Search results for: Bottom-up testing approach

Authors: Maha Sliti, Walid Abdallah, Noureddine Boudriga

Abstract:

In the frame of this work, we present an optical multicasting approach based on optical code-words. Our approach associates, in the edge node, an optical code-word to a group multicast address. In the core node, a set of tunable decoders are used to send a traffic data to multiple destinations based on the received code-word. The use of code-words, which correspond to the combination of an input port and a set of output ports, allows the implementation of an optical switching matrix. At the reception of a burst, it will be delayed in an optical memory. And, the received optical code-word is split to a set of tunable optical decoders. When it matches a configured code-word, the delayed burst is switched to a set of output ports.

Keywords: Optical multicast, optical burst switching networks, optical code-words, tunable decoder, virtual optical memory.

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Authors: T. Hacib, M. R. Mekideche, N. Ferkha

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This paper presents an approach which is based on the use of supervised feed forward neural network, namely multilayer perceptron (MLP) neural network and finite element method (FEM) to solve the inverse problem of parameters identification. The approach is used to identify unknown parameters of ferromagnetic materials. The methodology used in this study consists in the simulation of a large number of parameters in a material under test, using the finite element method (FEM). Both variations in relative magnetic permeability and electrical conductivity of the material under test are considered. Then, the obtained results are used to generate a set of vectors for the training of MLP neural network. Finally, the obtained neural network is used to evaluate a group of new materials, simulated by the FEM, but not belonging to the original dataset. Noisy data, added to the probe measurements is used to enhance the robustness of the method. The reached results demonstrate the efficiency of the proposed approach, and encourage future works on this subject.

Keywords: Inverse problem, MLP neural network, parametersidentification, FEM.

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Authors: Nerijus Remeikis, Ignas Skucas, Vida Melninkaite

Abstract:

Text categorization - the assignment of natural language documents to one or more predefined categories based on their semantic content - is an important component in many information organization and management tasks. Performance of neural networks learning is known to be sensitive to the initial weights and architecture. This paper discusses the use multilayer neural network initialization with decision tree classifier for improving text categorization accuracy. An adaptation of the algorithm is proposed in which a decision tree from root node until a final leave is used for initialization of multilayer neural network. The experimental evaluation demonstrates this approach provides better classification accuracy with Reuters-21578 corpus, one of the standard benchmarks for text categorization tasks. We present results comparing the accuracy of this approach with multilayer neural network initialized with traditional random method and decision tree classifiers.

Keywords: Text categorization, decision trees, neural networks, machine learning.

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Authors: Mohanad Alata, Mohammad Molhim, Abdullah Ramini

Abstract:

Fuzzy C-means Clustering algorithm (FCM) is a method that is frequently used in pattern recognition. It has the advantage of giving good modeling results in many cases, although, it is not capable of specifying the number of clusters by itself. In FCM algorithm most researchers fix weighting exponent (m) to a conventional value of 2 which might not be the appropriate for all applications. Consequently, the main objective of this paper is to use the subtractive clustering algorithm to provide the optimal number of clusters needed by FCM algorithm by optimizing the parameters of the subtractive clustering algorithm by an iterative search approach and then to find an optimal weighting exponent (m) for the FCM algorithm. In order to get an optimal number of clusters, the iterative search approach is used to find the optimal single-output Sugenotype Fuzzy Inference System (FIS) model by optimizing the parameters of the subtractive clustering algorithm that give minimum least square error between the actual data and the Sugeno fuzzy model. Once the number of clusters is optimized, then two approaches are proposed to optimize the weighting exponent (m) in the FCM algorithm, namely, the iterative search approach and the genetic algorithms. The above mentioned approach is tested on the generated data from the original function and optimal fuzzy models are obtained with minimum error between the real data and the obtained fuzzy models.

Keywords: Fuzzy clustering, Fuzzy C-Means, Genetic Algorithm, Sugeno fuzzy systems.

