Search results for: Spectral Angle Mapper Classifier.

Authors: Neeraj Kumar Fuloria, Shivkanya Fuloria, Amit Singh

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2-Phenyl propionic acid and oxadiazoles possess antimicrobial potential. 2-Phenyl propane hydrazide (1), on cyclization with aromatic acids offered 2-aryl-5-(1-phenylethyl)-1,3,4-oxadiazole derivatives (1A-E). The PPA derived oxadiazoles were characterized by elemental analysis and spectral studies. The compounds were screened for antimicrobial potential. The compound 1D bearing strong electron withdrawing group showed maximum antimicrobial potential. Other compounds also displayed antimicrobial potential to a certain extent. The SAR of newer oxadiazoles indicated that substitution of strong electronegative group in the PPA derived oxadiazoles enhanced their antimicrobial potential.

Keywords: antimicrobial, imines, oxadiazoles, PPA

Procedia PDF Downloads 330

Authors: Jinlu Sun, Shouxiang Lu, Siuming Lo

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Large passenger ship, especially luxury cruise, is one of the most prevalent means of marine transportation and tourism nowadays. In case of an accident, an effective evacuation would be the ultimate way to minimize the consequence. Ship heeling and trim has a considerable influence on passenger walking speed and posture during ship evacuation. To investigate passenger movement pattern under the combined effect of ship heeling and trim, a ship corridor simulator was developed. Both fast and freely individual walking experiments by male and female experimental subjects under heeling and trim conditions were conducted and recorded therein. It is found that routes of experimental subjects would change due to the heeling and trim angles, although they always walk along the right side because of cultural factors. Experimental subjects would also change their posture to adapt the combined heeling and trim conditions, such as leaning forward, adopting larger arm swaying, shorter and more frequent steps. While for individual walking speed, the speed would decrease with the increasing heeling and trim angles. But the maximum individual walking speed is achieved at heeling angle of 0° with trim angle ranging from -15° to -5 °, instead of on level ground, which may be attributable to the effect of the gravitational acceleration. Female is approximately 10% slower than male due to the discrepancy in physical quality. Besides, individual walking speed shows similar trends in both fast and freely walking modes, and the speed value in freely walking mode is about 78% of that in fast walking mode under each experimental condition. Furthermore, to designate the movement pattern of passengers in heeling and trim conditions, a model of the walking speed reduction was proposed. This work would provide guidance on the development of evacuation models and the design of evacuation facilities on board.

Keywords: evacuation, heeling, individual walking speed, ship corridor simulator, trim

Procedia PDF Downloads 245

Authors: Shahram Nowrouzieh, Abbas Rezaei Asl, Mohamad Ali Jafari

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Cotton, as a strategic crop, plays an important role in providing human food and clothing need, because of its oil, protein, and fiber. Iran has been one of the largest cotton producers in the world in the past, but unfortunately, for economic reasons, its production is reduced now. One of the ways to reduce the cost of cotton production is to expand the mechanization of cotton harvesting. Iranian farmers do not accept the function of cotton harvesters. One reason for this lack of acceptance of cotton harvesting machines is the number of field losses on these machines. So, the majority of cotton fields are harvested by hand. Although the correct setting of the harvesting machine is very important in the cotton losses, the morphological properties of the cotton plant also affect the performance of cotton harvesters. In this study, the effect of some cotton morphological properties such as the height of the cotton plant, number, and length of sympodial and monopodial branches, boll dimensions, boll weight, number of carpels and bracts angle were evaluated on the performance of cotton picker. In this research, the efficiency of John Deere 9920 spindle Cotton picker is investigated on five different Iranian cotton cultivars. The results indicate that there was a significant difference between the five cultivars in terms of machine harvest efficiency. Golestan cultivar showed the best cotton harvester performance with an average of 87.6% of total harvestable seed cotton and Khorshid cultivar had the least cotton harvester performance. The principal component analysis showed that, at 50.76% probability, the cotton picker efficiency is affected by the bracts angle positively and by boll dimensions, the number of carpels and the height of cotton plants negatively. The seed cotton remains (in the plant and on the ground) after harvester in PCA scatter plot were in the same zone with boll dimensions and several carpels.

Keywords: cotton, bract, harvester, carpel

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Authors: Payel Das, Gnaneshwar Nelakanti

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In this paper we analyse the iterated discrete Legendre Galerkin method for Fredholm-Hammerstein integral equations with smooth kernel. Using sufficiently accurate numerical quadrature rule, we obtain superconvergence rates for the iterated discrete Legendre Galerkin solutions in both infinity and $L^2$-norm. Numerical examples are given to illustrate the theoretical results.

