Search results for: Data representation
6576 Accurate Visualization of Graphs of Functions of Two Real Variables
Authors: Zeitoun D. G., Thierry Dana-Picard
Abstract:
The study of a real function of two real variables can be supported by visualization using a Computer Algebra System (CAS). One type of constraints of the system is due to the algorithms implemented, yielding continuous approximations of the given function by interpolation. This often masks discontinuities of the function and can provide strange plots, not compatible with the mathematics. In recent years, point based geometry has gained increasing attention as an alternative surface representation, both for efficient rendering and for flexible geometry processing of complex surfaces. In this paper we present different artifacts created by mesh surfaces near discontinuities and propose a point based method that controls and reduces these artifacts. A least squares penalty method for an automatic generation of the mesh that controls the behavior of the chosen function is presented. The special feature of this method is the ability to improve the accuracy of the surface visualization near a set of interior points where the function may be discontinuous. The present method is formulated as a minimax problem and the non uniform mesh is generated using an iterative algorithm. Results show that for large poorly conditioned matrices, the new algorithm gives more accurate results than the classical preconditioned conjugate algorithm.
Keywords: Function singularities, mesh generation, point allocation, visualization, collocation least squares method, Augmented Lagrangian method, Uzawa's Algorithm, Preconditioned Conjugate Gradien
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 16956575 Survey Based Data Security Evaluation in Pakistan Financial Institutions against Malicious Attacks
Authors: Naveed Ghani, Samreen Javed
Abstract:
In today’s heterogeneous network environment, there is a growing demand for distrust clients to jointly execute secure network to prevent from malicious attacks as the defining task of propagating malicious code is to locate new targets to attack. Residual risk is always there no matter what solutions are implemented or whet so ever security methodology or standards being adapted. Security is the first and crucial phase in the field of Computer Science. The main aim of the Computer Security is gathering of information with secure network. No one need wonder what all that malware is trying to do: It's trying to steal money through data theft, bank transfers, stolen passwords, or swiped identities. From there, with the help of our survey we learn about the importance of white listing, antimalware programs, security patches, log files, honey pots, and more used in banks for financial data protection but there’s also a need of implementing the IPV6 tunneling with Crypto data transformation according to the requirements of new technology to prevent the organization from new Malware attacks and crafting of its own messages and sending them to the target. In this paper the writer has given the idea of implementing IPV6 Tunneling Secessions on private data transmission from financial organizations whose secrecy needed to be safeguarded.
Keywords: Network worms, malware infection propagating malicious code, virus, security, VPN.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 27946574 A Prediction-Based Reversible Watermarking for MRI Images
Authors: Nuha Omran Abokhdair, Azizah Bt Abdul Manaf
Abstract:
Reversible watermarking is a special branch of image watermarking, that is able to recover the original image after extracting the watermark from the image. In this paper, an adaptive prediction-based reversible watermarking scheme is presented, in order to increase the payload capacity of MRI medical images. The scheme divides the image into two parts, Region of Interest (ROI) and Region of Non-Interest (RONI). Two bits are embedded in each embeddable pixel of RONI and one bit is embedded in each embeddable pixel of ROI. The experimental results demonstrate that the proposed scheme is able to achieve high embedding capacity. This is mainly caused by two reasons. First, the pixels that were excluded from data embedding due to overflow/underflow are used for data embedding. Second, large location map that need to be added to watermark data as overhead is eliminated and thus lower data embedding capacity is prevented. Moreover, the scheme provides good visual quality to the watermarked image.
Keywords: Medical image watermarking, reversible watermarking, Difference Expansion, Prediction-Error Expansion.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 19066573 Using TRACE and SNAP Codes to Establish the Model of Maanshan PWR for SBO Accident
Authors: B. R. Shen, J. R. Wang, J. H. Yang, S. W. Chen, C. Shih, Y. Chiang, Y. F. Chang, Y. H. Huang
Abstract:
In this research, TRACE code with the interface code-SNAP was used to simulate and analyze the SBO (station blackout) accident which occurred in Maanshan PWR (pressurized water reactor) nuclear power plant (NPP). There are four main steps in this research. First, the SBO accident data of Maanshan NPP were collected. Second, the TRACE/SNAP model of Maanshan NPP was established by using these data. Third, this TRACE/SNAP model was used to perform the simulation and analysis of SBO accident. Finally, the simulation and analysis of SBO with mitigation equipments was performed. The analysis results of TRACE are consistent with the data of Maanshan NPP. The mitigation equipments of Maanshan can maintain the safety of Maanshan in the SBO according to the TRACE predictions.
