in-situ tests, and more extensive results that would inform new policymaking.

Keywords: remote sensing, oil pollution quatification, amazon forest, hyperspectral remote sensing

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

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The attractive and multifunctional properties of ZnO make it a promising material for the fabrication of highly sensitive and selective efficient gas sensors at room temperature. This presented article focuses on the development of highly selective and sensitive H₂ gas sensor based on the Pd-Pt decorated ZnO framework and its sensing mechanisms. The gas sensing performance of sputter made Pd-Pt/ZnO electrode on anodized porous silicon (PSi) substrate toward H₂ gas is studied under low detection limit (2–500 ppm) of H₂ in the air. The chemiresistive sensor demonstrated sublimate selectivity, good sensing response, and fast response/recovery time with excellent stability towards H₂ at low temperature operation under ambient environment. The elaborate selective measurement of Pd-Pt/ZnO/PSi structure was performed towards different oxidizing and reducing gases. This structure exhibited advance and reversible response to H₂ gas, which revealed that the acquired architecture with ZnO framework is a promising candidate for H₂ gas sensor.

Keywords: sputtering, porous silicon, ZnO framework, XPS spectra, gas sensor

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Authors: Ling Dai

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Surface-sensing devices such as atomic force microscope have been widely used to characterize the surface structure and properties of nanoscale polymer films. However, using molecular dynamics simulations, we show that there is intrinsic and unavoidable inelastic deformation at polymer surfaces induced by the sensing tip. For linear chain polymers like perfluoropolyether, such tip-induced deformation derives from the differences in the atomic interactions which are atomic specie-based Van der Waals interactions, and resulting in atomic shuffling and causing inelastic alternation in both molecular structures and mechanical properties at the regions of the polymer surface. For those aromatic chain polymers like epoxy, the intrinsic deformation is depicted as the intra-chain rotation of aromatic rings and kinking of linear atomic connections. The present work highlights the need to reinterpret the data obtained from surface-sensing tests by considering this intrinsic inelastic deformation occurring at polymer surfaces.

Keywords: polymer, surface, nano, molecular dynamics

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Authors: B. Siva Kumar Reddy, B. Lakshmi

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Cognitive Radio is a turning out technology that empowers viable usage of the spectrum. Energy Detector-based Sensing is the most broadly utilized spectrum sensing strategy. Besides, it is a lot of generic as receivers does not like any information on the primary user's signals, channel data, of even the sort of modulation. This paper puts forth the execution of energy detection sensing for AM (Amplitude Modulated) signal at 710 KHz, FM (Frequency Modulated) signal at 103.45 MHz (local station frequency), Wi-Fi signal at 2.4 GHz and WiMAX signals at 6 GHz. The OFDM/OFDMA based WiMAX physical layer with convolutional channel coding is actualized utilizing USRP N210 (Universal Software Radio Peripheral) and GNU Radio based Software Defined Radio (SDR). Test outcomes demonstrated the BER (Bit Error Rate) augmentation with channel noise and BER execution is dissected for different Eb/N0 (the energy per bit to noise power spectral density ratio) values.

Keywords: BER, Cognitive Radio, GNU Radio, OFDM, SDR, WiMAX

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Authors: Jianfang Wang, Xianzhe Chen, Zhuoliang Liu, Cheng-An Tao, Yujiao Li

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Organophosphorus (OPs) pesticide used as insecticides are widely used in agricultural pest control, household and storage deworming. The detection of pesticides needs more simple and efficient methods. One of the best ways is to make electrochemical biosensors. In this paper, an electrochemical enzyme biosensor based on acetylcholine esterase (AChE) was constructed, and its sensing properties and sensing mechanisms were studied. Reduced graphene oxide-polydopamine complexes (RGO-PDA), gold nanoparticles (AuNPs) and silver nanoparticles (AgNPs) were prepared firstly and composited with AChE and chitosan (CS), then fixed on the glassy carbon electrode (GCE) surface to construct the biosensor GCE/RGO-PDA-AuNPs-AgNPs-AChE-CS by one-pot method. The results show that graphene oxide (GO) can be reduced by dopamine (DA) and dispersed well in RGO-PDA complexes. And the composites have a synergistic catalysis effect and can improve the surface resistance of GCE. The biosensor selectively can detect acetylcholine (ACh) and OPs pesticide with good linear range and high sensitivity. The performance of the biosensor is affected by the ratio and adding ways of AChE and the adding of AuNPs and AChE. And the biosensor can achieve a detection limit of 2.4 ng/L for methyl parathion and a wide linear detection range of 0.02 ng/L ~ 80 ng/L, and has excellent stability, good anti-interference ability, and excellent preservation performance, indicating that the sensor has practical value.

