Search results for: olive oil extraction
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 2131

Search results for: olive oil extraction

1261 Cellular Traffic Prediction through Multi-Layer Hybrid Network

Authors: Supriya H. S., Chandrakala B. M.

Abstract:

Deep learning based models have been recently successful adoption for network traffic prediction. However, training a deep learning model for various prediction tasks is considered one of the critical tasks due to various reasons. This research work develops Multi-Layer Hybrid Network (MLHN) for network traffic prediction and analysis; MLHN comprises the three distinctive networks for handling the different inputs for custom feature extraction. Furthermore, an optimized and efficient parameter-tuning algorithm is introduced to enhance parameter learning. MLHN is evaluated considering the “Big Data Challenge” dataset considering the Mean Absolute Error, Root Mean Square Error and R^2as metrics; furthermore, MLHN efficiency is proved through comparison with a state-of-art approach.

Keywords: MLHN, network traffic prediction

Procedia PDF Downloads 90
1260 SUSTAINEXT–Validating a Zero-Waste: Dynamic, Multivalorization Route Biorefinery for Plant Extracts

Authors: Adriana Diaz Triana, Wolfgang Wimmer, Sebastian Glaser, Rainer Pamminger

Abstract:

SUSTAINEXT is a pioneer initiative in Extremadura, Spain under the EU Biobased industries. SUSTANEXT will scale-up and validate an industrial facility to produce botanical extracts, based on three key pillars. First, the whole valorization of bio-based feedstocks with a zero-waste and zero-emissions ambition. SUSTAINEXT will be deployed with six feedstocks. Three medicinal and aromatic plants (Rosemary, Chamomile, and Lemon verbena) will be locally sourced from disused tobacco fields with installed agri-voltaics; and three underexploited agro-industrial side streams will be further valorized (Olive, artichoke-cardoon, and pomegranate). Second, a dynamic, analytical biorefinery (DYANA) will isolate polyphenol and tri-terpenes from feedstocks in a disruptive and circular way. SUSTAINEXT explores 12 valorization routes (VRs) to extract and purify 46 functional ingredients, of which 13 are new in the market and 12 are newly produced in Europe. Third, the integrated and versatile value chain engages all actors, from feedstocks suppliers to extract users in the industries of food, animal feed, nutraceuticals, cosmetics, chemical performance, soil enhancers and fertilizers. This paper addresses SUTAINEXT activities towards zero impacts and full regulatory compliance. A comprehensive Life Cycle Thinking approach is proposed, with four complementary assessments running iteratively along the project duration (4,5 years). These are the Life Cycle Cost (LCCA), Life Cycle (LCA), Social Life Cycle (S-LCA) and Circularity (CA) assessments. The LCA will help evaluate the feedstock suitability parameters and intrinsic characteristics that quantify the feedstock´s grade for a determined use, and the feedstock´s suitability index for a specific VR. The LCA will also study the emissions, land use change, energy generation and consumption, and other environmental aspects and impacts of the VRs, to identify the most resource efficient and less impactful distribution of products from the circular biorefinery model used in SUSTAINEXT. Challenges to complete the LCA include the definition of the system boundaries, carrying out a robust inventory, and the proper allocation of impacts to the different VRs.

Keywords: biorefinery, botanical extracts, life cycle assessment, valorization routes.

Procedia PDF Downloads 24
1259 Numerical Study on the Effect of Spudcan Penetration on the Jacket Platform

Authors: Xiangming Ge, Bing Pan, Wei He, Hao Chen, Yong Zhou, Jiayao Wu, Weijiang Chu

Abstract:

How the extraction and penetration of spudcan affect the performance of the adjacent pile foundation supporting the jacket platform was studied in the program FLAC3D depending on a wind farm project in Bohai sea. The simulations were conducted at the end of the spudcan penetration, which induced a pockmark in the seabed. The effects of the distance between the pile foundation and the pockmark were studied. The displacement at the mudline arose when the pockmark was closer. The bearing capacity of this jacket platform with deep pile foundations has been less influenced by the process of spudcan penetration, which can induce severe stresses on the pile foundation. The induced rotation was also satisfied with the rotation-controlling criteria.

