Search results for: vegetable oil extraction

Authors: Hari Babu Kotte, Radhika Ambatipudi, Dr. Kent Bertilsson

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The experimental and theoretical results of a ZVS (Zero Voltage Switching) isolated flyback DC-DC converter using multilayered coreless PCB step down 2:1 transformer are presented. The performance characteristics of the transformer are shown which are useful for the parameters extraction. The measured energy efficiency of the transformer is found to be more than 94% with the sinusoidal input voltage excitation. The designed flyback converter has been tested successfully upto the output power level of 10W, with a switching frequency in the range of 2.7MHz-4.3MHz. The input voltage of the converter is varied from 25V-40V DC. Frequency modulation technique is employed by maintaining constant off time to regulate the output voltage of the converter. The energy efficiency of the isolated flyback converter circuit under ZVS condition in the MHz frequency region is found to be approximately in the range of 72-84%. This paper gives the comparative results in terms of the energy efficiency of the hard switched and soft switched flyback converter in the MHz frequency region.

Keywords: Coreless PCB step down transformer, DC-DCconverter, Flyback, Hard Switched Converter, MHz frequencyregion, Multilayered PCB transformer, Zero Voltage Switching

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Authors: Shun Hattori

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In recent years, many researches to mine the exploding Web world, especially User Generated Content (UGC) such as weblogs, for knowledge about various phenomena and events in the physical world have been done actively, and also Web services with the Web-mined knowledge have begun to be developed for the public. However, there are few detailed investigations on how accurately Web-mined data reflect physical-world data. It must be problematic to idolatrously utilize the Web-mined data in public Web services without ensuring their accuracy sufficiently. Therefore, this paper introduces the simplest Web Sensor and spatiotemporallynormalized Web Sensor to extract spatiotemporal data about a target phenomenon from weblogs searched by keyword(s) representing the target phenomenon, and tries to validate the potential and reliability of the Web-sensed spatiotemporal data by four kinds of granularity analyses of coefficient correlation with temperature, rainfall, snowfall, and earthquake statistics per day by region of Japan Meteorological Agency as physical-world data: spatial granularity (region-s population density), temporal granularity (time period, e.g., per day vs. per week), representation granularity (e.g., “rain" vs. “heavy rain"), and media granularity (weblogs vs. microblogs such as Tweets).

Keywords: Granularity analysis, knowledge extraction, spatiotemporal data mining, Web credibility, Web mining, Web sensor.

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Authors: J. Alamelu Mangai, Satej Wagle, V. Santhosh Kumar

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The exponential increase in the volume of medical image database has imposed new challenges to clinical routine in maintaining patient history, diagnosis, treatment and monitoring. With the advent of data mining and machine learning techniques it is possible to automate and/or assist physicians in clinical diagnosis. In this research a medical image classification framework using data mining techniques is proposed. It involves feature extraction, feature selection, feature discretization and classification. In the classification phase, the performance of the traditional kNN k nearest neighbor classifier is improved using a feature weighting scheme and a distance weighted voting instead of simple majority voting. Feature weights are calculated using the interestingness measures used in association rule mining. Experiments on the retinal fundus images show that the proposed framework improves the classification accuracy of traditional kNN from 78.57 % to 92.85 %.

Keywords: Medical Image Mining, Data Mining, Feature Weighting, Association Rule Mining, k nearest neighbor classifier.

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Authors: B. K. Yadav, A. Gandhi, A. K. Verma, T. S. Rao, A. Saraswat, E. R. Kumar, M. Sarkar, K. N. Vyas

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This paper deals with the conceptual design of Experimental Helium Cooling Loop (EHCL) for Indian Test Blanket Module (TBM) and its related thermal hydraulic experiments. Indian TBM team is developing Lead Lithium cooled Ceramic Breeder (IN-LLCB) TBM to be tested in ITER. The TBM box structure is cooled by high pressure (8 MPa) and high temperature (300-500C) helium gas.

The first wall of TBM made of complex channel geometry having several parallel channels carrying helium gas for efficient heat extraction. Several mock-ups of these channels need to be tested before finalizing the TBM first wall design and fabrication. Besides the individual testing of such mock-ups of breeding blanket, the testing of Pb-Li to helium heat exchanger, the operational experience of helium loop and understanding of the behavior of high pressure and high temperature system components are very essential for final development of Helium Cooling System for LLCB TBM in ITER. The main requirements and characteristics of the EHCL and its conceptual design are presented in this paper.

Keywords: DEMO, EHCL, ITER, LLCB TBM.