Keywords: acetylcholine esterase, electrochemical biosensor, nanoparticles, organophosphates, reduced graphene oxide

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Authors: S. S. Chong, A. R. Abdul Aziz, S. W. Harun, H. Arof

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A miniaturized non-adiabatic silica microfiber is proposed for biological oxygen demand (BOD) ratio chemical oxygen demand (COD) sensing for the first time. BOD and COD are two main parameters to justify quality of wastewater. A ratio, BOD:COD can usually be established between the two analytical methods once COD and BOD value has been gathered. This ratio plays a vital role to determine appropriate strategy in wastewater treatment. A non-adiabatic microfiber sensor was formed by tapering the SMF to generate evanescent field where sensitive to perturbation of sensing medium. Because difference ratio BOD and COD contain in solution, this may induced changes of effective refractive index between microfiber and sensing medium. Attenuation wavelength shift to right with 0.5 nm and 3.5 nm while BOD:COD equal to 0.09 and 0.18 respectively. Significance difference wavelength shift may relate with the biodegradability of analyte. This proposed sensor is compact, reliable and feasible to determine the BOD:COD. Further research and investigation should be proceeded to enhance sensitivity and precision of the sensor for several of wastewater online monitoring.

Keywords: non-adiabatic fiber sensor, environmental sensing, biodegradability, evanescent field

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Authors: M. M. Hefnawy, A. M. A. Homoda, M. A. Abounassif, A. M. Alanazia, A. Al-Majed, Gamal A. E. Mostafa

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PVC membrane sensors using different approach e.g. ion-pair, ionophore, and Schiff-base has been used as testing membrane sensor. Analytical applications of membrane sensors for direct measurement of variety of different ions in complex biological and environmental sample are reported. The most important step of such PVC membrane sensor is the sensing active material. The potentiometric sensors have some outstanding advantages including simple design, operation, wide linear dynamic range, relative fast response time, and rotational selectivity. The analytical applications of these techniques to pharmaceutical compounds in dosage forms are also discussed. The construction and electrochemical response characteristics of Poly (vinyl chloride) membrane sensors for moxifloxacin HCl (MOX) are described. The sensing membranes incorporate ion association complexes of moxifloxacin cation and sodium tetraphenyl borate (NaTPB) (sensor 1), phosphomolybdic acid (PMA) (sensor 2) or phosphotungstic acid (PTA) (sensor 3) as electroactive materials. The sensors display a fast, stable and near-Nernstian response over a relative wide moxifloxacin concentration range (1 ×10-2-4.0×10-6, 1 × 10-2-5.0×10-6, 1 × 10-2-5.0×10-6 M), with detection limits of 3×10-6, 4×10-6 and 4.0×10-6 M for sensor 1, 2 and 3, respectively over a pH range of 6.0-9.0. The sensors show good discrimination of moxifloxacin from several inorganic and organic compounds. The direct determination of 400 µg/ml of moxifloxacin show an average recovery of 98.5, 99.1 and 98.6 % and a mean relative standard deviation of 1.8, 1.6 and 1.8% for sensors 1, 2, and 3 respectively. The proposed sensors have been applied for direct determination of moxifloxacin in some pharmaceutical preparations. The results obtained by determination of moxifloxacin in tablets using the proposed sensors are comparable favorably with those obtained using the US Pharmacopeia method. The sensors have been used as indicator electrodes for potentiometric titration of moxifloxacin.

Keywords: potentiometry, PVC, membrane sensors, ion-pair, ionophore, schiff-base, moxifloxacin HCl, sodium tetraphenyl borate, phosphomolybdic acid, phosphotungstic acid

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Authors: Dianxun Zheng, Wuxing Jing, Lin Hetong