Keywords: offshore foundation, pile-soil interaction, spudcan penetration, FLAC3D

Procedia PDF Downloads 216
1258 Antioxidant Extraction from Indonesian Crude Palm Oil and Its Antioxidation Activity

Authors: Supriyono, Sumardiyono, Puti Pertiwi

Abstract:

Crude palm oil (CPO) is a vegetable oil that came from a palm tree bunch. Palm oil tree was known as highest vegetable oil yield. It was grown across Equatorial County, especially in Malaysia and Indonesia. The greenish red color on CPO was came from carotenoid antioxidant, which could be extracted and use separately as functional food and other purposes as antioxidant source. Another antioxidant that also found in CPO is tocopherol. The aim of the research work is to find antioxidant activity on CPO comparing to the synthetic antioxidant that available in a market. On this research work, antioxidant was extracted by using a mixture of acetone and n. hexane, while activity of the antioxidant extract was determine by DPPH method. The extracted matter was shown that their antioxidant activity was about 45% compare to pure tocopherol and beta carotene.

Keywords: antioxidant, , beta carotene, , crude palm oil, , DPPH, , tocopherol

Procedia PDF Downloads 293
1257 Role of Selenite and Selenate Uptake by Maize Plants in Chlorophyll A and B Content

Authors: F. Garousi, S. Veres, É. Bódi, S. Várallyay, B. Kovács

Abstract:

Extracting and determining chlorophyll pigments (chlorophyll a and b) in green leaves are the procedures based on the solvent extraction of pigments in samples using N,N-dimethylformamide as the extractant. In this study, two species of soluble inorganic selenium forms, selenite (Se( IV)) and selenate (Se( VI)) at different concentrations were investigated on maize plants that were growing in nutrient solutions during 2 weeks and at the end of the experiment, amounts of chlorophyll a and b for first and second leaves of maize were measured. In accordance with the results we observed that our regarded Se concentrations in both forms of Se( IV) and Se( VI) were not effective on maize plants’ chlorophyll a and b significantly although high level of 3 mg.kg-1 Se( IV) had negative affect on growth of the samples that had been treated by it but about Se( VI) samples we did not observe this state and our different considered Se( VI) concentrations were not toxic for maize plants.

Keywords: maize, sodium selenate, sodium selenite, chlorophyll a and b

Procedia PDF Downloads 403
1256 Hydrometallurgical Production of Nickel Ores from Field Bugetkol

Authors: A. T. Zhakiyenova, E. E. Zhatkanbaev, Zh. K. Zhatkanbaeva

Abstract:

Nickel plays an important role in mechanical engineering and creation of military equipment; practically all steel are alloyed by nickel and other metals for receiving more durable, heat-resistant, corrosion-resistant steel and cast iron. There are many ways of processing of nickel in the world. Generally, it is igneous metallurgy methods. In this article, the review of majority existing ways of technologies of processing silicate nickel - cobalt ores is considered. Leaching of ores of a field Bugetkol is investigated by solution of sulfuric acid. We defined a specific consumption of sulfuric acid in relation to the mass of ore and to the mass of metal.

Keywords: cobalt, degree of extraction, hydrometallurgy, igneous metallurgy, leaching, matte, nickel

Procedia PDF Downloads 390
1255 Text Data Preprocessing Library: Bilingual Approach

Authors: Kabil Boukhari

Abstract:

In the context of information retrieval, the selection of the most relevant words is a very important step. In fact, the text cleaning allows keeping only the most representative words for a better use. In this paper, we propose a library for the purpose text preprocessing within an implemented application to facilitate this task. This study has two purposes. The first, is to present the related work of the various steps involved in text preprocessing, presenting the segmentation, stemming and lemmatization algorithms that could be efficient in the rest of study. The second, is to implement a developed tool for text preprocessing in French and English. This library accepts unstructured text as input and provides the preprocessed text as output, based on a set of rules and on a base of stop words for both languages. The proposed library has been made on different corpora and gave an interesting result.

Keywords: text preprocessing, segmentation, knowledge extraction, normalization, text generation, information retrieval

Procedia PDF Downloads 95
1254 Comparative Analysis between Corn and Ramon (Brosimum alicastrum) Starches to Be Used as Sustainable Bio-Based Plastics

Authors: C. R. Ríos-Soberanis, V. M. Moo-Huchin, R. J. Estrada-Leon, E. Perez-Pacheco

Abstract:

Polymers from renewable resources have attracted an increasing amount of attention over the last two decades, predominantly due to two major reasons: firstly environmental concerns, and secondly the realization that our petroleum resources are finite. Finding new uses for agricultural commodities is also an important area of research. Therefore, it is crucial to get new sources of natural materials that can be used in different applications. Ramon tree (Brosimum alicastrum) is a tropical plant that grows freely in Yucatan countryside. This paper focuses on the seeds recollection, processing and starch extraction and characterization in order to find out about its suitability as biomaterial. Results demonstrated that it has a high content of qualities to be used not only as comestible but also as an important component in polymeric blends.

