Abstract: In the field of concepts, the measure of Wu and Palmer [1] has the advantage of being simple to implement and have good performances compared to the other similarity measures [2]. Nevertheless, the Wu and Palmer measure present the following disadvantage: in some situations, the similarity of two elements of an IS-A ontology contained in the neighborhood exceeds the similarity value of two elements contained in the same hierarchy. This situation is inadequate within the information retrieval framework. To overcome this problem, we propose a new similarity measure based on the Wu and Palmer measure. Our objective is to obtain realistic results for concepts not located in the same way. The obtained results show that compared to the Wu and Palmer approach, our measure presents a profit in terms of relevance and execution time.
Abstract: This paper presents a review on vision aided systems
and proposes an approach for visual rehabilitation using stereo vision
technology. The proposed system utilizes stereo vision, image
processing methodology and a sonification procedure to support
blind navigation. The developed system includes a wearable
computer, stereo cameras as vision sensor and stereo earphones, all
moulded in a helmet. The image of the scene infront of visually
handicapped is captured by the vision sensors. The captured images
are processed to enhance the important features in the scene in front,
for navigation assistance. The image processing is designed as model
of human vision by identifying the obstacles and their depth
information. The processed image is mapped on to musical stereo
sound for the blind-s understanding of the scene infront. The
developed method has been tested in the indoor and outdoor
environments and the proposed image processing methodology is
found to be effective for object identification.
Abstract: Cities denote instantaneously a challenge and an
opportunity for climate change policy. Cities are the place where
most energy services are needed because urbanization is closely
linked to high population densities and concentration of economic
activities and production (Urban energy demand). Consequently, it is
critical to explain about the role of cities within the world-s energy
systems and its correlation with the climate change issue. With more
than half of the world-s population already living in urban areas, and
that percentage expected to rise to 75 per cent by 2050, it is clear that
the path to sustainable development must pass through cities. Cities
expanding in size and population pose increased challenges to the
environment, of which energy is part as a natural resource, and to the
quality of life. Nowadays, most cities have already understood the
importance of sustainability, both at their local scale as in terms of
their contribution to sustainability at higher geographical scales. It
requires the perception of a city as a complex and dynamic
ecosystem, an open system, or cluster of systems, where the energy
as well as the other natural resources is transformed to satisfy the
needs of the different urban activities. In fact, buildings and
transportation generally represent most of cities direct energy
demand, i.e., between 60 per cent and 80 per cent of the overall
consumption. Buildings, both residential and services are usually
influenced by the local physical and social conditions. In terms of
transport, the energy demand is also strongly linked with the specific
characteristics of a city (urban mobility).The concept of a “smart
city" builds on statistics as seven key axes of a city-s success in
moving towards common platform (brain nerve)of sustainable urban
energy systems.
With the aforesaid knowledge, the authors have suggested a frame
work to role of cities, as energy actors for smart city management.
The authors have discusses the potential elements needed for energy
in smart cities and also identified potential energy actions and
relevant barriers. Furthermore, three levels of city smartness in cities
actions to overcome market /institutional failures with a local
approach are distinguished. The authors have made an attempt to
conceive and implement concepts of city smartness by adopting the
city or local government as nerve center through an integrated
planning approach. Finally, concluding with recommendations for
the organization of the Smart Sustainable Cities for positive changes
of urban India.
Abstract: A new strategy of control is formulated for chaos synchronization of non-identical chaotic systems with different orders using the Borne and Gentina practical criterion associated with the Benrejeb canonical arrow form matrix, to drift the stability property of dynamic complex systems. The designed controller ensures that the state variables of controlled chaotic slave systems globally synchronize with the state variables of the master systems, respectively. Numerical simulations are performed to illustrate the efficiency of the proposed method.
Abstract: Information on weed distribution within the field is
necessary to implement spatially variable herbicide application.
Since hand labor is costly, an automated weed control system could be
feasible. This paper deals with the development of an algorithm for
real time specific weed recognition system based on Histogram
Analysis of an image that is used for the weed classification. This
algorithm is specifically developed to classify images into broad and
narrow class for real-time selective herbicide application. The
developed system has been tested on weeds in the lab, which have
shown that the system to be very effectiveness in weed identification.
Further the results show a very reliable performance on images of
weeds taken under varying field conditions. The analysis of the results
shows over 95 percent classification accuracy over 140 sample images
(broad and narrow) with 70 samples from each category of weeds.
Abstract: More and more natural disasters are happening every
year: floods, earthquakes, volcanic eruptions, etc. In order to reduce
the risk of possible damages, governments all around the world are
investing into development of Early Warning Systems (EWS) for
environmental applications. The most important task of the EWS is
identification of the onset of critical situations affecting environment
and population, early enough to inform the authorities and general
public. This paper describes an approach for monitoring of flood
protections systems based on machine learning methods. An
Artificial Intelligence (AI) component has been developed for
detection of abnormal dike behaviour. The AI module has been
integrated into an EWS platform of the UrbanFlood project (EU
Seventh Framework Programme) and validated on real-time
measurements from the sensors installed in a dike.
