Abstract: This research proposes a methodology for patent-citation-based technology input-output analysis by applying the patent information to input-output analysis developed for the dependencies among different industries. For this analysis, a technology relationship matrix and its components, as well as input and technology inducement coefficients, are constructed using patent information. Then, a technology inducement coefficient is calculated by normalizing the degree of citation from certain IPCs to the different IPCs (International patent classification) or to the same IPCs. Finally, we construct a Dependency Structure Matrix (DSM) based on the technology inducement coefficient to suggest a useful application for this methodology.
Abstract: The paper presents a complete discrete statistical framework, based on a novel vector quantization (VQ) front-end process. This new VQ approach performs an optimal distribution of VQ codebook components on HMM states. This technique that we named the distributed vector quantization (DVQ) of hidden Markov models, succeeds in unifying acoustic micro-structure and phonetic macro-structure, when the estimation of HMM parameters is performed. The DVQ technique is implemented through two variants. The first variant uses the K-means algorithm (K-means- DVQ) to optimize the VQ, while the second variant exploits the benefits of the classification behavior of neural networks (NN-DVQ) for the same purpose. The proposed variants are compared with the HMM-based baseline system by experiments of specific Arabic consonants recognition. The results show that the distributed vector quantization technique increase the performance of the discrete HMM system.
Abstract: Software Reliability is one of the key factors in the software development process. Software Reliability is estimated using reliability models based on Non Homogenous Poisson Process. In most of the literature the Software Reliability is predicted only in testing phase. So it leads to wrong decision-making concept. In this paper, two Software Reliability concepts, testing and operational phase are studied in detail. Using S-Shaped Software Reliability Growth Model (SRGM) and Exponential SRGM, the testing and operational reliability values are obtained. Finally two reliability values are compared and optimal release time is investigated.
Abstract: In this paper, a robust digital image watermarking
scheme for copyright protection applications using the singular value
decomposition (SVD) is proposed. In this scheme, an entropy
masking model has been applied on the host image for the texture
segmentation. Moreover, the local luminance and textures of the host
image are considered for watermark embedding procedure to
increase the robustness of the watermarking scheme. In contrast to all
existing SVD-based watermarking systems that have been designed
to embed visual watermarks, our system uses a pseudo-random
sequence as a watermark. We have tested the performance of our
method using a wide variety of image processing attacks on different
test images. A comparison is made between the results of our
proposed algorithm with those of a wavelet-based method to
demonstrate the superior performance of our algorithm.
Abstract: A self tuning PID control strategy using reinforcement
learning is proposed in this paper to deal with the control of wind
energy conversion systems (WECS). Actor-Critic learning is used to
tune PID parameters in an adaptive way by taking advantage of the
model-free and on-line learning properties of reinforcement learning
effectively. In order to reduce the demand of storage space and to
improve the learning efficiency, a single RBF neural network is used
to approximate the policy function of Actor and the value function of
Critic simultaneously. The inputs of RBF network are the system
error, as well as the first and the second-order differences of error.
The Actor can realize the mapping from the system state to PID
parameters, while the Critic evaluates the outputs of the Actor and
produces TD error. Based on TD error performance index and
gradient descent method, the updating rules of RBF kernel function
and network weights were given. Simulation results show that the
proposed controller is efficient for WECS and it is perfectly
adaptable and strongly robust, which is better than that of a
conventional PID controller.
Abstract: With the rapid growth in business size, today's businesses orient towards electronic technologies. Amazon.com and e-bay.com are some of the major stakeholders in this regard. Unfortunately the enormous size and hugely unstructured data on the web, even for a single commodity, has become a cause of ambiguity for consumers. Extracting valuable information from such an everincreasing data is an extremely tedious task and is fast becoming critical towards the success of businesses. Web content mining can play a major role in solving these issues. It involves using efficient algorithmic techniques to search and retrieve the desired information from a seemingly impossible to search unstructured data on the Internet. Application of web content mining can be very encouraging in the areas of Customer Relations Modeling, billing records, logistics investigations, product cataloguing and quality management. In this paper we present a review of some very interesting, efficient yet implementable techniques from the field of web content mining and study their impact in the area specific to business user needs focusing both on the customer as well as the producer. The techniques we would be reviewing include, mining by developing a knowledge-base repository of the domain, iterative refinement of user queries for personalized search, using a graphbased approach for the development of a web-crawler and filtering information for personalized search using website captions. These techniques have been analyzed and compared on the basis of their execution time and relevance of the result they produced against a particular search.
