Search results for: spectral reflectance

Authors: B. Siva Kumar Reddy, B. Lakshmi

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WiMAX has adopted an Adaptive Modulation and Coding (AMC) in OFDM to endure higher data rates and error free transmission. AMC schemes employ the Channel State Information (CSI) to efficiently utilize the channel and maximize the throughput and for better spectral efficiency. This CSI has given to the transmitter by the channel estimators. In this paper, LSE (Least Square Error) and MMSE (Minimum Mean square Error) estimators are suggested and BER (Bit Error Rate) performance has been analyzed. Channel equalization is also integrated with with AMC-OFDM system and presented with Constant Modulus Algorithm (CMA) and Least Mean Square (LMS) algorithms with convergence rates analysis. Simulation results proved that increment in modulation scheme size causes to improvement in throughput along with BER value. There is a trade-off among modulation size, throughput, BER value and spectral efficiency. Results also reported the requirement of channel estimation and equalization in high data rate systems.

Keywords: AMC, CSI, CMA, OFDM, OFDMA, WiMAX

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Authors: Cesar Hernández, Diego Giral, Fernando Santa

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The spectral handoff is important in cognitive wireless networks to ensure an adequate quality of service and performance for secondary user communications. This work proposes a benchmarking of performance of the three spectrum handoff models: VIKOR, SAW and MEW. Four evaluation metrics are used. These metrics are, accumulative average of failed handoffs, accumulative average of handoffs performed, accumulative average of transmission bandwidth and, accumulative average of the transmission delay. As a difference with related work, the performance of the three spectrum handoff models was validated with captured data of spectral occupancy in experiments realized at the GSM frequency band (824 MHz-849 MHz). These data represent the actual behavior of the licensed users for this wireless frequency band. The results of the comparative show that VIKOR Algorithm provides 15.8% performance improvement compared to a SAW Algorithm and, 12.1% better than the MEW Algorithm.

Keywords: cognitive radio, decision making, MEW, SAW, spectrum handoff, VIKOR

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Authors: Murada Alholy, Mengshi Lin, Omar Alhaj, Mahmoud Abugoush

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Alicyclobacillus is a causative agent of spoilage in pasteurized and heat-treated apple juice products. Differentiating between this genus and the closely related Bacillus is crucially important. In this study, Fourier transform infrared spectroscopy (FT-IR) was used to identify and discriminate between four Alicyclobacillus strains and four Bacillus isolates inoculated individually into apple juice. Loading plots over the range of 1350 and 1700 cm-1 reflected the most distinctive biochemical features of Bacillus and Alicyclobacillus. Multivariate statistical methods (e.g. principal component analysis (PCA) and soft independent modeling of class analogy (SIMCA)) were used to analyze the spectral data. Distinctive separation of spectral samples was observed. This study demonstrates that FT-IR spectroscopy in combination with multivariate analysis could serve as a rapid and effective tool for fruit juice industry to differentiate between Bacillus and Alicyclobacillus and to distinguish between species belonging to these two genera.

Keywords: alicyclobacillus, bacillus, FT-IR, spectroscopy, PCA

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Authors: Teguh Endah Saraswati, Kusumandari Kusumandari, Candra Purnawan, Annisa Dinan Ghaisani, Aufara Mahayum

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The present study aims to investigate the degradation of methylene blue (MB) using TiO₂-carbon (TiO₂-C) photocatalyst combined with dielectric discharge (DBD) plasma. The carbon materials used in the photocatalyst were activated carbon and graphite. The thin layer of TiO₂-C photocatalyst was prepared by ball milling method which was then deposited on the plastic sheet. The characteristic of TiO₂-C thin layer was analyzed using X-ray diffraction (XRD), scanning electron microscopy (SEM) with energy dispersive X-ray (EDX) spectroscopy, and UV-Vis diffuse reflectance spectrophotometer. The XRD diffractogram patterns of TiO₂-G thin layer in various weight compositions of 50:1, 50:3, and 50:5 show the 2θ peaks found around 25° and 27° are the main characteristic of TiO₂ and carbon. SEM analysis shows spherical and regular morphology of the photocatalyst. Analysis using UV-Vis diffuse reflectance shows TiO₂-C has narrower band gap energy. The DBD plasma reactor was generated using two electrodes of Cu tape connected with stainless steel mesh and Fe wire separated by a glass dielectric insulator, supplied by a high voltage 5 kV with an air flow rate of 1 L/min. The optimization of the weight composition of TiO₂-C thin layer was studied based on the highest reduction of the MB concentration achieved, examined by UV-Vis spectrophotometer. The changes in pH values and color of MB indicated the success of MB degradation. Moreover, the degradation efficiency of MB was also studied in various higher concentrations of 50, 100, 200, 300 ppm treated for 0, 2, 4, 6, 8, 10 min. The degradation efficiency of MB treated in combination system of photocatalysis and DBD plasma reached more than 99% in 6 min, in which the greater concentration of methylene blue dye, the lower degradation rate of methylene blue dye would be achieved.

