Abstract: This work presents a new type of the affine projection
(AP) algorithms which incorporate the sparsity condition of a
system. To exploit the sparsity of the system, a weighted l1-norm
regularization is imposed on the cost function of the AP algorithm.
Minimizing the cost function with a subgradient calculus and
choosing two distinct weighting for l1-norm, two stochastic gradient
based sparsity regularized AP (SR-AP) algorithms are developed.
Experimental results exhibit that the SR-AP algorithms outperform
the typical AP counterparts for identifying sparse systems.
Abstract: This research focuses on assessing the ground water quality of Northern Lebanon affected by saline water intrusion. The chemical, physical and microbiological parameters were collected in various seasons spanning over the period of two years. Results were assessed using Geographic Information System (GIS) due to its visual capabilities in presenting the pollution extent in the studied region. Future projections of the excessive pumping were also simulated using GIS in order to assess the extent of the problem of saline intrusion in the near future.
Abstract: We present a new framework of the data-reusing (DR)
adaptive algorithms by incorporating a constraint on noise, referred
to as a noise constraint. The motivation behind this work is that the
use of the statistical knowledge of the channel noise can contribute
toward improving the convergence performance of an adaptive filter
in identifying a noisy linear finite impulse response (FIR) channel.
By incorporating the noise constraint into the cost function of the
DR adaptive algorithms, the noise constrained DR (NC-DR) adaptive
algorithms are derived. Experimental results clearly indicate their
superior performance over the conventional DR ones.
Abstract: The aim of this research is to understand how the
emerging power bloc BRICS employs infrastructure development
narratives to construct a new world order. BRICS is an international
body consisting of five emerging countries that collaborate on
economic and political issues: Brazil, Russia, India, China, and South
Africa. This study explores the projection of infrastructure
development narratives through an analysis of BRICS’ attention to
infrastructure investment and financing, its support of the New
Partnership on African Development and the establishment of the
New Development Bank in Shanghai. The theory of Strategic
Narratives is used to explore BRICS’ commitment to infrastructure
development and to distinguish three layers: system narratives
(BRICS as a global actor to propose development reform), identity
narratives (BRICS as a collective identity joining efforts to act upon
development aspirations) and issue narratives (BRICS committed to a
range of issues of which infrastructure development is prominent).
The methodology that is employed is a narrative analysis of BRICS’
official documents, media statements, and website imagery. A
comparison of these narratives illuminates tensions at the three layers
and among the five member states. Identifying tensions among
development infrastructure narratives provides an indication of how
policymaking for infrastructure development could be improved.
Subsequently, it advances BRICS’ ability to act as a global actor to
construct a new world order.
Abstract: Myoelectric control system is the fundamental
component of modern prostheses, which uses the myoelectric signals
from an individual’s muscles to control the prosthesis movements.
The surface electromyogram signal (sEMG) being noninvasive has
been used as an input to prostheses controllers for many years.
Recent technological advances has led to the development of
implantable myoelectric sensors which enable the internal
myoelectric signal (MES) to be used as input to these prostheses
controllers. The intramuscular measurement can provide focal
recordings from deep muscles of the forearm and independent signals
relatively free of crosstalk thus allowing for more independent
control sites. However, little work has been done to compare the two
inputs. In this paper we have compared the classification accuracy of
six pattern recognition based myoelectric controllers which use
surface myoelectric signals recorded using untargeted (symmetric)
surface electrode arrays to the same controllers with multichannel
intramuscular myolectric signals from targeted intramuscular
electrodes as inputs. There was no significant enhancement in the
classification accuracy as a result of using the intramuscular EMG
measurement technique when compared to the results acquired using
the surface EMG measurement technique. Impressive classification
accuracy (99%) could be achieved by optimally selecting only five
channels of surface EMG.
Abstract: The Haussmannization plan of Cairo in 1867 formed a
regular network of roundabout spaces, though deteriorated at present.
The method of identifying the spatial structure of roundabout Cairo
for conservation matches the voronoi diagram with the space syntax
through their geometrical property of spatial convexity. In this
initiative, the primary convex hull of first-order voronoi adopts the
integral and control measurements of space syntax on Cairo’s
roundabout generators. The functional essence of royal palaces
optimizes the roundabout structure in terms of spatial measurements
and the symbolic voronoi projection of 'Tahrir Roundabout' over the
Giza Nile and Pyramids. Some roundabouts of major public and
commercial landmarks surround the pole of 'Ezbekia Garden' with a
higher control than integral measurements, which filter the new
spatial structure from the adjacent traditional town. Nevertheless, the
least integral and control measures correspond to the voronoi
contents of pollutant workshops and the plateau of old Cairo Citadel
with the visual compensation of new royal landmarks on top.