Keywords: hammerstein integral equations, spectral method, discrete galerkin, numerical quadrature, superconvergence

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Authors: Rujia Chen, Akbar Ghobakhlou, Ajit Narayanan

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This study investigates the task of identifying musical instruments in polyphonic compositions using Convolutional Neural Networks (CNNs) from spectrogram inputs, focusing on binary classification. The model showed promising results, with an accuracy of 97% on solo instrument recognition. When applied to polyphonic combinations of 1 to 10 instruments, the overall accuracy was 64%, reflecting the increasing challenge with larger ensembles. These findings contribute to the field of Music Information Retrieval (MIR) by highlighting the potential and limitations of current approaches in handling complex musical arrangements. Future work aims to include a broader range of musical sounds, including electronic and synthetic sounds, to improve the model's robustness and applicability in real-time MIR systems.

Keywords: binary classifier, CNN, spectrogram, instrument

Procedia PDF Downloads 53

Authors: Mohamed H. Kosba, Heba A. Ibrahim, H. Rozita

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Statement of the Problem: The life expectancy for transfusion-dependent thalassemia patients has increased dramatically with iron-chelation therapy and other modern management modalities. In these patients, the most dominant maxillofacial manifestations are protrusion of zygomatic bones and premaxilla due to the hyperplasia of bone marrow. The purpose of this study is to determine the prevalence of malocclusion and orthodontic treatment needs according to the Dental Aesthetic Index (DAI) among Malay transfusion-dependent thalassemia patients. Orientation: This is a cross-sectional study consist of 43 Malay transfusion-dependent thalassemia patients, 22 males, and 19 females with the mean age of 15.9 years old (SD 3.58). The subjects were selected randomly from patients attending Paediatrics and Internal Medicine Clinic at Hospital USM and Hospital Sultana Bahiyah. The subjects were assessed for malocclusion according to Angle’s classification, and orthodontic treatment needs using DAI. The results show that 22 of the subjects (51.1%) have class II malocclusion, 12 subjects (28%) have class І, while 9 subjects (20.9%) have class Ⅲ. The assessment of orthodontic treatment needs to reveal 22 cases (51.1%) fall in the normal/minor needs category, 12 subjects (28%) fall in the severe and very severe category, while 9 subjects (20.9%) fall in the definite category. Conclusion & Significance: Half of Malay transfusion-dependent thalassemia patients have Class Ⅱmalocclusion. About 28% had malocclusion and required orthodontic treatment. This research shows that Malay transfusion-dependent thalassemia may require orthodontic management; earlier intervention to reduce the complexity of the treatment later, suggesting functional appliance as a suitable treatment option for them, a twin block appliance together with headgear to restrict maxillary growth suggested for management. The current protocol implemented by the Malaysian Ministry of Health for the management of these patients seems to be sufficient since the result shows that about 28% require orthodontic treatment need, according to DAI.

Keywords: prevalence, DAI, thalassaemia, angle classification

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Authors: Yao Jie, Yeo Khoon Seng

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In recent decades, flapping wing aerodynamics has attracted great interest. Understanding the physics of biological flyers such as birds and insects can help improve the performance of micro air vehicles. The present research focuses on the aerodynamics of insect-like flapping wing flight with the approach of numerical computation. Insect model of hawkmoth is adopted in the numerical study with rigid wing assumption currently. The numerical model integrates the computational fluid dynamics of the flow and active control of wing kinematics to achieve stable flight. The computation grid is a hybrid consisting of background Cartesian nodes and clouds of mesh-free grids around immersed boundaries. The generalized finite difference method is used in conjunction with single value decomposition (SVD-GFD) in computational fluid dynamics solver to study the dynamics of a free hovering hummingbird hawkmoth. The longitudinal dynamics of the hovering flight is governed by three control parameters, i.e., wing plane angle, mean positional angle and wing beating frequency. In present work, a PID controller works out the appropriate control parameters with the insect motion as input. The controller is adjusted to acquire desired maneuvering of the insect flight. The numerical scheme in present study is proven to be accurate and stable to simulate the flight of the hummingbird hawkmoth, which has relatively high Reynolds number. The PID controller is responsive to provide feedback to the wing kinematics during the hovering flight. The simulated hovering flight agrees well with the real insect flight. The present numerical study offers a promising route to investigate the free flight aerodynamics of insects, which could overcome some of the limitations of experiments.