Keywords: activated carbon, DBD plasma, graphite, methylene blue, photocatalysis

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Authors: Fanqiang Kong, Chending Bian

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In this work, we exploit two assumed properties of the abundances of the observed signatures (endmembers) in order to reconstruct the abundances from hyperspectral data. Joint-sparsity is the first property of the abundances, which assumes the adjacent pixels can be expressed as different linear combinations of same materials. The second property is rank-deficiency where the number of endmembers participating in hyperspectral data is very small compared with the dimensionality of spectral library, which means that the abundances matrix of the endmembers is a low-rank matrix. These assumptions lead to an optimization problem for the sparse unmixing model that requires minimizing a combined l_2,p-norm and nuclear norm. We propose a variable splitting and augmented Lagrangian algorithm to solve the optimization problem. Experimental evaluation carried out on synthetic and real hyperspectral data shows that the proposed method outperforms the state-of-the-art algorithms with a better spectral unmixing accuracy.

Keywords: hyperspectral unmixing, joint-sparse, low-rank representation, abundance estimation

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Authors: Milad Vahidi, Mahmod R. Sahebi, Mehrnoosh Omati, Reza Mohammadi

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Forest management organizations need information to perform their work effectively. Remote sensing is an effective method to acquire information from the Earth. Two datasets of remote sensing images were used to classify forested regions. Firstly, all of extractable features from hyperspectral and PolSAR images were extracted. The optical features were spectral indexes related to the chemical, water contents, structural indexes, effective bands and absorption features. Also, PolSAR features were the original data, target decomposition components, and SAR discriminators features. Secondly, the particle swarm optimization (PSO) and the genetic algorithms (GA) were applied to select optimization features. Furthermore, the support vector machine (SVM) classifier was used to classify the image. The results showed that the combination of PSO and SVM had higher overall accuracy than the other cases. This combination provided overall accuracy about 90.56%. The effective features were the spectral index, the bands in shortwave infrared (SWIR) and the visible ranges and certain PolSAR features.

Keywords: hyperspectral, PolSAR, feature selection, SVM

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Authors: Shweta Singh, Dipali Bansal, Rashima Mahajan

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Psychoacoustics has become a potential area of research due to the growing interest of both laypersons and medical and mental health professionals. Non-invasive brain computer interface like Electroencephalography (EEG) is widely being used in this field. An attempt has been made in this paper to examine the response of EEG signals to acoustic stimuli further analysing the brain electrical activity. The real time EEG is acquired for 6 participants using a cost effective and portable EMOTIV EEG neuron headset. EEG data analysis is further done using EMOTIV test bench, EDF browser and EEGLAB (MATLAB Tool) application software platforms. Spectral analysis of acquired neural signals (AF3 channel) using these software platforms are clearly indicative of increased brain activity in various bands. The inferences drawn from such an analysis have significant correlation with subject’s subjective reporting of the experiences. The results suggest that the methodology adopted can further be used to assist patients with sleeping and depressive disorders.

Keywords: OM chant, spectral analysis, EDF browser, EEGLAB, EMOTIV, real time acquisition

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Authors: Malik Abid Hussain Khokhar, Muhammad Adnan Tahir, Hisham Bin Hafeez Awan

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Continuous environmental determinism and climatic change in the entire globe due to increasing land surface temperature (LST) has become a vital phenomenon nowadays. LST is accelerating because of increasing greenhouse gases in the environment which results of melting down ice caps, ice sheets and glaciers. It has not only worse effects on vegetation and water bodies of the region but has also severe impacts on monsoon areas in the form of capricious rainfall and monsoon failure extensive precipitation. Environment can be monitored with the help of various geographic information systems (GIS) based algorithms i.e. SC (Single), DA (Dual Angle), Mao, Sobrino and SW (Split Window). Estimation of LST is very much possible from digital image processing of satellite imagery. This paper will encompass extraction of LST of Abbottabad using SW technique of GIS and Remote Sensing over last ten years by means of Landsat 7 ETM+ (Environmental Thematic Mapper) and Landsat 8 vide their Thermal Infrared (TIR Sensor) and Optical Land Imager (OLI sensor less Landsat 7 ETM+) having 100 m TIR resolution and 30 m Spectral Resolutions. These sensors have two TIR bands each; their emissivity and spectral radiance will be used as input statistics in SW algorithm for LST extraction. Emissivity will be derived from Normalized Difference Vegetation Index (NDVI) threshold methods using 2-5 bands of OLI with the help of e-cognition software, and spectral radiance will be extracted TIR Bands (Band 10-11 and Band 6 of Landsat 7 ETM+). Accuracy of results will be evaluated by weather data as well. The successive research will have a significant role for all tires of governing bodies related to climate change departments.

