Search results for: methanolic extract
1005 A POX Controller Module to Prepare a List of Flow Header Information Extracted from SDN Traffic
Authors: Wisam H. Muragaa, Kamaruzzaman Seman, Mohd Fadzli Marhusin
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Software Defined Networking (SDN) is a paradigm designed to facilitate the way of controlling the network dynamically and with more agility. Network traffic is a set of flows, each of which contains a set of packets. In SDN, a matching process is performed on every packet coming to the network in the SDN switch. Only the headers of the new packets will be forwarded to the SDN controller. In terminology, the flow header fields are called tuples. Basically, these tuples are 5-tuple: the source and destination IP addresses, source and destination ports, and protocol number. This flow information is used to provide an overview of the network traffic. Our module is meant to extract this 5-tuple with the packets and flows numbers and show them as a list. Therefore, this list can be used as a first step in the way of detecting the DDoS attack. Thus, this module can be considered as the beginning stage of any flow-based DDoS detection method.Keywords: matching, OpenFlow tables, POX controller, SDN, table-miss
Procedia PDF Downloads 1951004 Intelligent Grading System of Apple Using Neural Network Arbitration
Authors: Ebenezer Obaloluwa Olaniyi
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In this paper, an intelligent system has been designed to grade apple based on either its defective or healthy for production in food processing. This paper is segmented into two different phase. In the first phase, the image processing techniques were employed to extract the necessary features required in the apple. These techniques include grayscale conversion, segmentation where a threshold value is chosen to separate the foreground of the images from the background. Then edge detection was also employed to bring out the features in the images. These extracted features were then fed into the neural network in the second phase of the paper. The second phase is a classification phase where neural network employed to classify the defective apple from the healthy apple. In this phase, the network was trained with back propagation and tested with feed forward network. The recognition rate obtained from our system shows that our system is more accurate and faster as compared with previous work.Keywords: image processing, neural network, apple, intelligent system
Procedia PDF Downloads 3941003 Recycling of Sclareolide in the Crystallization Mother Liquid of Sclareolide by Adsorption and Chromatography
Authors: Xiang Li, Kui Chen, Bin Wu, Min Zhou
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Sclareolide is made from sclareol by oxidiative synthesis and subsequent crystallization, while the crystallization mother liquor still contains 15%~30%wt of sclareolide to be reclaimed. With the reaction material of sclareol is provided as plant extract, many sorts of complex impurities exist in the mother liquor. Due to the difficulty in recycling sclareolide after solvent recovery, it is common practice for the factories to discard the mother liquor, which not only results in loss of sclareolide, but also contributes extra environmental burden. In this paper, a process based on adsorption and elution has been presented for recycling of sclareolide from mother liquor. After pretreatment of the crystallization mother liquor by HZ-845 resin to remove parts of impurities, sclareolide is adsorbed by HZ-816 resin. The HZ-816 resin loaded with sclareolide is then eluted by elution solvent. Finally, the eluent containing sclareolide is concentrated and fed into the crystallization step in the process. By adoption of the recycle from mother liquor, total yield of sclareolide increases from 86% to 90% with a stable purity of the final sclareolide products maintained.Keywords: sclareolide, resin, adsorption, chromatography
Procedia PDF Downloads 2311002 Using Phase Equilibrium Theory to Calculate Solubility of γ-Oryzanol in Supercritical CO2
Authors: Boy Arief Fachri
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Even its content is rich in antioxidants ϒ-oryzanol, rice bran is not used properly as functional food. This research aims to (1) extract ϒ-oryzanol; (2) determine the solubility of ϒ-oryzanol in supercritical CO2 based on phase equilibrium theory; and (3) study the effect of process variables on solubility. Extraction experiments were carried out for rice bran (5 g) at various extraction pressures, temperatures and reaction times. The flowrate of supercritical fluid through the extraction vessel was 25 g/min. The extracts were collected and analysed with high-pressure liquid chromatography (HPLC). The conclusion based on the experiments are as: (1) The highest experimental solubility was 0.303 mcg/mL RBO at T= 60°C, P= 90 atm, t= 30 min; (2) Solubility of ϒ-oryzanol was influenced by pressure and temperature. As the pressure and temperature increase, the solubility increases; (3) The solubility data of supercritical extraction can be successfully determined using phase equilibrium theory. Meanwhile, tocopherol was found and slightly investigated in this work.Keywords: rice bran, solubility, supercritical CO2, ϒ-orizanol
