Abstract: In this paper, a robust decentralized congestion control strategy is developed for a large scale network with Differentiated Services (Diff-Serv) traffic. The network is modeled by a nonlinear fluid flow model corresponding to two classes of traffic, namely the premium traffic and the ordinary traffic. The proposed congestion controller does take into account the associated physical network resource limitations and is shown to be robust to the unknown and time-varying delays. Our proposed decentralized congestion control strategy is developed on the basis of Diff-Serv architecture by utilizing a robust adaptive technique. A Linear Matrix Inequality (LMI) condition is obtained to guarantee the ultimate boundedness of the closed-loop system. Numerical simulation implementations are presented by utilizing the QualNet and Matlab software tools to illustrate the effectiveness and capabilities of our proposed decentralized congestion control strategy.
Abstract: According to synthetic plastics obtained from petroleum cause some environmental problems. Therefore, degradable plastics become widely used and studied for replacing the synthetic plastic waste. A biopolymer of poly hydroxybutyrate-co-hydroxyvalerate (PHBV) is subgroups of a main kind of polyhydroxyalkanoates (PHAs). Naturally, PHBV is hard, brittle and low flexible while natural rubber (NR) is high elastic latex. Then, they are blended and the biodegradation of the blended PHBV and NR films were examined in soil environment. The results showed that the degradation occurs predominantly in the bulk of the samples. The order of biodegradability was shown as follows: PHBV> PHBV/NR> NR. After biodegradation, the blended films were characterized by appearance analysis such as Scanning Electron Microscope (SEM), Fourier transform infrared spectroscopy (FTIR) and Differential Scanning Calorimetry (DSC). It was found that the biodegradation mainly occurred at the polymer surface.
Abstract: This paper presents the design and implementation of a fully integrated Capacitance-to-Voltage Converter (CVC) as the analog front-end for magnetometer interface IC. The application demands very low power solution operating in the frequency of around 20 KHz. The design adapts low power architecture to create low noise electronic interface for Capacitive Micro-machined Lorentz force magnetometer sensor. Using a 0.18-μm CMOS process, simulation results of this interface IC show that the proposed CVC can provide 33 dB closed loop gain, 20 nV/√Hz input referred noise at 20 KHz, while consuming 65 μA current from 1.8-V supply.
Abstract: The performance of state of the art worldwide telecommunication networks strongly depends on the efficiency of the applied routing mechanism. Game theoretical approaches to this problem offer new solutions. In this paper a new continuous network routing model is defined to describe data transfer in fixed telecommunication networks of multiple hosts. The nodes of the network correspond to routers whose latency is assumed to be traffic dependent. We propose that the whole traffic of the network can be decomposed to a finite number of tasks, which belong to various hosts. To describe the different latency-sensitivity, utility functions are defined for each task. The model is used to compare router and host intelligent types of routing methods, corresponding to various data transfer protocols. We analyze host intelligent routing as a transferable utility cooperative game with externalities. The main aim of the paper is to provide a framework in which the efficiency of various routing algorithms can be compared and the transferable utility game arising in the cooperative case can be analyzed.
Abstract: In this paper a genetic algorithm (GA) with dual-fitness function is proposed and applied to solve the deterministic identical machine scheduling problem. The mating fitness function value was used to determine the mating for chromosomes, while the selection fitness function value was used to determine their survivals. The performance of this algorithm was tested on deterministic identical machine scheduling using simulated data. The results obtained from the proposed GA were compared with classical GA and integer programming (IP). Results showed that dual-fitness function GA outperformed the classical single-fitness function GA with statistical significance for large problems and was competitive to IP, particularly when large size problems were used.
Abstract: Intercalation imparts interesting features to the host graphite material. Two different types of intercalated compounds called (GIC-bisulphate or Nyex 1000 and GIC-nitrate or Nyex 3000) were tested for their adsorption capacity and ability to undergo electrochemical regeneration. It was found that Nyex 3000 showed comparatively slow kinetics along with reduced adsorption capacity to one half for acid violet 17 as adsorbate. Acid violet 17 was selected as model organic pollutant for evaluating comparative performance of said adsorbents. Both adsorbent materials showed 100% regeneration efficiency as achieved by passing a charge of 36 C g-1 at a current density of 12 mA cm-2 and a treatment time of 60 min.
