Search results for: sequential extraction
1985 Development of a Computer Aided Diagnosis Tool for Brain Tumor Extraction and Classification
Authors: Fathi Kallel, Abdulelah Alabd Uljabbar, Abdulrahman Aldukhail, Abdulaziz Alomran
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The brain is an important organ in our body since it is responsible about the majority actions such as vision, memory, etc. However, different diseases such as Alzheimer and tumors could affect the brain and conduct to a partial or full disorder. Regular diagnosis are necessary as a preventive measure and could help doctors to early detect a possible trouble and therefore taking the appropriate treatment, especially in the case of brain tumors. Different imaging modalities are proposed for diagnosis of brain tumor. The powerful and most used modality is the Magnetic Resonance Imaging (MRI). MRI images are analyzed by doctor in order to locate eventual tumor in the brain and describe the appropriate and needed treatment. Diverse image processing methods are also proposed for helping doctors in identifying and analyzing the tumor. In fact, a large Computer Aided Diagnostic (CAD) tools including developed image processing algorithms are proposed and exploited by doctors as a second opinion to analyze and identify the brain tumors. In this paper, we proposed a new advanced CAD for brain tumor identification, classification and feature extraction. Our proposed CAD includes three main parts. Firstly, we load the brain MRI. Secondly, a robust technique for brain tumor extraction is proposed. This technique is based on both Discrete Wavelet Transform (DWT) and Principal Component Analysis (PCA). DWT is characterized by its multiresolution analytic property, that’s why it was applied on MRI images with different decomposition levels for feature extraction. Nevertheless, this technique suffers from a main drawback since it necessitates a huge storage and is computationally expensive. To decrease the dimensions of the feature vector and the computing time, PCA technique is considered. In the last stage, according to different extracted features, the brain tumor is classified into either benign or malignant tumor using Support Vector Machine (SVM) algorithm. A CAD tool for brain tumor detection and classification, including all above-mentioned stages, is designed and developed using MATLAB guide user interface.Keywords: MRI, brain tumor, CAD, feature extraction, DWT, PCA, classification, SVM
Procedia PDF Downloads 2421984 Human Action Recognition Using Wavelets of Derived Beta Distributions
Authors: Neziha Jaouedi, Noureddine Boujnah, Mohamed Salim Bouhlel
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In the framework of human machine interaction systems enhancement, we focus throw this paper on human behavior analysis and action recognition. Human behavior is characterized by actions and reactions duality (movements, psychological modification, verbal and emotional expression). It’s worth noting that many information is hidden behind gesture, sudden motion points trajectories and speeds, many research works reconstructed an information retrieval issues. In our work we will focus on motion extraction, tracking and action recognition using wavelet network approaches. Our contribution uses an analysis of human subtraction by Gaussian Mixture Model (GMM) and body movement through trajectory models of motion constructed from kalman filter. These models allow to remove the noise using the extraction of the main motion features and constitute a stable base to identify the evolutions of human activity. Each modality is used to recognize a human action using wavelets of derived beta distributions approach. The proposed approach has been validated successfully on a subset of KTH and UCF sports database.Keywords: feautures extraction, human action classifier, wavelet neural network, beta wavelet
Procedia PDF Downloads 4061983 Solvent Extraction, Spectrophotometric Determination of Antimony(III) from Real Samples and Synthetic Mixtures Using O-Methylphenyl Thiourea as a Sensitive Reagent
Authors: Shashikant R. Kuchekar, Shivaji D. Pulate, Vishwas B. Gaikwad
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A simple and selective method is developed for solvent extraction spectrophotometric determination of antimony(III) using O-Methylphenyl Thiourea (OMPT) as a sensitive chromogenic chelating agent. The basis of proposed method is formation of antimony(III)-OMPT complex was extracted with 0.0025 M OMPT in chloroform from aqueous solution of antimony(III) in 1.0 M perchloric acid. The absorbance of this complex was measured at 297 nm against reagent blank. Beer’s law was obeyed up to 15µg mL-1 of antimony(III). The Molar absorptivity and Sandell’s sensitivity of the antimony(III)-OMPT complex in chloroform are 16.6730 × 103 L mol-1 cm-1 and 0.00730282 µg cm-2 respectively. The stoichiometry of antimony(III)-OMPT complex was established from slope ratio method, mole ratio method and Job’s continuous variation method was 1:2. The complex was stable for more than 48 h. The interfering effect of various foreign ions was studied and suitable masking agents are used wherever necessary to enhance selectivity of the method. The proposed method is successfully applied for determination of antimony(III) from real samples alloy and synthetic mixtures. Repetition of the method was checked by finding relative standard deviation (RSD) for 10 determinations which was 0.42%.Keywords: solvent extraction, antimony, spectrophotometry, real sample analysis
Procedia PDF Downloads 3291982 Comparison of Soil Test Extractants for Determination of Available Soil Phosphorus
Authors: Violina Angelova, Stefan Krustev
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The aim of this work was to evaluate the effectiveness of different soil test extractants for the determination of available soil phosphorus in five internationally certified standard soils, sludge and clay (NCS DC 85104, NCS DC 85106, ISE 859, ISE 952, ISE 998). The certified samples were extracted with the following methods/extractants: CaCl₂, CaCl₂ and DTPA (CAT), double lactate (DL), ammonium lactate (AL), calcium acetate lactate (CAL), Olsen, Mehlich 3, Bray and Kurtz I, and Morgan, which are commonly used in soil testing laboratories. The phosphorus in soil extracts was measured colorimetrically using Spectroquant Pharo 100 spectrometer. The methods used in the study were evaluated according to the recovery of available phosphorus, facility of application and rapidity of performance. The relationships between methods are examined statistically. A good agreement of the results from different soil test was established for all certified samples. In general, the P values extracted by the nine extraction methods significantly correlated with each other. When grouping the soils according to pH, organic carbon content and clay content, weaker extraction methods showed analogous trends; also among the stronger extraction methods, common tendencies were found. Other factors influencing the extraction force of the different methods include soil: solution ratio, as well as the duration and power of shaking the samples. The mean extractable P in certified samples was found to be in the order of CaCl₂ < CAT < Morgan < Bray and Kurtz I < Olsen < CAL < DL < Mehlich 3 < AL. Although the nine methods extracted different amounts of P from the certified samples, values of P extracted by the different methods were strongly correlated among themselves. Acknowledgment: The financial support by the Bulgarian National Science Fund Projects DFNI Н04/9 and DFNI Н06/21 are greatly appreciated.Keywords: available soil phosphorus, certified samples, determination, soil test extractants