Keywords: PWR, TRACE, SBO, Maanshan.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 7366572 Salbutamol Sulphate-Ethylcellulose Tabletted Microcapsules: Pharmacokinetic Study using Convolution Approach
Authors: Ghulam Murtaza, Kalsoom Farzana
Abstract:
The aim of this article is to narrate the utility of novel simulation approach i.e. convolution method to predict blood concentration of drug utilizing dissolution data of salbutamol sulphate microparticulate formulations with different release patterns (1:1, 1:2 and 1:3, drug:polymer). Dissolution apparatus II USP 2007 and 900 ml double distilled water stirrd at 50 rpm was employed for dissolution analysis. From dissolution data, blood drug concentration was determined, and in return predicted blood drug concentration data was used to calculate the pharmacokinetic parameters i.e. Cmax, Tmax, and AUC. Convolution is a good biwaiver technique; however its better utility needs it application in the conditions where biorelevant dissolution media are used.
Keywords: Convolution, Dissolution, Pharmacokinetics, Salbutamol sulphate
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 25776571 High Performance in Parallel Data Integration: An Empirical Evaluation of the Ratio Between Processing Time and Number of Physical Nodes
Authors: Caspar von Seckendorff, Eldar Sultanow
Abstract:
Many studies have shown that parallelization decreases efficiency [1], [2]. There are many reasons for these decrements. This paper investigates those which appear in the context of parallel data integration. Integration processes generally cannot be allocated to packages of identical size (i. e. tasks of identical complexity). The reason for this is unknown heterogeneous input data which result in variable task lengths. Process delay is defined by the slowest processing node. It leads to a detrimental effect on the total processing time. With a real world example, this study will show that while process delay does initially increase with the introduction of more nodes it ultimately decreases again after a certain point. The example will make use of the cloud computing platform Hadoop and be run inside Amazon-s EC2 compute cloud. A stochastic model will be set up which can explain this effect.
Keywords: Process delay, speedup, efficiency, parallel computing, data integration, E-Commerce, Amazon Elastic Compute Cloud (EC2), Hadoop, Nutch.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 16186570 Improvements in Navy Data Networks and Tactical Communication Systems
Authors: Laurent Enel, Franck Guillem
Abstract:
This paper considers the benefits gained by using an efficient quality of service management such as DiffServ technique to improve the performance of military communications. Low delay and no blockage must be achieved especially for real time tactical data. All traffic flows generated by different applications do not need same bandwidth, same latency, same error ratio and this scalable technique of packet management based on priority levels is analysed. End to end architectures supporting various traffic flows and including lowbandwidth and high-delay HF or SHF military links as well as unprotected Internet sub domains are studied. A tuning of Diffserv parameters is proposed in accordance with different loads of various traffic and different operational situations.Keywords: Military data networks, Quality of service, Tacticalsystems.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 20576569 Text Mining of Twitter Data Using a Latent Dirichlet Allocation Topic Model and Sentiment Analysis
Authors: Sidi Yang, Haiyi Zhang
Abstract:
Twitter is a microblogging platform, where millions of users daily share their attitudes, views, and opinions. Using a probabilistic Latent Dirichlet Allocation (LDA) topic model to discern the most popular topics in the Twitter data is an effective way to analyze a large set of tweets to find a set of topics in a computationally efficient manner. Sentiment analysis provides an effective method to show the emotions and sentiments found in each tweet and an efficient way to summarize the results in a manner that is clearly understood. The primary goal of this paper is to explore text mining, extract and analyze useful information from unstructured text using two approaches: LDA topic modelling and sentiment analysis by examining Twitter plain text data in English. These two methods allow people to dig data more effectively and efficiently. LDA topic model and sentiment analysis can also be applied to provide insight views in business and scientific fields.
