Search results for: Solvent extraction.

Authors: Andrew P. Hurt, George J. Vine, Samantha E. Booth, Nichola J. Coleman

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Silver-exchanged zeolites and clays are used in polymer composites to confer broad-spectrum antimicrobial properties on a range of functional materials. Tobermorite is a layer lattice mineral whose potential as a carrier for Ag+ ions in antibacterial composites has not yet been investigated. Accordingly, in this study, synthetic tobermorite was ion-exchanged with 10 wt% silver ions and the resulting material was incorporated into a composite film with chitosan. Chitosan is a biocompatible, biodegradable derivative of chitin, a polysaccharide obtained from the shells of crustaceans. The solvent-cast Ag+-exchanged tobermorite-chitosan films were found to exhibit antimicrobial action against Staphylococcus aureus, Escherichia coli and Pseudomonas aeruginosa.

Keywords: Antimicrobial, chitosan, silver, tobermorite.

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Authors: Jun Yop An, Kyoung Ryoung Park, Jung-Gyu Lee, Hyung-Seop Youn, Jung-Yeon Kang, Gil Bu Kang, Soo Hyun Eom

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MinC plays an important role in bacterial cell division system by inhibiting FtsZ assembly. However, the molecular mechanism of the action is poorly understood. E. coli MinC Nterminus domain was purified and crystallized using 1.4 M sodium citrate pH 6.5 as a precipitant. X-ray diffraction data was collected and processed to 2.3 Å from a native crystal. The crystal belonged to space group P212121, with the unit cell parameters a = 52.7, b = 54.0, c = 64.7 Å. Assuming the presence of two molecules in the asymmetric unit, the Matthews coefficient value is 1.94 Å3 Da-1, which corresponds to a solvent content of 36.5%. The overall structure of MinCN is observed as a dimer form through anti-parallel ß-strand interaction.

Keywords: MinC, Cell division, Crystallization.

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Authors: Abobaker Mohammed Qasem Farhan, Shangming Yang, Mohammed Al-Nehari

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Pneumonia is a kind of lung disease that creates congestion in the chest. Such pneumonic conditions lead to loss of life due to the severity of high congestion. Pneumonic lung disease is caused by viral pneumonia, bacterial pneumonia, or COVID-19 induced pneumonia. The early prediction and classification of such lung diseases help reduce the mortality rate. We propose the automatic Computer-Aided Diagnosis (CAD) system in this paper using the deep learning approach. The proposed CAD system takes input from raw computerized tomography (CT) scans of the patient's chest and automatically predicts disease classification. We designed the Hybrid Deep Learning Algorithm (HDLA) to improve accuracy and reduce processing requirements. The raw CT scans are pre-processed first to enhance their quality for further analysis. We then applied a hybrid model that consists of automatic feature extraction and classification. We propose the robust 2D Convolutional Neural Network (CNN) model to extract the automatic features from the pre-processed CT image. This CNN model assures feature learning with extremely effective 1D feature extraction for each input CT image. The outcome of the 2D CNN model is then normalized using the Min-Max technique. The second step of the proposed hybrid model is related to training and classification using different classifiers. The simulation outcomes using the publicly available dataset prove the robustness and efficiency of the proposed model compared to state-of-art algorithms.

Keywords: CT scans, COVID-19, deep learning, image processing, pneumonia, lung disease.

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Authors: B. Sohbi, M. Meakaff, M. Emtir, M. Elgarni

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Natural gas is defined as gas obtained from a natural underground reservoir. It generally contains a large quantity of methane along with heavier hydrocarbons such as ethane, propane, isobutene, normal butane; also in the raw state it often contains a considerable amount of non hydrocarbons, such as nitrogen and the acid gases (carbon dioxide and hydrogen sulfide). The acid gases must be removed from natural gas before use. One of the processes witch are use in the industry to remove the acid gases from natural gas is the use of alkanolamine process. In this present paper, a simulation study for an industrial gas sweetening plant has been investigated. The aim of the study is to investigate the effect of using mixing amines as solvent on the gas treatment process using the software Hysys.

Keywords: Natural gas, alkanolamine process, gas sweetening plant, simulation, mixing amines.