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Optical remote sensing satellite, always running on the Sun-synchronous orbit, equipped laser warning equipment to alert CCD camera from laser attack. There have three ways to protect the CCD camera, closing the camera cover satellite attitude maneuver and satellite orbit avoidance. In order to enhance the safety of optical remote sensing satellite in orbit, this paper explores the strategy of satellite avoidance. The avoidance strategy is expressed as the evasion of pre-determined target points in the orbital coordinates of virtual satellite. The so-called virtual satellite is a passive vehicle which superposes a satellite at the initial stage of avoidance. The target points share the consistent cycle time and the same semi-major axis with the virtual satellite, which ensures the properties of the Sun-synchronous orbit remain unchanged. Moreover, to further strengthen the avoidance capability of satellite, it can perform multi-object avoid maneuvers. On occasions of fulfilling the orbit tasks of the satellite, the orbit can be restored back to virtual satellite through orbit maneuvers. There into, the avoid maneuvers adopts pulse guidance. and the fuel consumption is also optimized. The avoidance strategy discussed in this article is applicable to avoidance for optical remote sensing satellite when encounter the laser hostile attacks.

Keywords: optical remote sensing satellite, always running on the sun-synchronous

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Authors: Spoorthi Sripad

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Remote sensing is a powerful tool for acquiring information about the Earth's surface without direct contact, relying on the interaction of electromagnetic radiation with various materials and features. This paper explores the fundamental principle of "Interaction with Earth's Surface" in remote sensing, shedding light on the intricate processes that occur when electromagnetic waves encounter different surfaces. The absorption, reflection, and transmission of radiation generate distinct spectral signatures, allowing for the identification and classification of surface materials. The paper delves into the significance of the visible, infrared, and thermal infrared regions of the electromagnetic spectrum, highlighting how their unique interactions contribute to a wealth of applications, from land cover classification to environmental monitoring. The discussion encompasses the types of sensors and platforms used to capture these interactions, including multispectral and hyperspectral imaging systems. By examining real-world applications, such as land cover classification and environmental monitoring, the paper underscores the critical role of understanding the interaction with the Earth's surface for accurate and meaningful interpretation of remote sensing data.

Keywords: remote sensing, earth's surface interaction, electromagnetic radiation, spectral signatures, land cover classification, archeology and cultural heritage preservation

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

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In the present work, we have fabricated and studied a resistive H₂ gas sensor based on Pd-Pt decorated room temperature sputter grown nanocrystalline porous titanium dioxide (p-TiO₂) thin film on porous silicon (p-Si) substrate for fast H₂ detection. The gas sensing performance of Pd-Pt/p-TiO₂/p-Si sensing electrode towards H₂ gas under low (10-500 ppm) detection limit and operating temperature regime (25-200 °C) was discussed. The sensor is highly sensitive even at room temperature, with response (Ra/Rg) reaching ~102 for 500 ppm H₂ in dry air and its capability of sensing H₂ concentrations as low as ~10 ppm was demonstrated. At elevated temperature of 200 ℃, the response reached more than ~103 for 500 ppm H₂. Overall the fabricated resistive gas sensor exhibited high selectivity, good sensing response, and fast response/recovery time with good stability towards H₂.

Keywords: sputtering, porous silicon (p-Si), TiO₂ thin film, hydrogen gas sensor

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Authors: Ahmad Umar, Sheikh Akbar, Ahmed A. Ibrahim, Mohsen A. Alhamami

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The development of advanced materials for energy storage and gas sensing applications has gained significant attention in recent years. In this study, we synthesized and characterized PANI@MnO2@rGO ternary nanocomposites (NCs) to explore their potential in supercapacitors and gas sensing devices. The ternary NCs were synthesized through a multi-step process involving the hydrothermal synthesis of MnO2 nanoparticles, preparation of PANI@rGO composites and the assembly to the ternary PANI@MnO2@rGO ternary NCs. The structural, morphological, and compositional characteristics of the materials were thoroughly analyzed using techniques such as XRD, FESEM, TEM, FTIR, and Raman spectroscopy. In the realm of gas sensing, the ternary NCs exhibited excellent performance as NH3 gas sensors. The optimized operating temperature of 100 °C yielded a peak response of 15.56 towards 50 ppm NH3. The nanocomposites demonstrated fast response and recovery times of 6 s and 10 s, respectively, and displayed remarkable selectivity for NH3 gas over other tested gases. For supercapacitor applications, the electrochemical performance of the ternary NCs was evaluated using cyclic voltammetry and galvanostatic charge-discharge techniques. The composites exhibited pseudocapacitive behavior, with the capacitance reaching up to 185 F/g at 1 A/g and excellent capacitance retention of approximately 88.54% over 4000 charge-discharge cycles. The unique combination of rGO, PANI, and MnO2 nanoparticles in these ternary NCs offer synergistic advantages, showcasing their potential to address challenges in energy storage and gas sensing technologies.