Procedia PDF Downloads 3801001 Tax Morale Dimensions Analysis in Portugal and Spain
Authors: Cristina Sá, Carlos Gomes, António Martins
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The reasons that explain different behaviors towards tax obligations in similar countries are not completely understood yet. The main purpose of this paper is to identify and compare the factors that influence tax morale levels in Portugal and Spain. We use data from European Values Study (EVS). Using a sample of 2,652 individuals, a factor analysis was used to extract the underlying dimensions of tax morale of Portuguese and Spanish taxpayers. Based on a factor analysis, the results of this paper show that sociological and behavioral factors, psychological factors and political factors are important for a good understanding of taxpayers’ behavior in Iberian Peninsula. This paper added value relies on the analyses of a wide range of variables and on the comparison between Portugal and Spain. Our conclusions provided insights that tax authorities and politicians can use to better focus their strategies and actions in order to increase compliance, reduce tax evasion, fight underground economy and increase country´s competitiveness.Keywords: compliance, tax morale, Portugal, Spain
Procedia PDF Downloads 3051000 Active Disturbance Rejection Control for Maximization of Generated Power from Wind Energy Conversion Systems using a Doubly Fed Induction Generator
Authors: Tamou Nasser, Ahmed Essadki, Ali Boukhriss
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This paper presents the control of doubly fed induction generator (DFIG) used in the wind energy conversion systems. Maximum power point tracking (MPPT) strategy is used to extract the maximum of power during the conversion and taking care that the system does not exceed the operating limits. This is done by acting on the pitch angle to control the orientation of the turbine's blades. Having regard to its robustness and performance, active disturbance rejection control (ADRC) based on the extended state observer (ESO) is employed to achieve the control of both rotor and grid side converters. Simulations are carried out using matlab simulink.Keywords: active disturbance rejection control, extended state observer, doubly fed induction generator, maximum power point tracking
Procedia PDF Downloads 559999 Maximization of Generated Power from Wind Energy Conversion Systems Using a Doubly Fed Induction Generator with Active Disturbance Rejection Control
Authors: Tamou Nasser, Ahmed Essadki, Ali Boukhriss
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This paper presents the control of doubly fed induction generator (DFIG) used in the wind energy conversion systems. Maximum power point tracking (MPPT) strategy is used to extract the maximum of power during the conversion and taking care that the system does not exceed the operating limits. This is done by acting on the pitch angle to control the orientation of the turbine's blades. Having regard to its robustness and performance, active disturbance rejection control (ADRC) based on the extended state observer (ESO) is employed to achieve the control of both rotor and grid side converters. Simulations are carried out using matlab simulink.Keywords: active disturbance rejection control, extended state observer, doubly fed induction generator, maximum power point tracking
Procedia PDF Downloads 496998 The Impact of Scientific Content of National Geographic Channel on Drawing Style of Kindergarten Children
Authors: Ahmed Amin Mousa, Mona Yacoub
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This study depends on tracking children style through what they have drawn after being introduced to 16 visual content through National Geographic Abu Dhabi Channel programs and the study of the changing features in their drawings before applying the visual act with them. The researchers used Goodenough-Harris Test to analyse children drawings and to extract the features which changed in their drawing before and after the visual content. The results showed a positive change especially in the shapes of animals and their properties. Children become more aware of animals’ shapes. The study sample was 220 kindergarten children divided into 130 girls and 90 boys at the Orman Experimental Language School in Dokki, Giza, Egypt. The study results showed an improvement in children drawing with 85% than they were before watching videos.Keywords: National Geographic, children drawing, kindergarten, Goodenough-Harris Test
Procedia PDF Downloads 150997 An Efficient Acquisition Algorithm for Long Pseudo-Random Sequence
Authors: Wan-Hsin Hsieh, Chieh-Fu Chang, Ming-Seng Kao