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Authors: S. Farag, A. Kupeman

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In this paper, design of solid-state battery/supercapacitor emulator based on dc-dc boost converter is described. The emulator mimics charging behavior of any storage device based on a predefined behavior set by the user. The device is operated by a two-level control structure: high-level emulating controller and low- level input voltage controller. Simulation and experimental results are shown to demonstrate the emulator operation.

Keywords: Battery, Charger, Energy, Storage, Supercapacitor.

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Authors: T. Strobl, D. Raps, M. Hornung

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In this study, the adhesion of ice to solid substrates with different surface properties is compared. Clear ice, similar to atmospheric in-flight icing encounters, is accreted on the different substrates under controlled conditions. The ice adhesion behavior is investigated by means of a dynamic vibration testing technique with an electromagnetic shaker initiating ice de-bonding in the interface between the substrate and the ice. The results of the experiments reveal that the affinity for ice accretion is significantly influenced by the water contact angle of the respective sample.

Keywords: Contact angle, dynamic vibration measurement, ice adhesion, interfacial shear stress.

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Authors: Frantisek Bozek, Jiri Dvorak, Jaromir Mares, Hana Malachova

Abstract:

The value of emission factor was calculated in the older type of Diesel engine operating on an engine testing bench and then compared with the parameters monitored under similar conditions when the EnviroxTM additive was applied. It has been found out that the additive based on CeO2 nanoparticles reduces emission of NOx. The dependencies of NOx emissions on reduced torque, engine power and revolutions have been observed as well.

Keywords: Additive, air, cerium dioxide, emission factor, emissions, nanoparticles, nitrogen oxides

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Authors: Andrey V. Timofeev, Dmitry Egorov

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This paper describes an effective solution to the task of a remote monitoring of super-extended objects (oil and gas pipeline, railways, national frontier). The suggested solution is based on the principle of simultaneously monitoring of seismoacoustic and optical/infrared physical fields. The principle of simultaneous monitoring of those fields is not new but in contrast to the known solutions the suggested approach allows to control super-extended objects with very limited operational costs. So-called C-OTDR (Coherent Optical Time Domain Reflectometer) systems are used to monitor the seismoacoustic field. Far-CCTV systems are used to monitor the optical/infrared field. A simultaneous data processing provided by both systems allows effectively detecting and classifying target activities, which appear in the monitored objects vicinity. The results of practical usage had shown high effectiveness of the suggested approach.

Keywords: Bimodal processing, C-OTDR monitoring system, LPboost, SVM.

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Authors: J. Maksimainen

Abstract:

The values of managers and employees in organizations are phenomena that have captured the interest of researchers at large. Despite this attention, there continues to be a lack of agreement on what values are and how they influence individuals, or how they are constituted in individuals- mind. In this article content-based approach is presented as alternative reference frame for exploring values. In content-based approach human thinking in different contexts is set at the focal point. Differences in valuations can be explained through the information contents of mental representations. In addition to the information contents, attention is devoted to those cognitive processes through which mental representations of values are constructed. Such informational contents are in decisive role for understanding human behavior. By applying content-based analysis to an examination of values as mental representations, it is possible to reach a deeper to the motivational foundation of behaviors, such as decision making in organizational procedures, through understanding the structure and meanings of specific values at play.

Keywords: Content-based Approach, Mental Content, Mental Representations, Organizational values, Values

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Authors: Ali Ridho Barakbah, Yasushi Kiyoki

Abstract:

This paper presents a new approach for image segmentation by applying Pillar-Kmeans algorithm. This segmentation process includes a new mechanism for clustering the elements of high-resolution images in order to improve precision and reduce computation time. The system applies K-means clustering to the image segmentation after optimized by Pillar Algorithm. The Pillar algorithm considers the pillars- placement which should be located as far as possible from each other to withstand against the pressure distribution of a roof, as identical to the number of centroids amongst the data distribution. This algorithm is able to optimize the K-means clustering for image segmentation in aspects of precision and computation time. It designates the initial centroids- positions by calculating the accumulated distance metric between each data point and all previous centroids, and then selects data points which have the maximum distance as new initial centroids. This algorithm distributes all initial centroids according to the maximum accumulated distance metric. This paper evaluates the proposed approach for image segmentation by comparing with K-means and Gaussian Mixture Model algorithm and involving RGB, HSV, HSL and CIELAB color spaces. The experimental results clarify the effectiveness of our approach to improve the segmentation quality in aspects of precision and computational time.