Keywords: environment, Landsat 8, SW Algorithm, TIR

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Authors: Lukáš Klein, Karel Žídek

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Hyperspectral imaging counts among the most frequently used multidimensional sensing methods. While there are many approaches to capturing a hyperspectral data cube, optical compression is emerging as a valuable tool to reduce the setup complexity and the amount of data storage needed. Hyperspectral compressive imagers have been created in the past; however, they have primarily focused on relatively narrow sections of the electromagnetic spectrum. A broader spectral study of samples can provide helpful information, especially for applications involving the harmonic generation and advanced material characterizations. We demonstrate a broadband hyperspectral microscope based on the single-pixel camera principle. Captured spatially encoded data are processed to reconstruct a hyperspectral cube in a combined visible and near-infrared spectrum (from 400 to 2500 nm). Hyperspectral cubes can be reconstructed with a spectral resolution of up to 3 nm and spatial resolution of up to 7 µm (subject to diffraction) with a high compressive ratio.

Keywords: compressive imaging, hyperspectral imaging, near-infrared spectrum, single-pixel camera, visible spectrum

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Authors: Katerina Krizova, Inigo Molina

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The ongoing climate change affects various natural processes resulting in significant changes in human life. Since there is still a growing human population on the planet with more or less limited resources, agricultural production became an issue and a satisfactory amount of food has to be reassured. To achieve this, agriculture is being studied in a very wide context. The main aim here is to increase primary production on a spatial unit while consuming as low amounts of resources as possible. In Europe, nowadays, the staple issue comes from significantly changing the spatial and temporal distribution of precipitation. Recent growing seasons have been considerably affected by long drought periods that have led to quantitative as well as qualitative yield losses. To cope with such kind of conditions, new techniques and technologies are being implemented in current practices. However, behind assessing the right management, there is always a set of the necessary information about plot properties that need to be acquired. Remotely sensed data had gained attention in recent decades since they provide spatial information about the studied surface based on its spectral behavior. A number of space platforms have been launched carrying various types of sensors. Spectral indices based on calculations with reflectance in visible and NIR bands are nowadays quite commonly used to describe the crop status. However, there is still the staple limit by this kind of data - cloudiness. Relatively frequent revisit of modern satellites cannot be fully utilized since the information is hidden under the clouds. Therefore, microwave remote sensing, which can penetrate the atmosphere, is on its rise today. The scientific literature describes the potential of radar data to estimate staple soil (roughness, moisture) and vegetation (LAI, biomass, height) properties. Although all of these are highly demanded in terms of agricultural monitoring, the crop moisture content is the utmost important parameter in terms of agricultural drought monitoring. The idea behind this study was to exploit the unique combination of SAR (Sentinel-1) and optical (Sentinel-2) data from one provider (ESA) to describe potential crop water stress during dry cropping season of 2019 at six winter wheat plots in the central Czech Republic. For the period of January to August, Sentinel-1 and Sentinel-2 images were obtained and processed. Sentinel-1 imagery carries information about C-band backscatter in two polarisations (VV, VH). Sentinel-2 was used to derive vegetation properties (LAI, FCV, NDWI, and SAVI) as support for Sentinel-1 results. For each term and plot, summary statistics were performed, including precipitation data and soil moisture content obtained through data loggers. Results were presented as summary layouts of VV and VH polarisations and related plots describing other properties. All plots performed along with the principle of the basic SAR backscatter equation. Considering the needs of practical applications, the vegetation moisture content may be assessed using SAR data to predict the drought impact on the final product quality and yields independently of cloud cover over the studied scene.

Keywords: precision agriculture, remote sensing, Sentinel-1, SAR, water content

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Authors: Navneet Singh Deora, Aastha Deswal, H. N. Mishra

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Pasta is one of the most widely consumed food products around the world. Rapid determination of the moisture content in pasta will assist food processors to provide online quality control of pasta during large scale production. Rapid Fourier transform near-infrared method (FT-NIR) was developed for determining moisture content in pasta. A calibration set of 150 samples, a validation set of 30 samples and a prediction set of 25 samples of pasta were used. The diffuse reflection spectra of different types of pastas were measured by FT-NIR analyzer in the 4,000-12,000 cm-1 spectral range. Calibration and validation sets were designed for the conception and evaluation of the method adequacy in the range of moisture content 10 to 15 percent (w.b) of the pasta. The prediction models based on partial least squares (PLS) regression, were developed in the near-infrared. Conventional criteria such as the R2, the root mean square errors of cross validation (RMSECV), root mean square errors of estimation (RMSEE) as well as the number of PLS factors were considered for the selection of three pre-processing (vector normalization, minimum-maximum normalization and multiplicative scatter correction) methods. Spectra of pasta sample were treated with different mathematic pre-treatments before being used to build models between the spectral information and moisture content. The moisture content in pasta predicted by FT-NIR methods had very good correlation with their values determined via traditional methods (R2 = 0.983), which clearly indicated that FT-NIR methods could be used as an effective tool for rapid determination of moisture content in pasta. The best calibration model was developed with min-max normalization (MMN) spectral pre-processing (R2 = 0.9775). The MMN pre-processing method was found most suitable and the maximum coefficient of determination (R2) value of 0.9875 was obtained for the calibration model developed.