Keywords: paniI@mnO2@rGO ternary NCs, synergistic effects, supercapacitors, gas sensing, energy storage

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Authors: Bivek Bhusal, Ana Legrand

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Detection of crop stress is one of the major applications of remote sensing in agriculture. Multiple studies have demonstrated the capability of remote sensing using Unmanned Aerial Vehicle (UAV)-based multispectral imagery for detection of plant stress, but none so far on Nitrogen (N) stress and PLH feeding stress on green beans. In view of its wide host range, geographical distribution, and damage potential, Potato leafhopper- Empoasca fabae (Harris) has been emerging as a key pest in several countries. Monitoring methods for potato leafhopper (PLH) damage, as well as the laboratory techniques for detecting Nitrogen deficiency, are time-consuming and not always easily affordable. A study was initiated to demonstrate if the multispectral sensor attached to a drone can detect PLH stress and N deficiency in beans. Small-plot trials were conducted in the summer of 2023, where cages were used to manipulate PLH infestation in green beans (Provider cultivar) at their first-trifoliate stage. Half of the bean plots were introduced with PLH, and the others were kept insect-free. Half of these plots were grown with the recommended amount of N, and the others were grown without N. Canopy reflectance was captured using a five-band multispectral sensor. Our findings indicate that drone imagery could detect stress due to a lack of N and PLH damage in beans.

Keywords: potato leafhopper, nitrogen, remote sensing, spectral reflectance, beans

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Authors: Ngoc Tu Truong, Nuong T. Bui, Ben Rao, Ya L. Shen

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Quorum sensing is a phenomenon present in many gram-negative bacteria that allows bacterial communication and controlled expression of a large suite of genes through quorum sensing signals - N-acyl homoserine lactones (AHLs). In order to investigate the ability of the rhlR/rhlI quorum sensing system in Pseudomonas aeruginosa to express the ß-Galactosidase reporter gene, an engineered E. coli strain EpHL02, was genetically engineered. This engineered E. coli strain EpHL02 responded to the presence of the N-butanoyl homoserine lactone and N-hexanoyl homoserine lactone to express the ß-Galactosidase reporter gene at a concentration limit of 5x10⁻⁸ M. This was also found to be comparable to AHLs extraction from Serratia marcescens H31. Moreover, we examined this ability of this engineered E. coli strain for respond of AHLs from extractions of Pseudomonas aeruginosa ATCC9027. The results demonstrated that the rhlR/rhlI quorum sensing system can express the ß-Galactosidase reporter gene by using the N-butanoyl homoserine lactone, N-hexanoyl homoserine lactone and AHLs from extractions of Serratia marcescens H31 and Pseudomonas aeruginosa ATCC9027 in the engineered E. coli strain EpHL02.

Keywords: N-butanoyl homoserine lactone, C4-HSL, N-hexanoyl homoserine lactone, C6-HSL, Pseudomonas aeruginosa, quorum sensing, Serratia marcescens, ß-galactosidase reporter gene

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Authors: Caixia Gao, Chuanrong Li, Lingli Tang, Lingling Ma, Yaokai Liu, Xinhong Wang, Yongsheng Zhou

