Search results for: carotenoids extract

Authors: M. Benattou, K. Tamine

Abstract:

This paper presents a distributed intrusion detection system IDS, based on the concept of specialized distributed agents community representing agents with the same purpose for detecting distributed attacks. The semantic of intrusion events occurring in a predetermined network has been defined. The correlation rules referring the process which our proposed IDS combines the captured events that is distributed both spatially and temporally. And then the proposed IDS tries to extract significant and broad patterns for set of well-known attacks. The primary goal of our work is to provide intrusion detection and real-time prevention capability against insider attacks in distributed and fully automated environments.

Keywords: Mobile agent, specialized agent, interpreter agent, event rules, correlation.

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Authors: S. Sarumathi, N. Shanthi, M. Sharmila

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Clustering in data mining is an unsupervised learning technique of aggregating the data objects into meaningful groups such that the intra cluster similarity of objects are maximized and inter cluster similarity of objects are minimized. Over the past decades several clustering tools were emerged in which clustering algorithms are inbuilt and are easier to use and extract the expected results. Data mining mainly deals with the huge databases that inflicts on cluster analysis and additional rigorous computational constraints. These challenges pave the way for the emergence of powerful expansive data mining clustering softwares. In this survey, a variety of clustering tools used in data mining are elucidated along with the pros and cons of each software.

Keywords: Cluster Analysis, Clustering Algorithms, Clustering Techniques, Association, Visualization.

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Authors: A. Harifi, A. Aghagolzadeh

Abstract:

The main problem for recognition of handwritten Persian digits using Neural Network is to extract an appropriate feature vector from image matrix. In this research an asymmetrical segmentation pattern is proposed to obtain the feature vector. This pattern can be adjusted as an optimum model thanks to its one degree of freedom as a control point. Since any chosen algorithm depends on digit identity, a Neural Network is used to prevail over this dependence. Inputs of this Network are the moment of inertia and the center of gravity which do not depend on digit identity. Recognizing the digit is carried out using another Neural Network. Simulation results indicate the high recognition rate of 97.6% for new introduced pattern in comparison to the previous models for recognition of digits.

Keywords: Pattern recognition, Persian digits, NeuralNetwork.

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Authors: William Wong Xiu Shun, Yoonjin Hyun, Mingyu Kim, Seongi Choi, Namgyu Kim

Abstract:

The need to extract R&D keywords from issues and use them to retrieve R&D information is increasing rapidly. However, it is difficult to identify related issues or distinguish them. Although the similarity between issues cannot be identified, with an R&D lexicon, issues that always share the same R&D keywords can be determined. In detail, the R&D keywords that are associated with a particular issue imply the key technology elements that are needed to solve a particular issue. Furthermore, the relationship among issues that share the same R&D keywords can be shown in a more systematic way by clustering them according to keywords. Thus, sharing R&D results and reusing R&D technology can be facilitated. Indirectly, redundant investment in R&D can be reduced as the relevant R&D information can be shared among corresponding issues and the reusability of related R&D can be improved. Therefore, a methodology to cluster issues from the perspective of common R&D keywords is proposed to satisfy these demands.

Keywords: Clustering, Social Network Analysis, Text Mining, Topic Analysis.

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Authors: Sarra Senhadji, Imene Benzeguimi, Zohra Yagoub

Abstract:

Big Data represents the recent technology of manipulating voluminous and unstructured data sets over multiple sources. Therefore, NOSQL appears to handle the problem of unstructured data. Association rules mining is one of the popular techniques of data mining to extract hidden relationship from transactional databases. The algorithm for finding association dependencies is well-solved with Map Reduce. The goal of our work is to reduce the time of generating of frequent itemsets by using Map Reduce and NOSQL database oriented document. A comparative study is given to evaluate the performances of our algorithm with the classical algorithm Apriori.

Keywords: Apriori, Association rules mining, Big Data, data mining, Hadoop, Map Reduce, MongoDB, NoSQL.