Keywords: Text mining, Twitter, topic model, sentiment analysis.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 17866568 Topological Queries on Graph-structured XML Data: Models and Implementations
Authors: Hongzhi Wang, Jianzhong Li, Jizhou Luo
Abstract:
In many applications, data is in graph structure, which can be naturally represented as graph-structured XML. Existing queries defined on tree-structured and graph-structured XML data mainly focus on subgraph matching, which can not cover all the requirements of querying on graph. In this paper, a new kind of queries, topological query on graph-structured XML is presented. This kind of queries consider not only the structure of subgraph but also the topological relationship between subgraphs. With existing subgraph query processing algorithms, efficient algorithms for topological query processing are designed. Experimental results show the efficiency of implementation algorithms.Keywords: XML, Graph Structure, Topological query.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 14056567 Validation and Selection between Machine Learning Technique and Traditional Methods to Reduce Bullwhip Effects: a Data Mining Approach
Authors: Hamid R. S. Mojaveri, Seyed S. Mousavi, Mojtaba Heydar, Ahmad Aminian
Abstract:
The aim of this paper is to present a methodology in three steps to forecast supply chain demand. In first step, various data mining techniques are applied in order to prepare data for entering into forecasting models. In second step, the modeling step, an artificial neural network and support vector machine is presented after defining Mean Absolute Percentage Error index for measuring error. The structure of artificial neural network is selected based on previous researchers' results and in this article the accuracy of network is increased by using sensitivity analysis. The best forecast for classical forecasting methods (Moving Average, Exponential Smoothing, and Exponential Smoothing with Trend) is resulted based on prepared data and this forecast is compared with result of support vector machine and proposed artificial neural network. The results show that artificial neural network can forecast more precisely in comparison with other methods. Finally, forecasting methods' stability is analyzed by using raw data and even the effectiveness of clustering analysis is measured.Keywords: Artificial Neural Networks (ANN), bullwhip effect, demand forecasting, Support Vector Machine (SVM).
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 19956566 Discovery of Sequential Patterns Based On Constraint Patterns
Authors: Shigeaki Sakurai, Youichi Kitahata, Ryohei Orihara
Abstract:
This paper proposes a method that discovers sequential patterns corresponding to user-s interests from sequential data. This method expresses the interests as constraint patterns. The constraint patterns can define relationships among attributes of the items composing the data. The method recursively decomposes the constraint patterns into constraint subpatterns. The method evaluates the constraint subpatterns in order to efficiently discover sequential patterns satisfying the constraint patterns. Also, this paper applies the method to the sequential data composed of stock price indexes and verifies its effectiveness through comparing it with a method without using the constraint patterns.
Keywords: Sequential pattern mining, Constraint pattern, Attribute constraint, Stock price indexes
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 14096565 Modeling Prices of Electricity Futures at EEX
Authors: Robest Flasza, Milan Rippel, Jan Solc
Abstract:
The main aim of this paper is to develop and calibrate an econometric model for modeling prices of long term electricity futures contracts. The calibration of our model is performed on data from EEX AG allowing us to capture the specific features of German electricity market. The data sample contains several structural breaks which have to be taken into account for modeling. We model the data with an ARIMAX model which reveals high correlation between the price of electricity futures contracts and prices of LT futures contracts of fuels (namely coal, natural gas and crude oil). Besides this, also a share price index of representative electricity companies traded on Xetra, spread between 10Y and 1Y German bonds and exchange rate between EUR and USD appeared to have significant explanatory power over these futures contracts on EEX.Keywords: electricity futures, EEX, ARIMAX, emissionallowances
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 19936564 Data-driven ASIC for Multichannel Sensors
Authors: Eduard Atkin, Alexander Klyuev, Vitaly Shumikhin
Abstract:
An approach and its implementation in 0.18 m CMOS process of the multichannel ASIC for capacitive (up to 30 pF) sensors are described in the paper. The main design aim was to study an analog data-driven architecture. The design was done for an analog derandomizing function of the 128 to 16 structure. That means that the ASIC structure should provide a parallel front-end readout of 128 input analog sensor signals and after the corresponding fast commutation with appropriate arbitration logic their processing by means of 16 output chains, including analog-to-digital conversion. The principal feature of the ASIC is a low power consumption within 2 mW/channel (including a 9-bit 20Ms/s ADC) at a maximum average channel hit rate not less than 150 kHz.