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Authors: B. Geethanjali, K. Adalarasu, R. Rajsekaran

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Music has a great effect on human body and mind; it can have a positive effect on hormone system. Objective of this study is to analysis the effect of music (carnatic, hard rock and jazz) on brain activity during mental work load using electroencephalography (EEG). Eight healthy subjects without special musical education participated in the study. EEG signals were acquired at frontal (Fz), parietal (Pz) and central (Cz) lobes of brain while listening to music at three experimental condition (rest, music without mental task and music with mental task). Spectral powers features were extracted at alpha, theta and beta brain rhythms. While listening to jazz music, the alpha and theta powers were significantly (p < 0.05) high for rest as compared to music with and without mental task in Cz. While listening to Carnatic music, the beta power was significantly (p < 0.05) high for with mental task as compared to rest and music without mental task at Cz and Fz location. This finding corroborates that attention based activities are enhanced while listening to jazz and carnatic as compare to Hard rock during mental task.

Keywords: Music, Brain Function, Electroencephalography (EEG), Mental Task, Features extraction parameters

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Authors: Kanso Hassan, Elhore Ali, Soule-dupuy Chantal, Tazi Said

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Information Retrieval has the objective of studying models and the realization of systems allowing a user to find the relevant documents adapted to his need of information. The information search is a problem which remains difficult because the difficulty in the representing and to treat the natural languages such as polysemia. Intentional Structures promise to be a new paradigm to extend the existing documents structures and to enhance the different phases of documents process such as creation, editing, search and retrieval. The intention recognition of the author-s of texts can reduce the largeness of this problem. In this article, we present intentions recognition system is based on a semi-automatic method of extraction the intentional information starting from a corpus of text. This system is also able to update the ontology of intentions for the enrichment of the knowledge base containing all possible intentions of a domain. This approach uses the construction of a semi-formal ontology which considered as the conceptualization of the intentional information contained in a text. An experiments on scientific publications in the field of computer science was considered to validate this approach.

Keywords: Information research, text analyzes, intentionalstructure, segmentation, ontology, natural language processing.

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

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Classification of high resolution polarimetric Synthetic Aperture Radar (PolSAR) images plays an important role in land cover and land use management. Recently, classification algorithms based on Bag of Visual Words (BOVW) model have attracted significant interest among scholars and researchers in and out of the field of remote sensing. In this paper, BOVW model with pixel based low-level features has been implemented to classify a subset of San Francisco bay PolSAR image, acquired by RADARSAR 2 in C-band. We have used segment-based decision-making strategy and compared the result with the result of traditional Support Vector Machine (SVM) classifier. 90.95% overall accuracy of the classification with the proposed algorithm has shown that the proposed algorithm is comparable with the state-of-the-art methods. In addition to increase in the classification accuracy, the proposed method has decreased undesirable speckle effect of SAR images.

Keywords: Bag of Visual Words, classification, feature extraction, land cover management, Polarimetric Synthetic Aperture Radar.

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Authors: Abdallah S. Abdallah, A. Lynn Abbott, Mohamad Abou El-Nasr

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This paper presents a new technique for detection of human faces within color images. The approach relies on image segmentation based on skin color, features extracted from the two-dimensional discrete cosine transform (DCT), and self-organizing maps (SOM). After candidate skin regions are extracted, feature vectors are constructed using DCT coefficients computed from those regions. A supervised SOM training session is used to cluster feature vectors into groups, and to assign “face" or “non-face" labels to those clusters. Evaluation was performed using a new image database of 286 images, containing 1027 faces. After training, our detection technique achieved a detection rate of 77.94% during subsequent tests, with a false positive rate of 5.14%. To our knowledge, the proposed technique is the first to combine DCT-based feature extraction with a SOM for detecting human faces within color images. It is also one of a few attempts to combine a feature-invariant approach, such as color-based skin segmentation, together with appearance-based face detection. The main advantage of the new technique is its low computational requirements, in terms of both processing speed and memory utilization.

Keywords: Face detection, skin color segmentation, self-organizingmap.