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Authors: Abbas Teimouri, Alireza Najafi Chermahini, Leila Ghorbanian

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An efficient and green protocol for the synthesis of α- aminonitriles derivatives by one-pot reaction of different aldehydes with amines and trimethylsilyl cyanides has been developed using natural alumina, alumina sulfuric acid (ASA), nano-γ-alumina, nanoalumina sulfuric acid (nano-ASA) under microwave irradiation and solvent-free conditions. The advantages of methods are short reaction times, high yields, milder conditions and easy work up. The catalysts can be recovered for the subsequent reactions and reused without any appreciable loss of efficiency.

Keywords: Nano-γ-alumina, nano-alumina sulfuric acid, green synthesis, microwave irradiation, α-aminonitriles derivatives.

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Authors: Moheb R. Girgis, Tarek M. Mahmoud, Tarek Abd-El-Hafeez

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This paper proposes a system to extract images from web pages and then detect the skin color regions of these images. As part of the proposed system, using BandObject control, we built a Tool bar named 'Filter Tool Bar (FTB)' by modifying the Pavel Zolnikov implementation. The Yahoo! Team provides us with the Yahoo! SDK API, which also supports image search and is really useful. In the proposed system, we introduced three new methods for extracting images from the web pages (after loading the web page by using the proposed FTB, before loading the web page physically from the localhost, and before loading the web page from any server). These methods overcome the drawback of the regular expressions method for extracting images suggested by Ilan Assayag. The second part of the proposed system is concerned with the detection of the skin color regions of the extracted images. So, we studied two famous skin color detection techniques. The first technique is based on the RGB color space and the second technique is based on YUV and YIQ color spaces. We modified the second technique to overcome the failure of detecting complex image's background by using the saturation parameter to obtain an accurate skin detection results. The performance evaluation of the efficiency of the proposed system in extracting images before and after loading the web page from localhost or any server in terms of the number of extracted images is presented. Finally, the results of comparing the two skin detection techniques in terms of the number of pixels detected are presented.

Keywords: Browser Helper Object, Color spaces, Image and URL extraction, Skin detection, Web Browser events.

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Authors: M. Seneewong-Na-Ayuttaya, T. Pongprayoon

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The nanofiber sheet of Multiwall Cabon Nanotube (MWCNTs)/Polyacylonitile (PAN) composites was fabricated from electrospun nanofiber. Firstly the surface of MWCNTs was chemically modified, comparing two different techniques consisting of admicellar polymerization and functionalization to improve the dispersion and prevent the aggregation in the PAN matrix. The modified MWCNTs were characterized by the dispersion in dimethylformamide (DMF) solvent, Laser particle size, and FTRaman. Lastly, DSC, SEM and mechanical properties of the nanofiber sheet were examined. The results show that the mechanical properties of the nanofiber sheet prepared from admicellar polymerization-modified MWCNTs were higher than those of the others.

Keywords: Multiwall carbon nanotube, admicellar polymerization, functionalization, nanofiber sheet.

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Authors: Prima Luna, Afroditi Chatzifragkou, Dimitris Charalampopoulos

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Sorghum byproducts, namely bran, stalk, and panicle are examples of lignocellulosic biomass. These raw materials contain large amounts of polysaccharides, in particular hemicelluloses, celluloses, and lignins, which if efficiently extracted, can be utilised for the development of a range of added value products with potential applications in agriculture and food packaging sectors. The aim of this study was to characterise fractions extracted from sorghum bran and stalk with regards to their physicochemical properties that could determine their applicability as food-packaging materials. A sequential alkaline extraction was applied for the isolation of cellulosic, hemicellulosic and lignin fractions from sorghum stalk and bran. Lignin content, phenolic content and antioxidant capacity were also investigated in the case of the lignin fraction. Thermal analysis using differential scanning calorimetry (DSC) and X-Ray Diffraction (XRD) revealed that the glass transition temperature (T_g) of cellulose fraction of the stalk was ~78.33 ^oC at amorphous state (~65%) and water content of ~5%. In terms of hemicellulose, the T_g value of stalk was slightly lower compared to bran at amorphous state (~54%) and had less water content (~2%). It is evident that hemicelluloses generally showed a lower thermal stability compared to cellulose, probably due to their lack of crystallinity. Additionally, bran had higher arabinose-to-xylose ratio (0.82) than the stalk, a fact that indicated its low crystallinity. Furthermore, lignin fraction had T_g value of ~93 ^oC at amorphous state (~11%). Stalk-derived lignin fraction contained more phenolic compounds (mainly consisting of p-coumaric and ferulic acid) and had higher lignin content and antioxidant capacity compared to bran-derived lignin fraction.