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In this paper, a novel method termed the Phase Coherence Acquisition (PCA) is proposed for pseudo-random (PN) sequence acquisition. By employing complex phasors, the PCA requires only complex additions in the order of N, the length of the sequence, whereas the conventional method utilizing fast Fourier transform (FFT) requires complex multiplications and additions both in the order of Nlog2N . In order to combat noise, the input and local sequences are partitioned and mapped into complex phasors in PCA. The phase differences between pairs of input and local phasors are utilized for acquisition, and thus complex multiplications are avoided. For more noise-robustness capability, the multi-layer PCA is developed to extract the code phase step by step. The significant reduction of computational loads makes the PCA an attractive method, especially when the sequence length of is extremely large which becomes intractable for the FFT-based acquisition.Keywords: FFT, PCA, PN sequence, convolution theory
Procedia PDF Downloads 473996 A Linear Active Disturbance Rejection Control for Maximization of Generated Power from Wind Energy Conversion Systems Using a Doubly Fed Induction Generator
Authors: Tamou Nasser, Ahmed Essadki, Ali Boukhriss
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This paper presents the control of doubly fed induction generator (DFIG) used in the wind energy conversion systems. Maximum power point tracking (MPPT) strategy is used to extract the maximum of power during the conversion and taking care that the system does not exceed the operating limits. This is done by acting on the pitch angle to control the orientation of the turbine's blades. Having regard to its robustness and performance, active disturbance rejection control (ADRC) based on the extended state observer (ESO) is employed to achieve the control of both rotor and grid side converters. Simulations are carried out using MATLAB simulink.Keywords: active disturbance rejection control, extended state observer, doubly fed induction generator, maximum power point tracking
Procedia PDF Downloads 522995 One-Class Support Vector Machine for Sentiment Analysis of Movie Review Documents
Authors: Chothmal, Basant Agarwal
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Sentiment analysis means to classify a given review document into positive or negative polar document. Sentiment analysis research has been increased tremendously in recent times due to its large number of applications in the industry and academia. Sentiment analysis models can be used to determine the opinion of the user towards any entity or product. E-commerce companies can use sentiment analysis model to improve their products on the basis of users’ opinion. In this paper, we propose a new One-class Support Vector Machine (One-class SVM) based sentiment analysis model for movie review documents. In the proposed approach, we initially extract features from one class of documents, and further test the given documents with the one-class SVM model if a given new test document lies in the model or it is an outlier. Experimental results show the effectiveness of the proposed sentiment analysis model.Keywords: feature selection methods, machine learning, NB, one-class SVM, sentiment analysis, support vector machine
Procedia PDF Downloads 514994 Tool for Metadata Extraction and Content Packaging as Endorsed in OAIS Framework
Authors: Payal Abichandani, Rishi Prakash, Paras Nath Barwal, B. K. Murthy
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Information generated from various computerization processes is a potential rich source of knowledge for its designated community. To pass this information from generation to generation without modifying the meaning is a challenging activity. To preserve and archive the data for future generations it’s very essential to prove the authenticity of the data. It can be achieved by extracting the metadata from the data which can prove the authenticity and create trust on the archived data. Subsequent challenge is the technology obsolescence. Metadata extraction and standardization can be effectively used to resolve and tackle this problem. Metadata can be categorized at two levels i.e. Technical and Domain level broadly. Technical metadata will provide the information that can be used to understand and interpret the data record, but only this level of metadata isn’t sufficient to create trustworthiness. We have developed a tool which will extract and standardize the technical as well as domain level metadata. This paper is about the different features of the tool and how we have developed this.Keywords: digital preservation, metadata, OAIS, PDI, XML
Procedia PDF Downloads 390993 A Theoretical Overview of Thermoluminescence
Authors: Sadhana Agrawal, Tarkeshwari Verma, Shmbhavi Katyayan