Keywords: biomaterials, characterization techniques, natural resource, starch

Procedia PDF Downloads 327
1253 Visualization-Based Feature Extraction for Classification in Real-Time Interaction

Authors: Ágoston Nagy

Abstract:

This paper introduces a method of using unsupervised machine learning to visualize the feature space of a dataset in 2D, in order to find most characteristic segments in the set. After dimension reduction, users can select clusters by manual drawing. Selected clusters are recorded into a data model that is used for later predictions, based on realtime data. Predictions are made with supervised learning, using Gesture Recognition Toolkit. The paper introduces two example applications: a semantic audio organizer for analyzing incoming sounds, and a gesture database organizer where gestural data (recorded by a Leap motion) is visualized for further manipulation.

Keywords: gesture recognition, machine learning, real-time interaction, visualization

Procedia PDF Downloads 355
1252 On Musical Information Geometry with Applications to Sonified Image Analysis

Authors: Shannon Steinmetz, Ellen Gethner

Abstract:

In this paper, a theoretical foundation is developed for patterned segmentation of audio using the geometry of music and statistical manifold. We demonstrate image content clustering using conic space sonification. The algorithm takes a geodesic curve as a model estimator of the three-parameter Gamma distribution. The random variable is parameterized by musical centricity and centric velocity. Model parameters predict audio segmentation in the form of duration and frame count based on the likelihood of musical geometry transition. We provide an example using a database of randomly selected images, resulting in statistically significant clusters of similar image content.

Keywords: sonification, musical information geometry, image, content extraction, automated quantification, audio segmentation, pattern recognition

Procedia PDF Downloads 242
1251 Lifting Wavelet Transform and Singular Values Decomposition for Secure Image Watermarking

Authors: Siraa Ben Ftima, Mourad Talbi, Tahar Ezzedine

Abstract:

In this paper, we present a technique of secure watermarking of grayscale and color images. This technique consists in applying the Singular Value Decomposition (SVD) in LWT (Lifting Wavelet Transform) domain in order to insert the watermark image (grayscale) in the host image (grayscale or color image). It also uses signature in the embedding and extraction steps. The technique is applied on a number of grayscale and color images. The performance of this technique is proved by the PSNR (Pick Signal to Noise Ratio), the MSE (Mean Square Error) and the SSIM (structural similarity) computations.

Keywords: lifting wavelet transform (LWT), sub-space vectorial decomposition, secure, image watermarking, watermark

Procedia PDF Downloads 278
1250 Secured Transmission and Reserving Space in Images Before Encryption to Embed Data

Authors: G. R. Navaneesh, E. Nagarajan, C. H. Rajam Raju

Abstract:

Nowadays the multimedia data are used to store some secure information. All previous methods allocate a space in image for data embedding purpose after encryption. In this paper, we propose a novel method by reserving space in image with a boundary surrounded before encryption with a traditional RDH algorithm, which makes it easy for the data hider to reversibly embed data in the encrypted images. The proposed method can achieve real time performance, that is, data extraction and image recovery are free of any error. A secure transmission process is also discussed in this paper, which improves the efficiency by ten times compared to other processes as discussed.

Keywords: secure communication, reserving room before encryption, least significant bits, image encryption, reversible data hiding

Procedia PDF Downloads 413
1249 Power MOSFET Models Including Quasi-Saturation Effect

Authors: Abdelghafour Galadi

Abstract:

In this paper, accurate power MOSFET models including quasi-saturation effect are presented. These models have no internal node voltages determined by the circuit simulator and use one JFET or one depletion mode MOSFET transistors controlled by an “effective” gate voltage taking into account the quasi-saturation effect. The proposed models achieve accurate simulation results with an average error percentage less than 9%, which is an improvement of 21 percentage points compared to the commonly used standard power MOSFET model. In addition, the models can be integrated in any available commercial circuit simulators by using their analytical equations. A description of the models will be provided along with the parameter extraction procedure.

Keywords: power MOSFET, drift layer, quasi-saturation effect, SPICE model

Procedia PDF Downloads 198
1248 Removal of Metals from Heavy Oil

Authors: Ali Noorian

Abstract:

Crude oil contains various compounds of hydrocarbons but low concentrations of inorganic compounds or metals. Vanadium and Nickel are the most common metals in crude oil. These metals usually exist in solution in the oil and residual fuel oil in the refining process is condensed. Deleterious effects of metals in petroleum have been known for some time. These metals do not only contaminate the product but also cause intoxication and loss of catalyst and corrosion to equipment. In this study, removal of heavy metals and petroleum residues were investigated. These methods include physical, chemical and biological treatment processes. For example, processes such as solvent extraction and hydro-catalytic and catalytic methods are effective and practical methods, but typically often have high costs and cause environmental pollution. Furthermore, biological methods that do not cause environmental pollution have been discussed in recent years, but these methods have not yet been industrialized.