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Authors: Ayodeji Fasuyi

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Telfairia occidentalis is a leafy vegetable commonly grown in the tropics for nutritional benefits. The use of enzymes and probiotics is becoming prominent due to the ban on antibiotics as growth promoters in many parts of the world. It is conceived that with enzymes and probiotics additives, fibrous leafy vegetables can be incorporated into poultry feeds as protein source. However, certain antinutrients were also found in the leaves of Telfairia occidentalis. Four broiler starter and finisher diets were formulated for the two phases of the broiler experiments. A mixture of fiber degrading enzymes, Roxazyme G2 (combination of cellulase, glucanase and xylanase) and probiotics (Turbotox), a growth promoter, were used in broiler diets at 1:1. The Roxazyme G2/Turbotox mixtures were used in diets containing four varying levels of Telfairia occidentalis leaf meal (TOLM) at 0, 10, 20 and 30%. Diets 1 were standard broiler diets without TOLM and Roxazyme G2 and Turbotox additives. Diets 2, 3 and 4 had enzymes and probiotics additives. Certain mineral elements such as Ca, P, K, Na, Mg, Fe, Mn, Cu and Zn were found in notable quantities viz. 2.6 g/100 g, 1.2 g/100 g, 6.2 g/100 g, 5.1 g/100 g, 4.7 g/100 g, 5875 ppm, 182 ppm, 136 ppm and 1036 ppm, respectively. Phytin, phytin-P, oxalate, tannin and HCN were also found in ample quantities viz. 189.2 mg/100 g, 120.1 mg/100 g, 80.7 mg/100 g, 43.1 mg/100 g and 61.2 mg/100 g, respectively. The average weight gain was highest at 46.3 g/bird/day for birds on 10% TOLM diet but similar (P > 0.05) to 46.2 g/bird/day for birds on 20% TOLM. The feed conversion ratio (FCR) of 2.27 was the lowest and optimum for birds on 10% TOLM although similar (P > 0.05) to 2.29 obtained for birds on 20% TOLM. FCR of 2.61 was the highest at 2.61 for birds on 30% TOLM diet. The lowest FCR of 2.27 was obtained for birds on 10% TOLM diet although similar (P > 0.05) to 2.29 for birds on 20% TOLM diet. Most carcass characteristics and organ weights were similar (P > 0.05) for the experimental birds on the different diets except for kidney, gizzard and intestinal length. The values for kidney, gizzard and intestinal length were significantly higher (P < 0.05) for birds on the TOLM diets. The nitrogen retention had the highest value of 72.37 ± 0.10% for birds on 10% TOLM diet although similar (P > 0.05) to 71.54 ± 1.89 obtained for birds on the control diet without TOLM and enzymes/probiotics mixture. There was evidence of a better utilization of TOLM as a plant protein source. The carcass characteristics and organ weights all showed evidence of uniform tissue buildup and muscles development particularly in diets containing 10% of TOLM level. There was also better nitrogen utilization in birds on the 10% TOLM diet. Considering the cheap cost of TOLM, it is envisaged that its introduction into poultry feeds as a plant protein source will ultimately reduce the cost of poultry feeds.

Keywords: Telfairia occidentalis leaf meal, enzymes, probiotics, additives.

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Authors: Bing-Wen Chen, Alvin W. Y. Su, Yu-Lin Wang

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Electromyography (EMG) is one of the important indicators during exercise, as it is closely related to the level of muscle activations. This work quantifies the muscle conditions of the lower limbs in a constant workload exercise. Surface EMG signals of the vastus laterals (VL), vastus medialis (VM), rectus femoris (RF), gastrocnemius medianus (GM), gastrocnemius lateral (GL) and Soleus (SOL) were recorded from fourteen healthy males. The EMG signals were segmented in two phases: activation segment (AS) and relaxation segment (RS). Period entropy (PE), peak count (PC), zero crossing (ZC), wave length (WL), mean power frequency (MPF), median frequency (MDF) and root mean square (RMS) are calculated to provide the quantitative information of the measured EMG segments. The outcomes reveal that the PE, PC, ZC and RMS have significantly changed (p<.001); WL presents moderately changed (p<.01); MPF and MDF show no changed (p>.05) during exercise. The results also suggest that the RS is also preferred for performance evaluation, while the results of the extracted features in AS are usually affected directly by the amplitudes. It is further found that the VL exhibits the most significant changes within six muscles during pedaling exercise. The proposed work could be applied to quantify the stamina analysis and to predict the instant muscle status in athletes.

Keywords: EMG, feature extraction, muscle status, pedaling exercise, relaxation segment.

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Authors: Fantazi Walid, Ezzedine Tahar, Bargaoui Zoubeida

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This research presents the main ideas to implement an intelligent system composed by communicating wireless sensors measuring environmental data linked to drought indicators (such as air temperature, soil moisture , etc...). On the other hand, the setting up of a spatio temporal database communicating with a Web mapping application for a monitoring in real time in activity 24:00 /day, 7 days/week is proposed to allow the screening of the drought parameters time evolution and their extraction. Thus this system helps detecting surfaces touched by the phenomenon of drought. Spatio-temporal conceptual models seek to answer the users who need to manage soil water content for irrigating or fertilizing or other activities pursuing crop yield augmentation. Effectively, spatiotemporal conceptual models enable users to obtain a diagram of readable and easy data to apprehend. Based on socio-economic information, it helps identifying people impacted by the phenomena with the corresponding severity especially that this information is accessible by farmers and stakeholders themselves. The study will be applied in Siliana watershed Northern Tunisia.