Keywords: aerodynamics, flight control, computational fluid dynamics (CFD), flapping-wing flight

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Authors: Hussein Hakim, Zainab Al-Ramadhan, Ahmed Hashim

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Polymer nano composites of polyvinylpyrrolidone and poly-ethylene glycol with different concentrations of aluminum oxide (Al2O3) nano particles have been prepared by solution cast method. The optical characterizations have been done by analyzing the absorption (A) spectra in the 300–800 nm spectral region. It was found that the optical energy gap decreases with the increasing of Al2O3 nano particles content. The optical constants (refractive index, extinction coefficient, real and imaginary parts of the dielectric constant) are changing with increasing aluminum oxide nano particle concentrations.

Keywords: nanocomposites, polyvinylpyrrolidone, optical constants, polymers, blend

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Authors: D. Srinivasacharya, Nidhi Humnekar

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The goal of this research is to numerically investigate the convection of nanofluid flow in an inclined porous channel. Brownian motion and thermophoresis effects are accounted for by nanofluid. In addition, the flow in the porous region governs Brinkman’s equation. The perturbed state of the generalized eigenvalue problem is obtained using normal mode analysis, and Chebyshev spectral collocation was used to solve this problem. For various values of the governing parameters, the critical wavenumber and critical Rayleigh number are calculated, and preferred modes are identified.

Keywords: Brinkman model, inclined channel, nanofluid, linear stability, porous media

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Authors: Wu Peng, Anders Liljerehn, Martin Magnevall

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In metal cutting, tool wear gradually changes the micro geometry of the cutting edge. Today there is a significant gap in understanding the impact these geometrical changes have on the cutting forces which governs tool deflection and heat generation in the cutting zone. Accurate models and understanding of the interaction between the work piece and cutting tool leads to improved accuracy in simulation of the cutting process. These simulations are useful in several application areas, e.g., optimization of insert geometry and machine tool monitoring. This study aims to develop an extended Kienzle force model to account for the effect of rake angle variations and tool flank wear have on the cutting forces. In this paper, the starting point sets from cutting force measurements using orthogonal turning tests of pre-machined flanches with well-defined width, using triangular coated inserts to assure orthogonal condition. The cutting forces have been measured by dynamometer with a set of three different rake angles, and wear progression have been monitored during machining by an optical measuring collaborative robot. The method utilizes the measured cutting forces with the inserts flank wear progression to extend the mechanistic cutting forces model with flank wear as an input parameter. The adapted cutting forces model is validated in a turning process with commercial cutting tools. This adapted cutting forces model shows the significant capability of prediction of cutting forces accounting for tools flank wear and different-rake-angle cutting tool inserts. The result of this study suggests that the nonlinear effect of tools flank wear and interaction between the work piece and the cutting tool can be considered by the developed cutting forces model.

Keywords: cutting force, kienzle model, predictive model, tool flank wear

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Authors: Tetyana Baydyk, Ernst Kussul, Sandra Bonilla Meza

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There are many articles that attempt to establish the role of different facial fragments in face recognition. Various approaches are used to estimate this role. Frequently, authors calculate the entropy corresponding to the fragment. This approach can only give approximate estimation. In this paper, we propose to use a more direct measure of the importance of different fragments for face recognition. We propose to select a recognition method and a face database and experimentally investigate the recognition rate using different fragments of faces. We present two such experiments in the paper. We selected the PCNC neural classifier as a method for face recognition and parts of the LFW (Labeled Faces in the Wild) face database as training and testing sets. The recognition rate of the best experiment is comparable with the recognition rate obtained using the whole face.

Keywords: face recognition, labeled faces in the wild (LFW) database, random local descriptor (RLD), random features

Procedia PDF Downloads 346

Authors: D. Sankara Reddy, T. Kranthi Kumar, K. Sreevani

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This paper investigates the impact of carrier frequency offset (CFO) on the performance of different MIMO-OFDM schemes with high spectral efficiency for next generation of terrestrial digital TV. We show that all studied MIMO-OFDM schemes are sensitive to CFO when it is greater than 1% of intercarrier spacing. We show also that the Alamouti scheme is the most sensitive MIMO scheme to CFO.

Keywords: modulation and multiplexing (MIMO-OFDM), signal processing for transmission carrier frequency offset, future digital TV, imaging and signal processing

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Authors: Nileshkumar Vaishnav, Aditya Tatu

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An algebraic framework for processing graph signals axiomatically designates the graph adjacency matrix as the shift operator. In this setup, we often encounter a problem wherein we know the filtered output and the filter coefficients, and need to find out the input graph signal. Solution to this problem using direct approach requires O(N3) operations, where N is the number of vertices in graph. In this paper, we adapt the spectral graph partitioning method for partitioning of graphs and use it to reduce the computational cost of the filtering problem. We use the example of denoising of the temperature data to illustrate the efficacy of the approach.

