Search results for: nn based space vector modulator.

Authors: Hany Alashwal, Safaai Deris, Razib M. Othman

Abstract:

The protein domain structure has been widely used as the most informative sequence feature to computationally predict protein-protein interactions. However, in a recent study, a research group has reported a very high accuracy of 94% using hydrophobicity feature. Therefore, in this study we compare and verify the usefulness of protein domain structure and hydrophobicity properties as the sequence features. Using the Support Vector Machines (SVM) as the learning system, our results indicate that both features achieved accuracy of nearly 80%. Furthermore, domains structure had receiver operating characteristic (ROC) score of 0.8480 with running time of 34 seconds, while hydrophobicity had ROC score of 0.8159 with running time of 20,571 seconds (5.7 hours). These results indicate that protein-protein interaction can be predicted from domain structure with reliable accuracy and acceptable running time.

Keywords: Bioinformatics, protein-protein interactions, support vector machines, protein features.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1883

Authors: P. Pongsumpun, I.M. Tang

Abstract:

Plasmodium vivax malaria differs from P. falciparum malaria in that a person suffering from P. vivax infection can suffer relapses of the disease. This is due the parasite being able to remain dormant in the liver of the patients where it is able to re-infect the patient after a passage of time. During this stage, the patient is classified as being in the dormant class. The model to describe the transmission of P. vivax malaria consists of a human population divided into four classes, the susceptible, the infected, the dormant and the recovered. The effect of a time delay on the transmission of this disease is studied. The time delay is the period in which the P. vivax parasite develops inside the mosquito (vector) before the vector becomes infectious (i.e., pass on the infection). We analyze our model by using standard dynamic modeling method. Two stable equilibrium states, a disease free state E0 and an endemic state E1, are found to be possible. It is found that the E0 state is stable when a newly defined basic reproduction number G is less than one. If G is greater than one the endemic state E1 is stable. The conditions for the endemic equilibrium state E1 to be a stable spiral node are established. For realistic values of the parameters in the model, it is found that solutions in phase space are trajectories spiraling into the endemic state. It is shown that the limit cycle and chaotic behaviors can only be achieved with unrealistic parameter values.

Keywords: Equilibrium states, Hopf bifurcation, limit cyclebehavior, local stability, Plasmodium Vivax, time delay.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2209

Authors: Behnam Shirkhanghah, Vahid Shahbaznejhad-Fard, Houshyar Eimani-Kalesar, Babak Pahlevan

Abstract:

Flat double-layer grid is from category of space structures that are formed from two flat layers connected together with diagonal members. Increased stiffness and better seismic resistance in relation to other space structures are advantages of flat double layer space structures. The objective of this study is assessment and calculation of Behavior factor of flat double layer space structures. With regarding that these structures are used widely but Behavior factor used to design these structures against seismic force is not determined and exact, the necessity of study is obvious. This study is theoretical. In this study we used structures with span length of 16m and 20 m. All connections are pivotal. ANSYS software is used to non-linear analysis of structures.

Keywords: Behavior factor, Double-layer, Intensified resistance, Non-linear analysis

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2009

Authors: Mona Soliman Habib

Abstract:

This paper explores the scalability issues associated with solving the Named Entity Recognition (NER) problem using Support Vector Machines (SVM) and high-dimensional features. The performance results of a set of experiments conducted using binary and multi-class SVM with increasing training data sizes are examined. The NER domain chosen for these experiments is the biomedical publications domain, especially selected due to its importance and inherent challenges. A simple machine learning approach is used that eliminates prior language knowledge such as part-of-speech or noun phrase tagging thereby allowing for its applicability across languages. No domain-specific knowledge is included. The accuracy measures achieved are comparable to those obtained using more complex approaches, which constitutes a motivation to investigate ways to improve the scalability of multiclass SVM in order to make the solution more practical and useable. Improving training time of multi-class SVM would make support vector machines a more viable and practical machine learning solution for real-world problems with large datasets. An initial prototype results in great improvement of the training time at the expense of memory requirements.

