Abstract: The previous researches focused on the influence of
anthropogenic greenhouse gases exerting global warming, but not
consider whether desert sand may warm the planet, this could be
improved by accounting for sand's physical and geometric properties.
Here we show, sand particles (because of their geometry) at the desert
surface form an extended surface of up to 1 + π/4 times the planar area
of the desert that can contact sunlight, and at shallow depths of the
desert form another extended surface of at least 1 + π times the planar
area that can contact air. Based on this feature, an enhanced heat
exchange system between sunlight, desert sand, and air in the spaces
between sand particles could be built up automatically, which can
increase capture of solar energy, leading to rapid heating of the sand
particles, and then the heating of sand particles will dramatically heat
the air between sand particles. The thermodynamics of deserts may
thus have contributed to global warming, especially significant to
future global warming if the current desertification continues to
expand.
Abstract: This paper proposes a neural network weights and
topology optimization using genetic evolution and the
backpropagation training algorithm. The proposed crossover and
mutation operators aims to adapt the networks architectures and
weights during the evolution process. Through a specific inheritance
procedure, the weights are transmitted from the parents to their
offsprings, which allows re-exploitation of the already trained
networks and hence the acceleration of the global convergence of the
algorithm. In the preprocessing phase, a new feature extraction
method is proposed based on Legendre moments with the Maximum
entropy principle MEP as a selection criterion. This allows a global
search space reduction in the design of the networks. The proposed
method has been applied and tested on the well known MNIST
database of handwritten digits.
Abstract: In the Fe-3%Si sheets, grade Hi-B, with AlN and MnS
as inhibitors, the Goss grains which abnormally grow do not have a
size greater than the average size of the primary matrix. In this
heterogeneous microstructure, the size factor is not a required
condition for the secondary recrystallization. The onset of the small
Goss grain abnormal growth appears to be related to a particular
behavior of their grain boundaries, to the local texture and to the
distribution of the inhibitors. The presence and the evolution of
oriented clusters ensure to the small Goss grains a favorable
neighborhood to grow. The modified Monte-Carlo approach, which
is applied, considers the local environment of each grain. The grain
growth is dependent of its real spatial position; the matrix
heterogeneity is then taken into account. The grain growth conditions
are considered in the global matrix and in different matrixes
corresponding to A component clusters. The grain growth behaviour
is considered with introduction of energy only, energy and mobility,
energy and mobility and precipitates.
Abstract: The job shop scheduling problem (JSSP) is a
notoriously difficult problem in combinatorial optimization. This
paper presents a hybrid artificial immune system for the JSSP with the
objective of minimizing makespan. The proposed approach combines
the artificial immune system, which has a powerful global exploration
capability, with the local search method, which can exploit the optimal
antibody. The antibody coding scheme is based on the operation based
representation. The decoding procedure limits the search space to the
set of full active schedules. In each generation, a local search heuristic
based on the neighborhood structure proposed by Nowicki and
Smutnicki is applied to improve the solutions. The approach is tested
on 43 benchmark problems taken from the literature and compared
with other approaches. The computation results validate the
effectiveness of the proposed algorithm.
Abstract: One of the most important secrets of succesful companies is the fact that cooperation with NGOs will create a good reputation for them so that they can be immunized to economic crisis. The performance of the most admired companies in the world based on the ratings of Forbes and Fortune show us that most of these firms also have close relationships with their NGOs. Today, if companies do something wrong this information spreads very quickly to do the society. If people do not like the activities of a company, it can find itself in public relations nightmare that can threaten its repuation. Since the cost of communication has dropped dramatically due to the vast use of internet, the increase in communication among stakeholders via internet makes companies more visible. These multiple and interdependent interactions among the network of stakeholders is called as the network relationships. NGOs play the role of catalyst among the stakeholders of a firm to enhance the awareness. Succesful firms are aware of this fact that NGOs have a central role in today-s business world. Firms are also aware of the fact that they can enhance their corporate reputation via cooperation with the NGOs. This fact will be illustrated in this paper by examining some of the actions of the most succesful companies in terms of their cooperations with the NGOs.