Keywords: Image segmentation, K-means clustering, Pillaralgorithm, color spaces.

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Authors: Keny Ordaz-Hernandez, Xavier Fischer, Fouad Bennis

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This article illustrates a model selection management approach for virtual prototypes in interactive simulations. In those numerical simulations, the virtual prototype and its environment are modelled as a multiagent system, where every entity (prototype,human, etc.) is modelled as an agent. In particular, virtual prototyp ingagents that provide mathematical models of mechanical behaviour inform of computational methods are considered. This work argues that selection of an appropriate model in a changing environment,supported by models? characteristics, can be managed by the deter-mination a priori of specific exploitation and performance measures of virtual prototype models. As different models exist to represent a single phenomenon, it is not always possible to select the best one under all possible circumstances of the environment. Instead the most appropriate shall be selecting according to the use case. The proposed approach consists in identifying relevant metrics or indicators for each group of models (e.g. entity models, global model), formulate their qualification, analyse the performance, and apply the qualification criteria. Then, a model can be selected based on the performance prediction obtained from its qualification. The authors hope that this approach will not only help to inform engineers and researchers about another approach for selecting virtual prototype models, but also assist virtual prototype engineers in the systematic or automatic model selection.

Keywords: Virtual prototype models, domain, qualification criterion, model qualification, model assessment, environmental modelling.

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Authors: M. Imran Akram, Ahmed Pasha, Nabeel Iqbal

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In this paper a real-time trajectory generation algorithm for computing 2-D optimal paths for autonomous aerial vehicles has been discussed. A dynamic programming approach is adopted to compute k-best paths by minimizing a cost function. Collision detection is implemented to detect intersection of the paths with obstacles. Our contribution is a novel approach to the problem of trajectory generation that is computationally efficient and offers considerable gain over existing techniques.

Keywords: dynamic programming, graph search, path planning.

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Authors: Hamidreza Hoshyarmanesh, Hosein Madieh, Sanju Lama, Yaser Maddahi, Garnette R. Sutherland, Kourosh Zareinia

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This paper illustrates the concept of an algorithm to register specified markers on the neuroArm surgical manipulators, an image-guided MR-compatible tele-operated robot for microsurgery and stereotaxy. Two range-finding algorithms, namely time-of-flight and phase-shift, are evaluated for registration and supervisory control. The time-of-flight approach is implemented in a semi-field experiment to determine the precise position of a tiny retro-reflective moving object. The moving object simulates a surgical tool tip. The tool is a target that would be connected to the neuroArm end-effector during surgery inside the magnet bore of the MR imaging system. In order to apply flight approach, a 905-nm pulsed laser diode and an avalanche photodiode are utilized as the transmitter and receiver, respectively. For the experiment, a high frequency time to digital converter was designed using a field-programmable gate arrays. In the phase-shift approach, a continuous green laser beam with a wavelength of 530 nm was used as the transmitter. Results showed that a positioning error of 0.1 mm occurred when the scanner-target point distance was set in the range of 2.5 to 3 meters. The effectiveness of this non-contact approach exhibited that the method could be employed as an alternative for conventional mechanical registration arm. Furthermore, the approach is not limited by physical contact and extension of joint angles.

Keywords: 3D laser scanner, intraoperative MR imaging, neuroArm, real time registration, robot-assisted surgery, supervisory control.