Keywords: Alkaline extraction, bran, cellulose, hemicellulose, lignin, sorghum, stalk.

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Authors: S.I.Nikolaeva, Yu.V. Petrov, L.Ye.Skipnikova

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It has been shown that the solution of water shortage problem in Central Asia closely connected with inclusion of atmosphere water vapour into the system of response and water resources management. Some methods of water extraction from atmosphere have been discussed.

Keywords: potable water, water resources, water problems, water scarcity.

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Authors: Hema Nair

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This paper presents a new system developed in Java® for pattern recognition and pattern summarisation in multi-band (RGB) satellite images. The system design is described in some detail. Results of testing the system to analyse and summarise patterns in SPOT MS images and LANDSAT images are also discussed.

Keywords: Pattern recognition, image analysis, feature extraction, blackboard component, linguistic summary.

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Authors: M. Feliciano, F. Maia, A. Gonçalves

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Olive oil production sector plays an important role in Portuguese economy. It had a major growth over the last decade, increasing its weight in the overall national exports. International market penetration for Mediterranean traditional products is increasingly more demanding, especially in the Northern European markets, where consumers are looking for more sustainable products. Trying to support this growing demand this study addresses olive oil production under the environmental and eco-efficiency perspectives. The analysis considers two consecutive product life cycle stages: olive trees farming; and olive oil extraction in mills. Addressing olive farming, data collection covered two different organizations: a middle-size farm (~12ha) (F1) and a large-size farm (~100ha) (F2). Results from both farms show that olive collection activities are responsible for the largest amounts of Green House Gases (GHG) emissions. In this activities, estimate for the Carbon Footprint per olive was higher in F2 (188g CO₂e/kg_olive) than in F1 (148g CO₂e/kg_olive). Considering olive oil extraction, two different mills were considered: one using a two-phase system (2P) and other with a three-phase system (3P). Results from the study of two mills show that there is a much higher use of water in 3P. Energy intensity (EI) is similar in both mills. When evaluating the GHG generated, two conditions are evaluated: a biomass neutral condition resulting on a carbon footprint higher in 3P (184g CO₂e/L_{olive oil}) than in 2P (92g CO₂e/L_{olive oil}); and a non-neutral biomass condition in which 2P increase its carbon footprint to 273g CO₂e/L_{olive oil}. When addressing the carbon footprint of possible combinations among studied subsystems, results suggest that olive harvesting is the major source for GHG.

Keywords: Carbon footprint, environmental indicators, farming subsystem, industrial subsystem, olive oil.

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Authors: Congmin Z. Xie, Terry Healy, Peter Robinson, Kevin Stewart

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An HPLC-UV analytical method was developed to determine ethylenediaminetetraacetic acid (EDTA) in dairy wastewater and surface water. The optimizing separation was achieved by reversed–phase ion-pair liquid chromatography on a C18 column using methanol as mobile phase solvent, tetrabutylammonium bromide as the ion-pair reagent in pH 3.3 formate buffer solution at a flow rate of 0.9 mL min-1 with a UV detector at 265 nm. No interference of Ca, Mg or NO3 - was detected. Method performance was evaluated in terms of linearity, repeatability and reproducibility. The method detection limit was 5 μg L-1. The contents of EDTA in dairy effluents were 72 ~ 261 μg L-1 at a large dairy site. A change of EDTA concentration was observed downstream of the dairy effluent discharge, but this was well under the predicted no effect concentration for aquatic ecosystem.

Keywords: Dairy wastewater, EDTA, HPLC, surface water.