Abstract: Pairwise testing, which requires that every
combination of valid values of each pair of system factors be covered
by at lease one test case, plays an important role in software testing
since many faults are caused by unexpected 2-way interactions among
system factors. Although meta-heuristic strategies like simulated
annealing can generally discover smaller pairwise test suite, they may
cost more time to perform search, compared with greedy algorithms.
We propose a new method, improved Extremal Optimization (EO)
based on the Bak-Sneppen (BS) model of biological evolution, for
constructing pairwise test suites and define fitness function according
to the requirement of improved EO. Experimental results show that
improved EO gives similar size of resulting pairwise test suite and
yields an 85% reduction in solution time over SA.
Abstract: Both software applications and their development environment are becoming more and more distributed. This trend impacts not only the way software computes, but also how it looks. This article proposes a Human Computer Interface (HCI) template from three representative applications we have developed. These applications include a Multi-Agent System based software, a 3D Internet computer game with distributed game world logic, and a programming language environment used in constructing distributed neural network and its visualizations. HCI concepts that are common to these applications are described in abstract terms in the template. These include off-line presentation of global entities, entities inside a hierarchical namespace, communication and languages, reconfiguration of entity references in a graph, impersonation and access right, etc. We believe the metaphor that underlies an HCI concept as well as the relationships between a bunch of HCI concepts are crucial to the design of software systems and vice versa.
Abstract: This paper is a description approach to predict
incoming and outgoing data rate in network system by using
association rule discover, which is one of the data mining
techniques. Information of incoming and outgoing data in each
times and network bandwidth are network performance
parameters, which needed to solve in the traffic problem. Since
congestion and data loss are important network problems. The result
of this technique can predicted future network traffic. In addition,
this research is useful for network routing selection and network
performance improvement.
Abstract: Recent advancements in sensor technologies and
Wireless Body Area Networks (WBANs) have led to the
development of cost-effective healthcare devices which can be used
to monitor and analyse a person-s physiological parameters from
remote locations. These advancements provides a unique opportunity
to overcome current healthcare challenges of low quality service
provisioning, lack of easy accessibility to service varieties, high costs
of services and increasing population of the elderly experienced
globally. This paper reports on a prototype implementation of an
architecture that seamlessly integrates Wireless Body Area Network
(WBAN) with Web services (WS) to proactively collect
physiological data of remote patients to recommend diagnostic
services. Technologies based upon WBAN and WS can provide
ubiquitous accessibility to a variety of services by allowing
distributed healthcare resources to be massively reused to provide
cost-effective services without individuals physically moving to the
locations of those resources. In addition, these technologies can
reduce costs of healthcare services by allowing individuals to access
services to support their healthcare. The prototype uses WBAN body
sensors implemented on arduino fio platforms to be worn by the
patient and an android smart phone as a personal server. The
physiological data are collected and uploaded through GPRS/internet
to the Medical Health Server (MHS) to be analysed. The prototype
monitors the activities, location and physiological parameters such as
SpO2 and Heart Rate of the elderly and patients in rehabilitation.
Medical practitioners would have real time access to the uploaded
information through a web application.
Abstract: An application framework provides a reusable design
and implementation for a family of software systems. If the
framework contains defects, the defects will be passed on to the
applications developed from the framework. Framework defects are
hard to discover at the time the framework is instantiated. Therefore,
it is important to remove all defects before instantiating the
framework. In this paper, two measures for the adequacy of an
object-oriented system-based testing technique are introduced. The
measures assess the usefulness and uniqueness of the testing
technique. The two measures are applied to experimentally compare
the adequacy of two testing techniques introduced to test objectoriented
frameworks at the system level. The two considered testing
techniques are the New Framework Test Approach and Testing
Frameworks Through Hooks (TFTH). The techniques are also
compared analytically in terms of their coverage power of objectoriented
aspects. The comparison study results show that the TFTH
technique is better than the New Framework Test Approach in terms
of usefulness degree, uniqueness degree, and coverage power.
Abstract: In recent years, tuned mass damper (TMD) control systems for civil engineering structures have attracted considerable attention. This paper emphasizes on the application of particle swarm application (PSO) to design and optimize the parameters of the TMD control scheme for achieving the best results in the reduction of the building response under earthquake excitations. The Integral of the Time multiplied Absolute value of the Error (ITAE) based on relative displacement of all floors in the building is taken as a performance index of the optimization criterion. The problem of robustly TMD controller design is formatted as an optimization problem based on the ITAE performance index to be solved using the PSO technique which has a story ability to find the most optimistic results. An 11- story realistic building, located in the city of Rasht, Iran is considered as a test system to demonstrate effectiveness of the proposed method. The results analysis through the time-domain simulation and some performance indices reveals that the designed PSO based TMD controller has an excellent capability in reduction of the seismically excited example building.