Keywords: removal, metal, heavy oil, nickel, vanadium

Procedia PDF Downloads 380
1247 Application of Fuzzy Approach to the Vibration Fault Diagnosis

Authors: Jalel Khelil

Abstract:

In order to improve reliability of Gas Turbine machine especially its generator equipment, a fault diagnosis system based on fuzzy approach is proposed. Three various methods namely K-NN (K-nearest neighbors), F-KNN (Fuzzy K-nearest neighbors) and FNM (Fuzzy nearest mean) are adopted to provide the measurement of relative strength of vibration defaults. Both applications consist of two major steps: Feature extraction and default classification. 09 statistical features are extracted from vibration signals. 03 different classes are used in this study which describes vibrations condition: Normal, unbalance defect, and misalignment defect. The use of the fuzzy approaches and the classification results are discussed. Results show that these approaches yield high successful rates of vibration default classification.

Keywords: fault diagnosis, fuzzy classification k-nearest neighbor, vibration

Procedia PDF Downloads 468
1246 Improved Pattern Matching Applied to Surface Mounting Devices Components Localization on Automated Optical Inspection

Authors: Pedro M. A. Vitoriano, Tito. G. Amaral

Abstract:

Automated Optical Inspection (AOI) Systems are commonly used on Printed Circuit Boards (PCB) manufacturing. The use of this technology has been proven as highly efficient for process improvements and quality achievements. The correct extraction of the component for posterior analysis is a critical step of the AOI process. Nowadays, the Pattern Matching Algorithm is commonly used, although this algorithm requires extensive calculations and is time consuming. This paper will present an improved algorithm for the component localization process, with the capability of implementation in a parallel execution system.

Keywords: AOI, automated optical inspection, SMD, surface mounting devices, pattern matching, parallel execution

Procedia PDF Downloads 300
1245 Correlation Matrix for Automatic Identification of Meal-Taking Activity

Authors: Ghazi Bouaziz, Abderrahim Derouiche, Damien Brulin, Hélène Pigot, Eric Campo

Abstract:

Automatic ADL classification is a crucial part of ambient assisted living technologies. It allows to monitor the daily life of the elderly and to detect any changes in their behavior that could be related to health problem. But detection of ADLs is a challenge, especially because each person has his/her own rhythm for performing them. Therefore, we used a correlation matrix to extract custom rules that enable to detect ADLs, including eating activity. Data collected from 3 different individuals between 35 and 105 days allows the extraction of personalized eating patterns. The comparison of the results of the process of eating activity extracted from the correlation matrices with the declarative data collected during the survey shows an accuracy of 90%.

Keywords: elderly monitoring, ADL identification, matrix correlation, meal-taking activity

Procedia PDF Downloads 95
1244 A Genetic-Neural-Network Modeling Approach for Self-Heating in GaN High Electron Mobility Transistors

Authors: Anwar Jarndal

Abstract:

In this paper, a genetic-neural-network (GNN) based large-signal model for GaN HEMTs is presented along with its parameters extraction procedure. The model is easy to construct and implement in CAD software and requires only DC and S-parameter measurements. An improved decomposition technique is used to model self-heating effect. Two GNN models are constructed to simulate isothermal drain current and power dissipation, respectively. The two model are then composed to simulate the drain current. The modeling procedure was applied to a packaged GaN-on-Si HEMT and the developed model is validated by comparing its large-signal simulation with measured data. A very good agreement between the simulation and measurement is obtained.

Keywords: GaN HEMT, computer-aided design and modeling, neural networks, genetic optimization

Procedia PDF Downloads 384
1243 Effect of Signal Acquisition Procedure on Imagined Speech Classification Accuracy

Authors: M.R Asghari Bejestani, Gh. R. Mohammad Khani, V.R. Nafisi

Abstract:

Imagined speech recognition is one of the most interesting approaches to BCI development and a lot of works have been done in this area. Many different experiments have been designed and hundreds of combinations of feature extraction methods and classifiers have been examined. Reported classification accuracies range from the chance level to more than 90%. Based on non-stationary nature of brain signals, we have introduced 3 classification modes according to time difference in inter and intra-class samples. The modes can explain the diversity of reported results and predict the range of expected classification accuracies from the brain signal accusation procedure. In this paper, a few samples are illustrated by inspecting results of some previous works.