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: This study offers a new simple method for assessing
an axial part-through crack in a pipe wall. The method utilizes simple
approximate expressions for determining the fracture parameters K,
J, and employs these parameters to determine critical dimensions of a
crack on the basis of equality between the J-integral and the J-based
fracture toughness of the pipe steel. The crack tip constraint is taken
into account by the so-called plastic constraint factor C, by which the
uniaxial yield stress in the J-integral equation is multiplied. The
results of the prediction of the fracture condition are verified by burst
tests on test pipes.
Abstract: Performance management seems to be essential in
business area and is also an exciting topic. Despite significant and
myriads of research efforts, performance management guide today as a
rigorous approach is still in an immature state and metrics are often
selected based on intuitive and heuristic approach. In R&D side, the
difficulty to guide the proper performance management is even more
increasing due to the natural characteristics of R&D such as unique or
domain-specific problems. In our approach, we present R&D
performance management guide considering various characteristics of
R&D side: performance evaluation objectives, dimensions, metrics,
and uncertainties of R&D sector.
Abstract: Feed is one of the factors which play an important role in determining a successful development of an aquaculture industry. It is always critical to produce the best aquaculture diet at a minimum cost in order to trim down the operational cost and gain more profit. However, the feed mix problem becomes increasingly difficult since many issues need to be considered simultaneously. Thus, the purpose of this paper is to review the current techniques used by nutritionist and researchers to tackle the issues. Additionally, this paper introduce an enhance algorithm which is deemed suitable to deal with all the issues arise. The proposed technique refers to Hybrid Genetic Algorithm which is expected to obtain the minimum cost diet for farmed animal, while satisfying nutritional requirements. Hybrid GA technique with artificial bee algorithm is expected to reduce the penalty function and provide a better solution for the feed mix problem.
Abstract: The automatic discrimination of seismic signals is an important practical goal for earth-science observatories due to the large amount of information that they receive continuously. An essential discrimination task is to allocate the incoming signal to a group associated with the kind of physical phenomena producing it. In this paper, two classes of seismic signals recorded routinely in geophysical laboratory of the National Center for Scientific and Technical Research in Morocco are considered. They correspond to signals associated to local earthquakes and chemical explosions. The approach adopted for the development of an automatic discrimination system is a modular system composed by three blocs: 1) Representation, 2) Dimensionality reduction and 3) Classification. The originality of our work consists in the use of a new wavelet called "modified Mexican hat wavelet" in the representation stage. For the dimensionality reduction, we propose a new algorithm based on the random projection and the principal component analysis.
Abstract: Grid scheduling is the process of mapping grid jobs to resources over multiple administrative domains. Traditionally, application-level schedulers have been tightly integrated with the application itself and were not easily applied to other applications. This design is generic that decouples the scheduler core (the search procedure) from the application-specific (e.g. application performance models) and platform-specific (e.g. collection of resource information) components used by the search procedure. In this decoupled approach the application details are not revealed completely to broker, but customer will give the application to resource provider for execution. In a decoupled approach, apart from scheduling, the resource selection can be performed independently in order to achieve scalability.
Abstract: The after–sales activities are nowadays acknowledged
as a relevant source of revenue, profit and competitive advantage in
most manufacturing industries. Top and middle management,
therefore, should focus on the definition of a structured business
performance measurement system for the after-sales business. The
paper aims at filling this gap, and presents an integrated methodology
for the after-sales network performance measurement, and provides
an empirical application to automotive case companies and their
official service network. This is the first study that presents an
integrated multivariate approach for total assessment and
improvement of after-sale services.
Abstract: This paper reviews the major contributions to the Motion Planning (MP) field throughout a 35-year period, from classic approaches to heuristic algorithms. Due to the NP-Hardness of the MP problem, heuristic methods have outperformed the classic approaches and have gained wide popularity. After surveying around 1400 papers in the field, the amount of existing works for each method is identified and classified. Especially, the history and applications of numerous heuristic methods in MP is investigated. The paper concludes with comparative tables and graphs demonstrating the frequency of each MP method's application, and so can be used as a guideline for MP researchers.
Abstract: The concept of housing affordability is a contested
issue, but a pressing and widespread problem for many countries.
Simple ratio measures based on housing expenditure and income are
habitually used to defined and assess housing affordability. However,
conceptualising and measuring affordability in this manner focuses
only on financial attributes and fails to deal with wider issues such as
housing quality, location and access to services and facilities.
The research is based on the notion that the housing affordability
problem encompasses more than the financial costs of housing and a
households ability to meet such costs and must address larger issues
such as social and environmental sustainability and the welfare of
households. Therefore, the need arises for a broad and more
encompassing set of attributes by which housing affordability can be
assessed. This paper presents a system of criteria by which the
affordability of different housing locations could be assessed in a
comprehensive and sustainable manner. Moreover, the paper explores
the way in which such criteria could be measured.