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Authors: S. Buloyan, V. Mamikonyan, H. Hakobyan, H. Harutyunyan, H. Gasparyan

Abstract:

The liver is the strongest regenerating organ of the organism, and even with 2/3 surgically removed, it can regenerate completely. Hence liver cirrhosis may only develop when the regenerating system is off. We present the results of a comparative study of structural and functional characteristics of rat liver tissue under the conditions of toxic liver cirrhosis development, induced by carbon tetrachloride, and its prevention/treatment by natural compounds with antioxidant and immune stimulating action. Studies were made on Wister rats, weighing 120~140 g. Grape seeds extracts, separately and in combination with well-known anticirrhotic drug ursodeoxycholic acid (Urdoxa), have demonstrated effectiveness in prevention of liver cirrhosis development and its treatment.

Keywords: Carbon tetrachloride, GSE, liver cirrhosis, prevention, treatment.

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Authors: Mazhar B. Tayel, Amr H. Yassin

Abstract:

A proposed small-signal model parameters for a pseudomorphic high electron mobility transistor (PHEMT) is presented. Both extrinsic and intrinsic circuit elements of a smallsignal model are determined using genetic algorithm (GA) as a stochastic global search and optimization tool. The parameters extraction of the small-signal model is performed on 200-μm gate width AlGaAs/InGaAs PHEMT. The equivalent circuit elements for a proposed 18 elements model are determined directly from the measured S- parameters. The GA is used to extract the parameters of the proposed small-signal model from 0.5 up to 18 GHz.

Keywords: PHEMT, Genetic Algorithms, small signal modeling, optimization.

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Authors: Dimitri Perrin, Heather J. Ruskin, Martin Crane

Abstract:

This study focuses on examining why the range of experience with respect to HIV infection is so diverse, especially in regard to the latency period. An agent-based approach in modelling the infection is used to extract high-level behaviour which cannot be obtained analytically from the set of interaction rules at the cellular level. A prototype model encompasses local variation in baseline properties, contributing to the individual disease experience, and is included in a network which mimics the chain of lymph nodes. The model also accounts for stochastic events such as viral mutations. The size and complexity of the model require major computational effort and parallelisation methods are used.

Keywords: HIV, Immune modelling, Agent-based system, individual response.

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Authors: Anjum Iqbal, Mohd Aizaini Maarof

Abstract:

Artificial Immune System (AIS) is relatively naive paradigm for intelligent computations. The inspiration for AIS is derived from natural Immune System (IS). Classically it is believed that IS strives to discriminate between self and non-self. Most of the existing AIS research is based on this approach. Danger Theory (DT) argues this approach and proposes that IS fights against danger producing elements and tolerates others. We, the computational researchers, are not concerned with the arguments among immunologists but try to extract from it novel abstractions for intelligent computation. This paper aims to follow DT inspiration for intelligent data processing. The approach may introduce new avenue in intelligent processing. The data used is system calls data that is potentially significant in intrusion detection applications.

Keywords: artificial immune system, danger theory, intelligent processing, system calls

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Authors: Nathar Shah

Abstract:

Concurrency and synchronization are becoming big issues as every new PC comes with multi-core processors. A major reason for Object-Oriented Programming originally was to enable easier reuse: encode your algorithm into a class and thoroughly debug it, then you can reuse the class again and again. However, when we get to concurrency and synchronization, this is often not possible. Thread-safety issues means that synchronization constructs need to be entangled into every class involved. We contributed a detailed literature review of issues and challenges in concurrent programming and present a methodology that uses the Aspect- Oriented paradigm to address this problem. Aspects will allow us to extract the synchronization concerns as schemes to be “weaved in" later into the main code. This allows the aspects to be separately tested and verified. Hence, the functional components can be weaved with reusable synchronization schemes that are robust and scalable.

Keywords: Aspect-orientation, development methodologysoftware concurrency, synchronization.

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Authors: Nidal F. Shilbayeh, Belal AbuHaija, Zainab N. Al-Qudsy

Abstract:

In this paper, we propose a new robust and secure system that is based on the combination between two different transforms Discrete wavelet Transform (DWT) and Contourlet Transform (CT). The combined transforms will compensate the drawback of using each transform separately. The proposed algorithm has been designed, implemented and tested successfully. The experimental results showed that selecting the best sub-band for embedding from both transforms will improve the imperceptibility and robustness of the new combined algorithm. The evaluated imperceptibility of the combined DWT-CT algorithm which gave a PSNR value 88.11 and the combination DWT-CT algorithm improves robustness since it produced better robust against Gaussian noise attack. In addition to that, the implemented system shored a successful extraction method to extract watermark efficiently.