Keywords: Named entity recognition, support vector machines, language independence, bioinformatics.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1657

Authors: C. P. Autry, A.W. Roscoe

Abstract:

Authentication protocols based on public key infrastructure (PKI) and trusted third party (TTP) are no longer adequate for industrial scale IoT networks thanks to issues such as low compute and power availability, the use of widely distributed and commercial off-the-shelf (COTS) systems, and the increasingly sophisticated attackers and attacks we now have to counter. For example, there is increasing concern about nation-state-based interference and future quantum computing capability. We have examined this space from first principles and have developed several approaches to group and point-to-point authentication for IoT that do not depend on the use of a centralised client-server model. We emphasise the use of quantum resistant primitives such as strong cryptographic hashing and the use multi-factor authentication.

Keywords: Authentication, enterprise IoT cybersecurity, public key infrastructure, trusted third party.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 429

Authors: Süha Yılmaz, Melih Turgut

Abstract:

These In this work, a regular unit speed curve in six dimensional Euclidean space, whose Frenet curvatures are constant, is considered. Thereafter, a method to calculate Frenet apparatus of this curve is presented.

Keywords: Classical Differential Geometry, Euclidean 6-space, Frenet Apparatus of the curves.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1256

Authors: E. A. Mlybari, M. S. Elbisy, A. H. Alshahri, O. M. Albarakati

Abstract:

Sea level rise threatens to increase the impact of future  storms and hurricanes on coastal communities. Accurate sea level  change prediction and supplement is an important task in determining  constructions and human activities in coastal and oceanic areas. In  this study, support vector machines (SVM) is proposed to predict  daily tidal levels along the Jeddah Coast, Saudi Arabia. The optimal  parameter values of kernel function are determined using a genetic  algorithm. The SVM results are compared with the field data and  with back propagation (BP). Among the models, the SVM is superior  to BPNN and has better generalization performance.

 

Keywords: Tides, Prediction, Support Vector Machines, Genetic Algorithm, Back-Propagation Neural Network, Risk, Hazards.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2356

Authors: Gbenga F. Akomolafe, Joseph Omojola, Ezekiel S. Joshua, Seyi C. Adediwura, Elijah T. Adesuji, Michael O. Odey, Oyinade A. Dedeke, Ayo H. Labulo

Abstract:

Microgravity is known to be a major abiotic stress in space which affects plants depending on the duration of exposure. In this work, tomatoes seeds were exposed to long hours of simulated microgravity condition using a one-axis clinostat. The seeds were sown on a 1.5% combination of plant nutrient and agar-agar solidified medium in three Petri dishes. One of the Petri dishes was mounted on the clinostat and allowed to rotate at the speed of 20 rpm for 72 hours, while the others were subjected to the normal gravity vector. The anatomical sections of both clinorotated and normal gravity plants were made after 72 hours and observed using a Phase-contrast digital microscope. The percentage germination, as well as the growth rate of the normal gravity seeds, was higher than the clinorotated ones. The germinated clinorotated roots followed different directions unlike the normal gravity ones which grew towards the direction of gravity vector. The clinostat was able to switch off gravistimulation. Distinct cellular arrangement was observed for tomatoes under normal gravity condition, unlike those of clinorotated ones. The root epidermis and cortex of normal gravity are thicker than the clinorotated ones. This implied that under long-term microgravity influence, plants do alter their anatomical features as a way of adapting to the stress condition.

Keywords: Anatomy, Clinostat, Germination, Microgravity, Lycopersicon esculentum.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1002

Authors: Y. V. Kim

Abstract:

This article presents an approach with regards to the Functional Testing of Space System (SS) that could be a space vehicle (spacecraft-S/C) and/or its equipment and components – S/C subsystems. This test should finalize the Space Qualification Tests (SQT) campaign. It could be considered as a generic test and used for a wide class of SS that, from the point of view of System Dynamics and Control Theory, may be described by the ordinary differential equations. The suggested methodology is based on using semi-natural experiment laboratory stand that does not require complicated, precise and expensive technological control-verification equipment. However, it allows for testing totally assembled system during Assembling, Integration and Testing (AIT) activities at the final phase of SQT, involving system hardware (HW) and software (SW). The test physically activates system input (sensors) and output (actuators) and requires recording their outputs in real time. The data are then inserted in a laboratory computer, where it is post-experiment processed by the MATLAB/Simulink Identification Toolbox. It allows for estimating the system dynamics in the form of estimation of its differential equation coefficients through the verification experimental test and comparing them with expected mathematical model, prematurely verified by mathematical simulation during the design process. Mathematical simulation results presented in the article show that this approach could be applicable and helpful in SQT practice. Further semi-natural experiments should specify detail requirements for the test laboratory equipment and test-procedures.

Keywords: system dynamics, space system ground tests, space qualification, system dynamics identification, satellite attitude control, assembling integration and testing

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 496

Authors: Ahmet Tekcan

Abstract:

Let X be a connected space, X be a space, let p : X -→ X be a continuous map and let (X, p) be a covering space of X. In the first section we give some preliminaries from covering spaces and their automorphism groups. In the second section we derive some algebraic properties of both universal and regular covering spaces (X, p) of X and also their automorphism groups A(X, p).

Keywords: covering space, universal covering, regular covering, fundamental group, automorphism group.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1983

Authors: Abdellatif Kasbi, Abderrafii Rahali

Abstract:

This paper appraises the performances of two control scenarios, for doubly fed induction generator (DFIG) operating in wind generation system (WGS), which are the direct decoupled control (DDC) and indirect decoupled control (IDC). Both control scenarios studied combines vector control and Maximum Power Point Tracking (MPPT) control theory so as to maximize the captured power through wind turbine. Modeling of DFIG based WGS and details of both control scenarios have been presented, a proportional integral controller is employed in the active and reactive power control loops for both control methods. The performance of the both control scenarios in terms of power reference tracking and robustness against machine parameters inconstancy has been shown, analyzed and compared, which can afford a reference to the operators and engineers of a wind farm. All simulations have been implemented via MATLAB/Simulink.

Keywords: DFIG, WGS, DDC, IDC, vector control, MPPT.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 672

Authors: Usha Lokala, Srinivas Nowduri, Prabhakar K. Sharma

Abstract:

Useful information has been extracted from the road accident data in United Kingdom (UK), using data analytics method, for avoiding possible accidents in rural and urban areas. This analysis make use of several methodologies such as data integration, support vector machines (SVM), correlation machines and multinomial goodness. The entire datasets have been imported from the traffic department of UK with due permission. The information extracted from these huge datasets forms a basis for several predictions, which in turn avoid unnecessary memory lapses. Since data is expected to grow continuously over a period of time, this work primarily proposes a new framework model which can be trained and adapt itself to new data and make accurate predictions. This work also throws some light on use of SVM’s methodology for text classifiers from the obtained traffic data. Finally, it emphasizes the uniqueness and adaptability of SVMs methodology appropriate for this kind of research work.

Keywords: Road accident, machine learning, support vector machines.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1092

Authors: Abdulaziz Alsadhan, Naveed Khan

Abstract:

In recent years intrusions on computer network are the major security threat. Hence, it is important to impede such intrusions. The hindrance of such intrusions entirely relies on its detection, which is primary concern of any security tool like Intrusion detection system (IDS). Therefore, it is imperative to accurately detect network attack. Numerous intrusion detection techniques are available but the main issue is their performance. The performance of IDS can be improved by increasing the accurate detection rate and reducing false positive. The existing intrusion detection techniques have the limitation of usage of raw dataset for classification. The classifier may get jumble due to redundancy, which results incorrect classification. To minimize this problem, Principle component analysis (PCA), Linear Discriminant Analysis (LDA) and Local Binary Pattern (LBP) can be applied to transform raw features into principle features space and select the features based on their sensitivity. Eigen values can be used to determine the sensitivity. To further classify, the selected features greedy search, back elimination, and Particle Swarm Optimization (PSO) can be used to obtain a subset of features with optimal sensitivity and highest discriminatory power. This optimal feature subset is used to perform classification. For classification purpose, Support Vector Machine (SVM) and Multilayer Perceptron (MLP) are used due to its proven ability in classification. The Knowledge Discovery and Data mining (KDD’99) cup dataset was considered as a benchmark for evaluating security detection mechanisms. The proposed approach can provide an optimal intrusion detection mechanism that outperforms the existing approaches and has the capability to minimize the number of features and maximize the detection rates.