Keywords: WSN, database spatio-temporal, GIS, web-mapping, indicator of drought.

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Authors: Atanu K Samanta, Asim Ali Khan

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Due to the acquisition of huge amounts of brain tumor magnetic resonance images (MRI) in clinics, it is very difficult for radiologists to manually interpret and segment these images within a reasonable span of time. Computer-aided diagnosis (CAD) systems can enhance the diagnostic capabilities of radiologists and reduce the time required for accurate diagnosis. An intelligent computer-aided technique for automatic detection of a brain tumor through MRI is presented in this paper. The technique uses the following computational methods; the Level Set for segmentation of a brain tumor from other brain parts, extraction of features from this segmented tumor portion using gray level co-occurrence Matrix (GLCM), and the Artificial Neural Network (ANN) to classify brain tumor images according to their respective types. The entire work is carried out on 50 images having five types of brain tumor. The overall classification accuracy using this method is found to be 98% which is significantly good.

Keywords: Artificial neural network, ANN, brain tumor, computer-aided diagnostic, CAD system, gray-level co-occurrence matrix, GLCM, level set method, tumor segmentation.

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Authors: Mangesh S. Deshpande, Raghunath S. Holambe

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Mel Frequency Cepstral Coefficient (MFCC) features are widely used as acoustic features for speech recognition as well as speaker recognition. In MFCC feature representation, the Mel frequency scale is used to get a high resolution in low frequency region, and a low resolution in high frequency region. This kind of processing is good for obtaining stable phonetic information, but not suitable for speaker features that are located in high frequency regions. The speaker individual information, which is non-uniformly distributed in the high frequencies, is equally important for speaker recognition. Based on this fact we proposed an admissible wavelet packet based filter structure for speaker identification. Multiresolution capabilities of wavelet packet transform are used to derive the new features. The proposed scheme differs from previous wavelet based works, mainly in designing the filter structure. Unlike others, the proposed filter structure does not follow Mel scale. The closed-set speaker identification experiments performed on the TIMIT database shows improved identification performance compared to other commonly used Mel scale based filter structures using wavelets.

Keywords: Speaker identification, Wavelet transform, Feature extraction, MFCC, GMM.

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Authors: Y. Outaleb, K. Bouhadef, O. Rahli

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Double-diffusive steady convection in a partially porous cavity with partially permeable walls and under the combined buoyancy effects of thermal and mass diffusion was analysed numerically using finite volume method. The top wall is well insulated and impermeable while the bottom surface is partially well insulated and impermeable and partially submitted to constant temperature T1 and concentration C1. Constant equal temperature T2 and concentration C2 are imposed along the vertical surfaces of the enclosure. Mass suction/injection and injection/suction are respectively considered at the bottom of the porous centred partition and at one of the vertical walls. Heat and mass transfer characteristics as streamlines and average Nusselt numbers and Sherwood numbers were discussed for different values of buoyancy ratio, Rayleigh number, and injection/suction coefficient. It is especially noted that increasing the injection factor disadvantages the exchanges in the case of the injection while the transfer is augmented in case of suction. On the other hand, a critical value of the buoyancy ratio was highlighted for which heat and mass transfers are minimized.

Keywords: Double diffusive convection, Injection/Extraction, Partially porous cavity