Keywords: FT-NIR, pasta, moisture determination, food engineering

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Authors: Ronak Khosravi, Mahmood Abbasi Layegh, Siamak Haghipour, Avin Esmaili

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In this paper, a study on classification of musical woodwind instruments using a small set of features selected from a broad range of extracted ones by the sequential forward selection method was carried out. Firstly, we extract 42 features for each record in the music database of 402 sound files belonging to five different groups of Flutes (end blown and internal duct), Single –reed, Double –reed (exposed and capped), Triple reed and Quadruple reed. Then, the sequential forward selection method is adopted to choose the best feature set in order to achieve very high classification accuracy. Two different classification techniques of support vector machines and relevance vector machines have been tested out and an accuracy of up to 96% can be achieved by using 21 time, frequency and coefficient features and relevance vector machine with the Gaussian kernel function.

Keywords: coefficient features, relevance vector machines, spectral features, support vector machines, temporal features

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Authors: Keerti Kembhavi, M. R. Archana, V. Anjaneyappa

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Most asphalt pavement condition evaluation use rating frameworks in which asphalt pavement distress is estimated by type, extent, and severity. Rating is carried out by the pavement condition rating (PCR), which is tedious and expensive. This paper presents the development of a low-cost technique for image pavement distress analysis that permits the identification of pothole and cracks. The paper explores the application of image processing tools for the detection of potholes and cracks. Longitudinal cracking and pothole are detected using Fuzzy-C- Means (FCM) and proceeded with the Spectral Theory algorithm. The framework comprises three phases, including image acquisition, processing, and extraction of features. A digital camera (Gopro) with the holder is used to capture pavement distress images on a moving vehicle. FCM classifier and Spectral Theory algorithms are used to compute features and classify the longitudinal cracking and pothole. The Matlab2016Ra Image preparing tool kit utilizes performance analysis to identify the viability of pavement distress on selected urban stretches of Bengaluru city, India. The outcomes of image evaluation with the utilization semi-computerized image handling framework represented the features of longitudinal crack and pothole with an accuracy of about 80%. Further, the detected images are validated with the actual dimensions, and it is seen that dimension variability is about 0.46. The linear regression model y=1.171x-0.155 is obtained using the existing and experimental / image processing area. The R2 correlation square obtained from the best fit line is 0.807, which is considered in the linear regression model to be ‘large positive linear association’.

Keywords: crack detection, pothole detection, spectral clustering, fuzzy-c-means

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Authors: K. Swapna, Sk. Mahamuda, Ch, Annapurna, A. Srinivasa Rao, G. Vijaya Prakash

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Samarium ions doped Alkali Fluoro Tungsten Tellurite (AFTT) Glasses have been prepared by using the melt quenching technique and characterized through various spectroscopic techniques such as optical absorption, excitation, emission and decay spectral studies. From the measured absorption spectra of Sm3+ ions in AFTT glasses, the optical band gap and Urbach energies have been evaluated. The spectroscopic parameters such as oscillator strengths (f), Judd-Ofelt (J-O) intensity parameters (Ωλ), spontaneous emission probability (AR), branching ratios (βR) and radiative lifetimes (τR) of various excited levels have been determined from the absorption spectrum by using J-O analysis. A strong luminescence in the reddish-orange spectral region has been observed for all the Sm3+ ions doped AFTT glasses. It consisting four emission transitions occurring from the 4G5/2metastable state to the lower lying states 6H5/2, 6H7/2, 6H9/2 and 6H11/2 upon exciting the sample with a 478 nm line of an argon ion laser. The stimulated emission cross-sections (σe) and branching ratios (βmeas) were estimated from the emission spectra for all emission transitions. Correlation of the radiative lifetime with the experimental lifetime measured from the day curves allows us to measure the quantum efficiency of the prepared glasses. In order to know the colour emission of the prepared glasses under near UV excitation, the emission intensities were analyzed using CIE 1931 colour chromaticity diagram. The aforementioned spectral studies carried out on Sm3+ ions doped AFTT glasses allowed us to conclude that, these glasses are best suited for orange-red visible lasers.

Keywords: fluoro tungsten tellurite glasses, judd-ofelt intensity parameters, lifetime, stimulated emission cross-section

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Authors: Nageeb A. H. Haroun, Sabyasachi Mondal, Precious Sibanda

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The effects of thermal radiation, Soret and Dufour parameters on mixed convection and nanofluid flow over a stretching sheet in the presence of a magnetic field are investigated. The flow is subject to temperature dependent viscosity and a chemical reaction parameter. It is assumed that the nanoparticle volume fraction at the wall may be actively controlled. The physical problem is modelled using systems of nonlinear differential equations which have been solved numerically using a spectral relaxation method. In addition to the discussion on heat and mass transfer processes, the velocity, nanoparticles volume fraction profiles as well as the skin friction coefficient are determined for different important physical parameters. A comparison of current findings with previously published results for some special cases of the problem shows an excellent agreement.

