Search results for: Multiple correspondence analysis
9393 Multiple Positive Periodic Solutions of a Competitor-Competitor-Mutualist Lotka-Volterra System with Harvesting Terms
Authors: Yongkun Li, Erliang Xu
Abstract:
In this paper, by using Mawhin-s continuation theorem of coincidence degree theory, we establish the existence of multiple positive periodic solutions of a competitor-competitor-mutualist Lotka-Volterra system with harvesting terms. Finally, an example is given to illustrate our results.
Keywords: Positive periodic solutions, competitor-competitor mutualist Lotka-Volterra systems, coincidence degree, harvesting term.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 13439392 Existence of Multiple Positive Periodic Solutions to n Species Nonautonomous Lotka-Volterra Cooperative Systems with Harvesting Terms
Authors: Kaihong Zhao
Abstract:
In this paper, the existence of 2n positive periodic solutions for n species non-autonomous Lotka-Volterra cooperative systems with harvesting terms is established by using Mawhin-s continuation theorem of coincidence degree theory and matrix inequality. An example is given to illustrate the effectiveness of our results.
Keywords: Multiple positive periodic solutions, Nonautonomous Lotka-Volterra cooperative system, Coincidence degree, Harvesting term.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 13269391 Decimation Filter Design Toolbox for Multi-Standard Wireless Transceivers using MATLAB
Authors: Shahana T. K., Babita R. Jose, K. Poulose Jacob, Sreela Sasi
Abstract:
The demand for new telecommunication services requiring higher capacities, data rates and different operating modes have motivated the development of new generation multi-standard wireless transceivers. A multi-standard design often involves extensive system level analysis and architectural partitioning, typically requiring extensive calculations. In this research, a decimation filter design tool for wireless communication standards consisting of GSM, WCDMA, WLANa, WLANb, WLANg and WiMAX is developed in MATLAB® using GUIDE environment for visual analysis. The user can select a required wireless communication standard, and obtain the corresponding multistage decimation filter implementation using this toolbox. The toolbox helps the user or design engineer to perform a quick design and analysis of decimation filter for multiple standards without doing extensive calculation of the underlying methods.
Keywords: Decimation filter, MATLAB® toolbox, Multistandard transceivers, Sigma-delta A/D converter.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 29139390 Lower Order Harmonics Minimisation in CHB Inverter Using GA and Decomposition by WT
Authors: V. Joshi Manohar, P. Sujatha, K. S. R. Anjaneyulu
Abstract:
Nowadays Multilevel inverters are widely using in various applications. Modulation strategy at fundamental switching frequency like, SHEPWM is prominent technique to eliminate lower order of harmonics with less switching losses and better harmonic profile. The equations which are formed by SHE are highly nonlinear transcendental in nature, there may exist single, multiple or even no solutions for a particular MI. However, some loads such as electrical drives, it is required to operate in whole range of MI. In order to solve SHE equations for whole range of MI, intelligent techniques are well suited to solve equations so as to produce lest %THDV. Hence, this paper uses Continuous genetic algorithm for minimising harmonics. This paper also presents wavelet based analysis of harmonics. The developed algorithm is simulated and %THD from FFT analysis and Wavelet analysis are compared. MATLAB programming environment and SIMULINK models are used whenever necessary.
Keywords: Cascade H-Bridge Inverter (CHB), Continuous Genetic Algorithm (C-GA), Selective Harmonic Elimination Pulse Width Modulation (SHEPWM), Total Harmonic Distortion (%THDv), Wavelet Transform (WT).