Meanwhile, the extended suburbs of infinite voronoi polygons
arrange high control generators of chateaux housing in 'garden city'
environs. The point pattern of roundabouts determines the
geometrical characteristics of voronoi polygons. The measured
lengths of voronoi edges alternate between the zoned short range at
the new poles of Cairo and the distributed structure of longer range.
Nevertheless, the shortest range of generator-vertex geometry
concentrates at 'Ezbekia Garden' where the crossways of vast Cairo
intersect, which maximizes the variety of choice at different spatial
resolutions. However, the symbolic 'Hippodrome' which is the largest
public landmark forms exclusive geometrical measurements, while
structuring a most integrative roundabout to parallel the royal syntax.
Overview of the symbolic convex hull of voronoi with space syntax
interconnects Parisian Cairo with the spatial chronology of scattered
monuments to conceive one universal Cairo structure. Accordingly,
the approached methodology of 'voronoi-syntax' prospects the future
conservation of roundabout Cairo at the inferred city-level concept.
Abstract: The aim of this work is to detect geometrical shape
objects in an image. In this paper, the object is considered to be as a
circle shape. The identification requires find three characteristics,
which are number, size, and location of the object. To achieve the
goal of this work, this paper presents an algorithm that combines
from some of statistical approaches and image analysis techniques.
This algorithm has been implemented to arrive at the major
objectives in this paper. The algorithm has been evaluated by using
simulated data, and yields good results, and then it has been applied
to real data.
Abstract: Machine visualization is an area of interest with fast
and progressive development. We present a method of machine
visualization which will be applicable in real industrial conditions
according to current needs and demands. Real factory data were
obtained in a newly built research plant. Methods described in this
paper were validated on a case study. Input data were processed and
the virtual environment was created. The environment contains
information about dimensions, structure, disposition, and function.
Hardware was enhanced by modular machines, prototypes, and
accessories. We added functionalities and machines into the virtual
environment. The user is able to interact with objects such as testing
and cutting machines, he/she can operate and move them. Proposed
design consists of an environment with two degrees of freedom of
movement. Users are in touch with items in the virtual world which
are embedded into the real surroundings. This paper describes development of the virtual environment. We
compared and tested various options of factory layout virtualization
and visualization. We analyzed possibilities of using a 3D scanner in
the layout obtaining process and we also analyzed various virtual
reality hardware visualization methods such as: Stereoscopic (CAVE)
projection, Head Mounted Display (HMD) and augmented reality
(AR) projection provided by see-through glasses.
Abstract: In the context of the handwriting recognition, we
propose an off line system for the recognition of the Arabic
handwritten words of the Algerian departments. The study is based
mainly on the evaluation of neural network performances, trained
with the gradient back propagation algorithm. The used parameters to
form the input vector of the neural network are extracted on the
binary images of the handwritten word by several methods. The
Distribution parameters, the centered moments of the different
projections of the different segments, the centered moments of the
word image coding according to the directions of Freeman, and the
Barr features applied binary image of the word and on its different
segments. The classification is achieved by a multi layers perceptron.
A detailed experiment is carried and satisfactory recognition results
are reported.
Abstract: Group decision making with multiple attribute has
attracted intensive concern in the decision analysis area. This paper
assumes that the contributions of all the decision makers (DMs) are not
equal to the decision process based on different knowledge and
experience in group setting. The aim of this paper is to develop a novel
approach to determine weights of DMs in the group decision making
problems. In this paper, the weights of DMs are determined in the
group decision environment via angle cosine and projection method.
First of all, the average decision of all individual decisions is defined
as the ideal decision. After that, we define the weight of each decision
maker (DM) by aggregating the angle cosine and projection between
individual decision and ideal decision with associated direction
indicator μ. By using the weights of DMs, all individual decisions are
aggregated into a collective decision. Further, the preference order of
alternatives is ranked in accordance with the overall row value of
collective decision. Finally, an example in a chemical company is
provided to illustrate the developed approach.
Abstract: The article describes the effect of the replacement of
the used reference coordinate system in the georeferencing of an old
map of Europe. The map was georeferenced into three types of
projection – the equal-area conic (original cartographic projection),
cylindrical Plate Carrée and cylindrical Mercator map projection. The
map was georeferenced by means of the affine and the second-order
polynomial transformation. The resulting georeferenced raster
datasets from the Plate Carrée and Mercator projection were
projected into the equal-area conic projection by means of projection
equations. The output is the comparison of drawn graphics, the
magnitude of standard deviations for individual projections and types
of transformation.