Keywords: brain computer interface, silent talk, imagined speech, classification, signal processing

Procedia PDF Downloads 155
1242 Effectiveness of a Healthy Lifestyle Combined with Abdominal Massage on Treating Infertility Due to Endometriosis and Adhesions in the Fallopian Tubes

Authors: Flora Tajiki

Abstract:

Undoubtedly, the desire to experience the beauty of motherhood is a dream for every woman, and delays in achieving this can have significant psychological consequences. Endometriosis, which is the presence of endometrial tissue in organs other than the uterus, can cause infertility through adhesion and inflammation. The fallopian tubes play a crucial role in transferring the egg to the uterus; if adhesions are present, the chances of natural pregnancy decrease, while the likelihood of ectopic pregnancy and miscarriage increases. In cases of mild adhesions observed during hysterosalpingography or laparoscopy, the tubes may open, but in severe adhesions, this is usually not possible. The aim of this study is to assess the effectiveness of a healthy lifestyle combined with massage of the uterine and ovarian areas in relieving adhesions in the fallopian tubes and treating the complications of endometriosis. This case study focuses on a 33-year-old woman, who married at 20, and experienced a miscarriage five years ago that required curettage. Following this, a hysterosalpingography revealed blockages in both fallopian tubes. A laparoscopic examination also indicated endometriosis and specialists in infertility ruled out the possibility of natural pregnancy. Three years ago, she underwent an unsuccessful IVF procedure. Two years ago, she began a lifestyle modification program that included improving sleep patterns, eliminating sugar and preservatives, avoiding red meat and gluten, eating a balanced diet, walking, exercising, and incorporating beneficial foods like olive oil, almonds, and nutritious vegetables, along with abdominal massage using chamomile oil. She also took vitamin C and vitamin D supplements. After approximately twenty weeks of these methods, and given that infertility centers had indicated that surgery and repeated IVF were the only options for her to conceive, she became pregnant naturally and had a successful pregnancy and delivery. Endometriosis is one of the significant factors contributing to infertility and adhesions in the fallopian tubes and uterus, and unfortunately, it has no definitive cure and can recur even after surgery. The treatment of similar cases emphasizes lifestyle modifications, and this approach has proven to be both cost-effective and harmless. Therefore, it seems essential to focus on this treatment strategy.

Keywords: infertility, endometriosis, adhesions, fallopian tubes, healthy lifestyle, lifestyle modifications, abdominal massage, case study, natural pregnancy, ivf, psychological consequences, uterine health, complementary treatments, nutrition, women's health.

Procedia PDF Downloads 21
1241 Antiangiogenic and Pro-Apoptotic Properties of Shemamruthaa: An Herbal Preparation in Experimental Mammary Carcinoma-Bearing Rats and Breast Cancer Cell Line In vitro

Authors: Nandhakumar Elumalai, Purushothaman Ayyakannu, Sachidanandam T. Panchanatham

Abstract:

Background: Understanding the basic mechanisms and factors underlying the tumor growth and invasion has gained attention in recent times. The processes of angiogenesis and apoptosis are known to play a vital role in various stages of cancer. The vascular endothelial growth factor (VEGF) is well established as one of the key regulators of tumor angiogenesis while MMPs are known for their exclusive ability to degrade ECM. Objective: The present study was designed to evaluate the pro apoptotic and anti angiogenic activity of the herbal formulation Shemamruthaa. The anticancer activity of Shemamruthaa was tested in breast cancer cell line (MCF-7). Results of MTT, trypan blue and flow cytometric analysis of apoptotis suggested that Shemamruthaa can induce cytotoxicity in cancer cells, in a concentration- and time dependent manner and induce apoptosis. With these results, we further evaluated the antiangiogenic and pro-apoptotic activities of Shemamruthaa in DMBA induced mammary carcinoma in Sprague Dawley rats. Flavono tumour was induced in 8-week-old Sprague-Dawley rats by gastric intubation of 25 mg DMBA in 1ml olive oil. After 90 days of induction period, the rats were orally administered with Shemamruthaa (400 mg/kg body wt) for 45 days. Treatment with the drug SM significantly modulated the expression of p53, MMP-2, MMP-3, MMP-9 and VEGF by means of its anti angiogenic and protease inhibiting activity. Conclusion: Based on these results, it might be concluded that the formulation, Shemamruthaa, constituted of dried flowers of Hibiscus rosa-sinensis, fruits of Emblica officinalis, and honey has been found to exhibit pronounced antiproliferative and apoptotic effects. This enhanced anticancer effect of Shemamruthaa might be attributed to the synergistic action of polyphenols such as flavonoids, tannins, alkaloids, glycosides, saponins, steroids, terpenoids, vitamin C, niacin, pyrogallol, hydroxymethylfurfural, trilinolein, and other compounds present in the formulation. Collectively, these results demonstrate that Shemamruthaa holds potential to be developed as a potent chemotherapeutic agent against mammary carcinoma.