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 29019389 Forecasting Direct Normal Irradiation at Djibouti Using Artificial Neural Network
Authors: Ahmed Kayad Abdourazak, Abderafi Souad, Zejli Driss, Idriss Abdoulkader Ibrahim
Abstract:
In this paper Artificial Neural Network (ANN) is used to predict the solar irradiation in Djibouti for the first Time that is useful to the integration of Concentrating Solar Power (CSP) and sites selections for new or future solar plants as part of solar energy development. An ANN algorithm was developed to establish a forward/reverse correspondence between the latitude, longitude, altitude and monthly solar irradiation. For this purpose the German Aerospace Centre (DLR) data of eight Djibouti sites were used as training and testing in a standard three layers network with the back propagation algorithm of Lavenber-Marquardt. Results have shown a very good agreement for the solar irradiation prediction in Djibouti and proves that the proposed approach can be well used as an efficient tool for prediction of solar irradiation by providing so helpful information concerning sites selection, design and planning of solar plants.Keywords: Artificial neural network, solar irradiation, concentrated solar power, Lavenberg-Marquardt.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 10659388 Optimal Location of Multi Type Facts Devices for Multiple Contingencies Using Particle Swarm Optimization
Authors: S. Sutha, N. Kamaraj
Abstract:
In deregulated operating regime power system security is an issue that needs due thoughtfulness from researchers in the horizon of unbundling of generation and transmission. Electric power systems are exposed to various contingencies. Network contingencies often contribute to overloading of branches, violation of voltages and also leading to problems of security/stability. To maintain the security of the systems, it is desirable to estimate the effect of contingencies and pertinent control measurement can be taken on to improve the system security. This paper presents the application of particle swarm optimization algorithm to find the optimal location of multi type FACTS devices in a power system in order to eliminate or alleviate the line over loads. The optimizations are performed on the parameters, namely the location of the devices, their types, their settings and installation cost of FACTS devices for single and multiple contingencies. TCSC, SVC and UPFC are considered and modeled for steady state analysis. The selection of UPFC and TCSC suitable location uses the criteria on the basis of improved system security. The effectiveness of the proposed method is tested for IEEE 6 bus and IEEE 30 bus test systems.
Keywords: Contingency Severity Index, Particle Swarm Optimization, Performance Index, Static Security Assessment.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 27519387 Studding of Number of Dataset on Precision of Estimated Saturated Hydraulic Conductivity
Authors: M. Siosemarde, M. Byzedi
Abstract:
Saturated hydraulic conductivity of Soil is an important property in processes involving water and solute flow in soils. Saturated hydraulic conductivity of soil is difficult to measure and can be highly variable, requiring a large number of replicate samples. In this study, 60 sets of soil samples were collected at Saqhez region of Kurdistan province-IRAN. The statistics such as Correlation Coefficient (R), Root Mean Square Error (RMSE), Mean Bias Error (MBE) and Mean Absolute Error (MAE) were used to evaluation the multiple linear regression models varied with number of dataset. In this study the multiple linear regression models were evaluated when only percentage of sand, silt, and clay content (SSC) were used as inputs, and when SSC and bulk density, Bd, (SSC+Bd) were used as inputs. The R, RMSE, MBE and MAE values of the 50 dataset for method (SSC), were calculated 0.925, 15.29, -1.03 and 12.51 and for method (SSC+Bd), were calculated 0.927, 15.28,-1.11 and 12.92, respectively, for relationship obtained from multiple linear regressions on data. Also the R, RMSE, MBE and MAE values of the 10 dataset for method (SSC), were calculated 0.725, 19.62, - 9.87 and 18.91 and for method (SSC+Bd), were calculated 0.618, 24.69, -17.37 and 22.16, respectively, which shows when number of dataset increase, precision of estimated saturated hydraulic conductivity, increases.Keywords: dataset, precision, saturated hydraulic conductivity, soil and statistics.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 17829386 Unified, Low-Cost Analysis Framework for the Cycling Situation in Cities
Authors: Joerg Schweizer, Jason N. Meggs, Nazanin R. Dehkordi, Frederico Rupi, Anton Pashkevich
Abstract:
We propose a low-cost uniform analysis framework allowing comparison of the strengths and weaknesses of the bicycling experience within and between cities. A primary component is an expedient, one-page mobility survey from which mode share is calculated. The bicycle mode share of many cities remains unknown, creating a serious barrier for both scientists and policy makers aiming to understand and increase rates of bicycling. Because of its low cost and expedience, this framework could be replicated widely, uniformly filling the data gap. The framework has been applied to 13 Central European cities with success. Data is collected on multiple modes with specific questions regarding both behavior and quality of travel experience. Individual preferences are also collected, examining the conditions under which respondents would change behavior to adopt more sustainable modes (bicycling or public transportation). A broad analysis opportunity results, intended to inform policy choices.Keywords: bicycling, modal splits, transport policy, surveys.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 13969385 A Sub-Pixel Image Registration Technique with Applications to Defect Detection