Abstract: In this paper, enhanced ground proximity warning simulation and validation system is designed and implemented. First, based on square grid and sub-grid structure, the global digital terrain database is designed and constructed. Terrain data searching is implemented through querying the latitude and longitude bands and separated zones of global terrain database with the current aircraft position. A combination of dynamic scheduling and hierarchical scheduling is adopted to schedule the terrain data, and the terrain data can be read and delete dynamically in the memory. Secondly, according to the scope, distance, approach speed information etc. to the dangerous terrain in front, and using security profiles calculating method, collision threat detection is executed in real-time, and provides caution and warning alarm. According to this scheme, the implementation of the enhanced ground proximity warning simulation system is realized. Simulations are carried out to verify a good real-time in terrain display and alarm trigger, and the results show simulation system is realized correctly, reasonably and stable.
Abstract: Entrepreneurship has become an important and
extensively researched concept in business studies. Research on
foreign direct investment (FDI) has become widespread due to the
growth of FDI and its importance in globalization. Most
entrepreneurship studies examined the importance and influence of
entrepreneurial orientation in a micro-level context. On the other
hand, studies and research concerning FDI used statistical techniques
to analyze the effect, determinants, and motives of FDI on a
macroeconomic level, ignoring empirical studies on other noneconomic
determinants. In order to bridge the gap between the theory
and empirical evidence on FDI and the theory and research on
entrepreneurship, this study examines the impact of entrepreneurship
on inward foreign direct investment. The relationship between
entrepreneurship and foreign direct investment is investigated
through regression analysis of pooled time-series and cross-sectional
data. The results suggest that entrepreneurship has a significant effect
on FDI.
Abstract: A hybrid learning automata-genetic algorithm (HLGA) is proposed to solve QoS routing optimization problem of next generation networks. The algorithm complements the advantages of the learning Automato Algorithm(LA) and Genetic Algorithm(GA). It firstly uses the good global search capability of LA to generate initial population needed by GA, then it uses GA to improve the Quality of Service(QoS) and acquiring the optimization tree through new algorithms for crossover and mutation operators which are an NP-Complete problem. In the proposed algorithm, the connectivity matrix of edges is used for genotype representation. Some novel heuristics are also proposed for mutation, crossover, and creation of random individuals. We evaluate the performance and efficiency of the proposed HLGA-based algorithm in comparison with other existing heuristic and GA-based algorithms by the result of simulation. Simulation results demonstrate that this paper proposed algorithm not only has the fast calculating speed and high accuracy but also can improve the efficiency in Next Generation Networks QoS routing. The proposed algorithm has overcome all of the previous algorithms in the literature.
Abstract: This paper discusses the implementation of the Kalman
Filter along with the Global Positioning System (GPS) for indoor
robot navigation. Two dimensional coordinates is used for the map
building, and refers to the global coordinate which is attached to the
reference landmark for position and direction information the robot
gets. The Discrete Kalman Filter is used to estimate the robot position,
project the estimated current state ahead in time through time update
and adjust the projected estimated state by an actual measurement at
that time via the measurement update. The navigation test has been
performed and has been found to be robust.
Abstract: One very interesting field of research in Pattern Recognition that has gained much attention in recent times is Gesture Recognition. In this paper, we consider a form of dynamic hand gestures that are characterized by total movement of the hand (arm) in space. For these types of gestures, the shape of the hand (palm) during gesturing does not bear any significance. In our work, we propose a model-based method for tracking hand motion in space, thereby estimating the hand motion trajectory. We employ the dynamic time warping (DTW) algorithm for time alignment and normalization of spatio-temporal variations that exist among samples belonging to the same gesture class. During training, one template trajectory and one prototype feature vector are generated for every gesture class. Features used in our work include some static and dynamic motion trajectory features. Recognition is accomplished in two stages. In the first stage, all unlikely gesture classes are eliminated by comparing the input gesture trajectory to all the template trajectories. In the next stage, feature vector extracted from the input gesture is compared to all the class prototype feature vectors using a distance classifier. Experimental results demonstrate that our proposed trajectory estimator and classifier is suitable for Human Computer Interaction (HCI) platform.