Keywords: graph signal processing, graph partitioning, inverse filtering on graphs, algebraic signal processing

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Authors: T. D. Ibragimov, A. R. Imamaliyev, G. M. Bayramov

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The polymer network liquid crystals based on the liquid crystals Н37 and 5CB with polymethylvinilpirydine (PMVP) and polyethylene glycol (PEG) have been developed. Mesogene substance 4-n-heptyoxibenzoic acid (HOBA) is served for stabilization of obtaining composites. Kinetics of network formation is investigated by methods of polarization microscopy and integrated small-angle scattering. It is shown that gel-like states of the composite H-37 + PMVP + HOBA and 5CB+PEG+HOBA are formed at polymer concentration above 7 % and 9 %, correspondingly. At slow cooling, the system separates into a liquid crystal –rich phase and a liquid crystal-poor phase. At this case, transition of these phases in the H-37 + PMVP + HOBA (87 % + 12 % + 1 %) composite to an anisotropic state occurs at 49 оС and и 41 оС, accordingly, while the composite 5CB+PEG+HOBA (85% +13 % +2%) passes to anisotropic state at 36 оС corresponding to the isotropic-nematic transition of pure 5CB. The basic electro-optic parameters of the obtained composites are determined at room temperature. It is shown that the threshold voltage of the composite H-37 + PMVP + HOBA increase in comparison with pure H-37 and, accordingly, there is a shift of voltage dependence of rise times to the high voltage region. The contrast ratio worsens while decay time improves in comparison with the pure liquid crystal at all applied voltage. The switching times of the composite 5CB + PEG + HOBA (85% +13 % +2%) show anomalous behavior connected with incompleteness of the transition to an anisotropic state. Experimental results are explained by phase separation of the system, diminution of a working area of electro-optical effects and influence of areas with the high polymer concentration on areas with their low concentration.

Keywords: liquid crystals, polymers, small-angle scattering, optical properties

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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: Magdy Roman, Mostafa Shoeib, Mostafa Rostom

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Global vision, whether provided by overhead fixed cameras, on-board aerial vehicle cameras, or satellite images can always provide detailed information on the environment around mobile robots. In this paper, an intelligent vision-based method of path planning and obstacle avoidance for mobile robots is presented. The method integrates visual perception with a new proposed field-based path-planning method to overcome common path-planning problems such as local minima, unreachable destination and unnecessary lengthy paths around obstacles. The method proposes an exponential angle deviation field around each obstacle that affects the orientation of a close robot. As the robot directs toward, the goal point obstacles are classified into right and left groups, and a deviation angle is exponentially added or subtracted to the orientation of the robot. Exponential field parameters are chosen based on Lyapunov stability criterion to guarantee robot convergence to the destination. The proposed method uses obstacles' shape and location, extracted from global vision system, through a collision prediction mechanism to decide whether to activate or deactivate obstacles field. In addition, a search mechanism is developed in case of robot or goal point is trapped among obstacles to find suitable exit or entrance. The proposed algorithm is validated both in simulation and through experiments. The algorithm shows effectiveness in obstacles' avoidance and destination convergence, overcoming common path planning problems found in classical methods.

Keywords: path planning, collision avoidance, convergence, computer vision, mobile robots

Procedia PDF Downloads 181

Authors: Revaz Chigladze

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The purpose of the research is to investigate the surfaces of Jupiter's Galilean moons, namely which moon has the most uniform surface among them, what is the difference between the front (in the direction of motion) and the back sides of each moon's surface, as well as the temporal variations of the moons. Since 1981, the E. Kharadze National Astrophysical Observatory of Georgia has been conducting polarimetric (P) and photometric (M) observations of Jupiter's Galilean moons with telescopes of different diameters (40 cm and 125 cm) and the polarimeter ASEP-78 in combination with them and the latest generation photometer with a polarimeter and modern light receiver SBIG. As it turns out from the analysis of the observed material, the parameters P and M depend on α-the phase angle of the moon (satellite), L- the orbital latitude of the moon (satellite), λ- the wavelength, and t - the period of observation, i.e., P = P (α, L, λ , t), and similarly M = M (α, L, λ. , t). Based on the analysis of the observed material, the following was studied: Jupiter's Galilean moons: dependence of the magnitude and phase angle of the degree of linear polarization for different wavelengths; Dependence of the degree of polarization and the orbital longitude; dependence between the magnitude of the degree of polarization and the wavelength; time dependence of the degree of polarization and the dependence between photometric and polarimetric characteristics (including establishing correlation). From the analysis of the obtained results, we get: The magnitude of the degree of polarization of Jupiter's Galilean moons near the opposition significantly differs from zero. Europa appears to have the most uniform surface, and Callisto the least uniform. Time variations are most characteristic of Io, which confirms the presence of volcanic activity on its surface. Based on the observed material, it can be seen that the intensity of light reflected from the front hemisphere of the first three moons: Io, Europa, and Ganymede, is less than the intensity of light reflected from the rear hemisphere, and in the case of the Callisto it is the opposite. The paper provides a convincing (natural, real) explanation of this fact.