Keywords: DWT, CT, Digital Image Watermarking, Copyright Protection.

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Authors: Irwin Ma, Tony Wong, Thiagas Sankar

Abstract:

By systematically applying different engineering methods, difficult financial problems become approachable. Using a combination of theory and techniques such as wavelet transform, time series data mining, Markov chain based discrete stochastic optimization, and evolutionary algorithms, this work formulated a strategy to characterize and forecast non-linear time series. It attempted to extract typical features from the volatility data sets of S&P100 and S&P500 indices that include abrupt drops, jumps and other non-linearity. As a result, accuracy of forecasting has reached an average of over 75% surpassing any other publicly available results on the forecast of any financial index.

Keywords: Discrete stochastic optimization, genetic algorithms, genetic programming, volatility forecast

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Authors: Weitao Lin

Abstract:

To quickly extract adequate information from large-scale unstructured text data, this paper studies the representation of events in Chinese scenarios and performs the regularized abstraction. It proposes a Chinese event detection technique based on dependency parsing and rule matching. The method first performs dependency parsing on the original utterance, then performs pattern matching at the word or phrase granularity based on the results of dependent syntactic analysis, filters out the utterances with prominent non-event characteristics, and obtains the final results. The experimental results show the effectiveness of the method.

Keywords: Natural Language Processing, Chinese event detection, rules matching, dependency parsing.

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Authors: G. A. Oladosu, P. O. Ogbodogbo, C. I. Makinde, M. O. Tijani, O. A. Adegboyega

Abstract:

Saprolegniasis is a major pathogenic infection that contributes significantly to poor hatching rates in incubated fish eggs in the African catfish hatchery in Nigeria. Malachite green, known to be very effective against this condition, has been banned because it is carcinogenic. There is therefore the need for other effective, yet safer method of controlling saprolegniasis in incubated fish eggs. A total of 50 ml crude, chloroform extract of pyocyanin from which solvent was removed to attain 30 ml, having a concentration of 12.16 ug/ml was produced from 700 ml broth culture of Pseudomonas aeruginosa isolated from a previous study. In vitro susceptibility of the fungus was investigated by exposing fungal infected eggs to two different time-concentration ratios of pyocyanin; 0.275 ug/ml and 2.75 ug/ml for 1 and 24 h, and 5 mg/L malachite green as positive control while normal saline was the control. Efficacy of pyocyanin was evaluated using the degree of mycelial growth inhibition in the different treatments. Fertilized Clarias gariepinus eggs (between 45 to 64 eggs) were then incubated in 20 ml of medium containing the similar concentrations of pyocyanin and malachite green, with freshwater as control for 24 hours. Hatching rates of the incubated eggs were observed. Three samples of un-hatched eggs were taken from each medium and observed for the presence of fungal pathogens using microscopy. Another batch of three samples of un-hatched eggs from each treatment was also inoculated on Sabourand dextrose agar (SDA) using Egg-Agar Transfer technique to observe for fungal growth. Mycelial growth was inhibited in fungal infected eggs treated with 2.75 ug/ml for 24 h and the 5 mg/L malachite green for both 1 h and 24 h. The mortality rate was 100% in fertilized C. gariepinus eggs exposed for 24 h to 0.275 and 2.75 ug/ml of pyocyanin. The mortality rate was least in the malachite green followed by the control treatment. Embryonic development was observed to be arrested in the eggs treated with the two pyocyanin concentrations as they maintain their color but showed no development beyond the gastrula stage, whereas viable eggs in the control and malachite green treatments developed fully into healthy hatchlings. Furthermore, microscopy of the un-hatched eggs revealed the presence of a protozoan ciliate; Colpidium sp. (Tetrahymenidae), as well as a pathogenic fungus; Saprolegnia sp. in the control, but not in the malachite green and pyocyanin treatments. Growth of Saprolegnia sp. was also observed in SDA culture of un-hatched eggs from the control, but not from pyocyanin and malachite green treated eggs. Pyocyanin treatment of incubated eggs of Clarias gariepinus effectively prevented fungal infection in the eggs, but also arrested the development of the embryo. Therefore, crude chloroform extract of pyocyanin from Pseudomonas aeruginosa cannot be used in the control of Saprolegniasis in incubated Clarias gariepinus eggs at the concentration and duration tested in this study.