Authors: Zhen-Hui Hu, Jyh-Shong Ju, Ming-Hwei Perng
Abstract:
This paper presents a useful sub-pixel image registration method using line segments and a sub-pixel edge detector. In this approach, straight line segments are first extracted from gray images at the pixel level before applying the sub-pixel edge detector. Next, all sub-pixel line edges are mapped onto the orientation-distance parameter space to solve for line correspondence between images. Finally, the registration parameters with sub-pixel accuracy are analytically solved via two linear least-square problems. The present approach can be applied to various fields where fast registration with sub-pixel accuracy is required. To illustrate, the present approach is applied to the inspection of printed circuits on a flat panel. Numerical example shows that the present approach is effective and accurate when target images contain a sufficient number of line segments, which is true in many industrial problems.Keywords: Defect detection, Image registration, Straight line segment, Sub-pixel.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 19439384 Properties of Bacterial Nanocellulose for Scenic Arts
Abstract:
Kombucha (a symbiotic culture of bacteria and yeast) produces material capable of acquiring multiple shapes and textures that change significantly under different environment or temperature variations (e.g., when it is exposed to wet conditions), properties that may be explored in the scenic industry. This paper presents an analysis of its specific characteristics, exploring them as a non-conventional material for arts and performance. Costume Design uses surfaces as a powerful way of expression to represent concepts and stories; it may apply the unique features of nano bacterial cellulose (NBC) as assets in this artistic context. A mix of qualitative and quantitative (interventionist) methodology approaches were used such as review of relevant literature to deepen knowledge on the research topic (crossing bibliography from different fields of studies: biology, art, costume design, etc.); as well as descriptive methods: laboratorial experiments, document quantities, observation to identify material properties and possibilities used to express a multiple narrative ideas, concepts and feelings. The results confirmed that NBC is an interactive and versatile material viable to be used in an alternative scenic context; its unique aesthetic and performative qualities, which change in contact to moisture, are resources that can be used to show a visual and poetic impact on stage.
Keywords: Biotechnological materials, contemporary dance, costume design, nano bacterial cellulose, performing arts.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 4809383 Multiple Peaks Tracking Algorithm using Particle Swarm Optimization Incorporated with Artificial Neural Network
Authors: Mei Shan Ngan, Chee Wei Tan
Abstract:
Due to the non-linear characteristics of photovoltaic (PV) array, PV systems typically are equipped with the capability of maximum power point tracking (MPPT) feature. Moreover, in the case of PV array under partially shaded conditions, hotspot problem will occur which could damage the PV cells. Partial shading causes multiple peaks in the P-V characteristic curves. This paper presents a hybrid algorithm of Particle Swarm Optimization (PSO) and Artificial Neural Network (ANN) MPPT algorithm for the detection of global peak among the multiple peaks in order to extract the true maximum energy from PV panel. The PV system consists of PV array, dc-dc boost converter controlled by the proposed MPPT algorithm and a resistive load. The system was simulated using MATLAB/Simulink package. The simulation results show that the proposed algorithm performs well to detect the true global peak power. The results of the simulations are analyzed and discussed.Keywords: Photovoltaic (PV), Partial Shading, Maximum Power Point Tracking (MPPT), Particle Swarm Optimization (PSO) and Artificial Neural Network (ANN)
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 37439382 Multi-labeled Data Expressed by a Set of Labels
Authors: Tetsuya Furukawa, Masahiro Kuzunishi
Abstract:
Collected data must be organized to be utilized efficiently, and hierarchical classification of data is efficient approach to organize data. When data is classified to multiple categories or annotated with a set of labels, users request multi-labeled data by giving a set of labels. There are several interpretations of the data expressed by a set of labels. This paper discusses which data is expressed by a set of labels by introducing orders for sets of labels and shows that there are four types of orders, which are characterized by whether the labels of expressed data includes every label of the given set of labels within the range of the set. Desirable properties of the orders, data is also expressed by the higher set of labels and different sets of labels express different data, are discussed for the orders.