Abstract: Hair is a non homogenous complex material which
can be associated with a polymer. It is made up 95% of Keratin.
Hair has a great social significance for human beings. In the High
Middle Ages, for example, long hairs have been reserved for kings
and nobles.
Most common interest in hair is focused on hair growth, hair types
and hair care, but hair is also an important biomaterial which can
vary depending on ethnic origin or on age, hair colour for example
can be a sign of ethnic ancestry or age (dark hair for Asiatic, blond
hair for Caucasian and white hair for old people in general).
In this context, different approaches have been conducted to
determine the differences in mechanical properties and characterize
the fracture topography at the surface of hair depending on its type
and its age.
A tensile testing machine was especially designed to achieve
tensile tests on hair. This device is composed of a microdisplacement
system and a force sensor whose peak load is limited to
3N. The curves and the values extracted from each experiment, allow
us to compare the evolution of the mechanical properties from one
hair to another.
Observations with a Scanning Electron Microscope (SEM) and
with an interferometer were made on different hairs. Thus, it is
possible to access the cuticle state and the fracture topography for
each category.
Abstract: An evolutionary method whose selection and recombination
operations are based on generalization error-bounds of
support vector machine (SVM) can select a subset of potentially
informative genes for SVM classifier very efficiently [7]. In this
paper, we will use the derivative of error-bound (first-order criteria)
to select and recombine gene features in the evolutionary process,
and compare the performance of the derivative of error-bound with
the error-bound itself (zero-order) in the evolutionary process. We
also investigate several error-bounds and their derivatives to compare
the performance, and find the best criteria for gene selection
and classification. We use 7 cancer-related human gene expression
datasets to evaluate the performance of the zero-order and first-order
criteria of error-bounds. Though both criteria have the same strategy
in theoretically, experimental results demonstrate the best criterion
for microarray gene expression data.
Abstract: To compress, improve bit error performance and also enhance 2D images, a new scheme, called Iterative Cellular-Turbo System (IC-TS) is introduced. In IC-TS, the original image is partitioned into 2N quantization levels, where N is denoted as bit planes. Then each of the N-bit-plane is coded by Turbo encoder and transmitted over Additive White Gaussian Noise (AWGN) channel. At the receiver side, bit-planes are re-assembled taking into consideration of neighborhood relationship of pixels in 2-D images. Each of the noisy bit-plane values of the image is evaluated iteratively using IC-TS structure, which is composed of equalization block; Iterative Cellular Image Processing Algorithm (ICIPA) and Turbo decoder. In IC-TS, there is an iterative feedback link between ICIPA and Turbo decoder. ICIPA uses mean and standard deviation of estimated values of each pixel neighborhood. It has extra-ordinary satisfactory results of both Bit Error Rate (BER) and image enhancement performance for less than -1 dB Signal-to-Noise Ratio (SNR) values, compared to traditional turbo coding scheme and 2-D filtering, applied separately. Also, compression can be achieved by using IC-TS systems. In compression, less memory storage is used and data rate is increased up to N-1 times by simply choosing any number of bit slices, sacrificing resolution. Hence, it is concluded that IC-TS system will be a compromising approach in 2-D image transmission, recovery of noisy signals and image compression.
Abstract: Transport and logistics are the lifeblood of societies.
There is a strong correlation between overall growth in economic
activity and growth of transport. The movement of people and goods
has the potential for creating wealth and prosperity, therefore the
state of transportation infrastructure and especially the condition of
road networks is often a governmental priority. The design, building
and maintenance of national roads constitute a substantial share of
government budgets. Taking into account the magnitude and
importance of these investments, the expedience, efficiency and
sustainability of these projects are of great public interest. This paper
provides an overview of supply chain management principles applied
to road construction. In addition, road construction performance
measurement systems and ICT solutions are discussed. Road
construction in Estonia is analyzed. The authors propose the
development of a national performance measurement system for road
construction.
Abstract: Documents retrieval in Information Retrieval
Systems (IRS) is generally about understanding of
information in the documents concern. The more the system
able to understand the contents of documents the more
effective will be the retrieval outcomes. But understanding of the
contents is a very complex task. Conventional IRS apply algorithms
that can only approximate the meaning of document contents through
keywords approach using vector space model. Keywords may be
unstemmed or stemmed. When keywords are stemmed and conflated
in retrieving process, we are a step forwards in applying semantic
technology in IRS. Word stemming is a process in morphological
analysis under natural language processing, before syntactic and
semantic analysis. We have developed algorithms for Malay and
Arabic and incorporated stemming in our experimental systems in
order to measure retrieval effectiveness. The results have shown that
the retrieval effectiveness has increased when stemming is used in
the systems.