Keywords: Galilean moons, polarization, degree of polarization, photometry, front and rear hemispheres

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Authors: Mohammad Hassan Ziraksaz

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Fuel atomizers are used in a wide range of IC engines, turbojets and a variety of liquid propellant rocket engines. As the fuel spray fully develops its characters approach their ultimate amounts. Fuel spray characters such as SMD, injection pressure, mass flow rate, droplet velocity and spray cone angle play important roles to atomize the liquid fuel to finely atomized fuel droplets and finally form the fine fuel spray. Well performed, fully developed, fine spray without any defections, brings the idea of finding an experimental relation between the main effective spray characters. Extracting an experimental relation between SMD and other fuel spray physical characters in swirl fuel atomizers is the main scope of this experimental work. Droplet velocity, fuel mass flow rate, SMD and spray cone angle are the parameters which are measured. A set of twelve reverse engineering atomizers without any spray defections and a set of eight original atomizers as referenced well-performed spray are contributed in this work. More than 350 tests, mostly repeated, were performed. This work shows that although spray cone angle plays a very effective role in spray formation, after formation, it smoothly approaches to an almost constant amount while the other characters are changed to create fine droplets. Therefore, the work to find the relation between the characters is focused on SMD, droplet velocity, fuel mass flow rate, and injection pressure. The process of fuel spray formation begins in 5 Psig injection pressures, where a tiny fuel onion attaches to the injector tip and ended in 250 Psig injection pressure, were fully developed fine fuel spray forms. Injection pressure is gradually increased to observe how the spray forms. In each step, all parameters are measured and recorded carefully to provide a data bank. Various diagrams have been drawn to study the behavior of the parameters in more detail. Experiments and graphs show that the power equation can best show changes in parameters. The SMD experimental relation with pressure P, fuel mass flow rate Q ̇ and droplet velocity V extracted individually in pairs. Therefore, the proportional relation of SMD with other parameters is founded. Now it is time to find an experimental relation including all the parameters. Using obtained proportional relation, replacing the parameters with experimentally measured ones and drawing the graphs of experimental SMD versus proportion SMD (〖SMD〗_P), a correctional equation and consequently the final experimental equation is obtained. This experimental equation is specified to use for swirl fuel atomizers and the use of this experimental equation in different conditions shows about 3% error, which is expected to achieve lower error and consequently higher accuracy by increasing the number of experiments and increasing the accuracy of data collection.

Keywords: droplet velocity, experimental relation, mass flow rate, SMD, swirl fuel atomizer

Procedia PDF Downloads 154

Authors: Shivkanya Fuloria, Neeraj Kumar Fuloria, Sokinder Kumar

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m-Cresol and oxadiazoles are the potent antimicrobial moieties. 2-(m-Tolyloxy)acetohydrazide (1) on cyclization with aromatic acids yielded 2-(aryl)-5-(m-tolyloxymethyl)-1,3,4-oxadiazole (1A-E). The structures of newer oxadiazoles were confirmed by elemental and spectral analysis. The newer compounds were evaluated for their antimicrobial potential. The compound 1E containing strong electron withdrawing group showed maximum antimicrobial potential. Other compounds also displayed antimicrobial potential to certain extent. The SAR of newer oxadiazoles indicated that substitution of strong electronegative group in the tolyloxy derived oxadiazoles enhanced their antimicrobial potential.

Keywords: antibacterial, cresol, hydrazide, oxadiazoles

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Authors: Piyush Samant, Ravinder Agarwal

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Complementary and Alternative Medicine (CAM) techniques are quite popular and effective for chronic diseases. Iridology is more than 150 years old CAM technique which analyzes the patterns, tissue weakness, color, shape, structure, etc. for disease diagnosis. The objective of this paper is to validate the use of iridology for the diagnosis of the diabetes. The suggested model was applied in a systemic disease with ocular effects. 200 subject data of 100 each diabetic and non-diabetic were evaluated. Complete procedure was kept very simple and free from the involvement of any iridologist. From the normalized iris, the region of interest was cropped. All 63 features were extracted using statistical, texture analysis, and two-dimensional discrete wavelet transformation. A comparison of accuracies of six different classifiers has been presented. The result shows 89.66% accuracy by the random forest classifier.