Keywords: Classification Hierarchies, Multi-labeled Data, Multiple Classificaiton, Orders of Sets of Labels
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 12919381 Effective Personal Knowledge Management: A Proposed Online Framework
Authors: Shahrinaz Ismail, Mohd Sharifuddin Ahmad
Abstract:
This paper presents an analytical framework for an effective online personal knowledge management (PKM) of knowledge workers. The development of this framework is prompted by our qualitative research on the PKM processes and cognitive enablers of knowledge workers in eight organisations selected from three main industries in Malaysia. This multiple-case research identifies the relationships between the effectiveness of four online PKM processes: get/retrieve, understand/analyse, share, and connect. It also establishes the importance of cognitive enablers that mediate this relationship, namely, method, identify, decide and drive. Qualitative analysis is presented as the findings, supported by the preceded quantitative analysis on an exploratory questionnaire survey.Keywords: Bottom-up approach, knowledge organisation, organisational knowledge management, personal knowledge management, software agent technology.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 24699380 Efficient Design Optimization of Multi-State Flow Network for Multiple Commodities
Authors: Yu-Cheng Chou, Po Ting Lin
Abstract:
The network of delivering commodities has been an important design problem in our daily lives and many transportation applications. The delivery performance is evaluated based on the system reliability of delivering commodities from a source node to a sink node in the network. The system reliability is thus maximized to find the optimal routing. However, the design problem is not simple because (1) each path segment has randomly distributed attributes; (2) there are multiple commodities that consume various path capacities; (3) the optimal routing must successfully complete the delivery process within the allowable time constraints. In this paper, we want to focus on the design optimization of the Multi-State Flow Network (MSFN) for multiple commodities. We propose an efficient approach to evaluate the system reliability in the MSFN with respect to randomly distributed path attributes and find the optimal routing subject to the allowable time constraints. The delivery rates, also known as delivery currents, of the path segments are evaluated and the minimal-current arcs are eliminated to reduce the complexity of the MSFN. Accordingly, the correct optimal routing is found and the worst-case reliability is evaluated. It has been shown that the reliability of the optimal routing is at least higher than worst-case measure. Two benchmark examples are utilized to demonstrate the proposed method. The comparisons between the original and the reduced networks show that the proposed method is very efficient.
Keywords: Multiple Commodities, Multi-State Flow Network (MSFN), Time Constraints, Worst-Case Reliability (WCR)
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 14369379 Automatic Threshold Search for Heat Map Based Feature Selection: A Cancer Dataset Analysis
Authors: Carlos Huertas, Reyes Juarez-Ramirez
Abstract:
Public health is one of the most critical issues today; therefore, there is great interest to improve technologies in the area of diseases detection. With machine learning and feature selection, it has been possible to aid the diagnosis of several diseases such as cancer. In this work, we present an extension to the Heat Map Based Feature Selection algorithm, this modification allows automatic threshold parameter selection that helps to improve the generalization performance of high dimensional data such as mass spectrometry. We have performed a comparison analysis using multiple cancer datasets and compare against the well known Recursive Feature Elimination algorithm and our original proposal, the results show improved classification performance that is very competitive against current techniques.Keywords: Feature selection, mass spectrometry, biomarker discovery, cancer.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 15729378 Relay Node Placement for Connectivity Restoration in Wireless Sensor Networks Using Genetic Algorithms
Authors: Hanieh Tarbiat Khosrowshahi, Mojtaba Shakeri
Abstract:
Wireless Sensor Networks (WSNs) consist of a set of sensor nodes with limited capability. WSNs may suffer from multiple node failures when they are exposed to harsh environments such as military zones or disaster locations and lose connectivity by getting partitioned into disjoint segments. Relay nodes (RNs) are alternatively introduced to restore connectivity. They cost more than sensors as they benefit from mobility, more power and more transmission range, enforcing a minimum number of them to be used. This paper addresses the problem of RN placement in a multiple disjoint network by developing a genetic algorithm (GA). The problem is reintroduced as the Steiner tree problem (which is known to be an NP-hard problem) by the aim of finding the minimum number of Steiner points where RNs are to be placed for restoring connectivity. An upper bound to the number of RNs is first computed to set up the length of initial chromosomes. The GA algorithm then iteratively reduces the number of RNs and determines their location at the same time. Experimental results indicate that the proposed GA is capable of establishing network connectivity using a reasonable number of RNs compared to the best existing work.