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The magnificently accentuating phenomenon of luminescence has gathered a lot of attentions from last few decades. Probably defined as the one involving emission of light from certain kinds of substances on absorbing various energies in the form of external stimulus, the phenomenon claims a versatile pertinence. First observed and reported in an extract of Ligrium Nephriticum by Monards, the phenomenon involves turning of crystal clear water into colorful fluid when comes in contact with the special wood. In words of Sir G.G. Stokes, the phenomenon actually involves three different techniques – absorption, excitation and emission. With variance in external stimulus, the corresponding luminescence phenomenon is obtained. Here, this paper gives a concise discussion of thermoluminescence which is one of the types of luminescence obtained when the external stimulus is given in form of heat energy. A deep insight of thermoluminescence put forward a qualitative analysis of various parameters such as glow curves peaks, trap depth, frequency factors and order of kinetics.Keywords: frequency factor, glow curve peaks, thermoluminescence, trap depth
Procedia PDF Downloads 394992 Performance Evaluation of an Ontology-Based Arabic Sentiment Analysis
Authors: Salima Behdenna, Fatiha Barigou, Ghalem Belalem
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Due to the quick increase in the volume of Arabic opinions posted on various social media, Arabic sentiment analysis has become one of the most important areas of research. Compared to English, there is very little works on Arabic sentiment analysis, in particular aspect-based sentiment analysis (ABSA). In ABSA, aspect extraction is the most important task. In this paper, we propose a semantic aspect-based sentiment analysis approach for standard Arabic reviews to extract explicit aspect terms and identify the polarity of the extracted aspects. The proposed approach was evaluated using HAAD datasets. Experiments showed that the proposed approach achieved a good level of performance compared with baseline results. The F-measure was improved by 19% for the aspect term extraction tasks and 55% aspect term polarity task.Keywords: sentiment analysis, opinion mining, Arabic, aspect level, opinion, polarity
Procedia PDF Downloads 155991 Epileptic Seizure Prediction Focusing on Relative Change in Consecutive Segments of EEG Signal
Authors: Mohammad Zavid Parvez, Manoranjan Paul
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Epilepsy is a common neurological disorders characterized by sudden recurrent seizures. Electroencephalogram (EEG) is widely used to diagnose possible epileptic seizure. Many research works have been devoted to predict epileptic seizure by analyzing EEG signal. Seizure prediction by analyzing EEG signals are challenging task due to variations of brain signals of different patients. In this paper, we propose a new approach for feature extraction based on phase correlation in EEG signals. In phase correlation, we calculate relative change between two consecutive segments of an EEG signal and then combine the changes with neighboring signals to extract features. These features are then used to classify preictal/ictal and interictal EEG signals for seizure prediction. Experiment results show that the proposed method carries good prediction rate with greater consistence for the benchmark data set in different brain locations compared to the existing state-of-the-art methods.Keywords: EEG, epilepsy, phase correlation, seizure
Procedia PDF Downloads 305990 A Preliminary Study for Building an Arabic Corpus of Pair Questions-Texts from the Web: Aqa-Webcorp
Authors: Wided Bakari, Patrce Bellot, Mahmoud Neji
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With the development of electronic media and the heterogeneity of Arabic data on the Web, the idea of building a clean corpus for certain applications of natural language processing, including machine translation, information retrieval, question answer, become more and more pressing. In this manuscript, we seek to create and develop our own corpus of pair’s questions-texts. This constitution then will provide a better base for our experimentation step. Thus, we try to model this constitution by a method for Arabic insofar as it recovers texts from the web that could prove to be answers to our factual questions. To do this, we had to develop a java script that can extract from a given query a list of html pages. Then clean these pages to the extent of having a database of texts and a corpus of pair’s question-texts. In addition, we give preliminary results of our proposal method. Some investigations for the construction of Arabic corpus are also presented in this document.Keywords: Arabic, web, corpus, search engine, URL, question, corpus building, script, Google, html, txt
Procedia PDF Downloads 317989 Control of Fungal Growth in Sweet Orange and Mango Juices by Justica flava and Afromomum melegueta Extracts
Authors: Adferotimi Banso