Keywords: Data-driven architecture, derandomizer, multichannel sensor readout
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 14156563 REDD: Reliable Energy-Efficient Data Dissemination in Wireless Sensor Networks with Multiple Mobile Sinks
Authors: K. Singh, T. P. Sharma
Abstract:
In wireless sensor network (WSN) the use of mobile sink has been attracting more attention in recent times. Mobile sinks are more effective means of balancing load, reducing hotspot problem and elongating network lifetime. The sensor nodes in WSN have limited power supply, computational capability and storage and therefore for continuous data delivery reliability becomes high priority in these networks. In this paper, we propose a Reliable Energy-efficient Data Dissemination (REDD) scheme for WSNs with multiple mobile sinks. In this strategy, sink first determines the location of source and then directly communicates with the source using geographical forwarding. Every forwarding node (FN) creates a local zone comprising some sensor nodes that can act as representative of FN when it fails. Analytical and simulation study reveals significant improvement in energy conservation and reliable data delivery in comparison to existing schemes.Keywords: Energy Efficient, REED, Sink Mobility, WSN.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 19296562 The Robust Clustering with Reduction Dimension
Authors: Dyah E. Herwindiati
Abstract:
A clustering is process to identify a homogeneous groups of object called as cluster. Clustering is one interesting topic on data mining. A group or class behaves similarly characteristics. This paper discusses a robust clustering process for data images with two reduction dimension approaches; i.e. the two dimensional principal component analysis (2DPCA) and principal component analysis (PCA). A standard approach to overcome this problem is dimension reduction, which transforms a high-dimensional data into a lower-dimensional space with limited loss of information. One of the most common forms of dimensionality reduction is the principal components analysis (PCA). The 2DPCA is often called a variant of principal component (PCA), the image matrices were directly treated as 2D matrices; they do not need to be transformed into a vector so that the covariance matrix of image can be constructed directly using the original image matrices. The decomposed classical covariance matrix is very sensitive to outlying observations. The objective of paper is to compare the performance of robust minimizing vector variance (MVV) in the two dimensional projection PCA (2DPCA) and the PCA for clustering on an arbitrary data image when outliers are hiden in the data set. The simulation aspects of robustness and the illustration of clustering images are discussed in the end of paperKeywords: Breakdown point, Consistency, 2DPCA, PCA, Outlier, Vector Variance
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 16876561 Multivariate School Travel Demand Regression Based on Trip Attraction
Authors: Ben-Edigbe J, RahmanR
Abstract:
Since primary school trips usually start from home, attention by many scholars have been focused on the home end for data gathering. Thereafter category analysis has often been relied upon when predicting school travel demands. In this paper, school end was relied on for data gathering and multivariate regression for future travel demand prediction. 9859 pupils were surveyed by way of questionnaires at 21 primary schools. The town was divided into 5 zones. The study was carried out in Skudai Town, Malaysia. Based on the hypothesis that the number of primary school trip ends are expected to be the same because school trips are fixed, the choice of trip end would have inconsequential effect on the outcome. The study compared empirical data for home and school trip end productions and attractions. Variance from both data results was insignificant, although some claims from home based family survey were found to be grossly exaggerated. Data from the school trip ends was relied on for travel demand prediction because of its completeness. Accessibility, trip attraction and trip production were then related to school trip rates under daylight and dry weather conditions. The paper concluded that, accessibility is an important parameter when predicting demand for future school trip rates.Keywords: Trip generation, regression analysis, multiple linearregressions
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 18946560 Model Based Monitoring Using Integrated Data Validation, Simulation and Parameter Estimation
Authors: Reza Hayati, Maryam Sadi, Saeid Shokri, Mehdi Ahmadi Marvast, Saeid Hassan Boroojerdi, Amin Hamzavi Abedi
Abstract:
Efficient and safe plant operation can only be achieved if the operators are able to monitor all key process parameters. Instrumentation is used to measure many process variables, like temperatures, pressures, flow rates, compositions or other product properties. Therefore Performance monitoring is a suitable tool for operators. In this paper, we integrate rigorous simulation model, data reconciliation and parameter estimation to monitor process equipments and determine key performance indicator (KPI) of them. The applied method here has been implemented in two case studies.Keywords: Data Reconciliation, Measurement, Optimization, Parameter Estimation, Performance Monitoring.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 20706559 Investigating Ultra Violet (UV) Strength against Different Level of Altitude using New Environmental Data Management System