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Authors: Markandeya Kunchi

Abstract:

Usability testing (UT) is one of the vital steps in the User-centred design (UCD) process when designing a product. In an e-commerce ecosystem, UT becomes primary as new products, features, and services are launched very frequently. And, there are losses attached to the company if an unusable and inefficient product is put out to market and is rejected by customers. This paper tries to answer why UT is important in the product life-cycle of an E-commerce ecosystem. Secondary user research was conducted to find out work patterns, development methods, type of stakeholders, and technology constraints, etc. of a typical E-commerce company. Qualitative user interviews were conducted with product managers and designers to find out the structure, project planning, product management method and role of the design team in a mid-level company. The paper tries to address the usual apprehensions of the company to inculcate UT within the team. As well, it stresses upon factors like monetary resources, lack of usability expert, narrow timelines, and lack of understanding of higher management as some primary reasons. Outsourcing UT to vendors is also very prevalent with mid-level e-commerce companies, but it has its own severe repercussions like very little team involvement, huge cost, misinterpretation of the findings, elongated timelines, and lack of empathy towards the customer, etc. The shortfalls of the unavailability of a UT process in place within the team and conducting UT through vendors are bad user experiences for customers while interacting with the product, badly designed products which are neither useful and nor utilitarian. As a result, companies see dipping conversions rates in apps and websites, huge bounce rates and increased uninstall rates. Thus, there was a need for a more lean UT system in place which could solve all these issues for the company. This paper highlights on optimizing the UT process with a collaborative method. The degree of optimization and structure of collaborative method is the highlight of this paper. Collaborative method of UT is one in which the centralised design team of the company takes for conducting and analysing the UT. The UT is usually a formative kind where designers take findings into account and uses in the ideation process. The success of collaborative method of UT is due to its ability to sync with the product management method employed by the company or team. The collaborative methods focus on engaging various teams (design, marketing, product, administration, IT, etc.) each with its own defined roles and responsibility in conducting a smooth UT with users In-house. The paper finally highlights the positive results of collaborative UT method after conducting more than 100 In-lab interviews with users across the different lines of businesses. Some of which are the improvement of interaction between stakeholders and the design team, empathy towards users, improved design iteration, better sanity check of design solutions, optimization of time and money, effective and efficient design solution. The future scope of collaborative UT is to make this method leaner, by reducing the number of days to complete the entire project starting from planning between teams to publishing the UT report.

Keywords: Usability testing, collaborative method, e-commerce, product management method.

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Authors: Iliana Marinova, Valentin Mateev

Abstract:

In this paper a computer system for electromagnetic properties measurements is designed. The system employs Agilent 4294A precision impedance analyzer to measure the amplitude and the phase of a signal applied over a tested biological tissue sample. Measured by the developed computer system data could be used for tissue characterization in wide frequency range from 40Hz to 110MHz. The computer system can interface with output devices acquiring flexible testing process.

Keywords: Electromagnetic properties, human tissue, bioimpedance, measurement system.

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Authors: Farhad Alizadeh, Alireza Faregh Gharamaleki, Mojtaba Jalilzadeh, Houshang Gholami, Ali Akhoundzadeh

Abstract:

This study presented hybrid pre-processing approach along with a conceptual model to enhance the accuracy of river discharge prediction. In order to achieve this goal, Ensemble Empirical Mode Decomposition algorithm (EEMD), Discrete Wavelet Transform (DWT) and Mutual Information (MI) were employed as a hybrid pre-processing approach conjugated to Least Square Support Vector Machine (LSSVM). A conceptual strategy namely multi-station model was developed to forecast the Souris River discharge more accurately. The strategy used herein was capable of covering uncertainties and complexities of river discharge modeling. DWT and EEMD was coupled, and the feature selection was performed for decomposed sub-series using MI to be employed in multi-station model. In the proposed feature selection method, some useless sub-series were omitted to achieve better performance. Results approved efficiency of the proposed DWT-EEMD-MI approach to improve accuracy of multi-station modeling strategies.

Keywords: River stage-discharge process, LSSVM, discrete wavelet transform (DWT), ensemble empirical decomposition mode (EEMD), multi-station modeling.