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A laboratory investigation was conducted to determine the effect of Justica flava and Aframonium melegueta on the growth of Aspergillus niger, Rhizopus stolonifer and Fusarium species in sweet orange and mango juices. Aqueous extract (3%v/v) of Justica flava and Aframonium melegueta reduced the growth of the fungi, a combination of 2% (v/v) each of Justica flava and Aframonium melegueta extracts reduced the growth better. Partial purification of aqueous extracts of Justica flava and Aframonium melegueta showed that ethyl acetate fraction of the extracts exhibited the highest level of inhibition of growth of the test fungi compared with diethyl ether and n-hexane fractions. The results suggest that extracts of Justica flava and Aframonium melegueta may be important substitutes for conventional chemical preservatives in the processing of fruit juices.Keywords: aqueous, fraction, mango, orange, purification, sweet
Procedia PDF Downloads 344988 Image Instance Segmentation Using Modified Mask R-CNN
Authors: Avatharam Ganivada, Krishna Shah
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The Mask R-CNN is recently introduced by the team of Facebook AI Research (FAIR), which is mainly concerned with instance segmentation in images. Here, the Mask R-CNN is based on ResNet and feature pyramid network (FPN), where a single dropout method is employed. This paper provides a modified Mask R-CNN by adding multiple dropout methods into the Mask R-CNN. The proposed model has also utilized the concepts of Resnet and FPN to extract stage-wise network feature maps, wherein a top-down network path having lateral connections is used to obtain semantically strong features. The proposed model produces three outputs for each object in the image: class label, bounding box coordinates, and object mask. The performance of the proposed network is evaluated in the segmentation of every instance in images using COCO and cityscape datasets. The proposed model achieves better performance than the state-of-the-networks for the datasets.Keywords: instance segmentation, object detection, convolutional neural networks, deep learning, computer vision
Procedia PDF Downloads 70987 Inhibition of Pipelines Corrosion Using Natural Extracts
Authors: Eman Alzahrani, Hala M. Abo-Dief, Ashraf T. Mohamed
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The present work is aimed at examining carbon steel oil pipelines corrosion using three natural extracts (Eruca Sativa, Rosell and Mango peels) that are used as inhibitors of different concentrations ranging from 0.05-0.1wt. %. Two sulphur compounds are used as corrosion mediums. Weight loss method was used for measuring the corrosion rate of the carbon steel specimens immersed in technical white oil at 100ºC at various time intervals in absence and presence of the two sulphur compounds. The corroded specimens are examined using the chemical wear test, scratch test and hardness test. The scratch test is carried out using scratch loads from 0.5 Kg to 2.0 Kg. The scratch width is obtained at various scratch load and test conditions. The Brinell hardness test is carried out and investigated for both corroded and inhibited specimens. The results showed that three natural extracts can be used as environmentally friendly corrosion inhibitors.Keywords: inhibition, natural extract, oil pipelines corrosion, sulphur compounds
Procedia PDF Downloads 504986 An Analysis of Sequential Pattern Mining on Databases Using Approximate Sequential Patterns
Authors: J. Suneetha, Vijayalaxmi
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Sequential Pattern Mining involves applying data mining methods to large data repositories to extract usage patterns. Sequential pattern mining methodologies used to analyze the data and identify patterns. The patterns have been used to implement efficient systems can recommend on previously observed patterns, in making predictions, improve usability of systems, detecting events, and in general help in making strategic product decisions. In this paper, identified performance of approximate sequential pattern mining defines as identifying patterns approximately shared with many sequences. Approximate sequential patterns can effectively summarize and represent the databases by identifying the underlying trends in the data. Conducting an extensive and systematic performance over synthetic and real data. The results demonstrate that ApproxMAP effective and scalable in mining large sequences databases with long patterns.Keywords: multiple data, performance analysis, sequential pattern, sequence database scalability
Procedia PDF Downloads 337985 A Relationship Extraction Method from Literary Fiction Considering Korean Linguistic Features
Authors: Hee-Jeong Ahn, Kee-Won Kim, Seung-Hoon Kim
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The knowledge of the relationship between characters can help readers to understand the overall story or plot of the literary fiction. In this paper, we present a method for extracting the specific relationship between characters from a Korean literary fiction. Generally, methods for extracting relationships between characters in text are statistical or computational methods based on the sentence distance between characters without considering Korean linguistic features. Furthermore, it is difficult to extract the relationship with direction from text, such as one-sided love, because they consider only the weight of relationship, without considering the direction of the relationship. Therefore, in order to identify specific relationships between characters, we propose a statistical method considering linguistic features, such as syntactic patterns and speech verbs in Korean. The result of our method is represented by a weighted directed graph of the relationship between the characters. Furthermore, we expect that proposed method could be applied to the relationship analysis between characters of other content like movie or TV drama.Keywords: data mining, Korean linguistic feature, literary fiction, relationship extraction
