Search results for: fourier transform infrared spectroscopy(ftir)

Authors: Mazaher Yarmohamadi-Vasel, Ali Reza Modarresi-Alama, Sahar Shabzendedara

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Purpose/Objectives: The first purpose was synthesize Poly(N-(sulfophenyl)aniline) nanoflowers (PSANFLs) and Poly(N-(sulfophenyl)aniline) nanofibers/titanium dioxide nanoparticles ((PSANFs/TiO2NPs) by a solid-state mechano-chemical reaction and template-free method and use them in hybrid solar cell. Also, our second aim was to increase the solubility and the processability of conjugated nanomaterials in water through polar functionalized materials. poly[N-(4-sulfophenyl)aniline] is easily soluble in water because of the presence of polar groups of sulfonic acid in the polymer chain. Materials/Methods: Iron (III) chloride hexahydrate (FeCl3∙6H2O) were bought from Merck Millipore Company. Titanium oxide nanoparticles (TiO2, <20 nm, anatase) and Sodium diphenylamine-4-sulfonate (99%) were bought from Sigma-Aldrich Company. Titanium dioxide nanoparticles paste (PST-20T) was prepared from Sharifsolar Co. Conductive glasses coated with indium tin oxide (ITO) were bought from Xinyan Technology Co (China). For the first time we used the solid-state mechano-chemical reaction and template-free method to synthesize Poly(N-(sulfophenyl)aniline) nanoflowers. Moreover, for the first time we used the same technique to synthesize nanocomposite of Poly(N-(sulfophenyl)aniline) nanofibers and titanium dioxide nanoparticles (PSANFs/TiO2NPs) also for the first time this nanocomposite was synthesized. Examining the results of electrochemical calculations energy gap obtained by CV curves and UV–vis spectra demonstrate that PSANFs/TiO2NPs nanocomposite is a p-n type material that can be used in photovoltaic cells. Doctor blade method was used to creat films for three kinds of hybrid solar cells in terms of different patterns like ITO│TiO2NPs│Semiconductor sample│Al. In the following, hybrid photovoltaic cells in bilayer and bulk heterojunction structures were fabricated as ITO│TiO2NPs│PSANFLs│Al and ITO│TiO2NPs│PSANFs /TiO2NPs│Al, respectively. Fourier-transform infrared spectra, field emission scanning electron microscopy (FE-SEM), ultraviolet-visible spectra, cyclic voltammetry (CV) and electrical conductivity were the analysis that used to characterize the synthesized samples. Results and Conclusions: FE-SEM images clearly demonstrate that the morphology of the synthesized samples are nanostructured (nanoflowers and nanofibers). Electrochemical calculations of band gap from CV curves demonstrated that the forbidden band gap of the PSANFLs and PSANFs/TiO2NPs nanocomposite are 2.95 and 2.23 eV, respectively. I–V characteristics of hybrid solar cells and their power conversion efficiency (PCE) under 100 mWcm−2 irradiation (AM 1.5 global conditions) were measured that The PCE of the samples were 0.30 and 0.62%, respectively. At the end, all the results of solar cell analysis were discussed. To sum up, PSANFLs and PSANFLs/TiO2NPs were successfully synthesized by an affordable and straightforward mechanochemical reaction in solid-state under the green condition. The solubility and processability of the synthesized compounds have been improved compared to the previous work. We successfully fabricated hybrid photovoltaic cells of synthesized semiconductor nanostructured polymers and TiO2NPs as different architectures. We believe that the synthesized compounds can open inventive pathways for the development of other Poly(N-(sulfophenyl)aniline based hybrid materials (nanocomposites) proper for preparing new generation solar cells.

Keywords: mechanochemical synthesis, PSANFLs, PSANFs/TiO2NPs, solar cell

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Authors: Rajesh Kumar, Puneet Aggarwal

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In context of understanding problems faced by undergraduate students while carrying out laboratory experiments dealing with high voltages, it was found that most of the students are hesitant to work directly on machine. The reason is that error in the circuitry might lead to deterioration of machine and laboratory instruments. So, it has become inevitable to include modern pedagogic techniques for undergraduate students, which would help them to first carry out experiment in virtual system and then to work on live circuit. Further advantages include that students can try out their intuitive ideas and perform in virtual environment, hence leading to new research and innovations. In this paper, virtual environment used is of MATLAB/Simulink for three-phase induction machines. The performance analysis of three-phase induction machine is carried out using virtual environment which includes Direct Current (DC) Test, No-Load Test, and Block Rotor Test along with speed torque characteristics for different rotor resistances and input voltage, respectively. Further, this paper carries out computer aided teaching of basic Voltage Source Inverter (VSI) drive circuitry. Hence, this paper gave undergraduates a clearer view of experiments performed on virtual machine (No-Load test, Block Rotor test and DC test, respectively). After successful implementation of basic tests, VSI circuitry is implemented, and related harmonic distortion (THD) and Fast Fourier Transform (FFT) of current and voltage waveform are studied.