Procedia PDF Downloads 1441981 Chitosan Magnetic Nanoparticles and Its Analytical Applications
Authors: Eman Alzahrani
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Efficient extraction of proteins by removing interfering materials is necessary in proteomics, since most instruments cannot handle such contaminated sample matrices directly. In this study, chitosan-coated magnetic nanoparticles (CS-MNPs) for purification of myoglobin were successfully fabricated. First, chitosan (CS) was prepared by a deacetylation reaction during its extraction from shrimp-shell waste. Second, magnetic nanoparticles (MNPs) were synthesised, using the coprecipitation method, from aqueous Fe2+ and Fe3+ salt solutions by the addition of a base under an inert atmosphere, followed by modification of the surface of MNPs with chitosan. The morphology of the formed nanoparticles, which were about 23 nm in average diameter, was observed by transmission electron microscopy (TEM). In addition, nanoparticles were characterised using X-ray diffraction patterns (XRD), which showed the naked magnetic nanoparticles have a spinel structure and the surface modification did not result in phase change of the Fe3O4. The coating of MNPs was also demonstrated by scanning electron microscopy (SEM) analysis, energy dispersive analysis of X-ray spectroscopy (EDAX), and Fourier transform infrared (FT-IR) spectroscopy. The adsorption behaviour of MNPs and CS-MNPs towards myoglobin was investigated. It was found that the difference in adsorption capacity between MNPs and CS-MNPs was larger for CS-MNPs. This result makes CS-MNPs good adsorbents and attractive for using in protein extraction from biological samples.Keywords: chitosan, magnetic nanoparticles, coprecipitation, adsorption
Procedia PDF Downloads 4121980 A New Approach of Preprocessing with SVM Optimization Based on PSO for Bearing Fault Diagnosis
Authors: Tawfik Thelaidjia, Salah Chenikher
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Bearing fault diagnosis has attracted significant attention over the past few decades. It consists of two major parts: vibration signal feature extraction and condition classification for the extracted features. In this paper, feature extraction from faulty bearing vibration signals is performed by a combination of the signal’s Kurtosis and features obtained through the preprocessing of the vibration signal samples using Db2 discrete wavelet transform at the fifth level of decomposition. In this way, a 7-dimensional vector of the vibration signal feature is obtained. After feature extraction from vibration signal, the support vector machine (SVM) was applied to automate the fault diagnosis procedure. To improve the classification accuracy for bearing fault prediction, particle swarm optimization (PSO) is employed to simultaneously optimize the SVM kernel function parameter and the penalty parameter. The results have shown feasibility and effectiveness of the proposed approachKeywords: condition monitoring, discrete wavelet transform, fault diagnosis, kurtosis, machine learning, particle swarm optimization, roller bearing, rotating machines, support vector machine, vibration measurement
Procedia PDF Downloads 4331979 Study Mercapto-Nanoscavenger as a Promising Analytical Tool
Authors: Mohammed M. Algaradah
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A chelating mercapto- nanoscavenger has been developed exploiting the high surface area of monodisperse nano-sized mesoporous silica. The nanoscavenger acts as a solid phase trace metal extractant whilst suspended as a quasi-stable sol in aqueous samples. This mode of extraction requires no external agitation as the particles move naturally through the sample by Brownian motion, convection and slow sedimentation. Careful size selection enables the nanoscavenger to be easily recovered together with the extracted analyte by conventional filtration or centrifugation. The research describes the successful attachment of chelator mercapto to ca. 136 ± 15 nm high surface area (BET surface area = 1006 m2 g-1) mesoporous silica particles. The resulting material had a copper capacity of ca. 1.34 ± 0.10 mmol g-1 and was successfully applied to the collection of a trace element from water. Essentially complete recovery of Cu (II) has been achieved from freshwater samples giving typical preconcentration factors of 100 from 50 µg/l samples. Data obtained from a nanoscavenger-based extraction of copper from samples were not significantly different from those obtained by using a conventional colorimetric procedure employing complexation/solvent extraction.Keywords: nano scavenger, mesoporous silica, trace metal, preconcentration
Procedia PDF Downloads 781978 An Event Relationship Extraction Method Incorporating Deep Feedback Recurrent Neural Network and Bidirectional Long Short-Term Memory
Authors: Yin Yuanling
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A Deep Feedback Recurrent Neural Network (DFRNN) and Bidirectional Long Short-Term Memory (BiLSTM) are designed to address the problem of low accuracy of traditional relationship extraction models. This method combines a deep feedback-based recurrent neural network (DFRNN) with a bi-directional long short-term memory (BiLSTM) approach. The method combines DFRNN, which extracts local features of text based on deep feedback recurrent mechanism, BiLSTM, which better extracts global features of text, and Self-Attention, which extracts semantic information. Experiments show that the method achieves an F1 value of 76.69% on the CEC dataset, which is 0.0652 better than the BiLSTM+Self-ATT model, thus optimizing the performance of the deep learning method in the event relationship extraction task.Keywords: event relations, deep learning, DFRNN models, bi-directional long and short-term memory networks
Procedia PDF Downloads 1351977 An Automated System for the Detection of Citrus Greening Disease Based on Visual Descriptors
Authors: Sidra Naeem, Ayesha Naeem, Sahar Rahim, Nadia Nawaz Qadri