Abstract: In our research we aimed to test a managerial
approach for the fuzzy front end (FFE) of innovation by creating
controlled experiment/ business case in a breakthrough innovation
development. The experiment was in the sport industry and covered
all aspects of the customer discovery stage from ideation to
prototyping followed by patent application. In the paper we describe
and analyze mile stones, tasks, management challenges, decisions
made to create the break through innovation, evaluate overall
managerial efficiency that was at the considered FFE stage.
We set managerial outcome of the FFE stage as a valid product
concept in hand. In our paper we introduce hypothetical construct
“Q-factor” that helps us in the experiment to distinguish quality of
FFE outcomes.
The experiment simulated for entrepreneur the FFE of innovation
and put on his shoulders responsibility for the outcome of valid
product concept. While developing managerial approach to reach the
outcome there was a decision to look on product concept from the
cognitive psychology and cognitive science point of view. This view
helped us to develop the profile of a person whose projection (mental
representation) of a new product could optimize for a manager or
entrepreneur FFE activities. In the experiment this profile was tested
to develop breakthrough innovation for swimmers. Following the
managerial approach the product concept was created to help
swimmers to feel/sense water. The working prototype was developed
to estimate the product concept validity and value added effect for
customers.
Based on feedback from coachers and swimmers there were strong
positive effect that gave high value for customers, and for the
experiment – the valid product concept being developed by proposed
managerial approach for the FFE.
In conclusions there is a suggestion of managerial approach that
was derived from experiment.
Abstract: The 3D body movement signals captured during
human-human conversation include clues not only to the content of
people’s communication but also to their culture and personality.
This paper is concerned with automatic extraction of this information
from body movement signals. For the purpose of this research, we
collected a novel corpus from 27 subjects, arranged them into groups
according to their culture. We arranged each group into pairs and
each pair communicated with each other about different topics.
A state-of-art recognition system is applied to the problems of
person, culture, and topic recognition. We borrowed modeling,
classification, and normalization techniques from speech recognition.
We used Gaussian Mixture Modeling (GMM) as the main technique
for building our three systems, obtaining 77.78%, 55.47%, and
39.06% from the person, culture, and topic recognition systems
respectively. In addition, we combined the above GMM systems with
Support Vector Machines (SVM) to obtain 85.42%, 62.50%, and
40.63% accuracy for person, culture, and topic recognition
respectively.
Although direct comparison among these three recognition
systems is difficult, it seems that our person recognition system
performs best for both GMM and GMM-SVM, suggesting that intersubject
differences (i.e. subject’s personality traits) are a major
source of variation. When removing these traits from culture and
topic recognition systems using the Nuisance Attribute Projection
(NAP) and the Intersession Variability Compensation (ISVC)
techniques, we obtained 73.44% and 46.09% accuracy from culture
and topic recognition systems respectively.
Abstract: Recent research in neural networks science and
neuroscience for modeling complex time series data and statistical
learning has focused mostly on learning from high input space and
signals. Local linear models are a strong choice for modeling local
nonlinearity in data series. Locally weighted projection regression is
a flexible and powerful algorithm for nonlinear approximation in
high dimensional signal spaces. In this paper, different learning
scenario of one and two dimensional data series with different
distributions are investigated for simulation and further noise is
inputted to data distribution for making different disordered
distribution in time series data and for evaluation of algorithm in
locality prediction of nonlinearity. Then, the performance of this
algorithm is simulated and also when the distribution of data is high
or when the number of data is less the sensitivity of this approach to
data distribution and influence of important parameter of local
validity in this algorithm with different data distribution is explained.
Abstract: Recent perceived climate variability raises concerns
with unprecedented hydrological phenomena and extremes.
Distribution and circulation of the waters of the Earth become
increasingly difficult to determine because of additional uncertainty
related to anthropogenic emissions. The world wide observed
changes in the large-scale hydrological cycle have been related to an
increase in the observed temperature over several decades. Although
the effect of change in climate on hydrology provides a general
picture of possible hydrological global change, new tools and
frameworks for modelling hydrological series with nonstationary
characteristics at finer scales, are required for assessing climate
change impacts. Of the downscaling techniques, dynamic
downscaling is usually based on the use of Regional Climate Models
(RCMs), which generate finer resolution output based on atmospheric
physics over a region using General Circulation Model (GCM) fields
as boundary conditions. However, RCMs are not expected to capture
the observed spatial precipitation extremes at a fine cell scale or at a
basin scale. Statistical downscaling derives a statistical or empirical
relationship between the variables simulated by the GCMs, called
predictors, and station-scale hydrologic variables, called predictands.