Keywords: block rotor test, DC test, no load test, virtual environment, voltage source inverter

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Authors: Suman Chaudhary, Rupinder K. Kanwar, Jagat R. Kanwar

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Azadirachta indica, also known as Neem belonging to the mahogany family is actively gaining interest in the era of modern day medicine due to its extensive applications in homeopathic medicine such as Ayurveda and Unani. More than 140 phytochemicals have been extracted from neem leaves, seed, bark and flowers for agro-medicinal applications. Among the various components, neem leaf protein (NLP) is currently the most investigated active ingredient, due to its immunomodulatory activities against tumor growth. However, these therapeutic ingredients of neem are susceptible to degradation and cannot withstand the drastic pH changes under physiological environment, and therefore, there is an urgent need of an alternative strategy such as a nano-delivery system to exploit its medicinal benefits. This study hypothesizes that guar gum (GG) derived biodegradable nano-carrier based encapsulation of NLP will improve its stability, specificity and sensitivity, thus facilitating targeted anti-cancer therapeutics. GG is a galactomannan derived from the endosperm of the guar beans seeds. Synthesis of guar nanocapsules (NCs) was performed using nanoprecipitation technique where the GG was encapsulated with NLP. Preliminary experiments conducted to characterize the NCs confirmed spherical morphology with a narrow size distribution of 30-40 nm. Differential scanning colorimetric analysis (DSC) validated the stability of these NCs even at a temperature range of 50-60°C which was well within the physiological and storage conditions. Thermogravimetric (TGA) analysis indicated high decomposition temperature of these NCs ranging upto 350°C. Additionally, Fourier Transform Infrared spectroscopy (FTIR) and the SDS-PAGE data acquired confirmed the successful encapsulation of NLP in the NCs. The anti-cancerous therapeutic property of this NC was tested on colon cancer cells (caco-2) as they are one of the most prevalent form of cancer. These NCs (both NLP loaded and void) were also tested on human intestinal epithelial cells (FHs 74) cells to evaluate their effect on normal cells. Cytotoxicity evaluation of the NCs in the cell lines confirmed that the IC50 for NLP in FHs 74 cells was ~2 fold higher than in caco-2 cells, indicating that this nanoformulation system possessed biocompatible anti-cancerous properties Immunoconfocal microscopy analysis confirmed the time dependent internalization of the NCs within 6h. Recent findings performed using Annexin V and PI staining indicated a significant increase (p ≤ 0.001) in the early and late apoptotic cell population when treated with the NCs signifying the role of NLP in inducing apoptosis in caco-2 cells. This was further validated using Western blot, Polymerase chain reaction (PCR) and Fluorescence activated cell sorter (FACS) aided protein expressional analysis which presented a downregulation of survivin, an anti-apoptotic cell marker and upregulation of Bax/Bcl-2 ratio (pro-apoptotic indicator). Further, both the NLP NC and unencapsulated NLP treatment destabilized the mitochondrial membrane potential subsequently facilitating the release of the pro-apoptotic caspase cascade initiator, cytochrome-c. Future studies will be focused towards granting specificity to these NCs towards cancer cells, along with a comprehensive analysis of the anti-cancer potential of this naturally occurring compound in different cancer and in vivo animal models, will validate the clinical application of this unprecedented protein therapeutic.

Keywords: anti-tumor, guar gum, nanocapsules, neem leaf protein

Procedia PDF Downloads 177

Authors: Sheila Shahidi

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UV protection by fabrics has recently become a focus of great interest, particularly in connection with environmental degradation or ozone layer depletion. Fabrics provide simple and convenient protection against UV radiation (UVR), but not all fabrics offer sufficient UV protection. To describe the degree of UVR protection offered by clothing materials, the ultraviolet protection factor (UPF) is commonly used. UV-protective fabric can be generated by application of a chemical finish using normal wet-processing methodologies. However, traditional wet-processing techniques are known to consume large quantities of water and energy and may lead to adverse alterations of the bulk properties of the substrate. Recently, usage of plasmas to generate physicochemical surface modifications of textile substrates has become an intriguing approach to replace or enhance conventional wet-processing techniques. In this research work the effect of plasma treatment on UV protection properties of fabrics was investigated. DC magnetron sputtering was used and the parameters of plasma such as gas type, electrodes, time of exposure, power and, etc. were studied. The morphological and chemical properties of samples were analyzed using Scanning Electron Microscope (SEM) and Furrier Transform Infrared Spectroscopy (FTIR), respectively. The transmittance and UPF values of the original and plasma-treated samples were measured using a Shimadzu UV3101 PC (UV–Vis–NIR scanning spectrophotometer, 190–2, 100 nm range). It was concluded that, plasma which is an echo-friendly, cost effective and dry technique is being used in different branches of the industries, and will conquer textile industry in the near future. Also it is promising method for preparation of UV protection textile.

Keywords: fabric, plasma, textile, UV protection

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Authors: Samhani Ismail, Tahamina Begum, Faruque Reza, Zamzuri Idris, Hafizan Juahir, Jafri Malin Abdullah

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Holy Quran, a rhymed prosed scripture has a complete literary structure that exemplifies the peak of literary beauty. Memorizing of its verses could enhance one’s memory capacity and cognition while those who are listening to its recitation it is also believed that the Holy Quran alter brainwave producing neuronal excitation engaging with cognitive processes. 28 normal healthy subjects (male =14 & female = 14) were recruited and EEG recording was done using 128-electrode sensor net (Electrical Geosics, Inc.) with the impedance of ≤ 50kΩ. They listened to Sura Fatiha recited by Sheikh Qari Abdul Basit bin Abdus Samad. Arabic news and no sound were chosen as positive and negative control, respectively. The waveform was analysed by Fast Fourier Transform (FFT) to get the power in frequency bands. Bilateral frontal (F7, F8) and temporal region (T7, T8) showed decreased power significantly in alpha wave band in respondent stimulated by Sura Fatihah recitation reflects acoustic attention processing. However, decreased in alpha power in selective attention to memorized, and in familial but not memorized language, reveals the memorial processing in long-term memory. As a conclusion, Quranic recitation relates both cognitive element of memory and language in its listeners and memorizers.