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Citrus greening is a bacterial disease that causes considerable damage to citrus fruits worldwide. Efficient method for this disease detection must be carried out to minimize the production loss. This paper presents a pattern recognition system that comprises three stages for the detection of citrus greening from Orange leaves: segmentation, feature extraction and classification. Image segmentation is accomplished by adaptive thresholding. The feature extraction stage comprises of three visual descriptors i.e. shape, color and texture. From shape feature we have used asymmetry index, from color feature we have used histogram of Cb component from YCbCr domain and from texture feature we have used local binary pattern. Classification was done using support vector machines and k nearest neighbors. The best performances of the system is Accuracy = 88.02% and AUROC = 90.1% was achieved by automatic segmented images. Our experiments validate that: (1). Segmentation is an imperative preprocessing step for computer assisted diagnosis of citrus greening, and (2). The combination of shape, color and texture features form a complementary set towards the identification of citrus greening disease.Keywords: citrus greening, pattern recognition, feature extraction, classification
Procedia PDF Downloads 1761976 Model-Based Field Extraction from Different Class of Administrative Documents
Authors: Jinen Daghrir, Anis Kricha, Karim Kalti
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The amount of incoming administrative documents is massive and manually processing these documents is a costly task especially on the timescale. In fact, this problem has led an important amount of research and development in the context of automatically extracting fields from administrative documents, in order to reduce the charges and to increase the citizen satisfaction in administrations. In this matter, we introduce an administrative document understanding system. Given a document in which a user has to select fields that have to be retrieved from a document class, a document model is automatically built. A document model is represented by an attributed relational graph (ARG) where nodes represent fields to extract, and edges represent the relation between them. Both of vertices and edges are attached with some feature vectors. When another document arrives to the system, the layout objects are extracted and an ARG is generated. The fields extraction is translated into a problem of matching two ARGs which relies mainly on the comparison of the spatial relationships between layout objects. Experimental results yield accuracy rates from 75% to 100% tested on eight document classes. Our proposed method has a good performance knowing that the document model is constructed using only one single document.Keywords: administrative document understanding, logical labelling, logical layout analysis, fields extraction from administrative documents
Procedia PDF Downloads 2061975 Branched Chain Amino Acid Kinesio PVP Gel Tape from Extract of Pea (Pisum sativum L.) Based on Ultrasound-Assisted Extraction Technology
Authors: Doni Dermawan
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Modern sports competition as a consequence of the increase in the value of the business and entertainment in the field of sport has been demanding athletes to always have excellent physical endurance performance. Physical exercise is done in a long time, and intensive may pose a risk of muscle tissue damage caused by the increase of the enzyme creatine kinase. Branched Chain Amino Acids (BCAA) is an essential amino acid that is composed of leucine, isoleucine, and valine which serves to maintain muscle tissue, keeping the immune system, and prevent further loss of coordination and muscle pain. Pea (Pisum sativum L.) is a kind of leguminous plants that are rich in Branched Chain Amino Acids (BCAA) where every one gram of protein pea contains 82.7 mg of leucine; 56.3 mg isoleucine; and 56.0 mg of valine. This research aims to develop Branched Chain Amino Acids (BCAA) from pea extract is applied in dosage forms Gel PVP Kinesio Tape technology using Ultrasound-assisted Extraction. The method used in the writing of this paper is the Cochrane Collaboration Review that includes literature studies, testing the quality of the study, the characteristics of the data collection, analysis, interpretation of results, and clinical trials as well as recommendations for further research. Extraction of BCAA in pea done using ultrasound-assisted extraction technology with optimization variables includes the type of solvent extraction (NaOH 0.1%), temperature (20-250C), time (15-30 minutes) power (80 watt) and ultrasonic frequency (35 KHz). The advantages of this extraction method are the level of penetration of the solvent into the membrane of the cell is high and can increase the transfer period so that the BCAA substance separation process more efficient. BCAA extraction results are then applied to the polymer PVP (Polyvinylpyrrolidone) Gel powder composed of PVP K30 and K100 HPMC dissolved in 10 mL of water-methanol (1: 1) v / v. Preparations Kinesio Tape Gel PVP is the BCAA in the gel are absorbed into the muscle tissue, and joints through tensile force then provides stimulation to the muscle circulation with variable pressure so that the muscle can increase the biomechanical movement and prevent damage to the muscle enzyme creatine kinase. Analysis and evaluation of test preparation include interaction, thickness, weight uniformity, humidity, water vapor permeability, the levels of the active substance, content uniformity, percentage elongation, stability testing, release profile, permeation in vitro and in vivo skin irritation testing.Keywords: branched chain amino acid, BCAA, Kinesio tape, pea, PVP gel, ultrasound-assisted extraction
Procedia PDF Downloads 2831974 Multi-Stage Classification for Lung Lesion Detection on CT Scan Images Applying Medical Image Processing Technique
Authors: Behnaz Sohani, Sahand Shahalinezhad, Amir Rahmani, Aliyu Aliyu