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Authors: Seyedehfatemeh Golrizgashti, Seyedali Dalil

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The goal of this paper is proposing a supply chain value dashboard in home appliance manufacturing firms to create more value for all stakeholders via balanced scorecard approach. Balanced scorecard is an effective approach that managers have used to evaluate supply chain performance in many fields but there is a lack of enough attention to all supply chain stakeholders, improving value creation and, defining correlation between value indicators and performance measuring quantitatively. In this research the key stakeholders in home appliance supply chain, value indicators with respect to create more value for stakeholders and the most important metrics to evaluate supply chain value performance based on balanced scorecard approach have been selected via literature review. The most important indicators based on expert’s judgment acquired by in survey focused on creating more value for. Structural equation modelling has been used to disclose relations between value indicators and balanced scorecard metrics. The important result of this research is identifying effective value dashboard to create more value for all stakeholders in supply chain via balanced scorecard approach and based on an empirical study covering ten home appliance manufacturing firms in Iran. Home appliance manufacturing firms can increase their stakeholder's satisfaction by using this value dashboard.

Keywords: Supply chain management, balanced scorecard, value, Structural modeling, Stakeholders.

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Authors: Hsiu-Hua Cheng, Chi-Wei Chen

Abstract:

Lurking behavior is common in information-seeking oriented communities. Transferring users with lurking behavior to be contributors can assist virtual communities to obtain competitive advantages. Based on the ecological cognition framework, this study proposes a model to examine the antecedents of lurking behavior in information-seeking oriented virtual communities. This study argues desire for emotional support, desire for information support, desire for performance-approach, desire for performance -avoidance, desire for mastery-approach, desire for mastery-avoidance, desire for ability trust, desire for benevolence trust, and desire for integrity trust effect on lurking behavior. This study offers an approach to understanding the determinants of lurking behavior in online contexts.

Keywords: Lurking behavior, the ecological cognition framework, Information-seeking oriented virtual communities, Desire.

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Authors: A. Kebbeb, M. Mostefai, F. Benmerzoug, Y. Chahir

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The multimodal biometric identification is the combination of several biometric systems; the challenge of this combination is to reduce some limitations of systems based on a single modality while significantly improving performance. In this paper, we propose a new approach to the construction and the protection of a multimodal biometric database dedicated to an identification system. We use a topological watermarking to hide the relation between face image and the registered descriptors extracted from other modalities of the same person for more secure user identification.

Keywords: Biometric databases, Multimodal biometrics, security authentication, Digital watermarking.

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Authors: Carol B.Collins, M. H. N Tabrizi

Abstract:

The purposes of this paper are to (1) promote excellence in computer science by suggesting a cohesive innovative approach to fill well documented deficiencies in current computer science education, (2) justify (using the authors- and others anecdotal evidence from both the classroom and the real world) why this approach holds great potential to successfully eliminate the deficiencies, (3) invite other professionals to join the authors in proof of concept research. The authors- experiences, though anecdotal, strongly suggest that a new approach involving visual modeling technologies should allow computer science programs to retain a greater percentage of prospective and declared majors as students become more engaged learners, more successful problem-solvers, and better prepared as programmers. In addition, the graduates of such computer science programs will make greater contributions to the profession as skilled problem-solvers. Instead of wearily rememorizing code as they move to the next course, students will have the problem-solving skills to think and work in more sophisticated and creative ways.

Keywords: Algorithms, CASE, Problem-solving, UML.

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Authors: M. Raseen, A.Assi, P.W. C. Prasad, A. Harb

Abstract:

Binary Decision Diagrams (BDDs) are useful data structures for symbolic Boolean manipulations. BDDs are used in many tasks in VLSI/CAD, such as equivalence checking, property checking, logic synthesis, and false paths. In this paper we describe a new approach for the realization of a BDD package. To perform manipulations of Boolean functions, the proposed approach does not depend on the recursive synthesis operation of the IF-Then-Else (ITE). Instead of using the ITE operation, the basic synthesis algorithm is done using Boolean NOR operation.

Keywords: Binary Decision Diagram (BDD), ITE Operation, Boolean Function, NOR operation.