Keywords: Shemamruthaa, flavonoids, MCF-7 cell line, mammary cancer

Procedia PDF Downloads 252
1240 Synthesis and Characterization of Molecularly Imprinted Polymer as a New Adsorbent for the Removal of Pyridine from Organic Medium

Authors: Opeyemi Elujulo, Aderonke Okoya, Kehinde Awokoya

Abstract:

Molecularly imprinted polymers (MIP) for the adsorption of pyridine (PYD) was obtained from PYD (the template), styrene (the functional monomer), divinyl benzene (the crosslinker), benzoyl peroxide (the initiator), and water (the porogen). When the template was removed by solvent extraction, imprinted binding sites were left in the polymer material that are capable of selectively rebinding the target molecule. The material was characterized by Fourier transform infrared spectroscopy and differential scanning calorimetry. Batch adsorption experiments were performed to study the adsorption of the material in terms of adsorption kinetics, isotherms, and thermodynamic parameters. The results showed that the imprinted polymer exhibited higher affinity for PYD compared to non-imprinted polymer (NIP).

Keywords: molecularly imprinted polymer, bulk polymerization, environmental pollutant, adsorption

Procedia PDF Downloads 144
1239 Development of Academic Software for Medial Axis Determination of Porous Media from High-Resolution X-Ray Microtomography Data

Authors: S. Jurado, E. Pazmino

Abstract:

Determination of the medial axis of a porous media sample is a non-trivial problem of interest for several disciplines, e.g., hydrology, fluid dynamics, contaminant transport, filtration, oil extraction, etc. However, the computational tools available for researchers are limited and restricted. The primary aim of this work was to develop a series of algorithms to extract porosity, medial axis structure, and pore-throat size distributions from porous media domains. A complementary objective was to provide the algorithms as free computational software available to the academic community comprising researchers and students interested in 3D data processing. The burn algorithm was tested on porous media data obtained from High-Resolution X-Ray Microtomography (HRXMT) and idealized computer-generated domains. The real data and idealized domains were discretized in voxels domains of 550³ elements and binarized to denote solid and void regions to determine porosity. Subsequently, the algorithm identifies the layer of void voxels next to the solid boundaries. An iterative process removes or 'burns' void voxels in sequence of layer by layer until all the void space is characterized. Multiples strategies were tested to optimize the execution time and use of computer memory, i.e., segmentation of the overall domain in subdomains, vectorization of operations, and extraction of single burn layer data during the iterative process. The medial axis determination was conducted identifying regions where burnt layers collide. The final medial axis structure was refined to avoid concave-grain effects and utilized to determine the pore throat size distribution. A graphic user interface software was developed to encompass all these algorithms, including the generation of idealized porous media domains. The software allows input of HRXMT data to calculate porosity, medial axis, and pore-throat size distribution and provide output in tabular and graphical formats. Preliminary tests of the software developed during this study achieved medial axis, pore-throat size distribution and porosity determination of 100³, 320³ and 550³ voxel porous media domains in 2, 22, and 45 minutes, respectively in a personal computer (Intel i7 processor, 16Gb RAM). These results indicate that the software is a practical and accessible tool in postprocessing HRXMT data for the academic community.

Keywords: medial axis, pore-throat distribution, porosity, porous media

Procedia PDF Downloads 117
1238 A Summary-Based Text Classification Model for Graph Attention Networks

Authors: Shuo Liu

Abstract:

In Chinese text classification tasks, redundant words and phrases can interfere with the formation of extracted and analyzed text information, leading to a decrease in the accuracy of the classification model. To reduce irrelevant elements, extract and utilize text content information more efficiently and improve the accuracy of text classification models. In this paper, the text in the corpus is first extracted using the TextRank algorithm for abstraction, the words in the abstract are used as nodes to construct a text graph, and then the graph attention network (GAT) is used to complete the task of classifying the text. Testing on a Chinese dataset from the network, the classification accuracy was improved over the direct method of generating graph structures using text.