Procedia PDF Downloads 374984 Thermodynamic Optimization of an R744 Based Transcritical Refrigeration System with Dedicated Mechanical Subcooling Cycle
Authors: Mihir Mouchum Hazarika, Maddali Ramgopal, Souvik Bhattacharyya
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The thermodynamic analysis shows that the performance of the R744 based transcritical refrigeration cycle drops drastically for higher ambient temperatures. This is due to the peculiar s-shape of the isotherm in the supercritical region. However, subcooling of the refrigerant at the gas cooler exit enhances the performance of the R744 based system. The present study is carried out to analyze the R744 based transcritical system with dedicated mechanical subcooling cycle. Based on this proposed cycle, the thermodynamic analysis is performed, and optimum operating parameters are determined. The amount of subcooling and the pressure ratio in the subcooling cycle are the parameters which are needed to be optimized to extract the maximum COP from this proposed cycle. It is expected that this study will be helpful in implementing the dedicated subcooling cycle with R744 based transcritical system to improve the performance.Keywords: optimization, R744, subcooling, transcritical
Procedia PDF Downloads 303983 Breast Cancer Prediction Using Score-Level Fusion of Machine Learning and Deep Learning Models
Authors: Sam Khozama, Ali M. Mayya
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Breast cancer is one of the most common types in women. Early prediction of breast cancer helps physicians detect cancer in its early stages. Big cancer data needs a very powerful tool to analyze and extract predictions. Machine learning and deep learning are two of the most efficient tools for predicting cancer based on textual data. In this study, we developed a fusion model of two machine learning and deep learning models. To obtain the final prediction, Long-Short Term Memory (LSTM) and ensemble learning with hyper parameters optimization are used, and score-level fusion is used. Experiments are done on the Breast Cancer Surveillance Consortium (BCSC) dataset after balancing and grouping the class categories. Five different training scenarios are used, and the tests show that the designed fusion model improved the performance by 3.3% compared to the individual models.Keywords: machine learning, deep learning, cancer prediction, breast cancer, LSTM, fusion
Procedia PDF Downloads 157982 Inhibitory Effect on TNF-Alpha Release of Dioscorea membranacea and Its Compounds
Authors: Arunporn Itharat, Srisopa Ruangnoo, Pakakrong Thongdeeying
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The rhizomes of Dioscorea membranacea (DM) has long been used in Thai Traditional medicine to treat cancer and inflammatory conditions such as rheumatism. The objective of this study was to investigate anti-inflammatory activity by determining the inhibitory effect on LPS-induced TNF-α from RAW264.7 cells of crude extracts and pure isolated compounds from DM. Three known dihydrophenantrene compounds were isolated by a bioassay guided isolation method from DM ethanolic extract [2,4 dimethoxy-5,6-dihydroxy-9,10-dihydrophenanthrene (1) and 5-hydroxy-2,4,6-trimethoxy-9,10-dihydrophenanthrene(2) and 5,6,2 -trihydroxy 3,4-methoxy, 9,10- dihydrophenanthrene (3)]. 1 showed the highest inhibitory effect on PGE2, followed by 3 and 1 (IC50 = 2.26, 4.97 and >20 μg/ml or 8.31,17.25 and > 20 µM respectively). These findings suggest that this plant showed anti-inflamatory effects by displaying an inhibitory effect on TNF-α release, hence, this result supports the usage of Thai traditional medicine to treat inflammation related diseases.Keywords: Dioscorea membranacea, anti-inflammatory activity, TNF-Alpha , dihidrophenantrene compound
Procedia PDF Downloads 500981 Efficient Subsurface Mapping: Automatic Integration of Ground Penetrating Radar with Geographic Information Systems
Authors: Rauf R. Hussein, Devon M. Ramey