Keywords: Connectivity restoration, genetic algorithms, multiple-node failure, relay nodes, wireless sensor networks.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 10899377 Effects of Knitting Variables for Pressure Controlling of Tubular Compression Fabrics
Authors: Yu Shi, Rong Liu, Jingyun Lv
Abstract:
Compression textiles with ergonomic-fit and controllable pressure performance have demonstrated positive effect on prevention and treatment of chronic venous insufficiency (CVI). Well-designed compression textile products contribute to improving user compliance in their daily application. This study explored the effects of multiple knitting variables (yarn-machinery settings) on the physical-mechanical properties and the produced pressure magnitudes of tubular compression fabrics (TCFs) through experimental testing and multiple regression modeling. The results indicated that fabric physical (stitch densities and circumference) and mechanical (tensile) properties were affected by the linear density of inlay yarns, which, to some extent, influenced pressure magnitudes of the TCFs. Knitting variables (e.g., feeding velocity of inlay yarns and loop size settings) can alter circumferences and tensile properties of tubular fabrics, respectively, and significantly varied pressure values of the TCFs. This study enhanced the understanding of the effects of knitting factors on pressure controlling of TCFs, thus facilitating dimension and pressure design of compression textiles in future development.
Keywords: Laid-in knitted fabric, yarn-machinery settings, pressure magnitudes, quantitative analysis, compression textiles.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2369376 Microwave Imaging by Application of Information Theory Criteria in MUSIC Algorithm
Authors: M. Pourahmadi
Abstract:
The performance of time-reversal MUSIC algorithm will be dramatically degrades in presence of strong noise and multiple scattering (i.e. when scatterers are close to each other). This is due to error in determining the number of scatterers. The present paper provides a new approach to alleviate such a problem using an information theoretic criterion referred as minimum description length (MDL). The merits of the novel approach are confirmed by the numerical examples. The results indicate the time-reversal MUSIC yields accurate estimate of the target locations with considerable noise and multiple scattering in the received signals.
Keywords: Microwave imaging, Time reversal, MUSIC algorithm, Minimum Description Length (MDL).
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 17109375 Minimizing Examinee Collusion with a Latin- Square Treatment Structure
Authors: M. H. Omar
Abstract:
Cheating on standardized tests has been a major concern as it potentially minimizes measurement precision. One major way to reduce cheating by collusion is to administer multiple forms of a test. Even with this approach, potential collusion is still quite large. A Latin-square treatment structure for distributing multiple forms is proposed to further reduce the colluding potential. An index to measure the extent of colluding potential is also proposed. Finally, with a simple algorithm, the various Latin-squares were explored to find the best structure to keep the colluding potential to a minimum.Keywords: Colluding pairs, Scale for Colluding Potential, Latin-Square Structure, Minimization of Cheating.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 11569374 Adaptive Subchannel Allocation for MC-CDMA System
Authors: Cuiran Li, Jianli Xie, Chengshu Li
Abstract:
Multicarrier code-division multiple-access is one of the effective techniques to gain its multiple access capability, robustness against fading, and to mitigate the ISI. In this paper, we propose an improved mulcarrier CDMA system with adaptive subchannel allocation. We analyzed the performance of our proposed system in frequency selective fading environment with narrowband interference existing and compared it with that of parallel transmission over many subchannels (namely, conventional MC-CDMA scheme) and DS-CDMA system. Simulation results show that adaptive subchannel allocation scheme, when used in conventional multicarrier CDMA system, the performance will be greatly improved.Keywords: MC-CDMA, Rayleigh fading, Narrowbandinterference, Channel estimation.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 15619373 Performance Prediction of a SANDIA 17-m Vertical Axis Wind Turbine Using Improved Double Multiple Streamtube
Authors: Abolfazl Hosseinkhani, Sepehr Sanaye
Abstract:
Different approaches have been used to predict the performance of the vertical axis wind turbines (VAWT), such as experimental, computational fluid dynamics (CFD), and analytical methods. Analytical methods, such as momentum models that use streamtubes, have low computational cost and sufficient accuracy. The double multiple streamtube (DMST) is one of the most commonly used of momentum models, which divide the rotor plane of VAWT into upwind and downwind. In fact, results from the DMST method have shown some discrepancy compared with experiment results; that is because the Darrieus turbine is a complex and aerodynamically unsteady configuration. In this study, analytical-experimental-based corrections, including dynamic stall, streamtube expansion, and finite blade length correction are used to improve the DMST method. Results indicated that using these corrections for a SANDIA 17-m VAWT will lead to improving the results of DMST.