Keywords: African catfish, bioprophylaxis, embryo, saprolegniasis.

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Authors: Prabhakar Sathujoda

Abstract:

Vibration analysis of a misaligned rotor coupling bearing system has been carried out while decelerating through its critical speed. The finite element method (FEM) is used to model the rotor system and simulate flexural vibrations. A flexible coupling with a frictionless joint is considered in the present work. The continuous wavelet transform is used to extract the misalignment features from the simulated time response. Subcritical speeds at one-half, one-third, and one-fourth the critical speed have appeared in the wavelet transformed vibration response of a misaligned rotor coupling bearing system. These features are also verified through a parametric study.

Keywords: Continuous wavelet transform, flexible coupling, rotor system, sub critical speed.

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Authors: D. Mohd Nazrul Hisham, J. Mohd Lip, R. Suri, H. Mohamed Shafit, Z.Kharis, K. Shazlin, A. Normah, M.F. Nurul Nabilah

Abstract:

Presence of phytosterol compound in Durian seed (Durio zibethinus) or known as King of fruits has been discovered from screening work using reagent test. Further analysis work has been carried out using mass spectrometer in order to support the priliminary finding. Isolation and purification of the major phytosterol has been carried out using an open column chromatography. The separation was monitored using thin layer chromatography (TLC). Major isolated compounds and purified phytosterol were identified using mass spectrometer and nuclear magnetic resonance (NMR). This novel finding could promote utilization of durian seeds as a functional ingredient in food products through production of standardized extract based on phytosterol content.

Keywords: Agrowaste, durian, seed, phytosterol

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Authors: A. Ismail, M. S. Joy, J. E. Sinclair, M. I. Hamzah

Abstract:

This paper focuses on a novel method for semantic searching and retrieval of information about learning materials. Metametadata encapsulate metadata instances by using the properties and attributes provided by ontologies rather than describing learning objects. A novel metametadata taxonomy has been developed which provides the basis for a semantic search engine to extract, match and map queries to retrieve relevant results. The use of ontological views is a foundation for viewing the pedagogical content of metadata extracted from learning objects by using the pedagogical attributes from the metametadata taxonomy. Using the ontological approach and metametadata (based on the metametadata taxonomy) we present a novel semantic searching mechanism.These three strands – the taxonomy, the ontological views, and the search algorithm – are incorporated into a novel architecture (OMESCOD) which has been implemented.

Keywords: Metadata, metametadata, semantic, ontologies.

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Authors: Mehrnoush Shamsfard, Maryam Sadr Mousavi

Abstract:

Extracting thematic (semantic) roles is one of the major steps in representing text meaning. It refers to finding the semantic relations between a predicate and syntactic constituents in a sentence. In this paper we present a rule-based approach to extract semantic roles from Persian sentences. The system exploits a twophase architecture to (1) identify the arguments and (2) label them for each predicate. For the first phase we developed a rule based shallow parser to chunk Persian sentences and for the second phase we developed a knowledge-based system to assign 16 selected thematic roles to the chunks. The experimental results of testing each phase are shown at the end of the paper.

Keywords: Natural Language Processing, Semantic RoleLabeling, Shallow parsing, Thematic Roles.

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Authors: Said Boularouk, Didier Josselin, Eitan Altman

Abstract:

In this paper, we present a vocal ontology of OpenStreetMap data for the apprehension of space by visually impaired people. Indeed, the platform based on produsage gives a freedom to data producers to choose the descriptors of geocoded locations. Unfortunately, this freedom, called also folksonomy leads to complicate subsequent searches of data. We try to solve this issue in a simple but usable method to extract data from OSM databases in order to send them to visually impaired people using Text To Speech technology. We focus on how to help people suffering from visual disability to plan their itinerary, to comprehend a map by querying computer and getting information about surrounding environment in a mono-modal human-computer dialogue.

Keywords: Ontology, OpenStreetMap, visually impaired people, TTS, taxonomy.