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Integrating Ground Penetrating Radar (GPR) with Geographic Information Systems (GIS) can provide valuable insights for various applications, such as archaeology, transportation, and utility locating. Although there has been progress toward automating the integration of GPR data with GIS, fully automatic integration has not been achieved yet. Additionally, manually integrating GPR data with GIS can be a time-consuming and error-prone process. In this study, actual, real-world GPR applications are presented, and a software named GPR-GIS 10 is created to interactively extract subsurface targets from GPR radargrams and automatically integrate them into GIS. With this software, it is possible to quickly and reliably integrate the two techniques to create informative subsurface maps. The results indicated that automatic integration of GPR with GIS can be an efficient tool to map and view any subsurface targets in their appropriate location in a 3D space with the needed precision. The findings of this study could help GPR-GIS integrators save time and reduce errors in many GPR-GIS applications.Keywords: GPR, GIS, GPR-GIS 10, drone technology, automation
Procedia PDF Downloads 87980 Evolving Knowledge Extraction from Online Resources
Authors: Zhibo Xiao, Tharini Nayanika de Silva, Kezhi Mao
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In this paper, we present an evolving knowledge extraction system named AKEOS (Automatic Knowledge Extraction from Online Sources). AKEOS consists of two modules, including a one-time learning module and an evolving learning module. The one-time learning module takes in user input query, and automatically harvests knowledge from online unstructured resources in an unsupervised way. The output of the one-time learning is a structured vector representing the harvested knowledge. The evolving learning module automatically schedules and performs repeated one-time learning to extract the newest information and track the development of an event. In addition, the evolving learning module summarizes the knowledge learned at different time points to produce a final knowledge vector about the event. With the evolving learning, we are able to visualize the key information of the event, discover the trends, and track the development of an event.Keywords: evolving learning, knowledge extraction, knowledge graph, text mining
Procedia PDF Downloads 456979 Anti-proliferative Activity and HER2 Receptor Expression Analysis of MCF-7 (Breast Cancer Cell) Cells by Plant Extract Coleus Barbatus (Andrew)
Authors: Anupalli Roja Rani, Pavithra Dasari
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Background: Among several, breast cancer has emerged as the most common female cancer in developing countries. It is the most common cause of cancer-related deaths worldwide among women. It is a molecularly and clinically heterogeneous disease. Moreover, it is a hormone–dependent tumor in which estrogens can regulate the growth of breast cells by binding with estrogen receptors (ERs). Moreover, the use of natural products in cancer therapeutics is due to their properties of biocompatibility and less toxicity. Plants are the vast reservoirs for various bioactive compounds. Coleus barbatus (Lamiaceae) contains anticancer properties against several cancer cell lines. Method: In the present study, an attempt is being made to enrich the knowledge of the anticancer activity of pure compounds extracted from Coleus barbatus (Andrew). On human breast cancer cell lines MCF-7. Here in, we are assessing the antiproliferative activity of Coleus barbatus (Andrew) plant extracts against MCF 7 and also evaluating their toxicity in normal human mammary cell lines such as Human Mammary Epithelial Cells (HMEC). The active fraction of plant extract was further purified with the help of Flash chromatography, Medium Pressure Liquid Chromatography (MPLC) and preparative High-Performance Liquid Chromatography (HPLC). The structure of pure compounds will be elucidated by using modern spectroscopic methods like Nuclear magnetic resonance (NMR), Electrospray Ionisation Mass Spectrometry (ESI-MS) methods. Later, the growth inhibition morphological assessment of cancer cells and cell cycle analysis of purified compounds were assessed using FACS. The growth and progression of signaling molecules HER2, GRP78 was studied by secretion assay using ELISA and expression analysis by flow cytometry. Result: Cytotoxic effect against MCF-7 with IC50 values were derived from dose response curves, using six concentrations of twofold serially diluted samples, by SOFTMax Pro software (Molecular device) and respectively Ellipticine and 0.5% DMSO were used as a positive and negative control. Conclusion: The present study shows the significance of various bioactive compounds extracted from Coleus barbatus (Andrew) root material. It acts as an anti-proliferative and shows cytotoxic effects on human breast cancer cell lines MCF7. The plant extracts play an important role pharmacologically. The whole plant has been used in traditional medicine for decades and the studies done have authenticated the practice. Earlier, as described, the plant has been used in the ayurveda and homeopathy medicine. However, more clinical and pathological studies must be conducted to investigate the unexploited potential of the plant. These studies will be very useful for drug designing in the future.Keywords: coleus barbatus, HPLC, MPLC, NMR, MCF7, flash chromatograph, ESI-MS, FACS, ELISA.