Keywords: complementary and alternative medicine, classification, iridology, iris, feature extraction, disease prediction

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Authors: Loai Abdallah, Malik Yousef

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A domain space for the data should reflect the actual similarity between objects. Since objects belonging to the same cluster usually share some common traits even though their geometric distance might be relatively large. In general, the Euclidean distance of data points that represented by large number of features is not capturing the actual relation between those points. In this study, we propose a new method to construct a different space that is based on clustering to form a new distance metric. The new distance space is based on ensemble clustering (EC). The EC distance space is defined by tracking the membership of the points over multiple runs of clustering algorithm metric. Over this distance, we train the decision trees classifier (DT-EC). The results obtained by applying DT-EC on 10 datasets confirm our hypotheses that embedding the EC space as a distance metric would improve the performance.

Keywords: ensemble clustering, decision trees, classification, K nearest neighbors

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Authors: D. J. Madhu Kumar, D. Jagadeesh Prasad, Sana Sheik, E. P. Rejeesh

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A series of Mannich bases derived from 1,2,4-triazole(3a-k and 4a-k) are synthesized by treating a Schiff base with various substituted primary/secondary amines and formaldehyde. The Schiff base is prepared by treating 3-methyl-4-amino-5-mercapto-1,2,4-triazole with 3,4-dimethoxybenzaldehyde in the presence of acid catalyst. The triazole is prepared by treating acetic acid with thiocarbohydrazide at reflux temperature. All the synthesized samples are characterised by FT-IR, 1H-NMR, and LC-MASS spectral studies and screened for their anti-oxidant activity.

Keywords: mannich bases, anti-oxidant activity, schiff base, triazole

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Authors: Chih-Fong Tsai, Ya-Han Hu

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The aim of feature selection (or dimensionality reduction) is to filter out unrepresentative features (or variables) making the classifier perform better than the one without feature selection. Since there are many well-known feature selection algorithms, and different classifiers based on different selection results may perform differently, very few studies consider examining the effect of performing different feature selection algorithms on the classification performances by different classifiers over different types of datasets. In this paper, two widely used algorithms, which are the genetic algorithm (GA) and information gain (IG), are used to perform feature selection. On the other hand, three well-known classifiers are constructed, which are the CART decision tree (DT), multi-layer perceptron (MLP) neural network, and support vector machine (SVM). Based on 14 different types of datasets, the experimental results show that in most cases IG is a better feature selection algorithm than GA. In addition, the combinations of IG with DT and IG with SVM perform best and second best for small and large scale datasets.

Keywords: data mining, feature selection, pattern classification, dimensionality reduction

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Authors: Chiling Chen, Chiaoying Chou, Siyang Wu

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Taiwan locates at the west of Pacific Ocean and intersects between continental and marine climate. Typhoons frequently strike Taiwan and come with meteorological disasters, i.e., heavy flooding, landslides, loss of life and properties, etc. Global climate change brings more extremely meteorological disasters. So, develop techniques to improve disaster prevention and mitigation is needed, to improve rescue processes and rehabilitations is important as well. In this study, UAVs (Unmanned Aerial Vehicles) are applied to take instant images for improving the disaster investigation and rescue processes. Paddy rice fields in the central Taiwan are the study area. There have been attacked by heavy rain during the monsoon season in June 2016. UAV images provide the high ground resolution (3.5cm) with 3D Point Clouds to develop image discrimination techniques and digital surface model (DSM) on rice lodging. Firstly, image supervised classification with Maximum Likelihood Method (MLD) is used to delineate the area of rice lodging. Secondly, 3D point clouds generated by Pix4D Mapper are used to develop DSM for classifying the lodging levels of paddy rice. As results, discriminate accuracy of rice lodging is 85% by image supervised classification, and the classification accuracy of lodging level is 87% by DSM. Therefore, UAVs not only provide instant images of agricultural damage after the meteorological disaster, but the image discriminations on rice lodging also reach acceptable accuracy (>85%). In the future, technologies of UAVs and image discrimination will be applied to different crop fields. The results of image discrimination will be overlapped with administrative boundaries of paddy rice, to establish GIS-based assist system on agricultural damage discrimination. Therefore, the time and labor would be greatly reduced on damage detection and monitoring.