Keywords: auditory stimulation, cognition, EEG, linguistic, memory, Quranic recitation

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Authors: Naheem Olakunle Adesina

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The memristor is considered as one of the promising candidates for mamoelectronic engineering and applications. Owing to its high compatibility with CMOS, nanoscale size, and low power consumption, memristor has been employed in the design of commonly used circuits such as phase-locked loop (PLL). In this paper, we designed a memristor-based loop filter (LF) together with other components of PLL. Following this, we evaluated the noise-rejection feature of loop filter by comparing the noise levels of input and output signals of the filter. Our SPICE simulation results showed that memristor behaves like a linear resistor at high frequencies. The result also showed that loop filter blocks the high-frequency components from phase frequency detector so as to provide a stable control voltage to the voltage controlled oscillator (VCO). In addition, we examined the effects of temperature on the performance of the designed phase locked loop circuit. A critical temperature, where there is frequency drift of VCO as a result of variations in control voltage, is identified. In conclusion, the memristor is a suitable choice for nanoelectronic systems owing to a small area, low power consumption, dense nature, high switching speed, and endurance. The proposed memristor-based loop filter, together with other components of the phase locked loop, can be designed using memristive emulator and EDA tools in current CMOS technology and simulated.

Keywords: Fast Fourier Transform, hysteresis curve, loop filter, memristor, noise, phase locked loop, voltage controlled oscillator

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Authors: Belaynesh Chekol, Numan Çelebi

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The main purpose of this work is to recognize individual characters extracted from natural scene images using scale invariant feature transform (SIFT) features as an input to K-nearest neighbor (KNN); a classification learner algorithm. For this task, 1,068 and 78 images of English alphabet characters taken from Chars74k data set is used to train and test the classifier respectively. For each character image, We have generated describing features by using SIFT algorithm. This set of features is fed to the learner so that it can recognize and label new images of English characters. Two types of KNN (fine KNN and weighted KNN) were trained and the resulted classification accuracy is 56.9% and 56.5% respectively. The training time taken was the same for both fine and weighted KNN.

Keywords: character recognition, KNN, natural scene image, SIFT

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Authors: Salah Jellali, Nusiba Suliman, Yassine Charabi, Jamal Al-Sabahi, Ahmed Al Raeesi, Malik Al-Wardy, Mejdi Jeguirim

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Huge amounts of agricultural biomasses are worldwide produced. At the same time, large quantities of phosphorus are annually discharged into water bodies with possible serious effects onto the environment quality. The main objective of this work is to turn a local Omani biomass (date palm fronds wastes: DPFW) into an effective material for phosphorus recovery from aqueous and the reuse of this P-loaded material in agriculture as ecofriendly amendment. For this aim, the raw DPFW were firstly impregnated with 1 M salt separated solutions of CaCl₂, MgCl₂, FeCl₃, AlCl₃, and a mixture of MgCl₂/AlCl₃ for 24 h, and then pyrolyzed under N2 flow at 500 °C for 2 hours by using an adapted tubular furnace (Carbolite, UK). The synthetized biochars were deeply characterized through specific analyses concerning their morphology, structure, texture, and surface chemistry. These analyses included the use of a scanning electron microscope (SEM) coupled with an energy-dispersive X-Ray spectrometer (EDS), X-Ray diffraction (XRD), Fourier Transform Infrared (FTIR), sorption micrometrics, and X-ray Fluorescence (XRF) apparatus. Then, their efficiency in recovering phosphorus was investigated in batch mode for various contact times (1 min to 3 h), aqueous pH values (from 3 to 11), initial phosphorus concentrations (10-100 mg/L), presence of anions (nitrates, sulfates, and chlorides). In a second step, dynamic assays, by using laboratory columns (height of 30 cm and diameter of 3 cm), were performed in order to investigate the recovery of phosphorus by the modified biochar with a mixture of Mg/Al. The effect of the initial P concentration (25-100 mg/L), the bed depth height (3 to 8 g), and the flow rate (10-30 mL/min) was assessed. Experimental results showed that the biochars physico-chemical properties were very dependent on the type of the used modifying salt. The main affected parameters concerned the specific surface area, microporosity area, and the surface chemistry (pH of zero-point charge and available functional groups). These characteristics have significantly affected the phosphorus recovery efficiency from aqueous solutions. Indeed, the P removal efficiency in batch mode varies from about 5 mg/g for the Fe-modified biochar to more than 13 mg/g for the biochar functionalized with Mg/Al layered double hydroxides. Moreover, the P recovery seems to be a time dependent process and significantly affected by the pH of the aqueous media and the presence of foreign anions due to competition phenomenon. The laboratory column study of phosphorus recovery by the biochar functionalized with Mg/Al layered double hydroxides showed that this process is affected by the used phosphorus concentration, the flow rate, and especially the column bed depth height. Indeed, the phosphorus recovered amount increased from about 4.9 to more than 9.3 mg/g used biochar mass of 3 and 8 g, respectively. This work proved that salt-modified palm fronds-derived biochars could be considered as attractive and promising materials for phosphorus recovery from aqueous solutions even under dynamic conditions. The valorization of these P-loaded-modified biochars as eco-friendly amendment for agricultural soils is necessary will promote sustainability and circular economy concepts in the management of both liquid and solid wastes.

Keywords: date palm wastes, Mg/Al double-layered hydroxides functionalized biochars, phosphorus, recovery, sustainability, circular economy

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Authors: Gehan El-Sayed Sharaf El-Deen

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In this study, super paramagnetic iron-oxide nano- materials (SPMIN) were investigated for removal of toxic heavy metals from aqueous solution. The magnetic nanoparticles of 12 nm were synthesized using a co-precipitation method and characterized by transmission electron microscopy (TEM), transform infrared spectroscopy (FTIR), x-ray diffraction (XRD) and vibrating sample magnetometer (VSM). Batch experiments carried out to investigate the influence of different parameters such as contact time, initial concentration of metal ions, the dosage of SPMIN, desorption,pH value of solutions. The adsorption process was found to be highly pH dependent, which made the nanoparticles selectively adsorb these three metals from wastewater. Maximum sorption for all the studies cations obtained at the first half hour and reached equilibrium at one hour. The adsorption data of heavy metals studied were well fitted with the Langmuir isotherm and the equilibrium data show the percent removal of Ni2+, Zn2+ and Cd2+ were 96.5%, 80% and 75%, respectively. Desorption studies in acidic medium indicate that Zn2+, Ni2+ and Cd2+ were removed by 89%, 2% and 18% from the first cycle. Regeneration studies indicated that SPMIN nanoparticles undergoing successive adsorption–desorption processes for Zn2+ ions retained original metal removal capacity. The results revealed that the most prominent advantage of the prepared SPMIN adsorbent consisted in their separation convenience compared to the other adsorbents and SPMIN has high efficiency for removal the investigated metals from aqueous solution.