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Performances analysis of remote sensing sensor is required to pursue a range of scientific research and application objectives. Laboratory analysis of any remote sensing instrument is essential, but not sufficient to establish a valid inflight one. In this study, with the aid of the in situ measurements and corresponding image of three-gray scale permanent artificial target, the in-flight radiometric performances analyses (in-flight radiometric calibration, dynamic range and response linearity, signal-noise-ratio (SNR), radiometric resolution) of self-developed short-wave infrared (SWIR) camera are performed. To acquire the inflight calibration coefficients of the SWIR camera, the at-sensor radiances (L_i) for the artificial targets are firstly simulated with in situ measurements (atmosphere parameter and spectral reflectance of the target) and viewing geometries using MODTRAN model. With these radiances and the corresponding digital numbers (DN) in the image, a straight line with a formulation of L = G × DN + B is fitted by a minimization regression method, and the fitted coefficients, G and B, are inflight calibration coefficients. And then the high point (L_H) and the low point (L_L) of dynamic range can be described as L_H= (G × DN_H + B) and L_L= B, respectively, where DN_H is equal to 2ⁿ − 1 (n is the quantization number of the payload). Meanwhile, the sensor’s response linearity (δ) is described as the correlation coefficient of the regressed line. The results show that the calibration coefficients (G and B) are 0.0083 W·sr⁻¹m⁻²µm⁻¹ and −3.5 W·sr⁻¹m⁻²µm⁻¹; the low point of dynamic range is −3.5 W·sr⁻¹m⁻²µm⁻¹ and the high point is 30.5 W·sr⁻¹m⁻²µm⁻¹; the response linearity is approximately 99%. Furthermore, a SNR normalization method is used to assess the sensor’s SNR, and the normalized SNR is about 59.6 when the mean value of radiance is equal to 11.0 W·sr⁻¹m⁻²µm⁻¹; subsequently, the radiometric resolution is calculated about 0.1845 W•sr^-1m^-2μm^-1. Moreover, in order to validate the result, a comparison of the measured radiance with a radiative-transfer-code-predicted over four portable artificial targets with reflectance of 20%, 30%, 40%, 50% respectively, is performed. It is noted that relative error for the calibration is within 6.6%.

Keywords: calibration and validation site, SWIR camera, in-flight radiometric calibration, dynamic range, response linearity

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Authors: Urvee B. Trivedi, U. D. Dalal

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As wireless communication services grow quickly; the seriousness of spectrum utilization has been on the rise gradually. An emerging technology, cognitive radio has come out to solve today’s spectrum scarcity problem. To support the spectrum reuse functionality, secondary users are required to sense the radio frequency environment, and once the primary users are found to be active, the secondary users are required to vacate the channel within a certain amount of time. Therefore, spectrum sensing is of significant importance. Once sensing is done, different prediction rules apply to classify the traffic pattern of primary user. Primary user follows two types of traffic patterns: periodic and stochastic ON-OFF patterns. A cognitive radio can learn the patterns in different channels over time. Two types of classification methods are discussed in this paper, by considering edge detection and by using autocorrelation function. Edge detection method has a high accuracy but it cannot tolerate sensing errors. Autocorrelation-based classification is applicable in the real environment as it can tolerate some amount of sensing errors.

Keywords: cognitive radio (CR), probability of detection (PD), probability of false alarm (PF), primary user (PU), secondary user (SU), fast Fourier transform (FFT), signal to noise ratio (SNR)

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Authors: O. Sunantha, S. Zhenfeng, S. Phattraporn, A. Zeeshan

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The decline of soil organic carbon (SOC) in global agriculture is a critical issue requiring rapid and accurate estimation for informed policymaking. While it is recognized that SOC predictors vary significantly when derived from remote sensing data and environmental variables, identifying the specific parameters most suitable for accurately estimating SOC in diverse agricultural areas remains a challenge. This study utilizes remote sensing data to precisely estimate SOC and identify influential factors in diverse agricultural areas, such as paddy, corn, sugarcane, cassava, and perennial crops. Extreme gradient boosting (XGBoost), random forest (RF), and support vector regression (SVR) models are employed to analyze these factors' impact on SOC estimation. The results show key factors influencing SOC estimation include slope, vegetation indices (EVI), spectral reflectance indices (red index, red edge2), temperature, land use, and surface soil moisture, as indicated by their averaged importance scores across XGBoost, RF, and SVR models. Therefore, using different machine learning algorithms for SOC estimation reveals varying influential factors from remote sensing data and environmental variables. This approach emphasizes feature selection, as different machine learning algorithms identify various key factors from remote sensing data and environmental variables for accurate SOC estimation.

Keywords: factors influencing SOC estimation, remote sensing data, environmental variables, machine learning

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Authors: Amritansh Agarwal, Tejaswi Agarwal

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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: Ekin Nurbaş

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One of the essential challenges in array signal processing, which has drawn enormous research interest over the past several decades, is estimating the direction of arrival (DOA) of plane waves impinging on an array of sensors. In recent years, the Compressive Sensing based DoA estimation methods have been proposed by researchers, and it has been discovered that the Compressive Sensing (CS)-based algorithms achieved significant performances for DoA estimation even in scenarios where there are multiple coherent sources. On the other hand, the Genetic Algorithm, which is a method that provides a solution strategy inspired by natural selection, has been used in sparse representation problems in recent years and provides significant improvements in performance. With all of those in consideration, in this paper, a method that combines the Genetic Algorithm (GA) and the Multi-Criteria Decision Making (MCDM) approaches for Direction of Arrival (DoA) estimation in the Compressive Sensing (CS) framework is proposed. In this method, we generate a multi-objective optimization problem by splitting the norm minimization and reconstruction loss minimization parts of the Compressive Sensing algorithm. With the help of the Genetic Algorithm, multiple non-dominated solutions are achieved for the defined multi-objective optimization problem. Among the pareto-frontier solutions, the final solution is obtained with the multiple MCDM methods. Moreover, the performance of the proposed method is compared with the CS-based methods in the literature.