Keywords: Particle Swarm Optimization (PSO), Principle component analysis (PCA), Linear Discriminant Analysis (LDA), Local Binary Pattern (LBP), Support Vector Machine (SVM), Multilayer Perceptron (MLP).

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2722

Authors: M. Beisenbi, A. Sagymbay, S. Beisembina, A. Satpayeva

Abstract:

In this paper, the problem of unstable and deterministic chaotic processes in control systems is considered. The synthesis of a control system in the class of two-parameter structurally stable mappings is demonstrated. This is realized via the gradient-velocity method of Lyapunov vector functions. It is shown that the gradient-velocity method of Lyapunov vector functions allows generating an aperiodic robust stable system with the desired characteristics. A simple solution to the problem of synthesis of control systems for unstable and deterministic chaotic processes is obtained. Moreover, it is applicable for complex systems.

Keywords: Control system synthesis, deterministic chaotic processes, Lyapunov vector function, robust stability, structurally stable mappings.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 328

Authors: Rozilawati Binti Dollah, Masaki Aono

Abstract:

Classifying biomedical literature is a difficult and challenging task, especially when a large number of biomedical articles should be organized into a hierarchical structure. In this paper, we present an approach for classifying a collection of biomedical text abstracts downloaded from Medline database with the help of ontology alignment. To accomplish our goal, we construct two types of hierarchies, the OHSUMED disease hierarchy and the Medline abstract disease hierarchies from the OHSUMED dataset and the Medline abstracts, respectively. Then, we enrich the OHSUMED disease hierarchy before adapting it to ontology alignment process for finding probable concepts or categories. Subsequently, we compute the cosine similarity between the vector in probable concepts (in the “enriched" OHSUMED disease hierarchy) and the vector in Medline abstract disease hierarchies. Finally, we assign category to the new Medline abstracts based on the similarity score. The results obtained from the experiments show the performance of our proposed approach for hierarchical classification is slightly better than the performance of the multi-class flat classification.

Keywords: Biomedical literature, hierarchical text classification, ontology alignment, text mining.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1984

Authors: J. P. Dubois, O. M. Abdul-Latif

Abstract:

Support Vector Machine (SVM) is a statistical learning tool that was initially developed by Vapnik in 1979 and later developed to a more complex concept of structural risk minimization (SRM). SVM is playing an increasing role in applications to detection problems in various engineering problems, notably in statistical signal processing, pattern recognition, image analysis, and communication systems. In this paper, SVM was applied to the detection of SAR (synthetic aperture radar) images in the presence of partially developed speckle noise. The simulation was done for single look and multi-look speckle models to give a complete overlook and insight to the new proposed model of the SVM-based detector. The structure of the SVM was derived and applied to real SAR images and its performance in terms of the mean square error (MSE) metric was calculated. We showed that the SVM-detected SAR images have a very low MSE and are of good quality. The quality of the processed speckled images improved for the multi-look model. Furthermore, the contrast of the SVM detected images was higher than that of the original non-noisy images, indicating that the SVM approach increased the distance between the pixel reflectivity levels (the detection hypotheses) in the original images.