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Authors: U.K.Ghosh, M.K.Ghosh

Abstract:

The present experimental investigation brings about a comparative study of lactic acid production by pure strains of Lactobacilli (1) L. delbreuckii (NCIM2025), (2) L. pentosus (NCIM 2912), (3) Lactobacillus sp.(NCIM 2734, (4) Lactobacillus sp. (NCIM2084) and coculture of strain-1 and Stain-2 in solid bed of wheat bran, under the influence of different nitrogen sources such as baker-s yeast, meat extract and proteose peptone. Among the pure cultures, strain-3 attained lowest pH value of 3.44, hence highest acid formation 46.41 g/L, while the coculture attained an overall maximum value 47.56 g/L lactic acid (pH 3.38) at 15 g/L and 20 g/L level of baker-s yeast, respectively.

Keywords: Eco-friendly, lactic acid, lactobacilli, wheat bran

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Authors: M. N. Azian, A. N. Ilia Anisa, Y. Iwai

Abstract:

The mechanism for extraction bioactive compounds from plant matrix is essential for optimizing the extraction process. As a benchmark technique, a soxhlet extraction has been utilized for discussing the mechanism and compared with an accelerated water extraction. The trends of both techniques show that the process involves extraction and degradation. The highest yields of 6-, 8-, 10-gingerols and 6-shogaol in soxhlet extraction were 13.948, 7.12, 10.312 and 2.306 mg/g, respectively. The optimum 6-, 8-, 10-gingerols and 6-shogaol extracted by the accelerated water extraction at 140oC were 68.97±3.95 mg/g at 3min, 18.98±3.04 mg/g at 5min, 5.167±2.35 mg/g at 3min and 14.57±6.27 mg/g at 3min, respectively. The effect of temperature at 3mins shows that the concentration of 6-shogaol increased rapidly as decreasing the recovery of 6-gingerol.

Keywords: Mechanism, bioactive compounds, soxhlet extraction, accelerated water extraction.

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Authors: M. Anandhavalli Gauthaman

Abstract:

DNA microarrays allow the measurement of expression levels for a large number of genes, perhaps all genes of an organism, within a number of different experimental samples. It is very much important to extract biologically meaningful information from this huge amount of expression data to know the current state of the cell because most cellular processes are regulated by changes in gene expression. Association rule mining techniques are helpful to find association relationship between genes. Numerous association rule mining algorithms have been developed to analyze and associate this huge amount of gene expression data. This paper focuses on some of the popular association rule mining algorithms developed to analyze gene expression data.

Keywords: DNA microarray, gene expression, association rule mining.

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Authors: Soukaina Oujana, Peggy Zwolinski

Abstract:

Fines are heterogeneous residues created during the shredding of non-hazardous waste. They are one of the most challenging issues faced by recyclers, because they are at the present time considered as non-sortable and non-reusable mixtures destined to landfill. However, fines contain a large amount of recoverable materials that could be recycled or reused for the production of solid recovered fuel. This research is conducted in relation to a project named ValoRABES. The aim is to characterize fines and establish a suitable sorting process in order to extract the materials contained in the mixture and define their suitable recovery paths. This paper will highlight the importance of a good sampling and will propose a sampling methodology for fines characterization. First results about the characterization will be also presented.

Keywords: Fines, non-hazardous waste, recovery, shredding residues, waste characterization, waste sampling.

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Authors: Hyun-Koo Kim, Sangmoon Lee, Ho-Youl Jung, Ju H. Park

Abstract:

We present a system that finds road boundaries and constructs the virtual lane based on fusion data from a laser and a monocular sensor, and detects forward vehicle position even in no lane markers or bad environmental conditions. When the road environment is dark or a lot of vehicles are parked on the both sides of the road, it is difficult to detect lane and road boundary. For this reason we use fusion of laser and vision sensor to extract road boundary to acquire three dimensional data. We use parabolic road model to calculate road boundaries which is based on vehicle and sensors state parameters and construct virtual lane. And then we distinguish vehicle position in each lane.

Keywords: Vehicle Detection, Adaboost, Haar-like Feature, Road Boundary Detection

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Authors: S. Kherchaoui, A. Houacine

Abstract:

This paper presents a facial expression recognition system. It performs identification and classification of the seven basic expressions; happy, surprise, fear, disgust, sadness, anger, and neutral states. It consists of three main parts. The first one is the detection of a face and the corresponding facial features to extract the most expressive portion of the face, followed by a normalization of the region of interest. Then calculus of curvelet coefficients is performed with dimensionality reduction through principal component analysis. The resulting coefficients are combined with two ratios; mouth ratio and face edge ratio to constitute the whole feature vector. The third step is the classification of the emotional state using the SVM method in the feature space.