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Authors: Azam Marjani, Saeed Shirazian

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This work deals with modeling and simulation of SO2 removal in a ceramic membrane by means of FEM. A mass transfer model was developed to predict the performance of SO2 absorption in a chemical solvent. The model was based on solving conservation equations for gas component in the membrane. Computational fluid dynamics (CFD) of mass and momentum were used to solve the model equations. The simulations aimed to obtain the distribution of gas concentration in the absorption process. The effect of the operating parameters on the efficiency of the ceramic membrane was evaluated. The modeling findings showed that the gas phase velocity has significant effect on the removal of gas whereas the liquid phase does not affect the SO2 removal significantly. It is also indicated that the main mass transfer resistance is placed in the membrane and gas phase because of high tortuosity of the ceramic membrane.

Keywords: Gas separation, finite element, ceramic, sulphur dioxide, simulation.

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Authors: D. Kliaugaitė, J. K, Staniškis

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In this study tree types of multilayer gas barrier plastic packaging films were compared using life cycle assessment as a tool for resource efficient and environmentally low-impact materials selection. The first type of multilayer packaging film (PET-AlOx/LDPE) consists of polyethylene terephthalate with barrier layer AlOx (PET-AlOx) and low density polyethylene (LDPE). The second type of polymer film (PET/PE-EVOH-PE) is made of polyethylene terephthalate (PET) and co-extrusion film PE-EVOH-PE as barrier layer. And the third one type of multilayer packaging film (PET-PVOH/LDPE) is formed from polyethylene terephthalate with barrier layer PVOH (PET-PVOH) and low density polyethylene (LDPE).

All of analyzed packaging has significant impact to resource depletion, because of raw materials extraction and energy use and production of different kind of plastics. Nevertheless the impact generated during life cycle of functional unit of II type of packaging (PET/PE-EVOH-PE) was about 25% lower than impact generated by I type (PET-AlOx/LDPE) and III type (PET-PVOH/LDPE) of packaging.

Result revealed that the contribution of different gas barrier type to the overall environmental problem of packaging is not significant. The impact are mostly generated by using energy and materials during raw material extraction and production of different plastic materials as plastic polymers material as PE, LDPE and PET, but not gas barrier materials as AlOx, PVOH and EVOH.

The LCA results could be useful in different decision-making processes, for selecting resource efficient and environmentally low-impact materials.

Keywords: Polymer packaging, life cycle assessment, resource efficiency.

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Authors: Shagufta Tabassum, V. P. Pawar

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The study of static dielectric properties in a binary mixture of 1,2 dichloroethane (DE) and n,n dimethylformamide (DMF) polar liquids has been carried out in the frequency range of 10 MHz to 30 GHz for 11 different concentration using time domain reflectometry technique at 10ºC temperature. The dielectric relaxation study of solute-solvent mixture at microwave frequencies gives information regarding the creation of monomers and multimers as well as interaction between the molecules of the binary mixture. The least squares fit method is used to determine the values of dielectric parameters such as static dielectric constant (ε₀), dielectric constant at high frequency (ε_∞) and relaxation time (τ).

Keywords: Excess parameters, relaxation time, static dielectric constant, time domain reflectometry.

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Authors: Ravneet Kaur, Joydeep Acharya, Sudhanshu Gaur

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Artificial Intelligence (AI) has the potential to transform manufacturing by improving shop floor processes such as production, maintenance and quality. However, industrial datasets are notoriously difficult to extract in a real-time, streaming fashion thus, negating potential AI benefits. The main example is some specialized industrial controllers that are operated by custom software which complicates the process of connecting them to an Information Technology (IT) based data acquisition network. Security concerns may also limit direct physical access to these controllers for data acquisition. To connect the Operational Technology (OT) data stored in these controllers to an AI application in a secure, reliable and available way, we propose a novel Industrial IoT (IIoT) solution in this paper. In this solution, we demonstrate how video cameras can be installed in a factory shop floor to continuously obtain images of the controller HMIs. We propose image pre-processing to segment the HMI into regions of streaming data and regions of fixed meta-data. We then evaluate the performance of multiple Optical Character Recognition (OCR) technologies such as Tesseract and Google vision to recognize the streaming data and test it for typical factory HMIs and realistic lighting conditions. Finally, we use the meta-data to match the OCR output with the temporal, domain-dependent context of the data to improve the accuracy of the output. Our IIoT solution enables reliable and efficient data extraction which will improve the performance of subsequent AI applications.