Keywords: non-isothermal wedge, thermal radiation, nanofluid, magnetic field, soret and dufour effects

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Authors: Sarre Nzaba, Bulelwa Ntsendwana, Bekkie Mamba, Alex Kuvarega

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The discharge of azo dyes such as Brilliant black (BB) into the water bodies has carcinogenic and mutagenic effects on humankind and the ecosystem. Conventional water treatment techniques fail to degrade these dyes completely thereby posing more problems. Advanced oxidation processes (AOPs) are promising technologies in solving the problem. Anatase type nitrogen-platinum (N, Pt) co-doped TiO₂ photocatalysts were prepared by a modified sol-gel method using amine terminated polyamidoamine generation 1 (PG1) as a template and source of nitrogen. The resultant photocatalysts were characterized by X‐ray diffraction (XRD), scanning electron microscopy (SEM), transmission electron microscopy (TEM), X‐ray photoelectron spectroscopy (XPS), UV‐Vis diffuse reflectance spectroscopy, photoluminescence spectroscopy (PL), Fourier transform infrared spectroscopy (FTIR), Raman spectroscopy (RS), thermal gravimetric analysis (TGA). The results showed that the calcination atmosphere played an important role in the morphology, crystal structure, spectral absorption, oxygen vacancy concentration, and visible light photocatalytic performance of the catalysts. Anatase phase particles ranging between 9- 20 nm were also confirmed by TEM, SEM, and analysis. The origin of the visible light photocatalytic activity was attributed to both the elemental N and Pd dopants and the existence of oxygen vacancies. Co-doping imparted a shift in the visible region of the solar spectrum. The visible light photocatalytic activity of the samples was investigated by monitoring the photocatalytic degradation of brilliant black dye. Co-doped TiO₂ showed greater photocatalytic brilliant black degradation efficiency compared to singly doped N-TiO₂ or Pd-TiO₂ under visible light irradiation. The highest reaction rate constant of 3.132 x 10-2 min⁻¹ was observed for N, Pd co-doped TiO₂ (2% Pd). The results demonstrated that the N, Pd co-doped TiO₂ (2% Pd) sample could completely degrade the dye in 3 h, while the commercial TiO₂ showed the lowest dye degradation efficiency (52.66%).

Keywords: brilliant black, Co-doped TiO₂, polyamidoamine generation 1 (PAMAM G1), photodegradation

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Authors: Shigenori Togashi, Yukako Asano

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We developed an effective microfluidic device for photoreactions with low reflectance and good heat conductance. The performance of this microfluidic device was tested by carrying out a photoreactive synthesis of benzopinacol and acetone from benzophenone and 2-propanol. The yield reached 36% with an irradiation time of 469.2 s and was improved by more than 30% when compared to the values obtained by the batch method. Therefore, the microfluidic device was found to be effective for improving the yields of photoreactions.

Keywords: microfluidic device, photoreaction, black aluminum oxide, benzophenone, yield improvement

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Authors: Desta Gebretekle Shiferaw, Balakrishna Kalluraya

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Pyrazole is an aromatic five-membered heterocycle with two nitrogen and three carbon atoms in its ring structure. According to the literature, pyrazoline, pyrazole, and thiazole-containing moieties are found in various drug structures and are responsible for nearly all pharmacological effects. The pyrazoline linked to pyrazole moiety carbothioamides was synthesized via the reaction of pyrazole-bearing chalcones (3-(5-chloro-3-methyl-¹-phenyl-1H-pyrazol-4-yl)-¹-(substituted aryl) prop-2-ene-¹-one derivatives) with a nucleophile thiosemicarbohyrazide by heating in ethanol using fused sodium acetate as a catalyst. Then the carbothioamide derivatives were converted into the pyrazoline hybrid to pyrazole and thiazole derivatives by condensing with substituted phenacyl bromide in alcohol in a basic medium. Next, the chemical structure of the newly synthesized molecules was confirmed by IR, 1H-NMR, and mass spectral data. Further, they were screened for their in vitro antioxidant activity. Compared to butylated hydroxy anisole (BHA)., the antioxidant data showed that the synthesized compounds had good to moderate activity.

Keywords: pyrazoline-pyrazole carbothioamide derivatives, pyrazoline-pyrazole-thiazole derivatives, spectral studies, antioxidant activity

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Authors: Javier Muro, Anja Linstadter, Florian Manner, Lisa Schwarz, Stephan Wollauer, Paul Magdon, Gohar Ghazaryan, Olena Dubovyk

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Monitoring the trade-off between biomass production and biodiversity in grasslands is critical to evaluate the effects of management practices across environmental gradients. New generations of remote sensing sensors and machine learning approaches can model grasslands’ characteristics with varying accuracies. However, studies often fail to cover a sufficiently broad range of environmental conditions, and evidence suggests that prediction models might be case specific. In this study, biomass production and biodiversity indices (species richness and Fishers’ α) are modeled in 150 grassland plots for three sites across Germany. These sites represent a North-South gradient and are characterized by distinct soil types, topographic properties, climatic conditions, and management intensities. Predictors used are derived from Sentinel-1 & 2 and a set of topoedaphic variables. The transferability of the models is tested by training and validating at different sites. The performance of feed-forward deep neural networks (DNN) is compared to a random forest algorithm. While biomass predictions across gradients and sites were acceptable (r2 0.5), predictions of biodiversity indices were poor (r2 0.14). DNN showed higher generalization capacity than random forest when predicting biomass across gradients and sites (relative root mean squared error of 0.5 for DNN vs. 0.85 for random forest). DNN also achieved high performance when using the Sentinel-2 surface reflectance data rather than different combinations of spectral indices, Sentinel-1 data, or topoedaphic variables, simplifying dimensionality. This study demonstrates the necessity of training biomass and biodiversity models using a broad range of environmental conditions and ensuring spatial independence to have realistic and transferable models where plot level information can be upscaled to landscape scale.