Procedia PDF Downloads 109978 The Mechanical Behavior of a Cement-Fiber Composite Material
Authors: K. Harrat, M. Hidjeb, M. T’kint
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The aim of the present research work is to characterize a cement palm date fiber composite in order to be used in isolation and in the manufacture of new structural materials. This technique may possibly participate seriously in the preservation of the environment and develop a growing need for plant products. On one hand, It has been shown that the presence of natural fiber in the composite materials manufacture, based on hydraulic binder, has improved the mechanical behaviour of the material. On the Other hand, It has been proven that the durability of composite materials reinforced with untreated fibers was largely affected by the presence of organic matter. In order to extract the organic material, the fibers were treated with boiling water and then coated with different types of products. A considerable improvement in the sensitivity to water of the fibers, as well as in the mechanical strength and in the ductility of the composite material was observed. The fiber being sensitive to water, the study put the emphasis on its dimensional stability.Keywords: cement composite, durability, heat treatment, mechanical behaviour, vegetal fiber
Procedia PDF Downloads 451977 Algorithms used in Spatial Data Mining GIS
Authors: Vahid Bairami Rad
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Extracting knowledge from spatial data like GIS data is important to reduce the data and extract information. Therefore, the development of new techniques and tools that support the human in transforming data into useful knowledge has been the focus of the relatively new and interdisciplinary research area ‘knowledge discovery in databases’. Thus, we introduce a set of database primitives or basic operations for spatial data mining which are sufficient to express most of the spatial data mining algorithms from the literature. This approach has several advantages. Similar to the relational standard language SQL, the use of standard primitives will speed-up the development of new data mining algorithms and will also make them more portable. We introduced a database-oriented framework for spatial data mining which is based on the concepts of neighborhood graphs and paths. A small set of basic operations on these graphs and paths were defined as database primitives for spatial data mining. Furthermore, techniques to efficiently support the database primitives by a commercial DBMS were presented.Keywords: spatial data base, knowledge discovery database, data mining, spatial relationship, predictive data mining
Procedia PDF Downloads 457976 Genomic Analysis of Whole Genome Sequencing of Leishmania Major
Authors: Fatimazahrae Elbakri, Azeddine Ibrahimi, Meryem Lemrani, Dris Belghyti
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Leishmaniasis represents a major public health problem because of the number of cases recorded each year and the wide distribution of the disease. It is a parasitic disease of flagellated protozoa transmitted by the bite of certain species of sandfly, causing a spectrum of clinical pathology in humans ranging from disfiguring skin lesions to fatal visceral leishmaniasis. Cutaneous leishmaniasis due to Leishmania major is a polymorphic disease; in fact, the infection can be asymptomatic, localized, or disseminated. The objective of this work is to determine the genomic diversity that contributes to clinical variability by trying to identify the variation in chromosome number and to extract SNPs and SNPs and InDels; it is based on four sequences (WGS) of Leishmania major available on NCBI in Fastq form, from three countries: Tunisia, Algeria, and Israel, the analysis is set up from a pipeline to facilitate the discovery of genetic diversity, in particular SNP and chromosomal somy.Keywords: Leshmania major, cutaneous Leishmania, NGS, genomic, somy, variant calling
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