Keywords: Human machine interface, industrial internet of things, internet of things, optical character recognition, video analytic.

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Authors: K. Mohammed, M. Agarwal, J. Mewman, Y. Ren

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An optimum technic has been developed for extracting volatile organic compounds which contribute to the aroma of lime fruit (Citrus aurantifolia). The volatile organic compounds of healthy and infested lime fruit with California red scale Aonidiella aurantii were characterized using headspace solid phase microextraction (HS-SPME) combined with gas chromatography (GC) coupled flame ionization detection (FID) and gas chromatography with mass spectrometry (GC-MS) as a very simple, efficient and nondestructive extraction method. A three-phase 50/30 μm PDV/DVB/CAR fibre was used for the extraction process. The optimal sealing and fibre exposure time for volatiles reaching equilibrium from whole lime fruit in the headspace of the chamber was 16 and 4 hours respectively. 5 min was selected as desorption time of the three-phase fibre. Herbivorous activity induces indirect plant defenses, as the emission of herbivorous-induced plant volatiles (HIPVs), which could be used by natural enemies for host location. GC-MS analysis showed qualitative differences among volatiles emitted by infested and healthy lime fruit. The GC-MS analysis allowed the initial identification of 18 compounds, with similarities higher than 85%, in accordance with the NIST mass spectral library. One of these were increased by A. aurantii infestation, D-limonene, and three were decreased, Undecane, α-Farnesene and 7-epi-α-selinene. From an applied point of view, the application of the above-mentioned VOCs may help boost the efficiency of biocontrol programs and natural enemies’ production techniques.

Keywords: Lime fruit, Citrus aurantifolia, California red scale, Aonidiella aurantii, VOCs, HS-SPME/GC-FID-MS.

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Authors: J. Y. Tan, L. C. Lum, M. G. Lee, S. Mansouri, K. Hapgood, X. D. Chen, M. W. Woo

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Folic acid (FA) is known to be an important supplement to prevent neural tube defect (NTD) in pregnant women. Similar to some commercial formulations, sodium bicarbonate solution is used as a solvent for FA. This work uses the antisolvent vapour precipitation (AVP), incorporating ethanol vapour as the convective drying medium in place of air to produce branch-like micro-structure FA particles. Interestingly, the dissolution rate of the resultant particle is 2-3 times better than the particle produce from conventional air drying due to the higher surface area of particles produced. The higher dissolution rate could possibly improve the delivery and absorption of FA in human body. This application could potentially be extended to other commercial products, particularly in less soluble drugs to improve its solubility.

Keywords: Absorption, antisolvent vapour precipitation, dissolution rate, folic acid.

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Authors: Amit Kumar Bhandary, Prithviraj Gupta, Siddhartha Mukherjee, Mahua Ghosh Chaudhuri, Rajib Dey

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Chromite ores are primarily used for extraction of chromium, which is an expensive metal. For low grade chromite ores (containing less than 40% Cr₂O₃), the chromium extraction is not usually economically viable. India possesses huge quantities of low grade chromite reserves. This deposit can be utilized after proper physical beneficiation. Magnetic separation techniques may be useful after reduction for the beneficiation of low grade chromite ore. The sample collected from the sukinda mines is characterized by XRD which shows predominant phases like maghemite, chromite, silica, magnesia and alumina. The raw ore is crushed and ground to below 75 micrometer size. The microstructure of the ore shows that the chromite grains surrounded by a silicate matrix and porosity observed the exposed side of the chromite ore. However, this ore may be utilized in refractory applications. Chromite ores contain Cr₂O₃, FeO, Al₂O₃ and other oxides like Fe-Cr, Mg-Cr have a high tendency to form spinel compounds, which usually show high refractoriness. Initially, the low grade chromite ore (containing 34.8% Cr₂O₃) was reduced at 1200 ⁰C for 80 minutes with 30% coke fines by weight, before being subjected to magnetic separation. The reduction by coke leads to conversion of higher state of iron oxides converted to lower state of iron oxides. The pre-reduced samples are then characterized by XRD. The magnetically inert mass was then reacted with 20% MgO by weight at 1450 ⁰C for 2 hours. The resultant product was then tested for various refractoriness parameters like apparent porosity, slag resistance etc. The results were satisfactory, indicating that the resultant spinel compounds are suitable for refractory applications for elevated temperature processes.