Keywords: Facial expression identification, curvelet coefficients, support vector machine (SVM).

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Authors: N. Hachemi, A. Nouani, A. Benchabane

Abstract:

The influence of cultivation factors such as content of ammonium sulfate, glucose and water in the culture medium and particle size of dry orange waste, on their bioconversion for pectinase production was studied using complete factorial design. A polygalacturonase (PG) was isolated using ion exchange chromatography under gradient elution 0-0,5 m/l NaCl (column equilibrate with acetate buffer pH 4,5), subsequently by sephadex G75 column chromatography was applied and the molecular weight was obtained about 51,28 KDa. Purified PG enzyme exhibits a pH and temperature optima of activity at 5 and 35°C respectively. Treatment of apple juice by purified enzyme extract yielded a clear juice, which was competitive with juice yielded by pure Sigma Aldrich Aspergillus niger enzyme.

Keywords: Bioconversion, orange wastes, optimization, pectinase.

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Authors: E. S. Gower, M. O. J. Hawksford

Abstract:

An algorithm for learning an overcomplete dictionary using a Cauchy mixture model for sparse decomposition of an underdetermined mixing system is introduced. The mixture density function is derived from a ratio sample of the observed mixture signals where 1) there are at least two but not necessarily more mixture signals observed, 2) the source signals are statistically independent and 3) the sources are sparse. The basis vectors of the dictionary are learned via the optimization of the location parameters of the Cauchy mixture components, which is shown to be more accurate and robust than the conventional data mining methods usually employed for this task. Using a well known sparse decomposition algorithm, we extract three speech signals from two mixtures based on the estimated dictionary. Further tests with additive Gaussian noise are used to demonstrate the proposed algorithm-s robustness to outliers.

Keywords: expectation-maximization, Pitman estimator, sparsedecomposition

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Authors: Z. Nougrara

Abstract:

In this paper we propose a novel methodology for extracting a road network and its nodes from satellite images of Algeria country. This developed technique is a progress of our previous research works. It is founded on the information theory and the mathematical morphology; the information theory and the mathematical morphology are combined together to extract and link the road segments to form a road network and its nodes. We therefore have to define objects as sets of pixels and to study the shape of these objects and the relations that exist between them. In this approach, geometric and radiometric features of roads are integrated by a cost function and a set of selected points of a crossing road. Its performances were tested on satellite images of Algeria country.

Keywords: Satellite image, road network, nodes.

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Authors: F. Alborzi, H. Vafaei, M.H. Gholami, M.M. S. Esfahani

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In this article, the design of a Supply Chain Network (SCN) consisting of several suppliers, production plants, distribution centers and retailers, is considered. Demands of retailers are considered stochastic parameters, so we generate amounts of data via simulation to extract a few demand scenarios. Then a mixed integer two-stage programming model is developed to optimize simultaneously two objectives: (1) minimization the fixed and variable cost, (2) maximization the service level. A weighting method is utilized to solve this two objective problem and a numerical example is made to show the performance of the model.

Keywords: Mixed Integer Programming, Multi-objective Optimization, Stochastic Demand, Supply Chain Design, Two Stage Programming

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Authors: Dejan Stantic, Jun Jo

Abstract:

ECG contains very important clinical information about the cardiac activities of the heart. Often the ECG signal needs to be captured for a long period of time in order to identify abnormalities in certain situations. Such signal apart of a large volume often is characterised by low quality due to the noise and other influences. In order to extract features in the ECG signal with time-varying characteristics at first need to be preprocessed with the best parameters. Also, it is useful to identify specific parts of the long lasting signal which have certain abnormalities and to direct the practitioner to those parts of the signal. In this work we present a method based on wavelet transform, standard deviation and variable threshold which achieves 100% accuracy in identifying the ECG signal peaks and heartbeat as well as identifying the standard deviation, providing a quick reference to abnormalities.

Keywords: Electrocardiogram-ECG, Arrhythmia, Signal Processing, Wavelet Transform, Standard Deviation

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