Abstract: In the self-stabilizing algorithmic paradigm, each node has a local view of the system, in a finite amount of time the system converges to a global state with desired property. In a graph G =
(V, E), a subset S C V is a 2-packing if Vi c V: IN[i] n SI
Abstract: Since its independence in 1962, Algeria has struggled
to establish an educational system tailored to the needs of the
population it may address. Considering the historical connection with
France, Algeria has always looked at the French language as a
cultural imperative until late in the seventies. After the Arabization
policy of 1971 and the socioeconomic changes taking place
worldwide, the use of English as a communicating vehicle started to
gain more space within globalized Algeria. Consequently, disparities
in the use of French started to fade away at the cross-roads leaving
more space to the teaching of English as a second foreign language.
Moreover, the introduction of the Bologna Process and the
European Credit Transfer System in Higher Education has
necessitated some innovations in the design and development of new
curricula adapted to the socioeconomic market. In this paper, I will
try to highlight the important historical dimensions Algeria has taken
towards the implementation of an English language methodology and
to the status it acquired from second foreign language, to first foreign
language to “the language of knowledge and sciences". I will also
propose new pedagogical perspectives for a better treatment of the
English language in order to encourage independent and autonomous
learning.
Abstract: Classification is an interesting problem in functional
data analysis (FDA), because many science and application problems
end up with classification problems, such as recognition, prediction,
control, decision making, management, etc. As the high dimension
and high correlation in functional data (FD), it is a key problem to
extract features from FD whereas keeping its global characters, which
relates to the classification efficiency and precision to heavens. In this
paper, a novel automatic method which combined Genetic Algorithm
(GA) and classification algorithm to extract classification features is
proposed. In this method, the optimal features and classification model
are approached via evolutional study step by step. It is proved by
theory analysis and experiment test that this method has advantages in
improving classification efficiency, precision and robustness whereas
using less features and the dimension of extracted classification
features can be controlled.
Abstract: Artemisinin is a potential antimalarial drug effective
against the multidrug resistant forms of Malarial Parasites. The
current production of artemisinin is insufficient to meet the global
demand. In the present study microbial biotransformation of
arteannuin B, a biogenetic precursor of artemisinin to the later has
been investigated. Screening studies carried out on several soil borne
microorganisms have yielded one novel species with the
bioconversion ability. Crude cell free extract of 72h old culture of the
isolate had shown the bioconversion activity. On incubation with the
substrate arteannuin B, crude cell free extract of the isolate had
shown a bioconversion of 18.54% to artemisinin on molar basis with
a specific activity of 0.18 units/mg.
Abstract: Over the course of the past century, the global
automotive industry-s stance towards safety has evolved from one of
contempt to one nearing reverence. A suspension system that
provides safe handling and cornering capabilities can, with the help
of an efficient braking system, improve safety to a large extent. The
aim of this research is to propose a new automotive brake rotor
design and to compare it with automotive vented disk rotor. Static
structural and transient thermal analysis have been carried out on the
vented disk rotor and proposed rotor designs to evaluate and compare
their performance. Finite element analysis was employed for both
static structural and transient thermal analysis. Structural analysis
was carried out to study the stress and deformation pattern of the
rotors under extreme loads. Time varying temperature load was
applied on the rotors and the temperature distribution was analysed
considering cooling parameters (convection and radiation). This
dissertation illustrates the use of Finite Element Methods to examine
models, concluding with a comparative study of the proposed rotor
design and the conventional vented disk rotor for structural stability
and thermal efficiency.
Abstract: Transnational corporations (TNCs) are playing a major role in global R&D, not only through activities in their home countries but also increasingly abroad. However, the process of R&D offshoring is not yet discussed thoroughly. Based on in-depth case study on Agilent China Communications Operation, this paper presents a stage model for theorizing the R&D offshoring process. This stage model outlines 5 maturity levels of organization and the offshoring process: Subsidiary team, Mirror team, Independent team, Mirror sector and the Independent sector (from software engineering point of view, it is similar to the local team's capability level of maturity model). Moreover, the paper gives a detailed discussion on the relevant characteristics, as well as the ability/responsibility of transfer, priorities and the corresponding organization structure. It also gives the characteristics and key points of different level-s R&D offshoring implementation using actual team practice.