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Recently, medical imaging and specifically medical image processing is becoming one of the most dynamically developing areas of medical science. It has led to the emergence of new approaches in terms of the prevention, diagnosis, and treatment of various diseases. In the process of diagnosis of lung cancer, medical professionals rely on computed tomography (CT) scans, in which failure to correctly identify masses can lead to incorrect diagnosis or sampling of lung tissue. Identification and demarcation of masses in terms of detecting cancer within lung tissue are critical challenges in diagnosis. In this work, a segmentation system in image processing techniques has been applied for detection purposes. Particularly, the use and validation of a novel lung cancer detection algorithm have been presented through simulation. This has been performed employing CT images based on multilevel thresholding. The proposed technique consists of segmentation, feature extraction, and feature selection and classification. More in detail, the features with useful information are selected after featuring extraction. Eventually, the output image of lung cancer is obtained with 96.3% accuracy and 87.25%. The purpose of feature extraction applying the proposed approach is to transform the raw data into a more usable form for subsequent statistical processing. Future steps will involve employing the current feature extraction method to achieve more accurate resulting images, including further details available to machine vision systems to recognise objects in lung CT scan images.Keywords: lung cancer detection, image segmentation, lung computed tomography (CT) images, medical image processing
Procedia PDF Downloads 911973 Groundwater Utilization and Sustainability: A Case Study of Pydibheemavaram Industrial Area, India
Authors: G. Venkata Rao, R. Srinivasa Rao, B. Neelima Sri Priya
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The over extraction of groundwater from the coastal aquifers, result in reduction of groundwater resource and lowering of water level. In general, the depletion of groundwater level enhances the landward migration of saltwater wedge. Now a days the ground water extraction increases by year to year because increased population and industrialization. The ground water is the only source of irrigation, domestic and Industrial purposes at Pydibhimavaram industrial area, which is located in the coastal belt of Srikakulam district, India of Latitudes 18.145N 83.627E and Longitudes 18.099N 83.674E. The present study has been attempted to calculate amount of water getting recharged into this aquifer, status of rainfall pattern for the past two decades and the runoff is calculated by using Khosla’s formula with available rainfall and temperature in the study area. A decision support model has been developed on the basis of Monthly Extractions of the water from the ground through bore wells and the Net Recharge of the aquifer. It is concluded that the amount of extractions is exceeding the amount of recharge from May to October in a given year which will in turn damage the water balance in the subsurface layers.Keywords: aquifer, decision support model, groundwater extraction, run off estimation and rainfall
Procedia PDF Downloads 2941972 Geometallurgy of Niobium Deposits: An Integrated Multi-Disciplined Approach
Authors: Mohamed Nasraoui
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Spatial ore distribution, ore heterogeneity and their links with geological processes involved in Niobium concentration are all factors for consideration when bridging field observations to extraction scheme. Indeed, mineralogy changes of Nb-hosting phases, their textural relationships with hydrothermal or secondary minerals, play a key control over mineral processing. This study based both on filed work and ore characterization presents data from several Nb-deposits related to carbonatite complexes. The results obtained by a wide range of analytical techniques, including, XRD, XRF, ICP-MS, SEM, Microprobe, Spectro-CL, FTIR-DTA and Mössbauer spectroscopy, demonstrate how geometallurgical assessment, at all stage of mine development, can greatly assist in the design of a suitable extraction flowsheet and data reconciliation.Keywords: carbonatites, Nb-geometallurgy, Nb-mineralogy, mineral processing.
Procedia PDF Downloads 1581971 Aerogel Fabrication Via Modified Rapid Supercritical Extraction (RSCE) Process - Needle Valve Pressure Release
Authors: Haibo Zhao, Thomas Andre, Katherine Avery, Alper Kiziltas, Deborah Mielewski
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Silica aerogels were fabricated through a modified rapid supercritical extraction (RSCE) process. The silica aerogels were made using a tetramethyl orthosilicate precursor and then placed in a hot press and brought to the supercritical point of the solvent, ethanol. In order to control the pressure release without a pressure controller, a needle valve was used. The resulting aerogels were then characterized for their physical and chemical properties and compared to silica aerogels created using similar methods. The aerogels fabricated using this modified RSCE method were found to have similar properties to those in other papers using the unmodified RSCE method. Silica aerogel infused glass blanket composite, graphene reinforced silica aerogel composite were also successfully fabricated by this new method. The modified RSCE process and system is a prototype for better gas outflow control with a lower cost of equipment setup. Potentially, this process could be evolved to a continuous low-cost high-volume production process to meet automotive requirements.Keywords: aerogel, automotive, rapid supercritical extraction process, low cost production
Procedia PDF Downloads 1781970 Automatic Staging and Subtype Determination for Non-Small Cell Lung Carcinoma Using PET Image Texture Analysis
Authors: Seyhan Karaçavuş, Bülent Yılmaz, Ömer Kayaaltı, Semra İçer, Arzu Taşdemir, Oğuzhan Ayyıldız, Kübra Eset, Eser Kaya
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In this study, our goal was to perform tumor staging and subtype determination automatically using different texture analysis approaches for a very common cancer type, i.e., non-small cell lung carcinoma (NSCLC). Especially, we introduced a texture analysis approach, called Law’s texture filter, to be used in this context for the first time. The 18F-FDG PET images of 42 patients with NSCLC were evaluated. The number of patients for each tumor stage, i.e., I-II, III or IV, was 14. The patients had ~45% adenocarcinoma (ADC) and ~55% squamous cell carcinoma (SqCCs). MATLAB technical computing language was employed in the extraction of 51 features by using first order statistics (FOS), gray-level co-occurrence matrix (GLCM), gray-level run-length matrix (GLRLM), and Laws’ texture filters. The feature selection method employed was the sequential forward selection (SFS). Selected textural features were used in the automatic classification by k-nearest neighbors (k-NN) and support vector machines (SVM). In the automatic classification of tumor stage, the accuracy was approximately 59.5% with k-NN classifier (k=3) and 69% with SVM (with one versus one paradigm), using 5 features. In the automatic classification of tumor subtype, the accuracy was around 92.7% with SVM one vs. one. Texture analysis of FDG-PET images might be used, in addition to metabolic parameters as an objective tool to assess tumor histopathological characteristics and in automatic classification of tumor stage and subtype.Keywords: cancer stage, cancer cell type, non-small cell lung carcinoma, PET, texture analysis