Authors: M. Amir Abas, M. Dahlui
Abstract:
This paper presents the investigation results of UV measurement at different level of altitudes and the development of a new portable instrument for measuring UV. The rapid growth of industrial sectors in developing countries including Malaysia, brings not only income to the nation, but also causes pollution in various forms. Air pollution is one of the significant contributors to global warming by depleting the Ozone layer, which would reduce the filtration of UV rays. Long duration of exposure to high to UV rays has many devastating health effects to mankind directly or indirectly through destruction of the natural resources. This study aimed to show correlation between UV and altitudes which indirectly can help predict Ozone depletion. An instrument had been designed to measure and monitors the level of UV. The instrument comprises of two main blocks namely data logger and Graphic User Interface (GUI). Three sensors were used in the data logger to detect changes in the temperature, humidity and ultraviolet. The system has undergone experimental measurement to capture data at two different conditions; industrial area and high attitude area. The performance of the instrument showed consistency in the data captured and the results of the experiment drew a significantly high reading of UV at high altitudes.Keywords: Ozone Layer, Monitoring, Global Warming, Measurement, Ultraviolet
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 17276558 Determining the Online Purchasing Loyalty for Thai Herbal Products
Authors: Chummanond Natchaya, Rotchanakitumnuai Siriluck
Abstract:
The objective of this study is to identify the factors that influence the online purchasing loyalty for Thai herbal products. Survey research is used to gather data from Thai herb online merchants to assess factors that have impacts on enhancing loyalty. Data were collected from 300 online customers who had experience in online purchasing of Thai Herbal products. Prior experience consists of data from previous usage of online herbs, herb purchase and internet usage. E-Quality data consists of information quality, system quality, service quality and the product quality of Thai herbal products sold online. The results suggest that prior experience, Equality, attitude toward purchase and trust in online merchant have major impacts on loyalty. The good attitude and E-Quality of purchasing Thai herbal product online are the most significant determinants affecting loyalty.Keywords: e-Commerce, Thai herb, E-Quality, satisfaction, loyalty.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 18786557 Increasing the Resilience of Cyber Physical Systems in Smart Grid Environments using Dynamic Cells
Authors: Andrea Tundis, Carlos García Cordero, Rolf Egert, Alfredo Garro, Max Mühlhäuser
Abstract:
Resilience is an important system property that relies on the ability of a system to automatically recover from a degraded state so as to continue providing its services. Resilient systems have the means of detecting faults and failures with the added capability of automatically restoring their normal operations. Mastering resilience in the domain of Cyber-Physical Systems is challenging due to the interdependence of hybrid hardware and software components, along with physical limitations, laws, regulations and standards, among others. In order to overcome these challenges, this paper presents a modeling approach, based on the concept of Dynamic Cells, tailored to the management of Smart Grids. Additionally, a heuristic algorithm that works on top of the proposed modeling approach, to find resilient configurations, has been defined and implemented. More specifically, the model supports a flexible representation of Smart Grids and the algorithm is able to manage, at different abstraction levels, the resource consumption of individual grid elements on the presence of failures and faults. Finally, the proposal is evaluated in a test scenario where the effectiveness of such approach, when dealing with complex scenarios where adequate solutions are difficult to find, is shown.Keywords: Cyber-physical systems, energy management, optimization, smart grids, self-healing, resilience, security.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 10516556 Performance Comparison of ADTree and Naive Bayes Algorithms for Spam Filtering
Authors: Thanh Nguyen, Andrei Doncescu, Pierre Siegel
Abstract:
Classification is an important data mining technique and could be used as data filtering in artificial intelligence. The broad application of classification for all kind of data leads to be used in nearly every field of our modern life. Classification helps us to put together different items according to the feature items decided as interesting and useful. In this paper, we compare two classification methods Naïve Bayes and ADTree use to detect spam e-mail. This choice is motivated by the fact that Naive Bayes algorithm is based on probability calculus while ADTree algorithm is based on decision tree. The parameter settings of the above classifiers use the maximization of true positive rate and minimization of false positive rate. The experiment results present classification accuracy and cost analysis in view of optimal classifier choice for Spam Detection. It is point out the number of attributes to obtain a tradeoff between number of them and the classification accuracy.Keywords: Classification, data mining, spam filtering, naive Bayes, decision tree.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 14856555 File Format of Flow Chart Simulation Software - CFlow