Keywords: ecosystem services, grassland management, machine learning, remote sensing

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Authors: A. Giniatoulline

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We consider the internal oscillations of the ocean which are caused by the gravity force and the Coriolis force, for different models with changeable density, heat transfer, and salinity. Traditionally, the mathematical description of the resonance effect is related to the growing amplitude as a result of input vibrations. We offer a different approach: the study of the relation between the spectrum of the internal oscillations and the properties of the limiting amplitude of the solution for the harmonic input vibrations of the external forces. Using the results of the spectral theory of self-adjoint operators in Hilbert functional spaces, we prove that there exists an explicit relation between the localization of the frequency of the external input vibrations with respect to the essential spectrum of proper inner oscillations and the non-uniqueness of the limiting amplitude. The results may find their application in various problems concerning mathematical modeling of turbulent flows in the ocean.

Keywords: computational fluid dynamics, essential spectrum, limiting amplitude, rotating fluid, spectral theory, stratified fluid, the uniqueness of solutions of PDE equations

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Authors: Pradeepa Teegala, Ramreddy Chitteti

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This article analyzes the mixed convection flow of chemically reacting micropolar fluid over a truncated cone embedded in non-Darcy porous medium with convective boundary condition. In addition, heat generation/absorption and Joule heating effects are taken into consideration. The similarity solution does not exist for this complex fluid flow problem, and hence non-similarity transformations are used to convert the governing fluid flow equations along with related boundary conditions into a set of nondimensional partial differential equations. Many authors have been applied the spectral quasi-linearization method to solve the ordinary differential equations, but here the resulting nonlinear partial differential equations are solved for non-similarity solution by using a recently developed method called the spectral quasi-linearization method (SQLM). Comparison with previously published work on special cases of the problem is performed and found to be in excellent agreement. The effect of pertinent parameters namely, Biot number, mixed convection parameter, heat generation/absorption, Joule heating, Forchheimer number, chemical reaction, micropolar and magnetic field on physical quantities of the flow are displayed through graphs and the salient features are explored in detail. Further, the results are analyzed by comparing with two special cases, namely, vertical plate and full cone wherever possible.

Keywords: chemical reaction, convective boundary condition, joule heating, micropolar fluid, mixed convection, spectral quasi-linearization method

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Authors: Kamal, Dinesh Kumar, J. P. Narayan, Komal Rani

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This paper presents the effects of shape of basement topography on the characteristics of the basin-generated surface (BGS) waves and associated average spectral amplification (ASA) in the 3D basins having circular surface area. Seismic responses were computed using a recently developed 3D fourth-order spatial accurate time-domain finite-difference (FD) algorithm based on parsimonious staggered-grid approximation of 3D viscoelastic wave equations. An increase of amplitude amplification and ASA towards the centre of different considered basins was obtained. Further, it may be concluded that ASA in basin very much depends on the impedance contrast, exposure area of basement to the incident wave front, edge-slope, focusing of the BGS-waves and sediment-damping. There is an urgent need of incorporation of a map of differential ground motion (DGM) caused by the BGS-waves as one of the output maps of the seismic microzonation.

Keywords: 3D viscoelastic simulation, basin-generated surface waves, maximum displacement, average spectral amplification

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Authors: Bekim Berisha, Sebastian Hirsiger, Pavel Hora

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Advanced material models involving several sets of model parameters require a big experimental effort. As models are getting more and more complex like e.g. the so called “Homogeneous Anisotropic Hardening - HAH” model for description of the yielding behavior in the 2D/3D stress space, the number and complexity of the required experiments are also increasing continuously. In the context of sheet metal forming, these requirements are even more pronounced, because of the anisotropic behavior or sheet materials. In addition, some of the experiments are very difficult to perform e.g. the plane stress biaxial compression test. Accordingly, tensile tests in at least three directions, biaxial tests and tension-compression or shear-reverse shear experiments are performed to determine the parameters of the macroscopic models. Therefore, determination of the macroscopic model parameters based on virtual experiments is a very promising strategy to overcome these difficulties. For this purpose, in the framework of multiscale material modeling, a dislocation density based crystal plasticity model in combination with a FFT-based spectral solver is applied to perform virtual experiments. Modeling of the plastic behavior of metals based on crystal plasticity theory is a well-established methodology. However, in general, the computation time is very high and therefore, the computations are restricted to simplified microstructures as well as simple polycrystal models. In this study, a dislocation density based crystal plasticity model – including an implementation of the backstress – is used in a spectral solver framework to generate virtual experiments for three deep drawing materials, DC05-steel, AA6111-T4 and AA4045 aluminum alloys. For this purpose, uniaxial as well as multiaxial loading cases, including various pre-strain histories, has been computed and validated with real experiments. These investigations showed that crystal plasticity modeling in the framework of Representative Volume Elements (RVEs) can be used to replace most of the expensive real experiments. Further, model parameters of advanced macroscopic models like the HAH model can be determined from virtual experiments, even for multiaxial deformation histories. It was also found that crystal plasticity modeling can be used to model anisotropic hardening more accurately by considering the backstress, similar to well-established macroscopic kinematic hardening models. It can be concluded that an efficient coupling of crystal plasticity models and the spectral solver leads to a significant reduction of the amount of real experiments needed to calibrate macroscopic models. This advantage leads also to a significant reduction of computational effort needed for the optimization of metal forming process. Further, due to the time efficient spectral solver used in the computation of the RVE models, detailed modeling of the microstructure are possible.