Keywords: heavy metals, magnetic nanoparticles, removal efficiency, Batch technique

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Authors: Syahira Ibrahim, Herlina Abdul Rahim

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The amylose content is an essential element in determining the texture and taste of rice grains. This paper evaluates the use of VIS-SWNIRS in estimating the amylose content for seven varieties of rice grains available in the Malaysian market. Each type consists of 30 samples and all the samples are scanned using the spectroscopy to obtain a range of values between 680-1000nm. The Savitzky-Golay (SG) smoothing filter is applied to each sample’s data before the Principal Component Regression (PCR) technique is used to examine the data and produce a single value for each sample. This value is then compared with reference values obtained from the standard iodine colorimetric test in terms of its coefficient of determination, R2. Results show that this technique produced low R2 values of less than 0.50. In order to improve the result, the range should include a wavelength range of 1100-2500nm and the number of samples processed should also be increased.

Keywords: amylose content, diffuse reflectance, Malaysia rice grain, principal component regression (PCR), Visible and Shortwave near-infrared spectroscopy (VIS-SWNIRS)

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Authors: Chunhua Liao, Jinfei Wang, Bo Shan, Yang Song, Yongjun He, Taifeng Dong

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Winter wheat is one of the main crops in Canada. Forecasting of within-field variability of yield in winter wheat at the early stages is essential for precision farming. However, the crop yield modelling based on high spatial resolution satellite data is generally affected by the lack of continuous satellite observations, resulting in reducing the generalization ability of the models and increasing the difficulty of crop yield forecasting at the early stages. In this study, the correlations between Sentinel-2 data (vegetation indices and reflectance) and yield data collected by combine harvester were investigated and a generalized multivariate linear regression (MLR) model was built and tested with data acquired in different years. It was found that the four-band reflectance (blue, green, red, near-infrared) performed better than their vegetation indices (NDVI, EVI, WDRVI and OSAVI) in wheat yield prediction. The optimum phenological stage for wheat yield prediction with highest accuracy was at the growing stages from the end of the flowering to the beginning of the filling stage. The best MLR model was therefore built to predict wheat yield before harvest using Sentinel-2 data acquired at the end of the flowering stage. Further, to improve the ability of the yield prediction at the early stages, three simple unsupervised domain adaptation (DA) methods were adopted to transform the reflectance data at the early stages to the optimum phenological stage. The winter wheat yield prediction using multiple vegetation indices showed higher accuracy than using single vegetation index. The optimum stage for winter wheat yield forecasting varied with different fields when using vegetation indices, while it was consistent when using multispectral reflectance and the optimum stage for winter wheat yield prediction was at the end of flowering stage. The average testing RMSE of the MLR model at the end of the flowering stage was 604.48 kg/ha. Near the booting stage, the average testing RMSE of yield prediction using the best MLR was reduced to 799.18 kg/ha when applying the mean matching domain adaptation approach to transform the data to the target domain (at the end of the flowering) compared to that using the original data based on the models developed at the booting stage directly (“MLR at the early stage”) (RMSE =1140.64 kg/ha). This study demonstrated that the simple mean matching (MM) performed better than other DA methods and it was found that “DA then MLR at the optimum stage” performed better than “MLR directly at the early stages” for winter wheat yield forecasting at the early stages. The results indicated that the DA had a great potential in near real-time crop yield forecasting at the early stages. This study indicated that the simple domain adaptation methods had a great potential in crop yield prediction at the early stages using remote sensing data.

Keywords: wheat yield prediction, domain adaptation, Sentinel-2, within-field scale

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Authors: A. Bouriche, D. Merah, T. Bouchaour, L. Alachaher-Bedjaoui, U. Maschke

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Intensive research continues in the field of liquid crystals (LCs) for their potential use in modern display applications. Nematic LCs has been most commonly used due to the large birefringence and their sensitivity to even weak perturbation forces induced by electric, magnetic and optical fields. Polymer dispersed liquid crystals (PDLCs), composed of micron-sized nematic LC droplets dispersed in a polymer matrix is an important class of materials for applications in different domains of technology involving large area display devices, optical switches, phase modulators, variable attenuators, polarisers, flexible displays and smart windows. In this study the composites are prepared from mixtures of mono functional acrylic monomers, (Butylacrylate (ABu), 2-Ethylhexylacrylate (2-EHA), 2-Hydroxyethyl methacrylate (HEMA) and hydroxybutylmethacrylate (HBMA)) and two liquid crystals: (4-cyano-4'-n-pentyl-biphenyl) (5CB) and E7 which is an eutectic mixtures of four cyanoparaphenylenes. These mixtures are prepared adding the Darocur 1173 as photoinitiator, the 1.6-hexanediol diacrylate (HDDA) as cross-linker agent, and finally they are exposed to UV irradiation. The kinetic polymerization of monomer/LC mixture were investigated with the Fourier Transform Infra Red spectroscopy (FTIR). The electro-optical properties of the PDLC films were determined by measuring the voltage dependence on the transmitted light.

