Abstract: This article presents the development of a neural
network cognitive model for the classification and detection of
different frequency signals. The basic structure of the implemented
neural network was inspired on the perception process that humans
generally make in order to visually distinguish between high and low
frequency signals. It is based on the dynamic neural network concept,
with delays. A special two-layer feedforward neural net structure was
successfully implemented, trained and validated, to achieve
minimum target error. Training confirmed that this neural net
structure descents and converges to a human perception classification
solution, even when far away from the target.
Abstract: In this study, three strains of Vibrio parahaemolyticus
(690, BCRC 13023 and BCRC 13025) were subjected to acid
adaptation at pH 5.5 for 90 min. The survival of acid-adapted and
non-adapted V. parahaemolyticus strains under simulated gastric
condition and their protein expression profiles were investigated.
Results showed that acid adaptation increased the survival of the test
V. parahaemolyticus strains after exposure to simulated gastric juice
(pH 3). Additionally, acid adaptation also affected the protein
expression in these V. parahaemolyticus strains. Nine proteins,
identified as atpA, atpB, DnaK, GroEL, OmpU, enolase,
fructose-bisphosphate aldolase, phosphoglycerate kinase and
triosephosphate isomerase, were induced by acid adaptation in two or
three of the test strains. These acid-adaptive proteins may play
important regulatory roles in the acid tolerance response (ATR) of V.
parahaemolyticus.
Abstract: Software engineering education not only embraces
technical skills of software development but also necessitates
communication and interaction among learners. In this paper, it is
proposed to adapt the PBL methodology that is especially designed to
be integrated into software engineering classroom in order to promote
collaborative learning environment. This approach helps students
better understand the significance of social aspects and provides a
systematic framework to enhance teamwork skills. The adaptation of
PBL facilitates the transition to an innovative software development
environment where cooperative learning can be actualized.
Abstract: The search for competitive advantages as one of the
main activities of a company has become a principle of contemporary
theories on Strategic Management. Innovation facilitates a company's
adaptation to the global competitive environment, representing the
important strategic role that it has to play in relation to managerial
performance and, as such, underlines the growing importance of
innovation and the use of a company's technological assets. This
paper therefore studies the effect in the results of four dimensions of
technological innovation strategy on a sample of Spanish wineries,
situated in the Castilla La-Mancha region of Spain, all of which are
registered under the La Mancha Designation of Origin (DO).
Abstract: In this paper test generation methods and appropriate fault models for testing and analysis of embedded systems described as (extended) finite state machines ((E)FSMs) are presented. Compared to simple FSMs, EFSMs specify not only the control flow but also the data flow. Thus, we define a two-level fault model to cover both aspects. The goal of this paper is to reuse well-known FSM-based test generation methods for automation of embedded system testing. These methods have been widely used in testing and validation of protocols and communicating systems. In particular, (E)FSMs-based specification and testing is more advantageous because (E)FSMs support the formal semantic of already standardised formal description techniques (FDTs) despite of their popularity in the design of hardware and software systems.
Abstract: With advances in computer vision, non-contact gaze tracking systems are heading towards being much easier to operate and more comfortable for use, the technique proposed in this paper is specially designed for achieving these goals. For the convenience in operation, the proposal aims at the system with simple configuration which is composed of a fixed wide angle camera and dual infrared illuminators. Then in order to enhance the usability of the system based on single camera, a self-adjusting method which is called Real-time gaze Tracking Algorithm with head movement Compensation (RTAC) is developed for estimating the gaze direction under natural head movement and simplifying the calibration procedure at the same time. According to the actual evaluations, the average accuracy of about 1° is achieved over a field of 20×15×15 cm3.
Abstract: Manufacturing companies are facing a broad variety
of challenges caused by a dynamic production environment. To
succeed in such an environment, it is crucial to minimize the loss of
time required to trigger the adaptation process of a company-s
production structures. This paper presents an approach for the
continuous monitoring of production structures by neurologic
principles. It enhances classical monitoring concepts, which are
principally focused on reactive strategies, and enables companies to
act proactively. Thereby, strategic aspects regarding the
harmonization of certain life cycles are integrated into the decision
making process for triggering the reconfiguration process of the
production structure.
Abstract: Since the presentation of the backpropagation algorithm, a vast variety of improvements of the technique for training a feed forward neural networks have been proposed. This article focuses on two classes of acceleration techniques, one is known as Local Adaptive Techniques that are based on weightspecific only, such as the temporal behavior of the partial derivative of the current weight. The other, known as Dynamic Adaptation Methods, which dynamically adapts the momentum factors, α, and learning rate, η, with respect to the iteration number or gradient. Some of most popular learning algorithms are described. These techniques have been implemented and tested on several problems and measured in terms of gradient and error function evaluation, and percentage of success. Numerical evidence shows that these techniques improve the convergence of the Backpropagation algorithm.