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Authors: Mohammad Abdollahi

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Tomato (Lycopersicon esculentum Mill.) is one of the most popular, widely grown and the second most important vegetable crop, after potatoes. Nematodes have been identified as one of the major pests affecting tomato production throughout the world. The most destructive nematodes are the genus Meloidogyne. Most widespread and devastating species of this genus are M. incognita, M. javanica, and M. arenaria. These species can cause complete crop loss under adverse growing conditions. There are several potential methods for management of the root knot nematodes. Although the chemicals are widely used against the phytonematodes, because of hazardous effects of these compounds on non-target organisms and on the environment, there is a need to develop other control strategies. Nowadays, non-chemical measures are widely used to control the plant parasitic nematodes. Biocontrol of phytonematodes is an important method among environment-friendly measures of nematode management. There are some soil-inhabiting fungi that have biocontrol potential on phytonematodes, which can be used in nematode management program. The fungus Metarhizium anisopliae, originally is an entomopathogenic bioagent. Biocontrol potential of this fungus on some phytonematodes has been reported earlier. Recently, use of organic soil amendments as well as the use of bioagents is under special attention in sustainable agriculture. This research aimed to reduce the pesticide use in control of root-knot nematode, Meloidogyne javanica in tomato. The effects of M. anisopliae IMI 330189 and different levels of oak tree debris on M. javanica were determined. The combination effect of the fungus as well as the different rates of soil amendments was determined. Pots were filled with steam pasteurized soil mixture and the six leaf tomato seedlings were inoculated with 3000 second stage larvae of M. javanica/kg of soil. After eight weeks, plant growth parameters and nematode reproduction factors were compared. Based on the results of our experiment, combination of M. anisopliae IMI 330189 and oak debris caused more than 90% reduction in reproduction factor of nematode, at the rates of 100 and 150 g/kg soil (P ≤ 0.05). As compared to control, the reduction in number of galls was 76%. It was 86% for nematode reproduction factor, showing the significance of combined effect of both tested agents. Our results showed that plant debris can increase the biological activity of the tested bioagent. It was also proved that there was no adverse effect of oak debris, which potentially has antimicrobial activity, on antagonistic power of applied bioagent.

Keywords: Biological control, nematode management, organic soil, Quercus branti, root knot nematode, soil amendment.

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Authors: Lavanya Srinivasan

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Biometric identification is to identify unique features in a person like fingerprints, iris, ear, and voice recognition that need the subject's permission and physical contact. Gait biometric is used to identify the unique gait of the person by extracting moving features. The main advantage of gait biometric to identify the gait of a person at a distance, without any physical contact. In this work, the gait biometric is used for person re-identification. The person walking naturally compared with the same person walking with bag, coat and case recorded using long wave infrared, short wave infrared, medium wave infrared and visible cameras. The videos are recorded in rural and in urban environments. The pre-processing technique includes human identified using You Only Look Once, background subtraction, silhouettes extraction and synthesis Gait Entropy Image by averaging the silhouettes. The moving features are extracted from the Gait Entropy Energy Image. The extracted features are dimensionality reduced by the Principal Component Analysis and recognized using different classifiers. The comparative results with the different classifier show that Linear Discriminant Analysis outperform other classifiers with 95.8% for visible in the rural dataset and 94.8% for longwave infrared in the urban dataset.

Keywords: biometric, gait, silhouettes, You Only Look Once

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Authors: M. Jazouli, S. Elhoufi, A. Majda, A. Zarghili, R. Aalouane

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Autism spectrum disorder is a complex developmental disability. It is defined by a certain set of behaviors. Persons with Autism Spectrum Disorders (ASD) frequently engage in stereotyped and repetitive motor movements. The objective of this article is to propose a method to automatically detect this unusual behavior. Our study provides a clinical tool which facilitates for doctors the diagnosis of ASD. We focus on automatic identification of five repetitive gestures among autistic children in real time: body rocking, hand flapping, fingers flapping, hand on the face and hands behind back. In this paper, we present a gesture recognition system for children with autism, which consists of three modules: model-based movement tracking, feature extraction, and gesture recognition using artificial neural network (ANN). The first one uses the Microsoft Kinect sensor, the second one chooses points of interest from the 3D skeleton to characterize the gestures, and the last one proposes a neural connectionist model to perform the supervised classification of data. The experimental results show that our system can achieve above 93.3% recognition rate.

Keywords: ASD, stereotypical motor movements, repetitive gesture, kinect, artificial neural network.

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Authors: Yun-Yao Chi, Chieh-Kai Tsai, Dai-Ling Li

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In this paper, a method of fast 3D topography modeling using the high-resolution camera images is studied based on the characteristics of Unmanned Aerial Vehicle (UAV) system for low altitude aerial photogrammetry and the need of three dimensional (3D) urban landscape modeling. Firstly, the existing high-resolution digital camera with special design of overlap images is designed by reconstructing and analyzing the auto-flying paths of UAVs, which improves the self-calibration function to achieve the high precision imaging by software, and further increased the resolution of the imaging system. Secondly, several-angle images including vertical images and oblique images gotten by the UAV system are used for the detail measure of urban land surfaces and the texture extraction. Finally, the aerial photography and 3D topography construction are both developed in campus of Chang-Jung University and in Guerin district area in Tainan, Taiwan, provide authentication model for construction of 3D topography based on combined UAV-based camera images from system. The results demonstrated that the UAV system for low altitude aerial photogrammetry can be used in the construction of 3D topography production, and the technology solution in this paper offers a new, fast, and technical plan for the 3D expression of the city landscape, fine modeling and visualization.

Keywords: 3D, topography, UAV, images.