Keywords: acrylic monomers, films PDLC, liquid crystal, polymerisation

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Authors: A. Seddiki, M. Djebbouri, D. Guerchi

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Medical imaging produces human body pictures in digital form. Since these imaging techniques produce prohibitive amounts of data, compression is necessary for storage and communication purposes. Many current compression schemes provide a very high compression rate but with considerable loss of quality. On the other hand, in some areas in medicine, it may be sufficient to maintain high image quality only in region of interest (ROI). This paper discusses a contribution to the lossless compression in the region of interest of Scintigraphic images based on SPIHT algorithm and global transform thresholding using Huffman coding.

Keywords: global thresholding transform, huffman coding, region of interest, SPIHT coding, scintigraphic images

Procedia PDF Downloads 367

Authors: Li Li, Ahmed A. Abd El-Latif, Aya El-Fatyany, Mohamed Amin

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This paper proposes a new secret image sharing method based on integer discrete cosine transform (IntDCT). It first transforms the original image into the frequency domain (DCT coefficients) using IntDCT, which are operated on each block with size 8*8. Then, it generates shares among each DCT coefficients in the same place of each block, that is, all the DC components are used to generate DC shares, the ith AC component in each block are utilized to generate ith AC shares, and so on. The DC and AC shares components with the same number are combined together to generate DCT shadows. Experimental results and analyses show that the proposed method can recover the original image lossless than those methods based on traditional DCT and is more sensitive to tiny change in both the coefficients and the content of the image.

Keywords: secret image sharing, integer DCT, lossless recovery, sensitivity

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Authors: M. V. Chidananda Murthy, M. Z. Kurian, H. S. Guruprasad

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Super-resolution is the technique of intelligently upscaling images, avoiding artifacts or blurring, and deals with the recovery of a high-resolution image from one or more low-resolution images. Single-image super-resolution is a process of obtaining a high-resolution image from a set of low-resolution observations by signal processing. While super-resolution has been demonstrated to improve image quality in scaled down images in the image domain, its effects on the Fourier-based technique remains unknown. Super-resolution substantially improved the spatial resolution of the patient LGE images by sharpening the edges of the heart and the scar. This paper aims at investigating the effects of single image super-resolution on Fourier-based and image based methods of scale-up. In this paper, first, generate a training phase of the low-resolution image and high-resolution image to obtain dictionary. In the test phase, first, generate a patch and then difference of high-resolution image and interpolation image from the low-resolution image. Next simulation of the image is obtained by applying convolution method to the dictionary creation image and patch extracted the image. Finally, super-resolution image is obtained by combining the fused image and difference of high-resolution and interpolated image. Super-resolution reduces image errors and improves the image quality.

Keywords: image dictionary creation, image super-resolution, LGE images, patch extraction

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Authors: Marcio Leal, Marta Villamil

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Computacional recognition of sign languages aims to allow a greater social and digital inclusion of deaf people through interpretation of their language by computer. This article presents a model of recognition of two of global parameters from sign languages; hand configurations and hand movements. Hand motion is captured through an infrared technology and its joints are built into a virtual three-dimensional space. A Multilayer Perceptron Neural Network (MLP) was used to classify hand configurations and Dynamic Time Warping (DWT) recognizes hand motion. Beyond of the method of sign recognition, we provide a dataset of hand configurations and motion capture built with help of fluent professionals in sign languages. Despite this technology can be used to translate any sign from any signs dictionary, Brazilian Sign Language (Libras) was used as case study. Finally, the model presented in this paper achieved a recognition rate of 80.4%.

Keywords: artificial neural network, computer vision, dynamic time warping, infrared, sign language recognition

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Authors: Stephen Daniel Iduh, Evans Chidi Egwin, Oluwatosin Kudirat Shittu

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The process for the development of reliable and eco-friendly metallic Nanoparticles is an important step in the field of Nanotechnology for biomedical application. To achieve this, use of natural sources like biological systems becomes essential. In the present work, extracellular biosynthesis of gold Nanoparticles using aqueous leave and stembark extracts of K. senegalensis has been attempted. The gold Nanoparticles produced were characterized using High Resolution scanning electron microscopy, Ultra Violet–Visible spectroscopy, zeta-sizer Nano, Energy-Dispersive X-ray (EDAX) Spectroscopy and Fourier Transmission Infrared (FTIR) Spectroscopy. The cytotoxicity of the synthesized gold nanoparticles on MCF-7 cell line was evaluated using MTT assay. The result showed a rapid development of Nano size and shaped particles within 5 minutes of reaction with Surface Plasmon Resonance at 520 and 525nm respectively. An average particle size of 20-90nm was confirmed. The amount of the extracts determines the core size of the AuNPs. The core size of the AuNPs decreases as the amount of extract increases and it causes the shift of Surface Plasmon Resonance band. The FTIR confirms the presence of biomolecules serving as reducing and capping agents on the synthesised gold nanoparticles. The MTT assay shows a significant effect of gold nanoparticles which is concentration dependent. This environment-friendly method of biological gold Nanoparticle synthesis has the potential and can be directly applied in cancer therapy.