Procedia PDF Downloads 3211969 The Effect of Extrusion Processing on Solubility and Molecular Weight of Water-Soluble Arabinoxylan
Authors: Abdulmannan Fadel
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Arabinoxylan is a non-starch polysaccharide (NSP), which is one of the most important polysaccharides contained within cereal grains. Wheat endosperm pentosan and rice bran contain a significant amount of arabinoxylan (7% in rice bran and 10-12% in wheat endosperm pentosan). Several methods have been used for arabinoxylan extraction with varying degrees of success e.g. enzymatic and alkaline treatment. Yet, the use of extrusion alone as a pre-treatment to increase the yield and reduce the molecular weight in wheat endosperm pentosan and rice bran has not been investigated. The samples (wheat pentosan and rice bran) were extruded using a Twin-screw extruder at a range of screw speeds (80 and 160 rpm) and barrel temperatures range (80 to 140°C) with a throughput of 30 Kg hr-1 and moisture content of 25%. Arabinoxylans were extracted with water and the extraction yield and molecular weight was determined using size exclusion high-pressure liquid chromatography system. It was found that increasing screw speed from 80 rpm to 160 rpm, did not effect the extraction yield (p < 0.05) of arabinoxylan from either the wheat endosperm pentosan or the rice bran. However, the molecular weight of the extracted arabinoxylans from pentosan was found to decrease with increasing screw speed in wheat endosperm pentosan. These low molecular weight arabinoxylans have been suggested as immunomodulators.Keywords: arabinoxylans, extrusion, wheat endosperm pentosan, rice bran
Procedia PDF Downloads 4101968 Medium-Scale Multi-Juice Extractor for Food Processing
Authors: Flordeliza L. Mercado, Teresito G. Aguinaldo, Helen F. Gavino, Victorino T. Taylan
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Most fruits and vegetables are available in large quantities during peak season which are oftentimes marketed at low price and left to rot or fed to farm animals. The lack of efficient storage facilities, and the additional cost and unavailability of small machinery for food processing, results to low price and wastage. Incidentally, processed fresh fruits and vegetables are gaining importance nowadays and health conscious people are also into ‘juicing’. One way to reduce wastage and ensure an all-season availability of crop juices at reasonable costs is to develop equipment for effective extraction of juice. The study was conducted to design, fabricate and evaluate a multi-juice extractor using locally available materials, making it relatively cheaper and affordable for medium-scale enterprises. The study was also conducted to formulate juice blends using extracted juices and calamansi juice at different blending percentage, and evaluate its chemical properties and sensory attributes. Furthermore, the chemical properties of extracted meals were evaluated for future applications. The multi-juice extractor has an overall dimension of 963mm x 300mm x 995mm, a gross weight of 82kg and 5 major components namely; feeding hopper, extracting chamber, juice and meal outlet, transmission assembly, and frame. The machine performance was evaluated based on juice recovery, extraction efficiency, extraction rate, extraction recovery, and extraction loss considering type of crop as apple and carrot with three replications each and was analyzed using T-test. The formulated juice blends were subjected to sensory evaluation and data gathered were analyzed using Analysis of Variance appropriate for Complete Randomized Design. Results showed that the machine’s juice recovery (73.39%), extraction rate (16.40li/hr), and extraction efficiency (88.11%) for apple were significantly higher than for carrot while extraction recovery (99.88%) was higher for apple than for carrot. Extraction loss (0.12%) was lower for apple than for carrot, but was not significantly affected by crop. Based on adding percentage mark-up on extraction cost (Php 2.75/kg), the breakeven weight and payback period for a 35% mark-up is 4,710.69kg and 1.22 years, respectively and for a 50% mark-up, the breakeven weight is 3,492.41kg and the payback period is 0.86 year (10.32 months). Results on the sensory evaluation of juice blends showed that the type of juice significantly influenced all the sensory parameters while the blending percentage including their respective interaction, had no significant effect on all sensory parameters, making the apple-calamansi juice blend more preferred than the carrot-calamansi juice blend in terms of all the sensory parameter. The machine’s performance is higher for apple than for carrot and the cost analysis on the use of the machine revealed that it is financially viable with a payback period of 1.22 years (35% mark-up) and 0.86 year (50% mark-up) for machine cost, generating an income of Php 23,961.60 and Php 34,444.80 per year using 35% and 50% mark-up, respectively. The juice blends were of good qualities based on the values obtained in the chemical analysis and the extracted meal could also be used to produce another product based on the values obtained from proximate analysis.Keywords: food processing, fruits and vegetables, juice extraction, multi-juice extractor
Procedia PDF Downloads 3031967 Software Transactional Memory in a Dynamic Programming Language at Virtual Machine Level
Authors: Szu-Kai Hsu, Po-Ching Lin
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As more and more multi-core processors emerge, traditional sequential programming paradigm no longer suffice. Yet only few modern dynamic programming languages can leverage such advantage. Ruby, for example, despite its wide adoption, only includes threads as a simple parallel primitive. The global virtual machine lock of official Ruby runtime makes it impossible to exploit full parallelism. Though various alternative Ruby implementations do eliminate the global virtual machine lock, they only provide developers dated locking mechanism for data synchronization. However, traditional locking mechanism error-prone by nature. Software Transactional Memory is one of the promising alternatives among others. This paper introduces a new virtual machine: GobiesVM to provide a native software transactional memory based solution for dynamic programming languages to exploit parallelism. We also proposed a simplified variation of Transactional Locking II algorithm. The empirical results of our experiments show that support of STM at virtual machine level enables developers to write straightforward code without compromising parallelism or sacrificing thread safety. Existing source code only requires minimal or even none modi cation, which allows developers to easily switch their legacy codebase to a parallel environment. The performance evaluations of GobiesVM also indicate the difference between sequential and parallel execution is significant.Keywords: global interpreter lock, ruby, software transactional memory, virtual machine