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Authors: H. A. Lopez-Aguilar, E. A. Huerta-Reynoso, J. A. Gomez, J. A. Duarte-Moller, A. Perez-Hernandez

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Environmental performance of artisanal brick manufacture was studied by Lifecycle Assessment (LCA) methodology and Computational Fluid Dynamics (CFD) analysis in Mexico. The main objective of this paper is to evaluate the environmental impact during artisanal brick manufacture. LCA cradle-to-gate approach was complemented with CFD analysis to carry out an Environmental Impact Assessment (EIA). The lifecycle includes the stages of extraction, baking and transportation to the gate. The functional unit of this study was the production of a single brick in Chihuahua, Mexico and the impact categories studied were carcinogens, respiratory organics and inorganics, climate change radiation, ozone layer depletion, ecotoxicity, acidification/ eutrophication, land use, mineral use and fossil fuels. Laboratory techniques for fuel characterization, gas measurements in situ, and AP42 emission factors were employed in order to calculate gas emissions for inventory data. The results revealed that the categories with greater impacts are ecotoxicity and carcinogens. The CFD analysis is helpful in predicting the thermal diffusion and contaminants from a defined source. LCA-CFD synergy complemented the EIA and allowed us to identify the problem of thermal efficiency within the system.

Keywords: LCA, CFD, brick, artisanal.

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Authors: Somnath Dey, Debasis Samanta

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Iris-based biometric authentication is gaining importance in recent times. Iris biometric processing however, is a complex process and computationally very expensive. In the overall processing of iris biometric in an iris-based biometric authentication system, feature processing is an important task. In feature processing, we extract iris features, which are ultimately used in matching. Since there is a large number of iris features and computational time increases as the number of features increases, it is therefore a challenge to develop an iris processing system with as few as possible number of features and at the same time without compromising the correctness. In this paper, we address this issue and present an approach to feature extraction and feature matching process. We apply Daubechies D4 wavelet with 4 levels to extract features from iris images. These features are encoded with 2 bits by quantizing into 4 quantization levels. With our proposed approach it is possible to represent an iris template with only 304 bits, whereas existing approaches require as many as 1024 bits. In addition, we assign different weights to different iris region to compare two iris templates which significantly increases the accuracy. Further, we match the iris template based on a weighted similarity measure. Experimental results on several iris databases substantiate the efficacy of our approach.

Keywords: Iris recognition, biometric, feature processing, patternrecognition, pattern matching.

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Authors: Billel Kenidra, Mohamed Benmohammed

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Data mining technique used in the field of clustering is a subject of active research and assists in biological pattern recognition and extraction of new knowledge from raw data. Clustering means the act of partitioning an unlabeled dataset into groups of similar objects. Each group, called a cluster, consists of objects that are similar between themselves and dissimilar to objects of other groups. Several clustering methods are based on partitional clustering. This category attempts to directly decompose the dataset into a set of disjoint clusters leading to an integer number of clusters that optimizes a given criterion function. The criterion function may emphasize a local or a global structure of the data, and its optimization is an iterative relocation procedure. The K-Means algorithm is one of the most widely used partitional clustering techniques. Since K-Means is extremely sensitive to the initial choice of centers and a poor choice of centers may lead to a local optimum that is quite inferior to the global optimum, we propose a strategy to initiate K-Means centers. The improved K-Means algorithm is compared with the original K-Means, and the results prove how the efficiency has been significantly improved.

Keywords: Microarray data mining, biological pattern recognition, partitional clustering, k-means algorithm, centroid initialization.

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Authors: Deepti Tamrakar, Pritee Khanna

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This manuscript presents, palmprint recognition by combining different texture extraction approaches with high accuracy. The Region of Interest (ROI) is decomposed into different frequencytime sub-bands by wavelet transform up-to two levels and only the approximate image of two levels is selected, which is known as Approximate Image ROI (AIROI). This AIROI has information of principal lines of the palm. The Competitive Index is used as the features of the palmprint, in which six Gabor filters of different orientations convolve with the palmprint image to extract the orientation information from the image. The winner-take-all strategy is used to select dominant orientation for each pixel, which is known as Competitive Index. Further, PCA is applied to select highly uncorrelated Competitive Index features, to reduce the dimensions of the feature vector, and to project the features on Eigen space. The similarity of two palmprints is measured by the Euclidean distance metrics. The algorithm is tested on Hong Kong PolyU palmprint database. Different AIROI of different wavelet filter families are also tested with the Competitive Index and PCA. AIROI of db7 wavelet filter achievs Equal Error Rate (EER) of 0.0152% and Genuine Acceptance Rate (GAR) of 99.67% on the palm database of Hong Kong PolyU.