Keywords: anisotropic hardening, crystal plasticity, micro structure, spectral solver

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Authors: Javier Fernandez, Mayte Medina, Rafael Fernandez de Canete, Nuria Alcain, Juan Carlos Ramos-Diaz

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At present, the experimentation of anesthetic drugs on patients requires a regulation protocol, and the response of each patient to several doses of entry drug must be well known. Therefore, the development of pharmacological dose control systems is a promising field of research in anesthesiology. In this paper, it has been developed a non-linear compartmental the pharmacokinetic-pharmacodynamical model which describes the anesthesia depth effect in a sufficiently reliable way over a set of patients with the depth effect quantified by the Bi-Spectral Index. Afterwards, an Artificial Neural Network (ANN) predictive controller has been designed based on the depth of anesthesia model so as to keep the patient in the optimum condition while he undergoes surgical treatment. For the purpose of quantifying the efficiency of the neural predictive controller, a classical proportional-integral-derivative controller has also been developed to compare both strategies. Results show the superior performance of predictive neural controller during BiSpectral Index reference tracking.

Keywords: anesthesia, bi-spectral index, neural network control, pharmacokinetic-pharmacodynamical model

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Authors: Yimei Huang, Harvey Lui, Jianhua Zhao, Zhenguo Wu, Haishan Zeng

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Conventional laser treatment of skin diseases and cosmetic surgery is based on the principle of one-photon absorption selective photothermolysis which relies strongly on the difference in the light absorption between the therapeutic target and its surrounding tissue. However, when the difference in one-photon absorption is not sufficient, collateral damage would occur due to indiscriminate and nonspecific tissue heating. To overcome this problem, we developed a spatially selective photothermolysis method based on multiphoton absorption in which the heat generation is restricted to the focal point of a tightly focused near-infrared femtosecond laser beam aligned with the target of interest. A multimodal optical microscope with co-registered reflectance confocal imaging (RCM), two-photon fluorescence imaging (TPF), and second harmonic generation imaging (SHG) capabilities was used to perform and monitor the spatially selective photothermolysis. Skin samples excised from the shaved backs of euthanized NODSCID mice were used in this study. Treatments were performed by focusing and scaning the laser beam in the dermis with a 50µm×50µm target area. Treatment power levels of 200 mW to 400 mW and modulated pulse trains of different duration and period were experimented. Different treatment parameters achieved different degrees of spatial confinement of tissue alterations as visualized by 3-D RCM/TPF/SHG imaging. At 200 mW power level, 0.1 s pulse train duration, 4.1 s pulse train period, the tissue damage was found to be restricted precisely to the 50µm×50µm×10µm volume, where the laser focus spot had scanned through. The overlying epidermis/dermis tissue and the underneath dermis tissue were intact although there was light passing through these regions.

Keywords: multiphoton absorption photothermolysis, reflectance confocal microscopy, second harmonic generation microscopy, spatially selective photothermolysis, two-photon fluorescence microscopy

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Authors: N. Lakshmipathy, Ch. S. N. Murthy, M. Aruna

Abstract:

The design of lighting systems for surface mines is not an easy task because of the unique environment and work procedures encountered in the mines. The primary objective of this paper is to identify the major problems encountered in mine lighting application and to provide guidance in the solution of these problems. In the surface mining reflectance of surrounding surfaces is one of the important factors, which improve the vision, in the night hours. But due to typical working nature in the mines it is very difficult to fulfill these requirements, and also the orientation of the light at work site is a challenging task. Due to this reason machine operator and other workers in a mine need to be able to orient themselves in a difficult visual environment. The haul roads always keep on changing to tune with the mining activity. Other critical area such as dumpyards, stackyards etc. also change their phase with time, and it is difficult to illuminate such areas. Mining is a hazardous occupation, with workers exposed to adverse conditions; apart from the need for hard physical labor, there is exposure to stress and environmental pollutants like dust, noise, heat, vibration, poor illumination, radiation, etc. Visibility is restricted when operating load haul dumper and Heavy Earth Moving Machinery (HEMM) vehicles resulting in a number of serious accidents. one of the leading causes of these accidents is the inability of the equipment operator to see clearly people, objects or hazards around the machine. Results indicate blind spots are caused primarily by posts, the back of the operator's cab, and by lights and light brackets. The careful designed and implemented, lighting systems provide mine workers improved visibility and contribute to improved safety, productivity and morale. Properly designed lighting systems can improve visibility and safety during working in the opencast mines.