Keywords: Chinese natural language processing, text classification, abstract extraction, graph attention network

Procedia PDF Downloads 103
1237 Chromatography Study of Fundamental Properties of Medical Radioisotope Astatine-211

Authors: Evgeny E. Tereshatov

Abstract:

Astatine-211 is considered one of the most promising radionuclides for Targeted Alpha Therapy. In order to develop reliable procedures to label biomolecules and utilize efficient delivery vehicle principles, one should understand the main chemical characteristics of astatine. The short half-life of 211At (~7.2 h) and absence of any stable isotopes of this element are limiting factors towards studying the behavior of astatine. Our team has developed a procedure for rapid and efficient isolation of astatine from irradiated bismuth material in nitric acid media based on 3-octanone and 1-octanol extraction chromatography resins. This process has been automated and it takes 20 min from the beginning of the target dissolution to the At-211 fraction elution. Our next step is to consider commercially available chromatography resins and their applicability in astatine purification in the same media. Results obtained along with the corresponding sorption mechanisms will be discussed.

Keywords: astatine-211, chromatography, automation, mechanism, radiopharmaceuticals

Procedia PDF Downloads 94
1236 Evaluation of Neuroprotective Potential of Olea europaea and Malus domestica in Experimentally Induced Stroke Rat Model

Authors: Humaira M. Khan, Kanwal Asif

Abstract:

Ischemic stroke is a neurological disorder with a complex pathophysiology associated with motor, sensory and cognitive deficits. Major approaches developed to treat acute ischemic stroke fall into two categories, thrombolysis and neuroprotection. The objectives of this study were to evaluate the neuroprotective and anti-thrombolytic effects of Olea europaea (olive oil) and Malus domestica (apple cider vinegar) and their combination in rat stroke model. Furthermore, histopathological analysis was also performed to assess the severity of ischemia among treated and reference groups. Male albino rats (12 months age) weighing 300- 350gm were acclimatized and subjected to middle cerebral artery occlusion method for stroke induction. Olea europaea and Malus domestica was administered orally in dose of 0.75ml/kg and 3ml/kg and combination was administered at dose of 0.375ml/kg and 1.5ml/kg prophylactically for consecutive 21 days. Negative control group was dosed with normal saline whereas piracetam (250mg/kg) was administered as reference. Neuroprotective activity of standard piracetam, Olea europaea, Malus domestica and their combination was evaluated by performing functional outcome tests i.e. Cylinder, pasta, ladder run, pole and water maize tests. Rats were subjected to surgery after 21 days of treatment for analysis from stroke recovery. Olea europaea and Malus domestica in individual doses of 0.75ml/kg and 3ml/kg respectively showed neuroprotection by significant improvement in ladder run test (121.6± 0.92;128.2 ± 0.73) as compare to reference (125.4 ± 0.74). Both test doses showed significant neuroprotection as compare to reference (9.60 ± 0.50) in pasta test (8.40 ± 0.24;9.80 ± 0.37) whereas with cylinder test, experimental groups showed significant increase in movements (6.60 ± 0.24; 8.40 ± 0.24) in contrast to reference (7.80 ± 0.37).There was a decrease in percentage time taken f to reach the hidden maize in water maize test (56.80 ± 0.58;61.80 ± 0.66) at doses 0.75ml/kg and 3ml/kg respectively as compare to piracetam (59.40 ± 1.07). Olea europaea and Malus domestica individually showed significant reduction in duration of mobility (127.0 ± 0.44; 123.0 ± 0.44) in pole test as compare to piracetam (124.0 ± 0.70). Histopathological analysis revealed the significant extent of protection from ischemia after prophylactic treatments. Hence it is concluded that Olea europaea and Malus domestica are effective neuroprotective agents alone as compare to their combination.

Keywords: ischemia, Malus domestica, neuroprotection, Olea europaea

Procedia PDF Downloads 128
1235 Discovering Semantic Links Between Synonyms, Hyponyms and Hypernyms

Authors: Ricardo Avila, Gabriel Lopes, Vania Vidal, Jose Macedo

Abstract:

This proposal aims for semantic enrichment between glossaries using the Simple Knowledge Organization System (SKOS) vocabulary to discover synonyms, hyponyms and hyperonyms semiautomatically, in Brazilian Portuguese, generating new semantic relationships based on WordNet. To evaluate the quality of this proposed model, experiments were performed by the use of two sets containing new relations, being one generated automatically and the other manually mapped by the domain expert. The applied evaluation metrics were precision, recall, f-score, and confidence interval. The results obtained demonstrate that the applied method in the field of Oil Production and Extraction (E&P) is effective, which suggests that it can be used to improve the quality of terminological mappings. The procedure, although adding complexity in its elaboration, can be reproduced in others domains.