Keywords: Least Square-Support Vector Machine, SyntheticAperture Radar. Partially Developed Speckle, Multi-Look Model.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1499

Authors: Rihab Hamdi, Amel Hadri Hamida, Fatiha Khelili, Sakina Zerouali, Ouafae Bennis

Abstract:

This paper features a comparative study performance of sliding mode controller (SMC) for closed-loop voltage control of direct current to direct current (DC-DC) three-cells buck converter connected in parallel, operating in continuous conduction mode (CCM), based on pulse-width modulation (PWM) with SMC based on hysteresis modulation (HM) where an adaptive feedforward technique is adopted. On one hand, for the PWM-based SM, the approach is to incorporate a fixed-frequency PWM scheme which is effectively a variant of SM control. On the other hand, for the HM-based SM, oncoming an adaptive feedforward control that makes the hysteresis band variable in the hysteresis modulator of the SM controller in the aim to restrict the switching frequency variation in the case of any change of the line input voltage or output load variation are introduced. The results obtained under load change, input change and reference change clearly demonstrates a similar dynamic response of both proposed techniques, their effectiveness is fast and smooth tracking of the desired output voltage. The PWM-based SM technique has greatly improved the dynamic behavior with a bit advantageous compared to the HM-based SM technique, as well as provide stability in any operating conditions. Simulation studies in MATLAB/Simulink environment have been performed to verify the concept.

Keywords: Sliding mode control, pulse-width modulation, hysteresis modulation, DC-DC converter, parallel multi-cells converter, robustness.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 731

Authors: Rahul Malhotra

Abstract:

The field of wireless sensor networks (WSN) engages a lot of associates in the research community as an interdisciplinary field of interest. This type of network is inexpensive, multifunctionally attributable to advances in micro-electromechanical systems and conjointly the explosion and expansion of wireless communications. A mobile ad hoc network is a wireless network without fastened infrastructure or federal management. Due to the infrastructure-less mode of operation, mobile ad-hoc networks are gaining quality. During this work, we have performed an efficient performance study of the two major routing protocols: Ad hoc On-Demand Distance Vector Routing (AODV) and Dynamic Source Routing (DSR) protocols. We have used an accurate simulation model supported NS2 for this purpose. Our simulation results showed that AODV mitigates the drawbacks of the DSDV and provides better performance as compared to DSDV.

Keywords: Routing protocols, mobility, Mobile Ad-hoc Networks, Ad-hoc On-demand Distance Vector, Dynamic Source Routing, Destination Sequence Distance Vector, Quality of Service.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 673

Authors: M. Bakhouya, S. A. Bahra, T. El-Ghazawi

Abstract:

The Partitioned Global Address Space (PGAS) programming paradigm offers ease-of-use in expressing parallelism through a global shared address space while emphasizing performance by providing locality awareness through the partitioning of this address space. Therefore, the interest in PGAS programming languages is growing and many new languages have emerged and are becoming ubiquitously available on nearly all modern parallel architectures. Recently, new parallel machines with multiple cores are designed for targeting high performance applications. Most of the efforts have gone into benchmarking but there are a few examples of real high performance applications running on multicore machines. In this paper, we present and evaluate a parallelization technique for implementing a local DNA sequence alignment algorithm using a PGAS based language, UPC (Unified Parallel C) on a chip multithreading architecture, the UltraSPARC T1.

Keywords: Partitioned Global Address Space, Unified Parallel C, Multicore machines, Multi-threading Architecture, Sequence alignment.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1351

Authors: Dibyendu Ghoshal, Shimal Das

Abstract:

Image compression based on fractal coding is a lossy compression method and normally used for gray level images range and domain blocks in rectangular shape. Fractal based digital image compression technique provide a large compression ratio and in this paper, it is proposed using YUV colour space and the fractal theory which is based on iterated transformation. Fractal geometry is mainly applied in the current study towards colour image compression coding. These colour images possesses correlations among the colour components and hence high compression ratio can be achieved by exploiting all these redundancies. The proposed method utilises the self-similarity in the colour image as well as the cross-correlations between them. Experimental results show that the greater compression ratio can be achieved with large domain blocks but more trade off in image quality is good to acceptable at less than 1 bit per pixel.

Keywords: Fractal coding, Iterated Function System (IFS), Image compression, YUV colour space.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1943

Authors: R. Mallika, V. Saravanan

Abstract:

This paper gives a novel method for improving classification performance for cancer classification with very few microarray Gene expression data. The method employs classification with individual gene ranking and gene subset ranking. For selection and classification, the proposed method uses the same classifier. The method is applied to three publicly available cancer gene expression datasets from Lymphoma, Liver and Leukaemia datasets. Three different classifiers namely Support vector machines-one against all (SVM-OAA), K nearest neighbour (KNN) and Linear Discriminant analysis (LDA) were tested and the results indicate the improvement in performance of SVM-OAA classifier with satisfactory results on all the three datasets when compared with the other two classifiers.