Keywords: Monsoon, supervised classification, Pix4D, 3D point clouds, discriminate accuracy

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Authors: Arunkumar Balamurugan, G. Soundharya Lakshmi, V. Thenmozhi, M. Jegannath, V. R. Sanal Kumar

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Aerodynamics of insects is of topical interest in aeronautical industries due to its wide applications on various types of Micro Air Vehicles (MAVs). Note that the MAVs are having smaller geometric dimensions operate at significantly lower speeds on the order of 10 m/s and their Reynolds numbers range is approximately 1,50,000 or lower. In this paper, numerical study has been carried out to capture the flow physics of a biological inspired Swallowtail Butterfly with fixed wing having twin tail at a flight speed of 10 m/s. Comprehensive numerical simulations have been carried out on swallow butterfly with twin tail flying at a speed of 10 m/s with uniform upper and lower angles of attack in both lateral and longitudinal position for identifying the best wing orientation with better aerodynamic efficiency. Grid system in the computational domain is selected after a detailed grid refinement exercises. Parametric analytical studies have been carried out with different lateral and longitudinal angles of attack for finding the better aerodynamic efficiency at the same flight speed. The results reveal that lift coefficient significantly increases with marginal changes in the longitudinal angle and vice versa. But in the case of drag coefficient the conventional changes have been noticed, viz., drag increases at high longitudinal angles. We observed that the change of twin tail section has a significant impact on the formation of vortices and aerodynamic efficiency of the MAV’s. We concluded that for every lateral angle there is an exact longitudinal orientation for the existence of an aerodynamically efficient flying condition of any MAV. This numerical study is a pointer towards for the design optimization of Twin tail MAVs with flapping wings.

Keywords: aerodynamics of insects, MAV, swallowtail butterfly, twin tail MAV design

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Authors: Caixia Gao, Chuanrong Li, Lingli Tang, Lingling Ma, Yonggang Qian, Ning Wang

Abstract:

Knowledge of land surface temperature (LST) is of crucial important in energy balance studies and environment modeling. Satellite thermal infrared (TIR) imagery is the primary source for retrieving LST at the regional and global scales. Due to the combination of atmosphere and land surface of received radiance by TIR sensors, atmospheric effect correction has to be performed to remove the atmospheric transmittance and upwelling radiance. Spinning Enhanced Visible and Infrared Imager (SEVIRI) onboard Meteosat Second Generation (MSG) provides measurements every 15 minutes in 12 spectral channels covering from visible to infrared spectrum at fixed view angles with 3km pixel size at nadir, offering new and unique capabilities for LST, LSE measurements. However, due to its high temporal resolution, the atmosphere correction could not be performed with radiosonde profiles or reanalysis data since these profiles are not available at all SEVIRI TIR image acquisition times. To solve this problem, a two-part six-parameter semi-empirical diurnal temperature cycle (DTC) model has been applied to the temporal interpolation of ECMWF reanalysis data. Due to the fact that the DTC model is underdetermined with ECMWF data at four synoptic times (UTC times: 00:00, 06:00, 12:00, 18:00) in one day for each location, some approaches are adopted in this study. It is well known that the atmospheric transmittance and upwelling radiance has a relationship with water vapour content (WVC). With the aid of simulated data, the relationship could be determined under each viewing zenith angle for each SEVIRI TIR channel. Thus, the atmospheric transmittance and upwelling radiance are preliminary removed with the aid of instantaneous WVC, which is retrieved from the brightness temperature in the SEVIRI channels 5, 9 and 10, and a group of the brightness temperatures for surface leaving radiance (Tg) are acquired. Subsequently, a group of the six parameters of the DTC model is fitted with these Tg by a Levenberg-Marquardt least squares algorithm (denoted as DTC model 1). Although the retrieval error of WVC and the approximate relationships between WVC and atmospheric parameters would induce some uncertainties, this would not significantly affect the determination of the three parameters, td, ts and β (β is the angular frequency, td is the time where the Tg reaches its maximum, ts is the starting time of attenuation) in DTC model. Furthermore, due to the large fluctuation in temperature and the inaccuracy of the DTC model around sunrise, SEVIRI measurements from two hours before sunrise to two hours after sunrise are excluded. With the knowledge of td , ts, and β, a new DTC model (denoted as DTC model 2) is accurately fitted again with these Tg at UTC times: 05:57, 11:57, 17:57 and 23:57, which is atmospherically corrected with ECMWF data. And then a new group of the six parameters of the DTC model is generated and subsequently, the Tg at any given times are acquired. Finally, this method is applied to SEVIRI data in channel 9 successfully. The result shows that the proposed method could be performed reasonably without assumption and the Tg derived with the improved method is much more consistent with that from radiosonde measurements.