Keywords: ontology matching, mapping enrichment, semantic web, linked data, SKOS

Procedia PDF Downloads 218
1234 A Comparative Study on Automatic Feature Classification Methods of Remote Sensing Images

Authors: Lee Jeong Min, Lee Mi Hee, Eo Yang Dam

Abstract:

Geospatial feature extraction is a very important issue in the remote sensing research. In the meantime, the image classification based on statistical techniques, but, in recent years, data mining and machine learning techniques for automated image processing technology is being applied to remote sensing it has focused on improved results generated possibility. In this study, artificial neural network and decision tree technique is applied to classify the high-resolution satellite images, as compared to the MLC processing result is a statistical technique and an analysis of the pros and cons between each of the techniques.

Keywords: remote sensing, artificial neural network, decision tree, maximum likelihood classification

Procedia PDF Downloads 348
1233 Evaluation of Medicinal Plants, Catunaregam spinosa, Houttuynia cordata, and Rhapis excelsa from Malaysia for Antibacterial, Antifungal and Antiviral Properties

Authors: Yik Sin Chan, Bee Ling Chuah, Wei Quan Chan, Ri Jin Cheng, Yan Hang Oon, Kong Soo Khoo, Nam Weng Sit

Abstract:

Traditionally, medicinal plants have been used to treat different kinds of ailments including infectious diseases. They serve as a good source of lead compounds for the development of new and safer anti-infective agents. This study aimed to investigate the antimicrobial potential of the leaves of three medicinal plants, namely Catunaregam spinosa (Rubiaceae; Mountain pomegranate), Houttuynia cordata (Saururaceae; "fishy-smell herb") and Rhapis excelsa (Arecaceae; “broadleaf lady palm”). The leaves extracts were obtained by sequential extraction using hexane, chloroform, ethyl acetate, ethanol, methanol and water. The antibacterial and antifungal activities were assessed using a colorimetric broth microdilution method against a panel of human pathogenic bacteria (Gram-positive: Bacillus cereus and Staphylococcus aureus; Gram-negative: Escherichia coli, Klebsiella pneumoniae and Pseudomonas aeruginosa) and fungi (yeasts: Candida albicans, Candida parapsilosis and Cryptococcus neoformans; Moulds: Aspergillus fumigatus and Trichophyton mentagrophytes) respectively; while antiviral activity was evaluated against the Chikungunya virus on monkey kidney epithelial (Vero) cells by neutral red uptake assay. All the plant extracts showed bacteriostatic activity, however, only 72% of the extracts (13/18) were found to have bactericidal activity. The lowest minimum inhibitory concentration (MIC) and minimum bactericidal concentration (MBC) were given by the hexane extract of C. spinosa against S. aureus with the values of 0.16 and 0.31 mg/mL respectively. All the extracts also possessed fungistatic activity. Only the hexane, chloroform and ethyl acetate extracts of H. cordata exerted inhibitory activity against A. fumigatus, giving the lowest fungal susceptibility index of 16.7%. In contrast, only 61% of the extracts (11/18) showed fungicidal activity. The ethanol extract of R. excelsa exhibited the strongest fungicidal activity against C. albicans, C. parapsilosis and T. mentagrophytes with minimum fungicidal concentration (MFC) values of 0.04–0.08 mg/mL, in addition to its methanol extract against T. mentagrophytes (MFC=0.02 mg/mL). For anti-Chikungunya virus activity, only chloroform and ethyl acetate extracts of R. excelsa showed significant antiviral activity with 50% effective concentrations (EC50) of 29.9 and 78.1 g/mL respectively. Extracts of R. excelsa warrant further investigations into their active principles responsible for antifungal and antiviral properties.

Keywords: bactericidal, Chikungunya virus, extraction, fungicidal

Procedia PDF Downloads 405
1232 Contourlet Transform and Local Binary Pattern Based Feature Extraction for Bleeding Detection in Endoscopic Images

Authors: Mekha Mathew, Varun P Gopi

Abstract:

Wireless Capsule Endoscopy (WCE) has become a great device in Gastrointestinal (GI) tract diagnosis, which can examine the entire GI tract, especially the small intestine without invasiveness and sedation. Bleeding in the digestive tract is a symptom of a disease rather than a disease itself. Hence the detection of bleeding is important in diagnosing many diseases. In this paper we proposes a novel method for distinguishing bleeding regions from normal regions based on Contourlet transform and Local Binary Pattern (LBP). Experiments show that this method provides a high accuracy rate of 96.38% in CIE XYZ colour space for k-Nearest Neighbour (k-NN) classifier.

Keywords: Wireless Capsule Endoscopy, local binary pattern, k-NN classifier, contourlet transform

Procedia PDF Downloads 487