Authors: Syahanim Mohd Salleh, Zaihosnita Hood, Hairulliza Mohd Judi, Marini Abu Bakar
Abstract:
CFlow is a flow chart software, it contains facilities to draw and evaluate a flow chart. A flow chart evaluation applies a simulation method to enable presentation of work flow in a flow chart solution. Flow chart simulation of CFlow is executed by manipulating the CFlow data file which is saved in a graphical vector format. These text-based data are organised by using a data classification technic based on a Library classification-scheme. This paper describes the file format for flow chart simulation software of CFlow.Keywords: CFlow, flow chart, file format.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 25356554 Development of a Non-invasive System to Measure the Thickness of the Subcutaneous Adipose Tissue Layer for Human
Authors: Hyuck Ki Hong, Young Chang Jo, Yeon Shik Choi, Beom Joon Kim, Hyo Derk Park
Abstract:
To measure the thickness of the subcutaneous adipose tissue layer, a non-invasive optical measurement system (λ=1300 nm) is introduced. Animal and human subjects are used for the experiments. The results of human subjects are compared with the data of ultrasound device measurements, and a high correlation (r=0.94 for n=11) is observed. There are two modes in the corresponding signals measured by the optical system, which can be explained by two-layered and three-layered tissue models. If the target tissue is thinner than the critical thickness, detected data using diffuse reflectance method follow the three-layered tissue model, so the data increase as the thickness increases. On the other hand, if the target tissue is thicker than the critical thickness, the data follow the two-layered tissue model, so they decrease as the thickness increases.Keywords: Subcutaneous adipose tissue layer, non-invasive measurement system, two-layered and three-layered tissue models.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 18346553 Modeling Concave Globoidal Cam with Swinging Roller Follower : A Case Study
Authors: Nguyen Van Tuong, Premysl Pokorny
Abstract:
This paper describes a computer-aided design for design of the concave globoidal cam with cylindrical rollers and swinging follower. Four models with different modeling methods are made from the same input data. The input data are angular input and output displacements of the cam and the follower and some other geometrical parameters of the globoidal cam mechanism. The best cam model is the cam which has no interference with the rollers when their motions are simulated in assembly conditions. The angular output displacement of the follower for the best cam is also compared with that of in the input data to check errors. In this study, Pro/ENGINEER® Wildfire 2.0 is used for modeling the cam, simulating motions and checking interference and errors of the system.Keywords: Globoidal cam, sweep, pitch surface, modeling.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 36556552 A Preemptive Link State Spanning Tree Source Routing Scheme for Opportunistic Data Forwarding in MANET
Authors: R. Poonkuzhali, M. Y. Sanavullah, A. Sabari
Abstract:
Opportunistic Data Forwarding (ODF) has drawn much attention in mobile adhoc networking research in recent years. The effectiveness of ODF in MANET depends on a suitable routing protocol which provides a powerful source routing services. PLSR is featured by source routing, loop free and small routing overhead. The update messages in PLSR are integrated into a tree structure and no need to time stamp routing updates which reduces the routing overhead.
Keywords: Mobile ad hoc network (MANET), Opportunistic data forwarding (ODF), Preemptive link state spanning tree routing (PLSR), Depth First Search (DFS).
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 19126551 Enhanced Imperialist Competitive Algorithm for the Cell Formation Problem Using Sequence Data
Authors: S. H. Borghei, E. Teymourian, M. Mobin, G. M. Komaki, S. Sheikh
Abstract:
Imperialist Competitive Algorithm (ICA) is a recent meta-heuristic method that is inspired by the social evolutions for solving NP-Hard problems. The ICA is a population-based algorithm which has achieved a great performance in comparison to other metaheuristics. This study is about developing enhanced ICA approach to solve the Cell Formation Problem (CFP) using sequence data. In addition to the conventional ICA, an enhanced version of ICA, namely EICA, applies local search techniques to add more intensification aptitude and embed the features of exploration and intensification more successfully. Suitable performance measures are used to compare the proposed algorithms with some other powerful solution approaches in the literature. In the same way, for checking the proficiency of algorithms, forty test problems are presented. Five benchmark problems have sequence data, and other ones are based on 0-1 matrices modified to sequence based problems. Computational results elucidate the efficiency of the EICA in solving CFP problems.Keywords: Cell formation problem, Group technology, Imperialist competitive algorithm, Sequence data.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 15756550 Classifying of Maize Inbred Lines into Heterotic Groups using Diallel Analysis