Keywords: contrast, efficacy, illuminance, illumination, light, luminaire, luminance, reflectance, visibility

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Authors: Nahed O. Bawakid, Walied M. Alarif

Abstract:

With regard to the uniqueness of the red algae of the genus Laurencia as the source of C₁₅-acetogenins, along with the diversity of biological applications; the acetogenin content of the Red Sea L. obtusa was investigated. Fractionation and purification of the CH₂Cl₂/MeOH extract were done by applying several chromatographic techniques, including column and preparative thin-layer chromatography; followed by a series of ¹H nuclear magnetic resonance measurements to give rise of some interesting notes. A new rare chloroallene-based C₁₅ acetogenin, laurentusenin (1) along with a new furan ring containing C₁₅ acetogenin, laurenfuresenin (2), were isolated from the red alga L. obtusa. Comparing 1D and 2D NMR, MS, UV and IR spectral data for the new isolated compounds with the reported bromoallene containing acetogenins spectral data was played the crucial role for characterization of their hemical structures. The apoptosis induced by these two compounds was demonstrated by DNA fragmentation assay and microscopic observation. These observations suggest that (1) and (2) may be involved in regulation of programmed death in the initiation and propagation of inflammatory responses. The isolated metabolite (1) showed unusual substituted allene side chain, while (2) inserted furan ring as a new acetogenin nucleus.

Keywords: cyclic enyne, anti-inflammatory, fatty acids, marine algae, halogenations

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Authors: Hamed Mohamed Haggag

Abstract:

Prior to 12 November 1955, no earthquakes have been reported from the Abu Dabbab area in the International Seismological Center catalogue (ISC). The largest earthquake in Abu Dabbab area occurred on November 12, 1955 with magnitude Mb 6.0. The closest station from the epicenter was at Helwan (about 700 km to the north), so the depth of this event is not constrained and no foreshocks or aftershocks were recorded. Two other earthquakes of magnitude Mb 4.5 and 5.2 took place in the same area on March 02, 1982 and July 02, 1984, respectively. Since the installation of Aswan Seismic Network stations in 1982, (250-300 km to the south-west of Abu Dabbab area) then the Egyptian Natoinal Seismic Network stations, it was possible to record some activity from Abu Dabbab area. The recorded earthquakes at Abu Dabbab area as recorded from 1982 to 2014 shows that the earthquake epicenters are distributed in the same direction of the main trends of the faults in the area, which is parallel to the Red Sea coast. The spectral analysis was made for some earthquakes. The source parameters, seismic moment (Mo), source dimension (r), stress drop (Δδ), and apparent stress (δ) are determined for these events. The spectral analysis technique was completed using MAG software program.

Keywords: Abu Dabbab, seismicity, seismic moment, source parameter

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Authors: Tawfig Eltaif, Hesham A. Bakarman, N. Alsowaidi, M. R. Mokhtar, Malek Harbawi

Abstract:

In Commonly, it is primary problem that there is multiple user interference (MUI) noise resulting from the overlapping among the users in optical code-division multiple access (OCDMA) system. In this article, we aim to mitigate this problem by studying an interference cancellation scheme called successive interference cancellation (SIC) scheme. This scheme will be tested on two different detection schemes, spectral amplitude coding (SAC) and direct detection systems (DS), using partial modified prime (PMP) as the signature codes. It was found that SIC scheme based on both SAC and DS methods had a potential to suppress the intensity noise, that is to say, it can mitigate MUI noise. Furthermore, SIC/DS scheme showed much lower bit error rate (BER) performance relative to SIC/SAC scheme for different magnitude of effective power. Hence, many more users can be supported by SIC/DS receiver system.

Keywords: optical code-division multiple access (OCDMA), successive interference cancellation (SIC), multiple user interference (MUI), spectral amplitude coding (SAC), partial modified prime code (PMP)

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Authors: Courret Gilles, Pidoux Damien

Abstract:

Considering that sunshine is the ultimate reference in lighting, we have examined the spectral correlation between a series of electric light sources and sunlight. As the latter is marked by fluctuations, we have taken two spectra of reference: on the one hand, the CIE daylight standard illuminant, and on the other hand, the global illumination by the clear sky with the sun at 30° above the horizon. We determined the coefficients of correlation between the spectra filtered by the sensitivity of the CIE standard observer for photopic vision. We also calculated the luminous efficiency of the radiation in order to compare the ideal energy performances as well as the CIE color indexes Ra, Ra14, and Rf, since the choice of a light source requires a trade-off between color rendering and luminous efficiency. The benchmarking includes the most commonly used bulbs, various white LED (Lighting Emitting Diode) of warm white or cold white types, incandescent halogen as well as two HID lamps (High-Intensity Discharge) and two plasma lamps of different types, a solar simulator and a new version of the sulfur lamp. The latter obtains the best correlation, whether in comparison with the solar spectrum or that of the standard illuminant.

Keywords: electric light sources, plasma lamp, daylighting, sunlight, spectral correlation

Procedia PDF Downloads 155