Procedia PDF Downloads 2771966 Functionality and Application of Rice Bran Protein Hydrolysates in Oil in Water Emulsions: Their Stabilities to Environmental Stresses
Authors: R. Charoen, S. Tipkanon, W. Savedboworn, N. Phonsatta, A. Panya
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Rice bran protein hydrolysates (RBPH) were prepared from defatted rice bran of two different Thai rice cultivars (Plai-Ngahm-Prachinburi; PNP and Khao Dok Mali 105; KDM105) using an enzymatic method. This research aimed to optimize enzyme-assisted protein extraction. In addition, the functional properties of RBPH and their stabilities to environmental stresses including pH (3 to 8), ionic strength (0 mM to 500 mM) and the thermal treatment (30 °C to 90 °C) were investigated. Results showed that enzymatic process for protein extraction of defatted rice bran was as follows: enzyme concentration 0.075 g/ 5 g of protein, extraction temperature 50 °C and extraction time 4 h. The obtained protein hydrolysate powders had a degree of hydrolysis (%) of 21.05% in PNP and 19.92% in KDM105. The solubility of protein hydrolysates at pH 4-6 was ranged from 27.28-38.57% and 27.60-43.00% in PNP and KDM105, respectively. In general, antioxidant activities indicated by total phenolic content, FRAP, ferrous ion-chelating (FIC), and 2,2’-azino-bis-3-ethylbenzthiazoline-6-sulphonic acid (ABTS) of KDM105 had higher than PNP. In terms of functional properties, the emulsifying activity index (EAI) was was 8.78 m²/g protein in KDM105, whereas PNP was 5.05 m²/g protein. The foaming capacity at 5 minutes (%) was 47.33 and 52.98 in PNP and KDM105, respectively. Glutamine, Alanine, Valine, and Leucine are the major amino acid in protein hydrolysates where the total amino acid of KDM105 gave higher than PNP. Furthermore, we investigated environmental stresses on the stability of 5% oil in water emulsion (5% oil, 10 mM citrate buffer) stabilized by RBPH (3.5%). The droplet diameter of emulsion stabilized by KDM105 was smaller (d < 250 nm) than produced by PNP. For environmental stresses, RBPH stabilized emulsions were stable at pH around 3 and 5-6, at high salt (< 400 mM, pH 7) and at temperatures range between 30-50°C.Keywords: functional properties, oil in water emulsion, protein hydrolysates, rice bran protein
Procedia PDF Downloads 2061965 Exploring Selected Nigerian Fictional Work and Films as Sources of Peace Building and Conflict Resolution in the Natural Resource Extraction Regions of Nigeria: A Social Conflict Theoretical Perspective and Analysis
Authors: Joyce Onoromhenre Agofure
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Research has shown how fictional work and films reflect the destruction of the environment due to the exploitation of oil, gas, gold, and forest products by multinational companies for profits but overlook discussions on conflict resolution and peacebuilding. However, this paper examines the manner art forms project peace and conflict resolution, thereby contributing to mediation and stability geared towards changing appalling situations in the resource extraction regions of Nigeria. This paper draws from selected Nigerian films- Blood and Oil (2019), directed by Curtis Graham, Black November (2012), directed by Jeta Amata, and a novel- Death of Eternity (2007), by Adamu Kyuka Usman. The study seeks to show that the disruptions caused in the natural resource regions of Nigeria have not only left adverse effects on the social well-being of the people but require resolutions through means of peacebuilding. By adopting the theoretical insights of Social Conflict, this paper focuses on artistic processes that enhance peacebuilding and conflict resolution in non-violent ways by using scenes, visual effects, themes, and images that can educate by shaping opinions, influencing attitudes, and changing ideas and behavioral patterns of individuals and communities. Put together; the research will open up critical perceptions brought about by the artists of study to shed light on the dire need to sustain peace and actively participate in conflict resolution in natural resource extraction spaces.Keywords: natural resource, extraction, conflict resolution, peace building
Procedia PDF Downloads 751964 Enhancement of Light Extraction of Luminescent Coating by Nanostructuring
Authors: Aubry Martin, Nehed Amara, Jeff Nyalosaso, Audrey Potdevin, FrançOis ReVeret, Michel Langlet, Genevieve Chadeyron
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Energy-saving lighting devices based on LightEmitting Diodes (LEDs) combine a semiconductor chip emitting in the ultraviolet or blue wavelength region to one or more phosphor(s) deposited in the form of coatings. The most common ones combine a blue LED with the yellow phosphor Y₃Al₅O₁₂:Ce³⁺ (YAG:Ce) and a red phosphor. Even if these devices are characterized by satisfying photometric parameters (Color Rendering Index, Color Temperature) and good luminous efficiencies, further improvements can be carried out to enhance light extraction efficiency (increase in phosphor forward emission). One of the possible strategies is to pattern the phosphor coatings. Here, we have worked on different ways to nanostructure the coating surface. On the one hand, we used the colloidal lithography combined with the Langmuir-Blodgett technique to directly pattern the surface of YAG:Tb³⁺ sol-gel derived coatings, YAG:Tb³⁺ being used as phosphor model. On the other hand, we achieved composite architectures combining YAG:Ce coatings and ZnO nanowires. Structural, morphological and optical properties of both systems have been studied and compared to flat YAG coatings. In both cases, nanostructuring brought a significative enhancement of photoluminescence properties under UV or blue radiations. In particular, angle-resolved photoluminescence measurements have shown that nanostructuring modifies photons path within the coatings, with a better extraction of the guided modes. These two strategies have the advantage of being versatile and applicable to any phosphor synthesizable by sol-gel technique. They then appear as promising ways to enhancement luminescence efficiencies of both phosphor coatings and the optical devices into which they are incorporated, such as LED-based lighting or safety devices.Keywords: phosphor coatings, nanostructuring, light extraction, ZnO nanowires, colloidal lithography, LED devices
Procedia PDF Downloads 1711963 Multi-Criteria Optimal Management Strategy for in-situ Bioremediation of LNAPL Contaminated Aquifer Using Particle Swarm Optimization
Authors: Deepak Kumar, Jahangeer, Brijesh Kumar Yadav, Shashi Mathur