Keywords: genetic algorithm, direction of arrival esitmation, multi criteria decision making, compressive sensing

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Authors: Sajid Abas, Jon Pyo Hong, Jung-Ryun Le, Seungryong Cho

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Computed tomography and laminography are heavily investigated in a compressive sensing based image reconstruction framework to reduce the dose to the patients as well as to the radiosensitive devices such as multilayer microelectronic circuit boards. Nowadays researchers are actively working on optimizing the compressive sensing based iterative image reconstruction algorithm to obtain better quality images. However, the effects of the sampled data’s properties on reconstructed the image’s quality, particularly in an insufficient sampled data conditions have not been explored in computed laminography. In this paper, we investigated the effects of two data properties i.e. sampling density and data incoherence on the reconstructed image obtained by conventional computed laminography and a recently proposed method called spherical sinusoidal scanning scheme. We have found that in a compressive sensing based image reconstruction framework, the image quality mainly depends upon the data incoherence when the data is uniformly sampled.

Keywords: computed tomography, computed laminography, compressive sending, low-dose

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Authors: Rohit Dey, Sailendra Karra

Abstract:

This paper aims at solving the problem of multi-target searching in a Global Positioning System (GPS) denied environment using swarm robots with limited sensing and communication abilities. Typically, existing swarm-based search algorithms rely on the presence of a global coordinate system (vis-à-vis, GPS) that is shared by the entire swarm which, in turn, limits its application in a real-world scenario. This can be attributed to the fact that robots in a swarm need to share information among themselves regarding their location and signal from targets to decide their future course of action but this information is only meaningful when they all share the same coordinate frame. The paper addresses this very issue by eliminating any dependency of a search algorithm on the need of a predetermined global coordinate frame by the unification of the relative coordinate of individual robots when within the communication range, therefore, making the system more robust in real scenarios. Our algorithm assumes that all the robots in the swarm are equipped with range and bearing sensors and have limited sensing range and communication abilities. Initially, every robot maintains their relative coordinate frame and follow Levy walk random exploration until they come in range with other robots. When two or more robots are within communication range, they share sensor information and their location w.r.t. their coordinate frames based on which we unify their coordinate frames. Now they can share information about the areas that were already explored, information about the surroundings, and target signal from their location to make decisions about their future movement based on the search algorithm. During the process of exploration, there can be several small groups of robots having their own coordinate systems but eventually, it is expected for all the robots to be under one global coordinate frame where they can communicate information on the exploration area following swarm search techniques. Using the proposed method, swarm-based search algorithms can work in a real-world scenario without GPS and any initial information about the size and shape of the environment. Initial simulation results show that running our modified-Particle Swarm Optimization (PSO) without global information we can still achieve the desired results that are comparable to basic PSO working with GPS. In the full paper, we plan on doing the comparison study between different strategies to unify the coordinate system and to implement them on other bio-inspired algorithms, to work in GPS denied environment.

Keywords: bio-inspired search algorithms, decentralized control, GPS denied environment, swarm robotics, target searching, unifying coordinate systems

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Authors: R. H. Bari

Abstract:

The nanostructured thin films of CdSnO3 are sensitive to change in their environment. CdSnO3 is successfully used as gas sensor due to the dependence of the electrical conductivity on the ambient gas composition. Nanostructured CdSnO3 thin films of different substrate temperature (300 0C, 350 0C, 400 0C and 450 0C) were deposited onto heated glass substrate by simple spray pyrolysis (SP) technique. Sensing elements of nanostructured CdSnO3 were annealed at 500 0C for 1 hrs. Characterization includes a different analytical technique such as, X-ray diffractogram (XRD), energy dispersive X-ray analysis (EDAX), and Field emission scanning electron microscope (FE-SEM). The average grain size observed from XRD and FF-SEM was found to be less than 18.36 and 23 nm respectively. The films sprayed at substrate temperature for 400 0C was observed to be most sensitive (S = 530) to SO2 for 500 ppm at 300 0C. The response and recovery time is 4 sec, 8 sec respectively.