The main focus of the paper is on the need for using statistical
downscaling techniques for projection of local hydrometeorological
variables under climate change scenarios. The projections can be then
served as a means of input source to various hydrologic models to
obtain streamflow, evapotranspiration, soil moisture and other
hydrological variables of interest.
Abstract: This paper proposes a complementary combination scheme of affine projection algorithm (APA) filters with different order of input regressors. A convex combination provides an interesting way to keep the advantage of APA having different order of input regressors. Consequently, a novel APA which has the rapid convergence and the reduced steady-state error is derived. Experimental results show the good properties of the proposed algorithm.
Abstract: This paper is an attempt to describe some of the results that had been found through a journey of study in the field of particle physics. This study consists of two parts, one about the measurement of the cross section of the decay of the Z particle in two electrons, and the other deals with the measurement of the cross section of the multi-photon absorption process using a beam of Laser in the Liquid Argon Time Projection Chamber.
The first part of the paper concerns the results based on the analysis of a data sample containing 8120 ee candidates to reconstruct the mass of the Z particle for each event where each event has an ee pair with PT(e) > 20GeV, and η(e) < 2.5. Monte Carlo templates of the reconstructed Z particle were produced as a function of the Z mass scale. The distribution of the reconstructed Z mass in the data was compared to the Monte Carlo templates, where the total cross section is calculated to be equal to 1432pb.
The second part concerns the Liquid Argon Time Projection Chamber, LAr TPC, the results of the interaction of the UV Laser, Nd-YAG with λ= 266mm, with LAr and through the study of the multi-photon ionization process as a part of the R&D at Bern University. The main result of this study was the cross section of the process of the multi-photon ionization process of the LAr, σe = 1.24±0.10stat±0.30sys.10 -56cm4.
Abstract: The objective of this paper is finding the way of economic restructuring - that is, change in the shares of sectoral gross outputs - resulting in the maximum possible increase in the gross domestic product (GDP) combined with decreases in energy consumption and CO2 emissions. It uses an input-output model for the GDP and factorial models for the energy consumption and CO2 emissions to determine the projection of the gradient of GDP, and the antigradients of the energy consumption and CO2 emissions, respectively, on a subspace formed by the structure-related variables. Since the gradient (antigradient) provides a direction of the steepest increase (decrease) of the objective function, and their projections retain this property for the functions' limitation to the subspace, each of the three directional vectors solves a particular problem of optimal structural change. In the next step, a type of factor analysis is applied to find a convex combination of the projected gradient and antigradients having maximal possible positive correlation with each of the three. This convex combination provides the desired direction of the structural change. The national economy of the United States is used as an example of applications.
Abstract: Hydrological modelling plays a crucial role in the planning and management of water resources, most especially in water stressed regions where the need to effectively manage the available water resources is of critical importance. However, due to the complex, nonlinear and dynamic behaviour of hydro-climatic interactions, achieving reliable modelling of water resource systems and accurate projection of hydrological parameters are extremely challenging. Although a significant number of modelling techniques (process-based and data-driven) have been developed and adopted in that regard, the field of hydrological modelling is still considered as one that has sluggishly progressed over the past decades. This is majorly as a result of the identification of some degree of uncertainty in the methodologies and results of techniques adopted. In recent times, evolutionary computation (EC) techniques have been developed and introduced in response to the search for efficient and reliable means of providing accurate solutions to hydrological related problems. This paper presents a comprehensive review of the underlying principles, methodological needs and applications of a promising evolutionary computation modelling technique – genetic programming (GP). It examines the specific characteristics of the technique which makes it suitable to solving hydrological modelling problems. It discusses the opportunities inherent in the application of GP in water related-studies such as rainfall estimation, rainfall-runoff modelling, streamflow forecasting, sediment transport modelling, water quality modelling and groundwater modelling among others. Furthermore, the means by which such opportunities could be harnessed in the near future are discussed. In all, a case for total embracement of GP and its variants in hydrological modelling studies is made so as to put in place strategies that would translate into achieving meaningful progress as it relates to modelling of water resource systems, and also positively influence decision-making by relevant stakeholders.
Abstract: This paper considers the NP-hard problem of reconstructing binary matrices satisfying exactly-1-4-adjacency constraint from its row and column projections. This problem is formulated into a maximization problem. The objective function gives a measure of adjacency constraint for the binary matrices. The maximization problem is solved by the simulated annealing algorithm and experimental results are presented.