Authors: Mozhgan Ziaie Bidhendi, Rajab Choukan, Farokh Darvish, Khodadad Mostafavi, Eslam Majidi
Abstract:
The selection of parents and breeding strategies for the successful maize hybrid production will be facilitated by heterotic groupings of parental lines and determination of combining abilities of them. Fourteen maize inbred lines, used in maize breeding programs in Iran, were crossed in a diallel mating design. The 91 F1 hybrids and the 14 parental lines were studied during two years at four locations of Iran for investigation of combining ability of gentypes for grain yield and to determine heterotic patterns among germplasm sources, using both, the Griffing-s method and the biplot approach for diallel analysis. The graphical representation offered by biplot analysis allowed a rapid and effective overview of general combining ability (GCA) and specific combining ability (SCA) effects of the inbred lines, their performance in crosses, as well as grouping patterns of similar genotypes. GCA and SCA effects were significant for grain yield (GY). Based on significant positive GCA effects, the lines derived from LSC could be used as parent in crosses to increase GY. The maximum best- parent heterosis values and highest SCA effects resulted from crosses B73 × MO17 and A679 × MO17 for GY. The best heterotic patterns were LSC × RYD, which would be potentially useful in maize breeding programs to obtain high-yielding hybrids in the same climate of Iran.Keywords: biplot, diallel, Griffing, Heterotic pattern
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 56036549 A Systems Approach to Gene Ranking from DNA Microarray Data of Cervical Cancer
Authors: Frank Emmert Streib, Matthias Dehmer, Jing Liu, Max Mühlhauser
Abstract:
In this paper we present a method for gene ranking from DNA microarray data. More precisely, we calculate the correlation networks, which are unweighted and undirected graphs, from microarray data of cervical cancer whereas each network represents a tissue of a certain tumor stage and each node in the network represents a gene. From these networks we extract one tree for each gene by a local decomposition of the correlation network. The interpretation of a tree is that it represents the n-nearest neighbor genes on the n-th level of a tree, measured by the Dijkstra distance, and, hence, gives the local embedding of a gene within the correlation network. For the obtained trees we measure the pairwise similarity between trees rooted by the same gene from normal to cancerous tissues. This evaluates the modification of the tree topology due to progression of the tumor. Finally, we rank the obtained similarity values from all tissue comparisons and select the top ranked genes. For these genes the local neighborhood in the correlation networks changes most between normal and cancerous tissues. As a result we find that the top ranked genes are candidates suspected to be involved in tumor growth and, hence, indicates that our method captures essential information from the underlying DNA microarray data of cervical cancer.Keywords: Graph similarity, DNA microarray data, cancer.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 17436548 Futuristic Black Box Design Considerations and Global Networking for Real Time Monitoring of Flight Performance Parameters
Authors: K. Parandhama Gowd
Abstract:
The aim of this research paper is to conceptualize, discuss, analyze and propose alternate design methodologies for futuristic Black Box for flight safety. The proposal also includes global networking concepts for real time surveillance and monitoring of flight performance parameters including GPS parameters. It is expected that this proposal will serve as a failsafe real time diagnostic tool for accident investigation and location of debris in real time. In this paper, an attempt is made to improve the existing methods of flight data recording techniques and improve upon design considerations for futuristic FDR to overcome the trauma of not able to locate the block box. Since modern day communications and information technologies with large bandwidth are available coupled with faster computer processing techniques, the attempt made in this paper to develop a failsafe recording technique is feasible. Further data fusion/data warehousing technologies are available for exploitation.Keywords: Flight data recorder (FDR), black box, diagnostic tool, global networking, cockpit voice and data recorder (CVDR), air traffic control (ATC), air traffic, telemetry, tracking and control centers ATTTCC).
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 14326547 Image Distortion Correction Method of 2-MHz Side Scan Sonar for Underwater Structure Inspection
Authors: Youngseok Kim, Chul Park, Jonghwa Yi, Sangsik Choi
Abstract:
The 2-MHz Side Scan SONAR (SSS) attached to the boat for inspection of underwater structures is affected by shaking. It is difficult to determine the exact scale of damage of structure. In this study, a motion sensor is attached to the inside of the 2-MHz SSS to get roll, pitch, and yaw direction data, and developed the image stabilization tool to correct the sonar image. We checked that reliable data can be obtained with an average error rate of 1.99% between the measured value and the actual distance through experiment. It is possible to get the accurate sonar data to inspect damage in underwater structure.
Keywords: Image stabilization, motion sensor, safety inspection, sonar image, underwater structure.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1041