Keywords: Apparent porosity, beneficiation, low grade chromite, refractory, spinel compounds, slag resistance.

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Authors: H. Benjamin Fredrick David, R. Balasubramanian, A. Anbarasa Pandian

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Image retrieval is the most interesting technique which is being used today in our digital world. CBIR, commonly expanded as Content Based Image Retrieval is an image processing technique which identifies the relevant images and retrieves them based on the patterns that are extracted from the digital images. In this paper, two research works have been presented using CBIR. The first work provides an automated and interactive approach to the analysis of CBIR techniques. CBIR works on the principle of supervised machine learning which involves feature selection followed by training and testing phase applied on a classifier in order to perform prediction. By using feature extraction, the image transforms such as Contourlet, Ridgelet and Shearlet could be utilized to retrieve the texture features from the images. The features extracted are used to train and build a classifier using the classification algorithms such as Naïve Bayes, K-Nearest Neighbour and Multi-class Support Vector Machine. Further the testing phase involves prediction which predicts the new input image using the trained classifier and label them from one of the four classes namely 1- Normal brain, 2- Benign tumour, 3- Malignant tumour and 4- Severe tumour. The second research work includes developing a tool which is used for tumour stage identification using the best feature extraction and classifier identified from the first work. Finally, the tool will be used to predict tumour stage and provide suggestions based on the stage of tumour identified by the system. This paper presents these two approaches which is a contribution to the medical field for giving better retrieval performance and for tumour stages identification.

Keywords: Brain tumour detection, content based image retrieval, classification of tumours, image retrieval.

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Authors: M. R. Homaeinezhad, E. Tavakkoli, M. Habibi, S. A. Atyabi, A. Ghaffari

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This paper describes a new supervised fusion (hybrid) electrocardiogram (ECG) classification solution consisting of a new QRS complex geometrical feature extraction as well as a new version of the learning vector quantization (LVQ) classification algorithm aimed for overcoming the stability-plasticity dilemma. Toward this objective, after detection and delineation of the major events of ECG signal via an appropriate algorithm, each QRS region and also its corresponding discrete wavelet transform (DWT) are supposed as virtual images and each of them is divided into eight polar sectors. Then, the curve length of each excerpted segment is calculated and is used as the element of the feature space. To increase the robustness of the proposed classification algorithm versus noise, artifacts and arrhythmic outliers, a fusion structure consisting of five different classifiers namely as Support Vector Machine (SVM), Modified Learning Vector Quantization (MLVQ) and three Multi Layer Perceptron-Back Propagation (MLP–BP) neural networks with different topologies were designed and implemented. The new proposed algorithm was applied to all 48 MIT–BIH Arrhythmia Database records (within–record analysis) and the discrimination power of the classifier in isolation of different beat types of each record was assessed and as the result, the average accuracy value Acc=98.51% was obtained. Also, the proposed method was applied to 6 number of arrhythmias (Normal, LBBB, RBBB, PVC, APB, PB) belonging to 20 different records of the aforementioned database (between– record analysis) and the average value of Acc=95.6% was achieved. To evaluate performance quality of the new proposed hybrid learning machine, the obtained results were compared with similar peer– reviewed studies in this area.

Keywords: Feature Extraction, Curve Length Method, SupportVector Machine, Learning Vector Quantization, Multi Layer Perceptron, Fusion (Hybrid) Classification, Arrhythmia Classification, Supervised Learning Machine.