Abstract: Nowadays due to globalization of economy and
competition environment, innovation and technology plays key role
at creation of wealth and economic growth of countries. In fact
prompt growth of practical and technologic knowledge may results in
social benefits for countries when changes into effective innovation.
Considering the importance of innovation for the development of
countries, this study addresses the radical technological innovation
introduced by nanopapers at different stages of producing paper
including stock preparation, using authorized additives, fillers and
pigments, using retention, calender, stages of producing conductive
paper, porous nanopaper and Layer by layer self-assembly. Research
results show that in coming years the jungle related products will lose
considerable portion of their market share, unless embracing radical
innovation. Although incremental innovations can make this industry
still competitive in mid-term, but to have economic growth and
competitive advantage in long term, radical innovations are
necessary. Radical innovations can lead to new products and
materials which their applications in packaging industry can produce
value added. However application of nanotechnology in this industry
can be costly, it can be done in cooperation with other industries to
make the maximum use of nanotechnology possible. Therefore this
technology can be used in all the production process resulting in the
mass production of simple and flexible papers with low cost and
special properties such as facility at shape, form, easy transportation,
light weight, recovery and recycle marketing abilities, and sealing.
Improving the resistance of the packaging materials without reducing
the performance of packaging materials enhances the quality and the
value added of packaging. Improving the cellulose at nano scale can
have considerable electron optical and magnetic effects leading to
improvement in packaging and value added. Comparing to the
specifications of thermoplastic products and ordinary papers,
nanopapers show much better performance in terms of effective
mechanical indexes such as the modulus of elasticity, tensile strength,
and strain-stress. In densities lower than 640 kgm -3, due to the
network structure of nanofibers and the balanced and randomized
distribution of NFC in flat space, these specifications will even
improve more. For nanopapers, strains are 1,4Gpa, 84Mpa and 17%,
13,3 Gpa, 214Mpa and 10% respectively. In layer by layer self
assembly method (LbL) the tensile strength of nanopaper with Tio3
particles and Sio2 and halloysite clay nanotube are 30,4 ±7.6Nm/g
and 13,6 ±0.8Nm/g and 14±0.3,3Nm/g respectively that fall within
acceptable range of similar samples with virgin fiber. The usage of
improved brightness and porosity index in nanopapers can create
more competitive advantages at packaging industry.
Abstract: This paper derives some new sufficient conditions for
the stability of a class of neutral-type neural networks with discrete
time delays by employing a suitable Lyapunov functional. The
obtained conditions can be easily verified as they can be expressed
in terms of the network parameters only. It is shown that the results
presented in this paper for neutral-type delayed neural networks establish
a new set of stability criteria, and therefore can be considered
as the alternative results to the previously published literature results.
A numerical example is also given to demonstrate the applicability
of our proposed stability criterion.
Abstract: In this content analysis research note the aim was to explore to how sustainability and especially environmental issues are conveyed into environmental items in annual reports and disclosures. As The Global Reporting Initiative (GRI) is a globally wide multistakeholder process, the enterprises using voluntarily GRI framework are considered to be aware of sustainability and environmental concerns. The findings were that although these enterprises included in an environmentally sensitive industry sector and had special capabilities to consider environmental issues there were few GRIreporting enterprises presented substantially detailed environmental items in audited financial statements. There were only slight differences between publishing years 2008 and 2009 - the beginning years of economic turmoil. The environmental issues seemed not to be considered substantial enough for financial reporting as a basis for concerning investment or voting decisions.
Abstract: In this paper we present an off line system for the
recognition of the handwritten numeric chains. Our work is divided
in two big parts. The first part is the realization of a recognition
system of the isolated handwritten digits. In this case 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 digits by several methods: the
distribution sequence, the Barr features and the centred moments of
the different projections and profiles. The second part is the
extension of our system for the reading of the handwritten numeric
chains constituted of a variable number of digits. The vertical
projection is used to segment the numeric chain at isolated digits and
every digit (or segment) will be presented separately to the entry of
the system achieved in the first part (recognition system of the
isolated handwritten digits). The result of the recognition of the
numeric chain will be displayed at the exit of the global system.