Keywords: biosynthesis, gold nanoparticles, characterization, calotropis procera, cytotoxicity

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Authors: Zhijie Li, Wenhui Peng, Zelong Yuan, Jianchun Wang

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Turbulence is a complex phenomenon that plays a crucial role in various fields, such as engineering, atmospheric science, and fluid dynamics. Predicting and understanding its behavior over long time scales have been challenging tasks. Traditional methods, such as large-eddy simulation (LES), have provided valuable insights but are computationally expensive. In the past few years, machine learning methods have experienced rapid development, leading to significant improvements in computational speed. However, ensuring stable and accurate long-term predictions remains a challenging task for these methods. In this study, we introduce the implicit U-net enhanced Fourier neural operator (IU-FNO) as a solution for stable and efficient long-term predictions of the nonlinear dynamics in three-dimensional (3D) turbulence. The IU-FNO model combines implicit re-current Fourier layers to deepen the network and incorporates the U-Net architecture to accurately capture small-scale flow structures. We evaluate the performance of the IU-FNO model through extensive large-eddy simulations of three types of 3D turbulence: forced homogeneous isotropic turbulence (HIT), temporally evolving turbulent mixing layer, and decaying homogeneous isotropic turbulence. The results demonstrate that the IU-FNO model outperforms other FNO-based models, including vanilla FNO, implicit FNO (IFNO), and U-net enhanced FNO (U-FNO), as well as the dynamic Smagorinsky model (DSM), in predicting various turbulence statistics. Specifically, the IU-FNO model exhibits improved accuracy in predicting the velocity spectrum, probability density functions (PDFs) of vorticity and velocity increments, and instantaneous spatial structures of the flow field. Furthermore, the IU-FNO model addresses the stability issues encountered in long-term predictions, which were limitations of previous FNO models. In addition to its superior performance, the IU-FNO model offers faster computational speed compared to traditional large-eddy simulations using the DSM model. It also demonstrates generalization capabilities to higher Taylor-Reynolds numbers and unseen flow regimes, such as decaying turbulence. Overall, the IU-FNO model presents a promising approach for long-term dynamics prediction in 3D turbulence, providing improved accuracy, stability, and computational efficiency compared to existing methods.

Keywords: data-driven, Fourier neural operator, large eddy simulation, fluid dynamics

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Authors: Shivani Singla, Om Prakash Pandey, Gopi Sharma

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Metallic nanoparticle doped glasses has lead to rapid development in the field of optics. Large third order non-linearity, ultrafast time response, and a wide range of resonant absorption frequencies make these metallic nanoparticles more important in comparison to their bulk material. All these properties are highly dependent upon the size, shape, and surrounding environment of the nanoparticles. In a quest to find a suitable material for optical applications, several efforts have been devoted to improve the properties of such glasses in the past. In the present study, bismuth borate glass doped with different size gold nanoparticles (AuNPs) has been prepared using the conventional melt-quench technique. Synthesized glasses are characterized by X-ray diffraction (XRD) and Fourier Transformation Infrared spectroscopy (FTIR) to observe the structural modification in the glassy matrix with the variation in the size of the AuNPs. Glasses remain purely amorphous in nature even after the addition of AuNPs, whereas FTIR proposes that the main structure contains BO₃ and BO₄ units. Field emission scanning electron microscopy (FESEM) confirms the existence and variation in the size of AuNPs. Differential thermal analysis (DTA) depicts that prepared glasses are thermally stable and are highly suitable for the fabrication of optical fibers. The nonlinear optical parameters (nonlinear absorption coefficient and nonlinear refractive index) are calculated out by using the Z-scan technique with a Ti: sapphire laser at 800 nm. It has been concluded that the size of the nanoparticles highly influences the structural thermal and optical properties system.

Keywords: bismuth borate glass, different size, gold nanoparticles, nonlinearity

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Authors: Magdy B. Eteiba, Wael Ismael Wahba, Shimaa Barakat

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This paper presents a fault identification, classification and fault location estimation method based on Discrete Wavelet Transform and Adaptive Network Fuzzy Inference System (ANFIS) for medium voltage cable in the distribution system. Different faults and locations are simulated by ATP/EMTP, and then certain selected features of the wavelet transformed signals are used as an input for a training process on the ANFIS. Then an accurate fault classifier and locator algorithm was designed, trained and tested using current samples only. The results obtained from ANFIS output were compared with the real output. From the results, it was found that the percentage error between ANFIS output and real output is less than three percent. Hence, it can be concluded that the proposed technique is able to offer high accuracy in both of the fault classification and fault location.

Keywords: ANFIS, fault location, underground cable, wavelet transform

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Authors: R. V. Dahibhate, A. B. Deoghare, P. M. Padole

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Maintaining natural integrity of biosystem is paramount significant for orthopedic surgeon while performing surgery. Restoration is challenging task to rehabilitate trauma patient. Drilling is an inevitable procedure to fix implants. The task leads to rise in temperature at the contact site which intends to thermal necrosis. A precise monitoring can avoid thermal necrosis. To accomplish it, data acquiring instrument is integrated with the drill bit. To contemplate it, electronic feedback system is developed. It not only measures temperature without any physical contact in between measuring device and target but also visualizes the site and monitors correct movement of tool path. In the current research work an infrared thermometer data acquisition system is used which monitors variation in temperature at the drilling site and a camera captured movement of drill bit advancement. The result is presented in graphical form which represents variations in temperature, drill rotation and time. A feedback system helps in keeping drill speed in threshold limit.

Keywords: thermal necrosis, infrared thermometer, drilling tool, feedback system

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Authors: Hana Rabbouch

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In recent years, there has been considerable growth of denoising techniques mainly devoted to medical imaging. This important evolution is not only due to the progress of computing techniques, but also to the emergence of multi-resolution analysis (MRA) on both mathematical and algorithmic bases. In this paper, a comparative study is conducted between the two best-known MRA-based decomposition techniques: the Empirical Mode Decomposition (EMD) and the Discrete Wavelet Transform (DWT). The comparison is carried out in a framework of multi-scale denoising, where a Non-Local Means (NLM) filter is performed scale-by-scale to a sample of benchmark medical images. The results prove the effectiveness of the multiscaled denoising, especially when the NLM filtering is coupled with the EMD.