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In-situ remediation is a technique which can remediate either surface or groundwater at the site of contamination. In the present study, simulation optimization approach has been used to develop management strategy for remediating LNAPL (Light Non-Aqueous Phase Liquid) contaminated aquifers. Benzene, toluene, ethyl benzene and xylene are the main component of LNAPL contaminant. Collectively, these contaminants are known as BTEX. In in-situ bioremediation process, a set of injection and extraction wells are installed. Injection wells supply oxygen and other nutrient which convert BTEX into carbon dioxide and water with the help of indigenous soil bacteria. On the other hand, extraction wells check the movement of plume along downstream. In this study, optimal design of the system has been done using PSO (Particle Swarm Optimization) algorithm. A comprehensive management strategy for pumping of injection and extraction wells has been done to attain a maximum allowable concentration of 5 ppm and 4.5 ppm. The management strategy comprises determination of pumping rates, the total pumping volume and the total running cost incurred for each potential injection and extraction well. The results indicate a high pumping rate for injection wells during the initial management period since it facilitates the availability of oxygen and other nutrients necessary for biodegradation, however it is low during the third year on account of sufficient oxygen availability. This is because the contaminant is assumed to have biodegraded by the end of the third year when the concentration drops to a permissible level.Keywords: groundwater, in-situ bioremediation, light non-aqueous phase liquid, BTEX, particle swarm optimization
Procedia PDF Downloads 4341962 Exploring Subjective Simultaneous Mixed Emotion Experiences in Middle Childhood
Authors: Esther Burkitt
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Background: Evidence is mounting that mixed emotions can be experienced simultaneously in different ways across the lifespan. Four types of patterns of simultaneously mixed emotions (sequential, prevalent, highly parallel, and inverse types) have been identified in middle childhood and adolescence. Moreover, the recognition of these experiences tends to develop firstly when children consider peers rather than the self. This evidence from children and adolescents is based on examining the presence of experiences specified in adulthood. The present study, therefore, applied an exhaustive coding scheme to investigate whether children experience types of previously unidentified simultaneous mixed emotional experiences. Methodology: One hundred and twenty children (60 girls) aged 7 years 1 month - 9 years 2 months (X=8 years 1 month; SD = 10 months) were recruited from mainstream schools across the UK. Two age groups were formed (youngest, n = 61, 7 years 1 month- 8 years 1 months: oldest, n = 59, 8 years 2 months – 9 years 2 months) and allocated to one of two conditions hearing vignettes describing happy and sad mixed emotion events in age and gender-matched protagonist or themselves. Results: Loglinear analyses identified new types of flexuous, vertical, and other experiences along with established sequential, prevalent, highly parallel, and inverse types of experience. Older children recognised more complex experiences other than the self-condition. Conclusion: Several additional types of simultaneously mixed emotions are recognised in middle childhood. The theoretical relevance of simultaneous mixed emotion processing in childhood is considered, and the potential utility of the findings in emotion assessments is discussed.Keywords: emotion, childhood, self, other
Procedia PDF Downloads 721961 Implementing a Database from a Requirement Specification
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Creating a database scheme is essentially a manual process. From a requirement specification, the information contained within has to be analyzed and reduced into a set of tables, attributes and relationships. This is a time-consuming process that has to go through several stages before an acceptable database schema is achieved. The purpose of this paper is to implement a Natural Language Processing (NLP) based tool to produce a from a requirement specification. The Stanford CoreNLP version 3.3.1 and the Java programming were used to implement the proposed model. The outcome of this study indicates that the first draft of a relational database schema can be extracted from a requirement specification by using NLP tools and techniques with minimum user intervention. Therefore, this method is a step forward in finding a solution that requires little or no user intervention.Keywords: information extraction, natural language processing, relation extraction
Procedia PDF Downloads 2541960 The Extraction and Stripping of Hg(II) from Produced Water via Hollow Fiber Contactor
Authors: Dolapop Sribudda, Ura Pancharoen
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The separation of Hg(II) from produced water by hollow fiber contactors (HFC) was investigation. This system included of two hollow fiber modules in the series connecting. The first module used for the extraction reaction and the second module for stripping reaction. Aliquat336 extractant was fed from the organic reservoirs into the shell side of the first hollow fiber module and continuous to the shell side of the second module. The organic liquid was continuously feed recirculate and back to the reservoirs. The feed solution was pumped into the lumen (tube side) of the first hollow fiber module. Simultaneously, the stripping solution was pumped in the same way in tube side of the second module. The feed and stripping solution was fed which had a counter current flow. Samples were kept in the outlet of feed and stripping solution for 1 hour and characterized concentration of Hg(II) by Inductively Couple Plasma Atomic Emission Spectroscopy (ICP-AES). Feed solution was produced water from natural gulf of Thailand. The extractant was Aliquat336 dissolved in kerosene diluent. Stripping solution used was nitric acid (HNO3) and thiourea (NH2CSNH2). The effect of carrier concentration and type of stripping solution were investigated. Results showed that the best condition were 10 % (v/v) Aliquat336 and 1.0 M NH2CSNH2. At the optimum condition, the extraction and stripping of Hg(II) were 98% and 44.2%, respectively.Keywords: Hg(II), hollow fiber contactor, produced water, wastewater treatment
Procedia PDF Downloads 3981959 Modeling the Acquisition of Expertise in a Sequential Decision-Making Task
Authors: Cristóbal Moënne-Loccoz, Rodrigo C. Vergara, Vladimir López, Domingo Mery, Diego Cosmelli