Keywords: Vertical axis wind turbine, analytical, double multiple streamtube, streamtube expansion model, dynamic stall model, finite blade length correction.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 5609372 Proteomic Analysis of Tumor Tissue after Treatment with Ascorbic Acid
Authors: Seyeon Park, Mi Jang
Abstract:
Tumor cells have an invasive and metastatic phenotype that is the main cause of death for cancer patients. Tumor establishment and penetration consists of a series of complex processes involving multiple changes in gene expression. In this study, intraperitoneal administration of a high concentration of ascorbic acid inhibited tumor establishment and decreased tumor mass in BALB/C mice implanted with S-180 sarcoma cancer cells. To identify proteins involved in the ascorbic acid-mediated inhibition of tumor progression, changes in the tumor proteome associated with ascorbic acid treatment of BALB/C mice implanted with S-180 were investigated using two-dimensional gel electrophoresis and mass spectrometry. Twenty protein spots were identified whose expression was different between control and ascorbic acid treatment groups.Keywords: Ascorbic acid, Proteomic analysis, S-180 implantedBALB/C mouse
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 16659371 An Integrative Bayesian Approach to Supporting the Prediction of Protein-Protein Interactions: A Case Study in Human Heart Failure
Authors: Fiona Browne, Huiru Zheng, Haiying Wang, Francisco Azuaje
Abstract:
Recent years have seen a growing trend towards the integration of multiple information sources to support large-scale prediction of protein-protein interaction (PPI) networks in model organisms. Despite advances in computational approaches, the combination of multiple “omic" datasets representing the same type of data, e.g. different gene expression datasets, has not been rigorously studied. Furthermore, there is a need to further investigate the inference capability of powerful approaches, such as fullyconnected Bayesian networks, in the context of the prediction of PPI networks. This paper addresses these limitations by proposing a Bayesian approach to integrate multiple datasets, some of which encode the same type of “omic" data to support the identification of PPI networks. The case study reported involved the combination of three gene expression datasets relevant to human heart failure (HF). In comparison with two traditional methods, Naive Bayesian and maximum likelihood ratio approaches, the proposed technique can accurately identify known PPI and can be applied to infer potentially novel interactions.Keywords: Bayesian network, Classification, Data integration, Protein interaction networks.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 16049370 A Comparison Study of Electrical Characteristics in Conventional Multiple-gate Silicon Nanowire Transistors
Authors: Fatemeh Karimi, Morteza Fathipour, Hamdam Ghanatian, Vala Fathipour
Abstract:
In this paper electrical characteristics of various kinds of multiple-gate silicon nanowire transistors (SNWT) with the channel length equal to 7 nm are compared. A fully ballistic quantum mechanical transport approach based on NEGF was employed to analyses electrical characteristics of rectangular and cylindrical silicon nanowire transistors as well as a Double gate MOS FET. A double gate, triple gate, and gate all around nano wires were studied to investigate the impact of increasing the number of gates on the control of the short channel effect which is important in nanoscale devices. Also in the case of triple gate rectangular SNWT inserting extra gates on the bottom of device can improve the application of device. The results indicate that by using gate all around structures short channel effects such as DIBL, subthreshold swing and delay reduces.Keywords: SNWT (silicon nanowire transistor), non equilibriumGreen's function (NEGF), double gate (DG), triple gate (TG), multiple gate, cylindrical nano wire (CW), rectangular nano wire(RW), Poisson_ Schrödinger solver, drain induced barrier lowering(DIBL).
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 20679369 Performance Analysis of 5G for Low Latency Transmission Based on Universal Filtered Multi-Carrier Technique and Interleave Division Multiple Access
Authors: A. Asgharzadeh, M. Maroufi
Abstract:
5G mobile communication system has drawn more and more attention. The 5G system needs to provide three different types of services, including enhanced Mobile BroadBand (eMBB), massive machine-type communication (mMTC), and ultra-reliable and low-latency communication (URLLC). Universal Filtered Multi-Carrier (UFMC), Filter Bank Multicarrier (FBMC), and Filtered Orthogonal Frequency Division Multiplexing (f-OFDM) are suggested as a well-known candidate waveform for the coming 5G system. Themachine-to-machine (M2M) communications are one of the essential applications in 5G, and it involves exchanging of concise messages with a very short latency. However, in UFMC systems, the subcarriers are grouped into subbands but f-OFDM only one subband covers the entire band. Furthermore, in FBMC, a subband includes only one subcarrier, and the number of subbands is the same as the number of subcarriers. This paper mainly discusses the performance of UFMC with different parameters for the UFMC system. Also, paper shows that UFMC is the best choice outperforming OFDM in any case and FBMC in case of very short packets while performing similarly for long sequences with channel estimation techniques for Interleave Division Multiple Access (IDMA) systems.