Keywords: medical imaging, non local means, denoising, multiscaled analysis, empirical mode decomposition, wavelets

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Authors: Nebi Gedik

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One of the significant and continual public health problems in the world is breast cancer. Early detection is very important to fight the disease, and mammography has been one of the most common and reliable methods to detect the disease in the early stages. However, it is a difficult task, and computer-aided diagnosis (CAD) systems are needed to assist radiologists in providing both accurate and uniform evaluation for mass in mammograms. In this study, a multiresolution statistical method to classify mammograms as normal and abnormal in digitized mammograms is used to construct a CAD system. The mammogram images are represented by wave atom transform, and this representation is made by certain groups of coefficients, independently. The CAD system is designed by calculating some statistical features using each group of coefficients. The classification is performed by using support vector machine (SVM).

Keywords: wave atom transform, statistical features, multi-resolution representation, mammogram

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Authors: Bienvenu Gael Fouda Mbanga

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This study reports a new approach of preparation of carbon nanoparticles coated cerium oxide nanorods (CNPs/CeONRs) nanocomposite and reusing the spent adsorbent of Cd2+- CNPs/CeONRs nanocomposite for latent fingerprint detection (LFP) after removing Cd2+ ions from aqueous solution. CNPs/CeONRs nanocomposite was prepared by using CNPs and CeONRs with adsorption processes. The prepared nanocomposite was then characterized by using UV-visible spectroscopy (UV-visible), Fourier transforms infrared spectroscopy (FTIR), X-ray diffraction pattern (XRD), scanning electron microscope (SEM), Transmission electron microscopy (TEM), Energy-dispersive X-ray spectroscopy (EDS), Zeta potential, X-ray photoelectron spectroscopy (XPS). The average size of the CNPs was 7.84nm. The synthesized CNPs/CeONRs nanocomposite has proven to be a good adsorbent for Cd2+ removal from water with optimum pH 8, dosage 0. 5 g / L. The results were best described by the Langmuir model, which indicated a linear fit (R2 = 0.8539-0.9969). The adsorption capacity of CNPs/CeONRs nanocomposite showed the best removal of Cd2+ ions with qm = (32.28-59.92 mg/g), when compared to previous reports. This adsorption followed pseudo-second order kinetics and intra particle diffusion processes. ∆G and ∆H values indicated spontaneity at high temperature (40oC) and the endothermic nature of the adsorption process. CNPs/CeONRs nanocomposite therefore showed potential as an effective adsorbent. Furthermore, the metal loaded on the adsorbent Cd2+- CNPs/CeONRs has proven to be sensitive and selective for LFP detection on various porous substrates. Hence Cd2+-CNPs/CeONRs nanocomposite can be reused as a good fingerprint labelling agent in LFP detection so as to avoid secondary environmental pollution by disposal of the spent adsorbent.

Keywords: Cd2+-CNPs/CeONRs nanocomposite, cadmium adsorption, isotherm, kinetics, thermodynamics, reusable for latent fingerprint detection

Procedia PDF Downloads 121

Authors: Sarah E. Stief, Anne Theresa Eidhoff, Markus Voeth

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Despite all progress firms are facing the increasing need to adapt and assimilate digital technologies to transform their business activities in order to pursue business development. By using new digital technologies, firms can implement major business improvements in order to stay competitive and foster new growth potentials. The corresponding phenomenon of digital transformation has received some attention in previous literature in respect to industries such as media and publishing. Nevertheless, there is a lack of understanding of the concept and its organization within firms. With the help of twenty-three in-depth field interviews with German experts responsible for their company’s digital transformation, we examined what digital transformation encompasses, how it is organized and which opportunities and challenges arise within firms. Our results indicate that digital transformation is an inevitable task for all firms, as it bears the potential to comprehensively optimize and reshape established business activities and can thus be seen as a strategy of business development.

Keywords: business development, digitalization, digital strategies, digital transformation

Procedia PDF Downloads 427

Authors: Daoudi Abdelaziz, Mahmoudi Saïd, Chikh Mohamed Amine

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This paper presents a fully automatic segmentation method of the left ventricle at End Systolic (ES) and End Diastolic (ED) in the ultrasound images by means of an implicit deformable model (level set) based on Geodesic Active Contour model. A pre-processing Gaussian smoothing stage is applied to the image, which is essential for a good segmentation. Before the segmentation phase, we locate automatically the area of the left ventricle by using a detection approach based on the Hough Transform method. Consequently, the result obtained is used to automate the initialization of the level set model. This initial curve (zero level set) deforms to search the Endocardial border in the image. On the other hand, quantitative evaluation was performed on a data set composed of 15 subjects with a comparison to ground truth (manual segmentation).

Keywords: level set method, transform Hough, Gaussian smoothing, left ventricle, ultrasound images.

Procedia PDF Downloads 465

Authors: Julie Anne Braun, Leonardo D. da Fonseca, Gerson C. Parreira, Ricardo J. E. Andrade