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Authors: Elia Favarelli, Enrico Testi, Andrea Giorgetti

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Autonomous structural health monitoring (SHM) of many structures and bridges became a topic of paramount importance for maintenance purposes and safety reasons. This paper proposes a set of machine learning (ML) tools to perform automatic feature selection and detection of anomalies in a bridge from vibrational data and compare different feature extraction schemes to increase the accuracy and reduce the amount of data collected. As a case study, the Z-24 bridge is considered because of the extensive database of accelerometric data in both standard and damaged conditions. The proposed framework starts from the first four fundamental frequencies extracted through operational modal analysis (OMA) and clustering, followed by time-domain filtering (tracking). The fundamental frequencies extracted are then fed to a dimensionality reduction block implemented through two different approaches: feature selection (intelligent multiplexer) that tries to estimate the most reliable frequencies based on the evaluation of some statistical features (i.e., entropy, variance, kurtosis), and feature extraction (auto-associative neural network (ANN)) that combine the fundamental frequencies to extract new damage sensitive features in a low dimensional feature space. Finally, one-class classification (OCC) algorithms perform anomaly detection, trained with standard condition points, and tested with normal and anomaly ones. In particular, principal component analysis (PCA), kernel principal component analysis (KPCA), and autoassociative neural network (ANN) are presented and their performance are compared. It is also shown that, by evaluating the correct features, the anomaly can be detected with accuracy and an F1 score greater than 95%.

Keywords: Anomaly detection, dimensionality reduction, frequencies selection, modal analysis, neural network, structural health monitoring, vibration measurement.

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Authors: Tayeb Aissaoui, Inas M. AlNashef

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In recent years, green solvents named deep eutectic solvents (DESs) have been found to possess significant properties and to be applicable in several technologies. Choline chloride (ChCl) mixed with urea at a ratio of 1:2 and 80 °C was the first discovered DES. In this article, chemical structure and combination mechanism of ChCl: urea based DES were investigated. Moreover, the implementation of this DES in water removal from natural gas was reported. Dehydration of natural gas by ChCl:urea shows significant absorption efficiency compared to triethylene glycol. All above operations were retrieved from COSMOthermX software. This article confirms the potential application of DESs in gas industry.

Keywords: COSMO-RS, deep eutectic solvents, dehydration, natural gas, structure, organic salt.

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Authors: V. Veeraprathap, G. S. Harish, G. Narendra Kumar

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Uncontrolled growth of abnormal cells in the lung in the form of tumor can be either benign (non-cancerous) or malignant (cancerous). Patients with Lung Cancer (LC) have an average of five years life span expectancy provided diagnosis, detection and prediction, which reduces many treatment options to risk of invasive surgery increasing survival rate. Computed Tomography (CT), Positron Emission Tomography (PET), and Magnetic Resonance Imaging (MRI) for earlier detection of cancer are common. Gaussian filter along with median filter used for smoothing and noise removal, Histogram Equalization (HE) for image enhancement gives the best results without inviting further opinions. Lung cavities are extracted and the background portion other than two lung cavities is completely removed with right and left lungs segmented separately. Region properties measurements area, perimeter, diameter, centroid and eccentricity measured for the tumor segmented image, while texture is characterized by Gray-Level Co-occurrence Matrix (GLCM) functions, feature extraction provides Region of Interest (ROI) given as input to classifier. Two levels of classifications, K-Nearest Neighbor (KNN) is used for determining patient condition as normal or abnormal, while Artificial Neural Networks (ANN) is used for identifying the cancer stage is employed. Discrete Wavelet Transform (DWT) algorithm is used for the main feature extraction leading to best efficiency. The developed technology finds encouraging results for real time information and on line detection for future research.

Keywords: ANN, DWT, GLCM, KNN, ROI, artificial neural networks, discrete wavelet transform, gray-level co-occurrence matrix, k-nearest neighbor, region of interest.

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Authors: James E. Ponder

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The requirement for consistency in physics can sometimes offer a common ground between disciplines such that their fundamental equations share a common parameter set and mathematical method for equation extraction. The parameter set shared by Relativity and Quantum Wave Mechanics enables an analysis which will be seen to be very straightforward, primarily classical in nature using linear algebra concepts, yet deriving a theoretical estimate of the value of the Gravitational Constant along with dependencies never before known.

Keywords: Gravitational Constant, Physical Consistency, Quantum Mechanics, Relativity.

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Authors: Richard A. Wasniowski

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A wide spectrum of systems require reliable personal recognition schemes to either confirm or determine the identity of an individual person. This paper considers multimodal biometric system and their applicability to access control, authentication and security applications. Strategies for feature extraction and sensor fusion are considered and contrasted. Issues related to performance assessment, deployment and standardization are discussed. Finally future directions of biometric systems development are discussed.