Keywords: DWT, EER, Euclidean Distance, Gabor filter, PCA, ROI.

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Authors: Marios Poulos, George Bokos

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This paper makes an attempt to solve the problem of searching and retrieving of similar MRI photos via Internet services using morphological features which are sourced via the original image. This study is aiming to be considered as an additional tool of searching and retrieve methods. Until now the main way of the searching mechanism is based on the syntactic way using keywords. The technique it proposes aims to serve the new requirements of libraries. One of these is the development of computational tools for the control and preservation of the intellectual property of digital objects, and especially of digital images. For this purpose, this paper proposes the use of a serial number extracted by using a previously tested semantic properties method. This method, with its center being the multi-layers of a set of arithmetic points, assures the following two properties: the uniqueness of the final extracted number and the semantic dependence of this number on the image used as the method-s input. The major advantage of this method is that it can control the authentication of a published image or its partial modification to a reliable degree. Also, it acquires the better of the known Hash functions that the digital signature schemes use and produces alphanumeric strings for cases of authentication checking, and the degree of similarity between an unknown image and an original image.

Keywords: Computational Geometry, MRI photos, Image processing, pattern Recognition.

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Authors: Sandipan Chakroborty, Goutam Saha

Abstract:

A state of the art Speaker Identification (SI) system requires a robust feature extraction unit followed by a speaker modeling scheme for generalized representation of these features. Over the years, Mel-Frequency Cepstral Coefficients (MFCC) modeled on the human auditory system has been used as a standard acoustic feature set for speech related applications. On a recent contribution by authors, it has been shown that the Inverted Mel- Frequency Cepstral Coefficients (IMFCC) is useful feature set for SI, which contains complementary information present in high frequency region. This paper introduces the Gaussian shaped filter (GF) while calculating MFCC and IMFCC in place of typical triangular shaped bins. The objective is to introduce a higher amount of correlation between subband outputs. The performances of both MFCC & IMFCC improve with GF over conventional triangular filter (TF) based implementation, individually as well as in combination. With GMM as speaker modeling paradigm, the performances of proposed GF based MFCC and IMFCC in individual and fused mode have been verified in two standard databases YOHO, (Microphone Speech) and POLYCOST (Telephone Speech) each of which has more than 130 speakers.

Keywords: Gaussian Filter, Triangular Filter, Subbands, Correlation, MFCC, IMFCC, GMM.

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Authors: K. Amudha, C. Nelson Kennedy Babu, S. Balu

Abstract:

The security of the medical images and its related data is the major research area which is to be concentrated in today’s era. Security in the medical image indicates that the physician may hide patients’ related data in the medical image and transfer it safely to a defined location using reversible watermarking. Many reversible watermarking methods had proposed over the decade. This paper enhances the security level in brain tumor images to hide the patient’s detail, which has to be conferred with other physician’s suggestions. The details or the information will be hidden in Non-ROI area of the image by using the block cipher algorithm. The block cipher uses different keys to extract the details that are difficult for the intruder to detect all the keys and to spot the details, which are the key advantage of this method. The ROI is the tumor area and Non-ROI is the area rest of ROI. The Non-ROI should not be spoiled in any cause and the details in the Non-ROI should be extracted correctly. The reversible watermarking method proposed in this paper performs well when compared to existing methods in the process of extraction of an original image and providing information security.

Keywords: Brain tumor images, Block Cipher, Reversible watermarking, ROI.

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Authors: Elijah Acquah-Andoh

Abstract:

The UK has had its fair share of the shale gas revolutionary waves blowing across the global oil and gas industry at present. Although, its exploitation is widely agreed to have been delayed, shale gas was looked upon favorably by the UK Parliament when they recognized it as genuine energy source and granted licenses to industry to search and extract the resource. This, although a significant progress by industry, there yet remains another test the UK fracking resource must pass in order to render shale gas extraction feasible – it must be economically extractible and sustainably so. Developing unconventional resources is much more expensive and risky, and for shale gas wells, producing in commercial volumes is conditional upon drilling horizontal wells and hydraulic fracturing, techniques which increase CAPEX. Meanwhile, investment in shale gas development projects is sensitive to gas price and technical and geological risks. Using a Two-Factor Model, the economics of the Bowland shale wells were analyzed and the operational conditions under which fracking is profitable in the UK was characterized. We find that there is a great degree of flexibility about Opex spending; hence Opex does not pose much threat to the fracking industry in the UK. However, we discover Bowland shale gas wells fail to add value at gas price of $8/ Mmbtu. A minimum gas price of $12/Mmbtu at Opex of no more than $2/ Mcf and no more than $14.95M Capex are required to create value within the present petroleum tax regime, in the UK fracking industry.