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Polyurethanes (PU) are multifunctional polymers used across various industries. In construction, thermosetting polyurethanes are applied as coatings for flooring, paints, and waterproofing. They are widely specified in Brazil for waterproofing concrete structures like roof slabs and parking decks. Applied to concrete, they form a fully adhered membrane, providing a protective barrier with low water absorption, high chemical resistance, impermeability to liquids, and low vapor permeability. Their mechanical properties, including tensile strength (1 to 35 MPa) and Shore A hardness (83 to 88), depend on resin molecular weight and functionality, often using Methylene diphenyl diisocyanate. PU production, reliant on fossil-derived isocyanates and polyols, contributes significantly to carbon emissions. Sustainable alternatives, such as biopolyurethanes from renewable sources, are needed. Castor oil is a viable option for synthesizing sustainable polyurethanes. As a bio-based feedstock, castor oil is extensively cultivated in Brazil, making it a feasible option for the national market and ranking third internationally. This study aims to develop and characterize castor oil-based biopolyurethane for high-performance waterproofing and coating applications. A comparative analysis between castor oil-based PU and polyether polyol-based PU was conducted. Mechanical tests (tensile strength, Shore A hardness, abrasion resistance) and surface properties (contact angle, water absorption) were evaluated. Thermal, chemical, and morphological properties were assessed using thermogravimetric analysis (TGA), Fourier transform infrared spectroscopy (FTIR), and scanning electron microscopy (SEM). The results demonstrated that both polyurethanes exhibited high mechanical strength. Specifically, the tensile strength for castor oil-based PU was 19.18 MPa, compared to 12.94 MPa for polyether polyol-based PU. Similarly, the elongation values were 146.90% for castor oil-based PU and 135.50% for polyether polyol-based PU. Both materials exhibited satisfactory performance in terms of abrasion resistance, with mass loss of 0.067% for castor oil PU and 0.043% for polyether polyol PU and Shore A hardness values of 89 and 86, respectively, indicating high surface hardness. The results of the water absorption and contact angle tests confirmed the hydrophilic nature of polyether polyol PU, with a contact angle of 58.73° and water absorption of 2.53%. Conversely, the castor oil-based PU exhibited hydrophobic properties, with a contact angle of 81.05° and water absorption of 0.45%. The results of the FTIR analysis indicated the absence of a peak around 2275 cm-1, which suggests that all of the NCO groups were consumed in the stoichiometric reaction. This conclusion is supported by the high mechanical test results. The TGA results indicated that polyether polyol PU demonstrated superior thermal stability, exhibiting a mass loss of 13% at the initial transition (around 310°C), in comparison to castor oil-based PU, which experienced a higher initial mass loss of 25% at 335°C. In summary, castor oil-based PU demonstrated mechanical properties comparable to polyether polyol PU, making it suitable for applications such as trafficable coatings. However, its higher hydrophobicity makes it more promising for watertightness. Increasing environmental concerns necessitate reducing reliance on non-renewable resources and mitigating the environmental impacts of polyurethane production. Castor oil is a viable option for sustainable polyurethanes, aligning with emission reduction goals and responsible use of natural resources.

Keywords: polyurethane, castor oil, sustainable, waterproofing, construction industry

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Authors: Jorge Olivares, Fernando Maass, Pablo Martin

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Fractional derivatives have been considered recently as a way to solve different problems in Engineering. In this way, second kind modified Bessel functions are considered here. The order α fractional differential equations of second kind Bessel functions, Kᵥ(x), are studied with simple initial conditions. The Laplace transform and Caputo definition of fractional derivatives are considered. Solutions have been found for ν=1/3, 1/2, 2/3, -1/3, -1/2 and (-2/3). In these cases, the solutions are the sum of two hypergeometric functions. The α fractional derivatives have been for α=1/3, 1/2 and 2/3, and the above values of ν. No convergence has been found for the integer values of ν Furthermore when α has been considered as a rational found m/p, no general solution has been found. Clearly, this case is more difficult to treat than those of first kind Bessel Function.

Keywords: Caputo, modified Bessel functions, hypergeometric, linear fractional differential equations, transform Laplace

Procedia PDF Downloads 342

Authors: Ravi Ande, Mousumi Hazari

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One of the common geophysical techniques for mapping subsurface geo-electrical structures, extensive hydro-geological research, and engineering and environmental geophysics applications is the use of time domain electromagnetic (TDEM)/transient electromagnetic (TEM) soundings. A large transmitter loop for energising the ground and a small receiver loop or magnetometer for recording the transient voltage or magnetic field in the air or on the surface of the earth, with the receiver at the center of the loop or at any random point inside or outside the source loop, make up a large loop TEM system. In general, one can acquire data using one of the configurations with a large loop source, namely, with the receiver at the center point of the loop (central loop method), at an arbitrary in-loop point (in-loop method), coincident with the transmitter loop (coincidence-loop method), and at an arbitrary offset loop point (offset-loop method), respectively. Because of the mathematical simplicity associated with the expressions of EM fields, as compared to the in-loop and offset-loop systems, the central loop system (for ground surveys) and coincident loop system (for ground as well as airborne surveys) have been developed and used extensively for the exploration of mineral and geothermal resources, for mapping contaminated groundwater caused by hazardous waste and thickness of permafrost layer. Because a proper analytical expression for the TEM response over the layered earth model for the large loop TEM system does not exist, the forward problem used in this inversion scheme is first formulated in the frequency domain and then it is transformed in the time domain using Fourier cosine or sine transforms. Using the EMLCLLER algorithm, the forward computation is initially carried out in the frequency domain. As a result, the EMLCLLER modified the forward calculation scheme in NLSTCI to compute frequency domain answers before converting them to the time domain using Fourier Cosine and/or Sine transforms.

Keywords: time domain electromagnetic (TDEM), TEM system, geoelectrical sounding structure, Fourier cosine

Procedia PDF Downloads 92

Authors: Ali Akbar Attari, Ali Asghar Beheshti Shirazi

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In this paper, we propose a blind and robust audio watermarking scheme based on spread spectrum in Discrete Wavelet Transform (DWT) domain. Watermarks are embedded in the low-frequency coefficients, which is less audible. The key idea is dividing the audio signal into small frames, and magnitude of the 6^th level of DWT approximation coefficients is modifying based upon the Direct Sequence Spread Spectrum (DSSS) technique. Also, the psychoacoustic model for enhancing in imperceptibility, as well as Savitsky-Golay filter for increasing accuracy in extraction, is used. The experimental results illustrate high robustness against most common attacks, i.e. Gaussian noise addition, Low pass filter, Resampling, Requantizing, MP3 compression, without significant perceptual distortion (ODG is higher than -1). The proposed scheme has about 83 bps data payload.

Keywords: audio watermarking, spread spectrum, discrete wavelet transform, psychoacoustic, Savitsky-Golay filter

Procedia PDF Downloads 200