Keywords: Multimodal, biometric, recognition, fusion.

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Authors: Asım Egitmen, Aysen Demir, Burcu Darendeli, Fatma Ulusal, Bilgehan Güzel

Abstract:

Synthesizing supercritical carbon dioxide (scCO₂) soluble precursors would be helpful for many processes of material syntheses based on scCO₂. Ligand (amphi-(1Z, 2Z)-N-(2-fluoro-3-(trifluoromethyl) phenyl)-N'-hydroxy-2-(hydroxyimino) were synthesized from chloro glyoxime and flourus aniline and Pd(II) complex (precursor) prepared. For scCO₂ deposition method, organometallic precursor was dissolved in scCO₂ and impregnated onto the SBA-15 at 90 °C and 3000 psi. Then the organometallic precursor was reduced with H₂ in the CO₂ mixture (150 psi H₂ + 2850 psi CO₂). Pd deposited support material was characterized by ICP-OES, XRD, FE-SEM, TEM and EDX analyses. The Pd loading of the prepared catalyst, measured by ICP-OES showed a value of about 1.64% mol/g Pd of catalyst. Average particle size was found 5.3 nm. The catalytic activity of prepared catalyst was investigated over Suzuki-Miyaura C-C coupling reaction in different solvent with K₂CO₃ at 50 ^oC. The conversion ratio was determined by gas chromatography.

Keywords: Nanoparticle, nanotube, oximes, precursor, supercritical CO2.

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Authors: Er. Satwinder Singh, Dr. K.S. Kahlon, Rakesh Kumar, Er. Gurjeet Singh

Abstract:

The most reliable and accurate description of the actual behavior of a software system is its source code. However, not all questions about the system can be answered directly by resorting to this repository of information. What the reverse engineering methodology aims at is the extraction of abstract, goal-oriented “views" of the system, able to summarize relevant properties of the computation performed by the program. While concentrating on reverse engineering we had modeled the C++ files by designing the translator.

Keywords: Translator, Modeling, UML, DYNO, ISVis, TED.

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Authors: Homayon Ahmad Panahi, Hossein Sid Kalal, Atyeh Rahimi

Abstract:

A high performance thin layer chromatography system (HPTLC) for the separation of vitamin B2 and B12 has been developed. The separation was successfully using a solvent system of methanol, water, ammonia 7.3.1 (V/V) as mobile phase on HPTLC plates impregnated with boric acid. The effect of other mobile phases on the separation of vitamins was also examined. The method is based on different behavior of investigated compounds in impregnated TLC plates with different amount of boric acid. The Rf values of vitamin B2 and B12 are considered on non impregnated and impregnated silica gel HPTLC plate with boric acid. The effect of boric acid in the mobile phase and on HPTLC plates on the RF values of the vitamins has also been studied.

Keywords: High performance thin layer chromatography, HPTLC, Vitamin B2, Vitamin B12, Separation.

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Authors: Mu-Jen Young, Cheng-Yen Wu, Wen-Yuan Hsieh

Abstract:

Iron oxide nanoparticle was synthesized by reactive-precipitation method followed by high speed centrifuge and phase transfer in order to stabilized nanoparticles in the solvent. Particle size of SPIO was 8.2 nm by SEM, and the hydraulic radius was 17.5 nm by dynamic light scattering method. Coercivity and saturated magnetism were determined by VSM (vibrating sample magnetometer), coercivity of nanoparticle was lower than 10 Hc, and the saturated magnetism was higher than 65 emu/g. Stabilized SPIO was then transferred to aqueous phase by reacted with excess amount of poly (ethylene glycol) (PEG) silane. After filtration and dialysis, the SPIO T2 contrast agent was ready to use. The hydraulic radius of final product was about 70~100 nm, the relaxation rates R2 (1/T2) measured by magnetic resonance imaging (MRI) was larger than 200(sec-1).

Keywords: Contrast Agent, Iron Oxide Nanoparticle, Magnetic Resonance Imaging, Nanoparticle Stabilization

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