Keywords: Capex, economical, investment, profitability, shale gas development, sustainable.

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Authors: Xiang Yu, Chuntao Feng, Lu Yang, Meiyang Song, Wenhao Zhou

Abstract:

The existing two-dimensional micro-Doppler features extraction ignores the correlation information between the spatial and temporal dimension features. For the range-Doppler map, the time dimension is introduced, and a frequency modulation continuous wave (FMCW) radar human fall detection algorithm based on time-varying range-Doppler features is proposed. Firstly, the range-Doppler sequence maps are generated from the echo signals of the continuous motion of the human body collected by the radar. Then the three-dimensional data cube composed of multiple frames of range-Doppler maps is input into the three-dimensional Convolutional Neural Network (3D CNN). The spatial and temporal features of time-varying range-Doppler are extracted by the convolution layer and pool layer at the same time. Finally, the extracted spatial and temporal features are input into the fully connected layer for classification. The experimental results show that the proposed fall detection algorithm has a detection accuracy of 95.66%.

Keywords: FMCW radar, fall detection, 3D CNN, time-varying range-Doppler features.

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Authors: Z. Didar, A. Pourfarzad, M. H. Haddad Khodaparast

Abstract:

Nowadays, consumption of whole flours and flours with high extraction rate is recommended, because of their high amount of fibers, vitamins and minerals. Despite nutritional benefits of whole flour, concentration of some undesirable components such as phytic acid is higher than white flour. In this study, effect of several lactic acid bacteria sourdough on Toast bread is investigated. Sourdough from lactic acid bacteria (Lb. plantarum, Lb. reuteri) with different dough yield (250 and 300) is made and incubated at 30°C for 20 hour, then added to dough in the ratio of 10, 20 and 30% replacement. Breads that supplemented with Lb. plantarum sourdough had lower phytic acid. Higher replacement of sourdough and higher DY cause higher decrease in phytic acid content. Sourdough from Lb. plantarum, DY = 300 and 30% replacement cause the highest decrease in phytic acid content (49.63 mg/100g). As indicated by panelists, Lb. reuteri sourdough can present the greatest effect on overall quality score of the breads. DY reduction cause a decrease in bread quality score. Sensory score of Toast bread is 81.71 in the samples that treated with Lb. reuteri sourdough with DY = 250 and 20% replacement.

Keywords: Phytic Acid, Sourdough, Toast Bread, Whole Wheat Flour, Lactic Acid Bacteria.

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Authors: Hesam Sedaghat Nejad, Navid Hosseini, Arash Nikvar Hassani

Abstract:

Determination of the optimum block size with high profitability is one of the significant parameters in designation of the building stone mines. The aim of this study was to determine the optimum dimensions of building stone blocks in Delichai travertine mine of Damavand in Tehran province through combining the effective parameters proven in determination of the optimum dimensions in building stones such as the spacing of joints and gaps, extraction tools constraints with the help of modeling by Gemcom software. To this end, following simulation of the topography of the mine, the block model was prepared and then in order to use spacing joints and discontinuities as a limiting factor, the existing joints set was added to the model. Since only one almost horizontal joint set with a slope of 5 degrees was available, this factor was effective only in determining the optimum height of the block, and thus to determine the longitudinal and transverse optimum dimensions of the extracted block, the power of available loader in the mine was considered as the secondary limiting factor. According to the aforementioned factors, the optimal block size in this mine was measured as 3.4×4×7 meter.

Keywords: Building stone, optimum block size, Delichai Travertine Mine, loader power.

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Authors: C. Yaiprasert, K. Jaroensutasinee, M. Jaroensutasinee

Abstract:

To develop a process of extracting pixel values over the using of satellite remote sensing image data in Thailand. It is a very important and effective method of forecasting rainfall. This paper presents an approach for forecasting a possible rainfall area based on pixel values from remote sensing satellite images. First, a method uses an automatic extraction process of the pixel value data from the satellite image sequence. Then, a data process is designed to enable the inference of correlations between pixel value and possible rainfall occurrences. The result, when we have a high averaged pixel value of daily water vapor data, we will also have a high amount of daily rainfall. This suggests that the amount of averaged pixel values can be used as an indicator of raining events. There are some positive associations between pixel values of daily water vapor images and the amount of daily rainfall at each rain-gauge station throughout Thailand. The proposed approach was proven to be a helpful manual for rainfall forecasting from meteorologists by which using automated analyzing and interpreting process of meteorological remote sensing data.

Keywords: Pixel values, satellite image, water vapor, rainfall, image processing.

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