Keywords: Support vector machines-one against all, cancerclassification, Linear Discriminant analysis, K nearest neighbour, microarray gene expression, gene pair ranking.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2522

Authors: Tanawat Limwathanagura, Chartree Sithananun, Teekayu Limchamroon, Thanyarat Singhanart

Abstract:

The objective of this paper is to study the analysis and testing for determining the torsional stiffness of the student formula-s space frame. From past study, the space frame for Chulalongkorn University Student Formula team used in 2011 TSAE Auto Challenge Student Formula in Thailand was designed by considering required mass and torsional stiffness based on the numerical method and experimental method. The numerical result was compared with the experimental results to verify the torsional stiffness of the space frame. It can be seen from the large error of torsional stiffness of 2011 frame that the experimental result can not verify by the numerical analysis due to the different between the numerical model and experimental setting. In this paper, the numerical analysis and experiment of the same 2011 frame model is performed by improving the model setting. The improvement of both numerical analysis and experiment are discussed to confirm that the models from both methods are same. After the frame was analyzed and tested, the results are compared to verify the torsional stiffness of the frame. It can be concluded that the improved analysis and experiments can used to verify the torsional stiffness of the space frame.

Keywords: Space Frame, Student Formula, Torsional Stiffness, TSAE Auto Challenge

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 7963

Authors: Kumar Padmanabh, Rajarshi Roy

Abstract:

In this paper a special kind of buffer management policy is studied where the packet are preempted even when sufficient space is available in the buffer for incoming packets. This is done to congestion for future incoming packets to improve QoS for certain type of packets. This type of study has been done in past for ATM type of scenario. We extend the same for heterogeneous traffic where data rate and size of the packets are very versatile in nature. Typical example of this scenario is the buffer management in Differentiated Service Router. There are two aspects that are of interest. First is the packet size: whether all packets have same or different sizes. Second aspect is the value or space priority of the packets, do all packets have the same space priority or different packets have different space priorities. We present two types of policies to achieve QoS goals for packets with different priorities: the push out scheme and the expelling scheme. For this work the scenario of packets of variable length is considered with two space priorities and main goal is to minimize the total weighted packet loss. Simulation and analytical studies show that, expelling policies can outperform the push out policies when it comes to offering variable QoS for packets of two different priorities and expelling policies also help improve the amount of admissible load. Some other comparisons of push out and expelling policies are also presented using simulations.

Keywords: Buffer Management Policy, Diffserv, ATM, Pushout Policy, Expeling Policy.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1364

Authors: J. Mahanta, P.K. Das

Abstract:

A new class of fuzzy closed sets, namely fuzzy weakly closed set in a fuzzy topological space is introduced and it is established that this class of fuzzy closed sets lies between fuzzy closed sets and fuzzy generalized closed sets. Alongwith the study of fundamental results of such closed sets, we define and characterize fuzzy weakly compact space and fuzzy weakly closed space.

Keywords: Fuzzy weakly-closed set, fuzzy weakly-closed space, fuzzy weakly-compactness, MSC: 54A40, 54D30.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1742

Authors: A. Nachour, L. Ouzizi, Y. Aoura

Abstract:

Recent developments on multi-agent system have brought a new research field on image processing. Several algorithms are used simultaneously and improved in deferent applications while new methods are investigated. This paper presents a new automatic method for edge detection using several agents and many different actions. The proposed multi-agent system is based on parallel agents that locally perceive their environment, that is to say, pixels and additional environmental information. This environment is built using Vector Field Convolution that attract free agent to the edges. Problems of partial, hidden or edges linking are solved with the cooperation between agents. The presented method was implemented and evaluated using several examples on different synthetic and medical images. The obtained experimental results suggest that this approach confirm the efficiency and accuracy of detected edge.