Abstract: Software complexity metrics are used to predict
critical information about reliability and maintainability of software
systems. Object oriented software development requires a different
approach to software complexity metrics. Object Oriented Software
Metrics can be broadly classified into static and dynamic metrics.
Static Metrics give information at the code level whereas dynamic
metrics provide information on the actual runtime. In this paper we
will discuss the various complexity metrics, and the comparison
between static and dynamic complexity.
Abstract: Combinatorial optimization problems arise in many scientific and practical applications. Therefore many researchers try to find or improve different methods to solve these problems with high quality results and in less time. Genetic Algorithm (GA) and Simulated Annealing (SA) have been used to solve optimization problems. Both GA and SA search a solution space throughout a sequence of iterative states. However, there are also significant differences between them. The GA mechanism is parallel on a set of solutions and exchanges information using the crossover operation. SA works on a single solution at a time. In this work SA and GA are combined using new technique in order to overcome the disadvantages' of both algorithms.
Abstract: In this paper we propose a mixture of two different
distributions such as Exponential-Gamma, Exponential-Weibull and
Gamma-Weibull to model heterogeneous survival data. Various
properties of the proposed mixture of two different distributions are
discussed. Maximum likelihood estimations of the parameters are
obtained by using the EM algorithm. Illustrative example based on
real data are also given.
Abstract: A hybrid feature based adaptive particle filter algorithm is presented for object tracking in real scenarios with static camera.
The hybrid feature is combined by two effective features: the Grayscale Arranging Pairs (GAP) feature and the color histogram feature. The GAP feature has high discriminative ability even under conditions of severe illumination variation and dynamic background
elements, while the color histogram feature has high reliability to identify the detected objects. The combination of two features covers the shortage of single feature. Furthermore, we adopt an updating
target model so that some external problems such as visual angles can be overcame well. An automatic initialization algorithm is introduced which provides precise initial positions of objects. The experimental
results show the good performance of the proposed method.
Abstract: This paper presents a novel algorithm of stereo
correspondence with rank transform. In this algorithm we used the
genetic algorithm to achieve the accurate disparity map. Genetic
algorithms are efficient search methods based on principles of
population genetic, i.e. mating, chromosome crossover, gene
mutation, and natural selection. Finally morphology is employed to
remove the errors and discontinuities.
Abstract: With data centers, end-users can realize the pervasiveness of services that will be one day the cornerstone of our lives. However, data centers are often classified as computing systems that consume the most amounts of power. To circumvent such a problem, we propose a self-adaptive weighted sum methodology that jointly optimizes the performance and power consumption of any given data center. Compared to traditional methodologies for multi-objective optimization problems, the proposed self-adaptive weighted sum technique does not rely on a systematical change of weights during the optimization procedure. The proposed technique is compared with the greedy and LR heuristics for large-scale problems, and the optimal solution for small-scale problems implemented in LINDO. the experimental results revealed that the proposed selfadaptive weighted sum technique outperforms both of the heuristics and projects a competitive performance compared to the optimal solution.
Abstract: This work proposes a novel market-based air traffic flow control model considering competitive airlines in air traffic network. In the flow model, an agent based framework for resources (link/time pair) pricing is described. Resource agent and auctioneer for groups of resources are also introduced to simulate the flow management in Air Traffic Control (ATC). Secondly, the distributed group pricing algorithm is introduced, which efficiently reflect the competitive nature of the airline industry. Resources in the system are grouped according to the degree of interaction, and each auctioneer adjust s the price of one group of resources respectively until the excess demand of resources becomes zero when the demand and supply of resources of the system changes. Numerical simulation results show the feasibility of solving the air traffic flow control problem using market mechanism and pricing algorithms on the air traffic network.
Abstract: In this paper, we introduce GODYS-PC software
package for modeling, simulating and analyzing dynamic systems.
To illustrate the use of GODYS-PC we present a few examples
which concern modeling and simulating of engineering systems. In
order to compare GODYS-PC with widely used in academia and
industry Simulink®, the same examples are provided both in
GODYS-PC and Simulink®.