Keywords: nanostructured CdSnO3, spray pyrolysis, SO2 gas sensing, quick response

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Authors: Chun-Lin Chiang, Che-Yen Lee, Yu-Shan Yeh, Jiunn-Haur Shaw

Abstract:

Wafer fabrication is a critical part of the semiconductor process, when the finest linewidth with the improvement of technology continues to decline and the structure development from 2D towards to 3D. The nanoparticles contained in the slurry or in the ultrapure water which used for cleaning have a large influence on the manufacturing process. Therefore, semiconductor industry is hoping to find a viable method for on-line detection the nanoparticles size and concentration. The resistive pulse sensing technology is one of the methods that may cover this question. As we know that nanoparticles properties of material differ significantly from their properties at larger length scales. So, we want to clear that the metal and non-metal nanoparticles translocation dynamic when we use the resistive pulse sensing technology. In this study we try to use the finite element method that contains three governing equations to do multiphysics coupling simulations. The Navier-Stokes equation describes the laminar motion, the Nernst-Planck equation describes the ion transport, and the Poisson equation describes the potential distribution in the flow channel. To explore that the metal nanoparticles and the non-metal nanoparticles in different concentration electrolytes, through the nanochannel caused by ion current changes. Then the reliability of the simulation results was verified by resistive pulse sensing test. The existing results show that the lower ion concentration, the greater effect of nanoparticles on the ion concentration in the nanochannel. The conductive spikes are correlated with nanoparticles surface charge. Then we can be concluded that in the resistive pulse sensing technique, the ion concentration in the nanochannel and nanoparticle properties are important for the translocation dynamic, and they have the interactions.

Keywords: multiphysics simulations, resistive pulse sensing, nanoparticles, nanochannel

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Authors: Ozgun Oktar, Sevilay Can, Cengiz V. Ekici

Abstract:

The oil spill is a form of pollution caused by releasing of a liquid petroleum hydrocarbon into the marine environment. Considering the growth of ship traffic, increasing of off-shore oil drilling and seaside refineries affect the risk of oil spill upward. The oil spill is easy to spread to large areas when occurs especially on the sea surface. Remote sensing technology offers the easiest way to control/monitor the area of the oil spill in a large region. It’s usually easy to detect pollution when occurs by the ship accidents, however monitoring non-accidental pollution could be possible by remote sensing. It is also needed to observe specific regions daily and continuously by satellite solutions. Remote sensing satellites mostly and effectively used for monitoring oil pollution are RADARSAT, ENVISAT and MODIS. Spectral coverage and transition period of these satellites are not proper to monitor Marmara Sea and Istanbul Strait continuously. In this study, RASAT and GOKTURK-2 are suggested to use for monitoring Marmara Sea and Istanbul Strait. RASAT, with spectral resolution 420 – 730 nm, is the first Turkish-built satellite. GOKTURK-2’s resolution can reach up to 2,5 meters. This study aims to analyze the images from both satellites and produce maps to show the regions which have potentially affected by spills from shipping traffic.

Keywords: Marmara Sea, monitoring, oil spill, satellite remote sensing

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Authors: Brighton Chamunorwa

Abstract:

The current remote sensing of water quality procedures does not provide a step representing physical visualisation of the monitored dam. The application of the remote sensing of water quality techniques may benefit from use of mathematical morphology operators for shape identification. Given an input of dam outline, morphological operators such as the hit or miss transform identifies if the water body is present on input remotely sensed images. This study seeks to determine the accuracy of the hit or miss transform to identify dams monitored by the water resources authorities in South Africa on satellite images. To achieve this objective the study download a Landsat image acquired in winter and tested the capability of the hit or miss transform using shapefile boundaries of dams in the crocodile marico catchment. The results of the experiment show that it is possible to detect most dams on the Landsat image after the adjusting the erosion operator to detect pixel matching a percentage similarity of 80% and above. Successfully implementation of the current study contributes towards optimisation of mathematical morphology image operators. Additionally, the effort helps develop remote sensing of water quality monitoring with improved simulation of the conventional procedures.

Keywords: hit or miss transform, mathematical morphology, remote sensing, water quality monitoring

Procedia PDF Downloads 153