Keywords: Edge detection, medical MR images, multi-agent systems, vector field convolution.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1855

Authors: Xiaohua Liu, Juan F. Beltran, Nishant Mohanchandra, Godfried T. Toussaint

Abstract:

Support vector machines (SVMs) are considered to be the best machine learning algorithms for minimizing the predictive probability of misclassification. However, their drawback is that for large data sets the computation of the optimal decision boundary is a time consuming function of the size of the training set. Hence several methods have been proposed to speed up the SVM algorithm. Here three methods used to speed up the computation of the SVM classifiers are compared experimentally using a musical genre classification problem. The simplest method pre-selects a random sample of the data before the application of the SVM algorithm. Two additional methods use proximity graphs to pre-select data that are near the decision boundary. One uses k-Nearest Neighbor graphs and the other Relative Neighborhood Graphs to accomplish the task.

Keywords: Machine learning, data mining, support vector machines, proximity graphs, relative-neighborhood graphs, k-nearestneighbor graphs, random sampling, training data condensation.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1888

Authors: Simon Lessard, Pascal Bigras, Caroline Lau, Daniel Roy, Gilles Soulez, Jacques A. de Guise

Abstract:

The segmentation of endovascular tools in fluoroscopy images can be accurately performed automatically or by minimum user intervention, using known modern techniques. It has been proven in literature, but no clinical implementation exists so far because the computational time requirements of such technology have not yet been met. A classical segmentation scheme is composed of edge enhancement filtering, line detection, and segmentation. A new method is presented that consists of a vector that propagates in the image to track an edge as it advances. The filtering is performed progressively in the projected path of the vector, whose orientation allows for oriented edge detection, and a minimal image area is globally filtered. Such an algorithm is rapidly computed and can be implemented in real-time applications. It was tested on medical fluoroscopy images from an endovascular cerebral intervention. Ex- periments showed that the 2D tracking was limited to guidewires without intersection crosspoints, while the 3D implementation was able to cope with such planar difficulties.

Keywords: Edge detection, Line Enhancement, Segmentation, Fluoroscopy.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1699

Authors: C. Slim

Abstract:

This paper presents an integrated model, which hybridized data envelopment analysis (DEA) and support vector machine (SVM) together, to class countries according to their efficiency and performance. This model takes into account aspects of multi-dimensional indicators, decision-making hierarchy and relativity of measurement. Starting from a set of indicators of performance as exhaustive as possible, a process of successive aggregations has been developed to attain an overall evaluation of a country’s competitiveness.

Keywords: Artificial neural networks, support vector machine, data envelopment analysis, aggregations, indicators of performance.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1033

Authors: N.Subramanian, C.Murugesan

Abstract:

This paper is devoted to the study of the general properties of Orlicz space of entire sequence of fuzzy numbers by using infinite matrices.

Keywords: Fuzzy numbers, infinite matrix, Orlicz space, entiresequence.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1169

Authors: Eu Tteum Ha, Kwang Ryel Ryu

Abstract:

As smartphones are equipped with various sensors, there have been many studies focused on using these sensors to create valuable applications. Human activity recognition is one such application motivated by various welfare applications, such as the support for the elderly, measurement of calorie consumption, lifestyle and exercise patterns analyses, and so on. One of the challenges one faces when using smartphone sensors for activity recognition is that the number of sensors should be minimized to save battery power. In this paper, we show that a fairly accurate classifier can be built that can distinguish ten different activities by using only a single sensor data, i.e., the smartphone accelerometer data. The approach that we adopt to deal with this twelve-class problem uses various methods. The features used for classifying these activities include not only the magnitude of acceleration vector at each time point, but also the maximum, the minimum, and the standard deviation of vector magnitude within a time window. The experiments compared the performance of four kinds of basic multi-class classifiers and the performance of four kinds of ensemble learning methods based on three kinds of basic multi-class classifiers. The results show that while the method with the highest accuracy is ECOC based on Random forest.

Keywords: Ensemble learning, activity recognition, smartphone accelerometer.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2134