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Authors: P. Moeinzadeh, A. Hajfathaliha

Abstract:

Many firms implemented various initiatives such as outsourced manufacturing which could make a supply chain (SC) more vulnerable to various types of disruptions. So managing risk has become a critical component of SC management. Different types of SC vulnerability management methodologies have been proposed for managing SC risk, most offer only point-based solutions that deal with a limited set of risks. This research aims to reinforce SC risk management by proposing an integrated approach. SC risks are identified and a risk index classification structure is created. Then we develop a SC risk assessment approach based on the analytic network process (ANP) and the VIKOR methods under the fuzzy environment where the vagueness and subjectivity are handled with linguistic terms parameterized by triangular fuzzy numbers. By using FANP, risks weights are calculated and then inserted to the FVIKOR to rank the SC members and find the most risky partner.

Keywords: Analytic network process (ANP), Fuzzy sets, Supply chain risk management (SCRM), VIšekriterijumsko KOmpromisno Rangiranje (VIKOR)

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Authors: Khalid Abd, Kazem Abhary, Romeo Marian

Abstract:

Multiple criteria decision making (MCDM) is an approach to ranking the solutions and finding the best one when two or more solutions are provided. In this study, MCDM approach is proposed to select the most suitable scheduling rule of robotic flexible assembly cells (RFACs). Two MCDM approaches, Analytic Hierarchy Process (AHP) and Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) are proposed for solving the scheduling rule selection problem. The AHP method is employed to determine the weights of the evaluation criteria, while the TOPSIS method is employed to obtain final ranking order of scheduling rules. Four criteria are used to evaluate the scheduling rules. Also, four scheduling policies of RFAC are examined to choose the most appropriate one for this purpose. A numerical example illustrates applications of the suggested methodology. The results show that the methodology is practical and works in RFAC settings.

Keywords: AHP, TOPSIS, Scheduling rules selection

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Authors: Yao-Hong Tsai

Abstract:

This paper presents a weighted approach to unconstrained iris recognition. In nowadays, commercial systems are usually characterized by strong acquisition constraints based on the subject’s cooperation. However, it is not always achievable for real scenarios in our daily life. Researchers have been focused on reducing these constraints and maintaining the performance of the system by new techniques at the same time. With large variation in the environment, there are two main improvements to develop the proposed iris recognition system. For solving extremely uneven lighting condition, statistic based illumination normalization is first used on eye region to increase the accuracy of iris feature. The detection of the iris image is based on Adaboost algorithm. Secondly, the weighted approach is designed by Gaussian functions according to the distance to the center of the iris. Furthermore, local binary pattern (LBP) histogram is then applied to texture classification with the weight. Experiment showed that the proposed system provided users a more flexible and feasible way to interact with the verification system through iris recognition.

Keywords: Authentication, iris recognition, Adaboost, local binary pattern.

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Authors: Jakub Kraus, Vladimír Plos, Peter Vittek

Abstract:

This article deals with a new approach to the airport emergency plans, which are the basic documents and manuals for dealing with events with impact on safety or security. The article describes the identified parts in which the current airport emergency plans do not fulfill their role and which should therefore be considered in the creation of corrective measures. All these issues have been identified at airports in the Czech Republic and confirmed at airports in neighboring countries.

Keywords: Airport emergency plan, aviation safety, aviation security, comprehensive management system.

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Authors: Ahmed Alqaoud

Abstract:

There is wide range of scientific workflow systems today, each one designed to resolve problems at a specific level. In large collaborative projects, it is often necessary to recognize the heterogeneous workflow systems already in use by various partners and any potential collaboration between these systems requires workflow interoperability. Publish/Subscribe Scientific Workflow Interoperability Framework (PS-SWIF) approach was proposed to achieve workflow interoperability among workflow systems. This paper evaluates the PS-SWIF approach and its system to achieve workflow interoperability using Web Services with asynchronous notification messages represented by WS-Eventing standard. This experiment covers different types of communication models provided by Workflow Management Coalition (WfMC). These models are: Chained processes, Nested synchronous sub-processes, Event synchronous sub-processes, and Nested sub-processes (Polling/Deferred Synchronous). Also, this experiment shows the flexibility and simplicity of the PS-SWIF approach when applied to a variety of workflow systems (Triana, Taverna, Kepler) in local and remote environments.