Keywords: atmosphere correction, diurnal temperature cycle model, land surface temperature, SEVIRI

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Authors: Vladimir Hovhannisyan, Chen Yuan Dong

Abstract:

Recently nanoparticles (NPs) have been introduced in biomedicine as effective agents for cancer-targeted drug delivery and noninvasive tissue imaging. The most important requirements to these agents are their non-toxicity, biocompatibility and stability. In view of these criteria, the zeolite (ZL) nanoparticles (NPs) may be considered as perfect candidates for biomedical applications. ZLs are crystalline aluminosilicates consisting of oxygen-sharing SiO4 and AlO4 tetrahedral groups united by common vertices in three-dimensional framework and containing pores with diameters from 0.3 to 1.2 nm. Generally, the behavior and physical properties of ZLs are studied by SEM, X-ray spectroscopy, and AFM, whereas optical spectroscopic and microscopic approaches are not effective enough, because of strong scattering in common ZL bulk materials and powders. The light scattering can be reduced by using of ZL NPs. ZL NPs have large external surface area, high dispersibility in both aqueous and organic solutions, high photo- and thermal stability, and exceptional ability to adsorb various molecules and atoms in their nanopores. In this report, using multiphoton microscopy and nonlinear spectroscopy, we investigate nonlinear optical properties of clinoptilolite type of ZL micro- and nanoparticles with average diameters of 2200 nm and 240 nm, correspondingly. Multiphoton imaging is achieved using a laser scanning microscope system (LSM 510 META, Zeiss, Germany) coupled to a femtosecond titanium:sapphire laser (repetition rate- 80 MHz, pulse duration-120 fs, radiation wavelength- 720-820 nm) (Tsunami, Spectra-Physics, CA). Two Zeiss, Plan-Neofluar objectives (air immersion 20×∕NA 0.5 and water immersion 40×∕NA 1.2) are used for imaging. For the detection of the nonlinear response, we use two detection channels with 380-400 nm and 435-700 nm spectral bandwidths. We demonstrate that ZL micro- and nanoparticles can produce nonlinear optical response under the near-infrared femtosecond laser excitation. The interaction of hypericine, chlorin e6 and other dyes with ZL NPs and their photodynamic activity is investigated. Particularly, multiphoton imaging shows that individual ZL NPs particles adsorb Zn-tetraporphyrin molecules, but do not adsorb fluorescein molecules. In addition, nonlinear spectral properties of ZL NPs in native biotissues are studied. Nonlinear microscopy and spectroscopy may open new perspectives in the research and application of ZL NP in biomedicine, and the results may help to introduce novel approaches into the clinical environment.

Keywords: multiphoton microscopy, nanoparticles, nonlinear optics, zeolite

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Authors: Pengchao Wei, Xiangzhong Fang

Abstract:

Noise is ubiquitous in this world. Denoising is an essential technology, especially in image semantic segmentation, where noises are generally categorized into two main types i.e. feature noise and label noise. The main focus of this paper is aiming at modeling label noise, investigating the behaviors of different types of label noise on image semantic segmentation tasks using K-Nearest-Neighbor and Convolutional Neural Network classifier. The performance without label noise and with is evaluated and illustrated in this paper. In addition to that, the influence of feature noise on the image semantic segmentation task is researched as well and a feature noise reduction method is applied to mitigate its influence in the learning procedure.

Keywords: convolutional neural network, denoising, feature noise, image semantic segmentation, k-nearest-neighbor, label noise

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Authors: Priya Varshney, Soumya S. Mohapatra

Abstract:

Fabrication of anti-corrosion and self-cleaning superhydrophobic coatings for metallic surfaces which are regenerable and durable in the aggressive conditions has shown tremendous interest in materials science. In this work, the superhydrophobic coatings on metallic surfaces (aluminum, steel, copper) were prepared by two-step and one-step chemical etching process. In two-step process, roughness on surface was created by chemical etching and then passivation of roughened surface with low surface energy materials whereas, in one-step process, roughness on surface by chemical etching and passivation of surface with low surface energy materials were done in a single step. Beside this, the effect of etchant concentration and etching time on wettability and morphology was also studied. Thermal, mechanical, ultra-violet stability of these coatings were also tested. Along with this, regeneration of coatings and self-cleaning, corrosion resistance and water repelling characteristics were also studied. The surface morphology shows the presence of a rough microstuctures on the treated surfaces and the contact angle measurements confirms the superhydrophobic nature. It is experimentally observed that the surface roughness and contact angle increases with increase in etching time as well as with concentration of etchant. Superhydrophobic surfaces show the excellent self-cleaning behaviour. Coatings are found to be stable and maintain their superhydrophobicity in acidic and alkaline solutions. Water jet impact, floatation on water surface, and low temperature condensation tests prove the water-repellent nature of the coatings. These coatings are found to be thermal, mechanical and ultra-violet stable. These durable superhydrophobic metallic surfaces have potential industrial applications.

Keywords: superhydrophobic, water-repellent, anti-corrosion, self-cleaning

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

Abstract:

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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