Keywords: UFMC, IDMA, 5G, subband.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 4549368 Adaptive Radio Resource Allocation for Multiple Traffic OFDMA Broadband Wireless Access System
Authors: Lu Yanhui, Zhang Lizhi, Yin Changchuan, Yue Guangxin
Abstract:
In this paper, an adaptive radio resource allocation (RRA) algorithm applying to multiple traffic OFDMA system is proposed, which distributes sub-carrier and loading bits among users according to their different QoS requirements and traffic class. By classifying and prioritizing the users based on their traffic characteristic and ensuring resource for higher priority users, the scheme decreases tremendously the outage probability of the users requiring a real time transmission without impact on the spectrum efficiency of system, as well as the outage probability of data users is not increased compared with the RRA methods published.Keywords: OFDMA, adaptive radio resource allocation, QoS.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 16749367 Parametric Analysis on Information Technology Adoption and Organizational Efficiency in Northern Nigeria
Authors: A. Y. Dutse, S. I. Ningi
Abstract:
The adoption and diffusion of Information Technology (IT) is one of the fastest growing trends in organizations operating within Nigeria’s economy. Public and private organizations make huge capital investments in an attempt acquire and adopt the state-of-the-art IT for improving operational efficiency. In this study the level of IT adoption is considered the primary driver of efficiency witnessed by organizations. The research gathered data on the intensity of IT usage, and resultant efficiency increase in the organizations’ operations. The data was analyzed using multiple regression analysis and reveals that high level of IT usage has enhance efficiency of private and public organizations in Northern part of Nigeria with organizations having strategic intent on IT adoption indicating higher efficiency gains.
Keywords: IT Adoption, Nigeria, Organizational efficiency.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 13609366 Online Electric Current Based Diagnosis of Stator Faults on Squirrel Cage Induction Motors
Authors: Alejandro Paz Parra, Jose Luis Oslinger Gutierrez, Javier Olaya Ochoa
Abstract:
In the present paper, five electric current based methods to analyze electric faults on the stator of induction motors (IM) are used and compared. The analysis tries to extend the application of the multiple reference frames diagnosis technique. An eccentricity indicator is presented to improve the application of the Park’s Vector Approach technique. Most of the fault indicators are validated and some others revised, agree with the technical literatures and published results. A tri-phase 3hp squirrel cage IM, especially modified to establish different fault levels, is used for validation purposes.
Keywords: Motor fault diagnosis, induction motor, MCSA, ESA, Extended Park´s vector approach, multiparameter analysis.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 16639365 Dynamic Analysis of Nonlinear Models with Infinite Extension by Boundary Elements
Authors: Delfim Soares Jr., Webe J. Mansur
Abstract:
The Time-Domain Boundary Element Method (TDBEM) is a well known numerical technique that handles quite properly dynamic analyses considering infinite dimension media. However, when these analyses are also related to nonlinear behavior, very complex numerical procedures arise considering the TD-BEM, which may turn its application prohibitive. In order to avoid this drawback and model nonlinear infinite media, the present work couples two BEM formulations, aiming to achieve the best of two worlds. In this context, the regions expected to behave nonlinearly are discretized by the Domain Boundary Element Method (D-BEM), which has a simpler mathematical formulation but is unable to deal with infinite domain analyses; the TD-BEM is employed as in the sense of an effective non-reflexive boundary. An iterative procedure is considered for the coupling of the TD-BEM and D-BEM, which is based on a relaxed renew of the variables at the common interfaces. Elastoplastic models are focused and different time-steps are allowed to be considered by each BEM formulation in the coupled analysis.Keywords: Boundary Element Method, Dynamic Elastoplastic Analysis, Iterative Coupling, Multiple Time-Steps.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 15239364 A New Recognition Scheme for Machine- Printed Arabic Texts based on Neural Networks
Authors: Z. Shaaban
Abstract:
This paper presents a new approach to tackle the problem of recognizing machine-printed Arabic texts. Because of the difficulty of recognizing cursive Arabic words, the text has to be normalized and segmented to be ready for the recognition stage. The new scheme for recognizing Arabic characters depends on multiple parallel neural networks classifier. The classifier has two phases. The first phase categories the input character into one of eight groups. The second phase classifies the character into one of the Arabic character classes in the group. The system achieved high recognition rate.
Keywords: Neural Networks, character recognition, feature extraction, multiple networks, Arabic text.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1465