Keywords: Publish/subscribe, scientific workflow, web services, workflow interoperability.

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Authors: Ryad Zemouri, Paul Ciprian Patic

Abstract:

An adaptive software reliability prediction model using evolutionary connectionist approach based on Recurrent Radial Basis Function architecture is proposed. Based on the currently available software failure time data, Fuzzy Min-Max algorithm is used to globally optimize the number of the k Gaussian nodes. The corresponding optimized neural network architecture is iteratively and dynamically reconfigured in real-time as new actual failure time data arrives. The performance of our proposed approach has been tested using sixteen real-time software failure data. Numerical results show that our proposed approach is robust across different software projects, and has a better performance with respect to next-steppredictability compared to existing neural network model for failure time prediction.

Keywords: Neural network, Prediction error, Recurrent RadialBasis Function Network, Reliability prediction.

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Authors: S. Sundaravalli, M. C. Majumder, G. K. Vijayaraghavan

Abstract:

The study focuses to investigate the thermal response of delaminations and develop mathematical models using numerical results to obtain the optimum heat requirement and time to identify delaminations in GLARE type of Fibre Metal Laminates (FML) in both reflection mode and through-transmission (TT) mode of step pulsed active thermography (SPAT) method in the type of nondestructive testing and evaluation (NDTE) technique. The influence of applied heat flux and time on various sizes and depth of delaminations in FML is analyzed to investigate the thermal response through numerical simulations. A finite element method (FEM) is applied to simulate SPAT through ANSYS software based on 3D transient heat transfer principle with the assumption of reflection mode and TT mode of observation individually.

The results conclude that the numerical approach based on SPAT in reflection mode is more suitable for analysing smaller size of near-surface delaminations located at the thermal stimulator side and TT mode is more suitable for analysing smaller size of deeper delaminations located far from thermal stimulator side or near thermal detector/Infrared camera side. The mathematical models provide the optimum q and T at the required MRTD to identify unidentified delamination 7 with 25015.0022W/m2 at 2.531sec and delamination 8 with 16663.3356 W/m2 at 1.37857sec in reflection mode. In TT mode, the delamination 1 with 34954W/m2 at 13.0399sec, delamination 2 with 20002.67W/m2 at 1.998sec and delamination 7 with 20010.87 W/m2 at 0.6171sec could be identified.

Keywords: Step pulsed active thermography (SPAT), NDTE, FML, Delaminations, Finite element method.

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Authors: Azhar Hussain, Kashif Shahzad, Chunming Tang

Abstract:

this paper gives a novel approach towards real-time speed estimation of multiple traffic vehicles using fuzzy logic and image processing techniques with proper arrangement of camera parameters. The described algorithm consists of several important steps. First, the background is estimated by computing median over time window of specific frames. Second, the foreground is extracted using fuzzy similarity approach (FSA) between estimated background pixels and the current frame pixels containing foreground and background. Third, the traffic lanes are divided into two parts for both direction vehicles for parallel processing. Finally, the speeds of vehicles are estimated by Maximum a Posterior Probability (MAP) estimator. True ground speed is determined by utilizing infrared sensors for three different vehicles and the results are compared to the proposed algorithm with an accuracy of ± 0.74 kmph.

Keywords: Defuzzification, Fuzzy similarity approach, lane cropping, Maximum a Posterior Probability (MAP) estimator, Speed estimation

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Authors: C. E. Nugraheni, L. Abednego

Abstract:

This paper is concerned with minimization of mean tardiness and flow time in a real single machine production scheduling problem. Two variants of genetic algorithm as metaheuristic are combined with hyper-heuristic approach are proposed to solve this problem. These methods are used to solve instances generated with real world data from a company. Encouraging results are reported.

Keywords: Hyper-heuristics, evolutionary algorithms, production scheduling.

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