Abstract: With the advent of emerging personal computing paradigms such as ubiquitous and mobile computing, Web contents are becoming accessible from a wide range of mobile devices. Since these devices do not have the same rendering capabilities, Web contents need to be adapted for transparent access from a variety of client agents. Such content adaptation results in better rendering and faster delivery to the client device. Nevertheless, Web content adaptation sets new challenges for semantic markup. This paper presents an advanced components platform, called MorfeoSMC, enabling the development of mobility applications and services according to a channel model based on Services Oriented Architecture (SOA) principles. It then goes on to describe the potential for integration with the Semantic Web through a novel framework of external semantic annotation of mobile Web contents. The role of semantic annotation in this framework is to describe the contents of individual documents themselves, assuring the preservation of the semantics during the process of adapting content rendering, as well as to exploit these semantic annotations in a novel user profile-aware content adaptation process. Semantic Web content adaptation is a way of adding value to and facilitates repurposing of Web contents (enhanced browsing, Web Services location and access, etc).
Abstract: Software reuse can be considered as the most realistic
and promising way to improve software engineering productivity and
quality. Automated assistance for software reuse involves the
representation, classification, retrieval and adaptation of components.
The representation and retrieval of components are important to
software reuse in Component-Based on Software Development
(CBSD). However, current industrial component models mainly focus
on the implement techniques and ignore the semantic information
about component, so it is difficult to retrieve the components that
satisfy user-s requirements. This paper presents a method of business
component retrieval based on specification matching to solve the
software reuse of enterprise information system. First, a business
component model oriented reuse is proposed. In our model, the
business data type is represented as sign data type based on XML,
which can express the variable business data type that can describe the
variety of business operations. Based on this model, we propose
specification match relationships in two levels: business operation
level and business component level. In business operation level, we
use input business data types, output business data types and the
taxonomy of business operations evaluate the similarity between
business operations. In the business component level, we propose five
specification matches between business components. To retrieval
reusable business components, we propose the measure of similarity
degrees to calculate the similarities between business components.
Finally, a business component retrieval command like SQL is
proposed to help user to retrieve approximate business components
from component repository.
Abstract: The adaptive backstepping controller for inverted pendulum is designed by using the general motion control model. Backstepping is a novel nonlinear control technique based on the Lyapunov design approach, used when higher derivatives of parameter estimation appear. For easy parameter adaptation, the mathematical model of the inverted pendulum converted into the motion control model. This conversion is performed by taking functions of unknown parameters and dynamics of the system. By using motion control model equations, inverted pendulum is simulated without any information about not only parameters but also measurable dynamics. Also these results are compare with the adaptive backstepping controller which extended with integral action that given from [1].
Abstract: A novel method of individual level adaptive mutation rate control called the rank-scaled mutation rate for genetic algorithms is introduced. The rank-scaled mutation rate controlled genetic algorithm varies the mutation parameters based on the rank of each individual within the population. Thereby the distribution of the fitness of the papulation is taken into consideration in forming the new mutation rates. The best fit mutate at the lowest rate and the least fit mutate at the highest rate. The complexity of the algorithm is of the order of an individual adaptation scheme and is lower than that of a self-adaptation scheme. The proposed algorithm is tested on two common problems, namely, numerical optimization of a function and the traveling salesman problem. The results show that the proposed algorithm outperforms both the fixed and deterministic mutation rate schemes. It is best suited for problems with several local optimum solutions without a high demand for excessive mutation rates.
Abstract: The influence of physical (external added weight) and
neurophysiological (fatigue) factors on static and dynamic balance in
sport related activities was typified statically by the Romberg test
(one foot flat, eyes open) and dynamically by jumping and hopping
in both horizontal and vertical directions. Twenty healthy males were
participated in this study. In Static condition, added weight increased
body-s inertia and therefore decreased body sway in AP direction
though not significantly. Dynamically, added weight significantly
increased body sway in both ML and AP directions, indicating
instability, and the use of the counter rotating segments mechanism to
maintain balance was demonstrated. Fatigue on the other hand
significantly increased body sway during static balance as a
neurophysiological adaptation primarily to the inverted pendulum
mechanism. Dynamically, fatigue significantly increased body sway
in both ML and AP directions again indicating instability but with a
greater use of counter rotating segments mechanism. Differential
adaptations for each of the two balance mechanisms (inverted
pendulum and counter rotating segments) were found between one
foot flat and two feet flat dynamic conditions, as participants relied
more heavily on the first in the one foot flat conditions and relied
more on the second in the two feet flat conditions.
Abstract: In this paper, a field oriented control (FOC) induction motor drive is presented. In order to eliminate the speed sensor, an adaptation algorithm for tuning the rotor speed is proposed. Based on the Model Reference Adaptive System (MRAS) scheme, the rotor speed is tuned to obtain an exact FOC induction motor drive. The reference and adjustable models, developed in stationary stator reference frame, are used in the MRAS scheme to estimate induction rotor speed from measured terminal voltages and currents. The Integral Proportional (IP) gains speed controller are tuned by a modern approach that is the Particle Swarm Optimization (PSO) algorithm in order to optimize the parameters of the IP controller. The use of PSO as an optimization algorithm makes the drive robust, with faster dynamic response, higher accuracy and insensitive to load variation. The proposed algorithm has been tested by numerical simulation, showing the capability of driving load.