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Our daily interaction with computational interfaces is plagued of situations in which we go from inexperienced users to experts through self-motivated exploration of the same task. In many of these interactions, we must learn to find our way through a sequence of decisions and actions before obtaining the desired result. For instance, when drawing cash from an ATM machine, choices are presented in a step-by-step fashion so that a specific sequence of actions must be performed in order to produce the expected outcome. But, as they become experts in the use of such interfaces, do users adopt specific search and learning strategies? Moreover, if so, can we use this information to follow the process of expertise development and, eventually, predict future actions? This would be a critical step towards building truly adaptive interfaces that can facilitate interaction at different moments of the learning curve. Furthermore, it could provide a window into potential mechanisms underlying decision-making behavior in real world scenarios. Here we tackle this question using a simple game interface that instantiates a 4-level binary decision tree (BDT) sequential decision-making task. Participants have to explore the interface and discover an underlying concept-icon mapping in order to complete the game. We develop a Hidden Markov Model (HMM)-based approach whereby a set of stereotyped, hierarchically related search behaviors act as hidden states. Using this model, we are able to track the decision-making process as participants explore, learn and develop expertise in the use of the interface. Our results show that partitioning the problem space into such stereotyped strategies is sufficient to capture a host of exploratory and learning behaviors. Moreover, using the modular architecture of stereotyped strategies as a Mixture of Experts, we are able to simultaneously ask the experts about the user's most probable future actions. We show that for those participants that learn the task, it becomes possible to predict their next decision, above chance, approximately halfway through the game. Our long-term goal is, on the basis of a better understanding of real-world decision-making processes, to inform the construction of interfaces that can establish dynamic conversations with their users in order to facilitate the development of expertise.Keywords: behavioral modeling, expertise acquisition, hidden markov models, sequential decision-making
Procedia PDF Downloads 2491958 The Modification of Convolutional Neural Network in Fin Whale Identification
Authors: Jiahao Cui
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In the past centuries, due to climate change and intense whaling, the global whale population has dramatically declined. Among the various whale species, the fin whale experienced the most drastic drop in number due to its popularity in whaling. Under this background, identifying fin whale calls could be immensely beneficial to the preservation of the species. This paper uses feature extraction to process the input audio signal, then a network based on AlexNet and three networks based on the ResNet model was constructed to classify fin whale calls. A mixture of the DOSITS database and the Watkins database was used during training. The results demonstrate that a modified ResNet network has the best performance considering precision and network complexity.Keywords: convolutional neural network, ResNet, AlexNet, fin whale preservation, feature extraction
Procedia PDF Downloads 1121957 Algae for Wastewater Treatment and CO₂ Sequestration along with Recovery of Bio-Oil and Value Added Products
Authors: P. Kiran Kumar, S. Vijaya Krishna, Kavita Verma1, V. Himabindu
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Concern about global warming and energy security has led to increased biomass utilization as an alternative feedstock to fossil fuels. Biomass is a promising feedstock since it is abundant and cheap and can be transformed into fuels and chemical products. Microalgae biofuels are likely to have a much lower impact on the environment. Microalgae cultivation using sewage with industrial flue gases is a promising concept for integrated biodiesel production, CO₂ sequestration, and nutrients recovery. Autotrophic, Mixotrophic, and Heterotrophic are the three modes of cultivation for microalgae biomass. Several mechanical and chemical processes are available for the extraction of lipids/oily components from microalgae biomass. In organic solvent extraction methods, a prior drying of biomass and recovery of the solvent is required, which are energy-intensive. Thus, the hydrothermal process overcomes the drawbacks of conventional solvent extraction methods. In the hydrothermal process, the biomass is converted into oily components by processing in a hot, pressurized water environment. In this process, in addition to the lipid fraction of microalgae, other value-added products such as proteins, carbohydrates, and nutrients can also be recovered. In the present study was (Scenedesmus quadricauda) was isolated and cultivated in autotrophic, heterotrophic, and mixotrophically using sewage wastewater and industrial flue gas in batch and continuous mode. The harvested algae biomass from S. quadricauda was used for the recovery of lipids and bio-oil. The lipids were extracted from the algal biomass using sonication as a cell disruption method followed by solvent (Hexane) extraction, and the lipid yield obtained was 8.3 wt% with Palmitic acid, Oleic acid, and Octadeonoic acid as fatty acids. The hydrothermal process was also carried out for extraction of bio-oil, and the yield obtained was 18wt%. The bio-oil compounds such as nitrogenous compounds, organic acids, and esters, phenolics, hydrocarbons, and alkanes were obtained by the hydrothermal process of algal biomass. Nutrients such as NO₃⁻ (68%) and PO₄⁻ (15%) were also recovered along with bio-oil in the hydrothermal process.Keywords: flue gas, hydrothermal process, microalgae, sewage wastewater, sonication
Procedia PDF Downloads 1331956 A Fast and Robust Protocol for Reconstruction and Re-Enactment of Historical Sites
Authors: Sanaa I. Abu Alasal, Madleen M. Esbeih, Eman R. Fayyad, Rami S. Gharaibeh, Mostafa Z. Ali, Ahmed A. Freewan, Monther M. Jamhawi
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This research proposes a novel reconstruction protocol for restoring missing surfaces and low-quality edges and shapes in photos of artifacts at historical sites. The protocol starts with the extraction of a cloud of points. This extraction process is based on four subordinate algorithms, which differ in the robustness and amount of resultant. Moreover, they use different -but complementary- accuracy to some related features and to the way they build a quality mesh. The performance of our proposed protocol is compared with other state-of-the-art algorithms and toolkits. The statistical analysis shows that our algorithm significantly outperforms its rivals in the resultant quality of its object files used to reconstruct the desired model.Keywords: meshes, point clouds, surface reconstruction protocols, 3D reconstruction
Procedia PDF Downloads 449