Abstract: The work presented in this paper focus on Knowledge Management services enabling CSCW (Computer Supported Cooperative Work) applications to provide an appropriate adaptation to the user and the situation in which the user is working. In this paper, we explain how a knowledge management system can be designed to support users in different situations exploiting contextual data, users' preferences, and profiles of involved artifacts (e.g., documents, multimedia files, mockups...). The presented work roots in the experience we had in the MILK project and early steps made in the MAIS project.
Abstract: Yeast cells live in a constantly changing environment that requires the continuous adaptation of their genomic program in order to sustain their homeostasis, survive and proliferate. Due to the advancement of high throughput technologies, there is currently a large amount of data such as gene expression, gene deletion and protein-protein interactions for S. Cerevisiae under various environmental conditions. Mining these datasets requires efficient computational methods capable of integrating different types of data, identifying inter-relations between different components and inferring functional groups or 'modules' that shape intracellular processes. This study uses computational methods to delineate some of the mechanisms used by yeast cells to respond to environmental changes. The GRAM algorithm is first used to integrate gene expression data and ChIP-chip data in order to find modules of coexpressed and co-regulated genes as well as the transcription factors (TFs) that regulate these modules. Since transcription factors are themselves transcriptionally regulated, a three-layer regulatory cascade consisting of the TF-regulators, the TFs and the regulated modules is subsequently considered. This three-layer cascade is then modeled quantitatively using artificial neural networks (ANNs) where the input layer corresponds to the expression of the up-stream transcription factors (TF-regulators) and the output layer corresponds to the expression of genes within each module. This work shows that (a) the expression of at least 33 genes over time and for different stress conditions is well predicted by the expression of the top layer transcription factors, including cases in which the effect of up-stream regulators is shifted in time and (b) identifies at least 6 novel regulatory interactions that were not previously associated with stress-induced changes in gene expression. These findings suggest that the combination of gene expression and protein-DNA interaction data with artificial neural networks can successfully model biological pathways and capture quantitative dependencies between distant regulators and downstream genes.
Abstract: In blended learning environments, the Internet can be combined with other technologies. The aim of this research was to design, introduce and validate a model to support synchronous and asynchronous activities by managing content domains in an Adaptive Hypermedia System (AHS). The application is based on information recovery techniques, clustering algorithms and adaptation rules to adjust the user's model to contents and objects of study. This system was applied to blended learning in higher education. The research strategy used was the case study method. Empirical studies were carried out on courses at two universities to validate the model. The results of this research show that the model had a positive effect on the learning process. The students indicated that the synchronous and asynchronous scenario is a good option, as it involves a combination of work with the lecturer and the AHS. In addition, they gave positive ratings to the system and stated that the contents were adapted to each user profile.
Abstract: Lately, an interest has grown greatly in the usages of
RFID in an un-presidential applications. It is shown in the adaptation
of major software companies such as Microsoft, IBM, and Oracle
the RFID capabilities in their major software products. For example
Microsoft SharePoints 2010 workflow is now fully compatible with
RFID platform. In addition, Microsoft BizTalk server is also capable
of all RFID sensors data acquisition. This will lead to applications
that required high bit rate, long range and a multimedia content in
nature. Higher frequencies of operation have been designated for
RFID tags, among them are the 2.45 and 5.8 GHz. The higher the
frequency means higher range, and higher bit rate, but the drawback
is the greater cost. In this paper we present a single layer, low
profile patch antenna operates at 5.8 GHz with pure resistive input
impedance of 50 and close to directive radiation. Also, we propose
a modification to the design in order to improve the operation band
width from 8.7 to 13.8
Abstract: This paper proposes an effective adaptation learning
algorithm based on artificial neural networks for speed control of an
induction motor assumed to operate in a high-performance drives
environment. The structure scheme consists of a neural network
controller and an algorithm for changing the NN weights in order that
the motor speed can accurately track of the reference command. This
paper also makes uses a very realistic and practical scheme to
estimate and adaptively learn the noise content in the speed load
torque characteristic of the motor. The availability of the proposed
controller is verified by through a laboratory implementation and
under computation simulations with Matlab-software. The process is
also tested for the tracking property using different types of reference
signals. The performance and robustness of the proposed control
scheme have evaluated under a variety of operating conditions of the
induction motor drives. The obtained results demonstrate the
effectiveness of the proposed control scheme system performances,
both in steady state error in speed and dynamic conditions, was found
to be excellent and those is not overshoot.
Abstract: It is not easy to imagine how the existing city can be
converted to the principles of sustainability, however, the need for
innovation, requires a pioneering phase which must address the main
problems of rehabilitation of the operating models of the city. Today,
however, there is a growing awareness that the identification and
implementation of policies and measures to promote the adaptation,
resilience and reversibility of the city, require the contribution of our
discipline. This breakthrough is present in some recent international
experiences of Climate Plans, in which the envisaged measures are
closely interwoven with those of urban planning. These experiences,
provide some answers principle questions, such as: how the strategies
to combat climate can be integrated in the instruments of the local
government; what new and specific analysis must be introduced in
urban planning in order to understand the issues of urban
sustainability, and how the project compares with different spatial
scales.