Abstract: The aim of this paper is to examine the relationship among CO2 per capita emissions, energy consumption, economic growth and bilateral trade between Singapore and Malaysia for the 1970-2011 period. ARDL model and Granger causality tests are employed for the analysis. Results of bound F-statistics suggest that long-run relationship exists between CO2 per capita (PCO2) and its determinants. The EKC hypothesis is not supported in Malaysia. Carbon emissions are mainly determined by energy consumption in the short and long run. While, exports to Singapore is a significant variable in explaining PCO2 emissions in Malaysia in long-run. Furthermore, we find a unidirectional causal relationship running from economic growth to PCO2 emissions.
Abstract: The problem of optimal planning of multiple sources
of distributed generation (DG) in distribution networks is treated in
this paper using an improved Ant Colony Optimization algorithm
(ACO). This objective of this problem is to determine the DG
optimal size and location that in order to minimize the network real
power losses. Considering the multiple sources of DG, both size and
location are simultaneously optimized in a single run of the proposed
ACO algorithm. The various practical constraints of the problem are
taken into consideration by the problem formulation and the
algorithm implementation. A radial power flow algorithm for
distribution networks is adopted and applied to satisfy these
constraints. To validate the proposed technique and demonstrate its
effectiveness, the well-know 69-bus feeder standard test system is
employed.cm.
Abstract: Image registration is the process of establishing point
by point correspondence between images obtained from a same
scene. This process is very useful in remote sensing, medicine,
cartography, computer vision, etc. Then, the task of registration is to
place the data into a common reference frame by estimating the
transformations between the data sets. In this work, we develop a
rigid point registration method based on the application of genetic
algorithms and Hausdorff distance. First, we extract the feature points
from both images based on the algorithm of global and local
curvature corner. After refining the feature points, we use Hausdorff
distance as similarity measure between the two data sets and for
optimizing the search space we use genetic algorithms to achieve
high computation speed for its inertial parallel. The results show the
efficiency of this method for registration of satellite images.
Abstract: In this paper, we present a comparative study of the
genetic algorithms and Hessian-s methods for optimal research of the
active powers in an electric network of power. The objective function
which is the performance index of production of electrical energy is
minimized by satisfying the constraints of the equality type and
inequality type initially by the Hessian-s methods and in the second
time by the genetic Algorithms. The results found by the application
of AG for the minimization of the electric production costs of power
are very encouraging. The algorithms seem to be an effective
technique to solve a great number of problems and which are in
constant evolution. Nevertheless it should be specified that the
traditional binary representation used for the genetic algorithms
creates problems of optimization of management of the large-sized
networks with high numerical precision.
Abstract: Learning the gradient of neuron's activity function
like the weight of links causes a new specification which is
flexibility. In flexible neural networks because of supervising and
controlling the operation of neurons, all the burden of the learning is
not dedicated to the weight of links, therefore in each period of
learning of each neuron, in fact the gradient of their activity function,
cooperate in order to achieve the goal of learning thus the number of
learning will be decreased considerably.
Furthermore, learning neurons parameters immunes them against
changing in their inputs and factors which cause such changing.
Likewise initial selecting of weights, type of activity function,
selecting the initial gradient of activity function and selecting a fixed
amount which is multiplied by gradient of error to calculate the
weight changes and gradient of activity function, has a direct affect
in convergence of network for learning.
Abstract: This paper focuses on a critical component of the situational awareness (SA), the control of autonomous vertical flight for vectored thrust aerial vehicle (VTAV). With the SA strategy, we proposed a flight control procedure to address the dynamics variation and performance requirement difference of flight trajectory for an unmanned helicopter model with vectored thrust configuration. This control strategy for chosen model of VTAV has been verified by simulation of take-off and forward maneuvers using software package Simulink and demonstrated good performance for fast stabilization of motors, consequently, fast SA with economy in energy can be asserted during search-and-rescue operations.
Abstract: the research was accomplished on fresh in Latvia wild
growing cranberries and cranberry cultivars. The aim of the study
was to evaluate effect of pretreatment method and drying conditions
on the volatile compounds composition in cranberries. Berries
pre-treatment methods were: perforation, halving and
steam-blanching. The berries before drying in a cabinet drier were
pre-treated using all three methods, in microwave vacuum
drier – using a steam-blanching and halving. Volatile compounds in
cranberries were analysed using GC-MS of extracts obtained by
SPME. During present research 21 various volatile compounds were
detected in fresh cranberries: the cultivar 'Steven' - 15, 'Bergman'
and 'Early black' – 13, 'Ben Lear' and 'Pilgrim' – 11 and wild
cranberries – 14 volatile compounds. In dried cranberries 20 volatile
compounds were detected. Mathematical data processing allows
drawing a conclusion that there exists the significant influence of
cranberry cultivar, pre-treatment method and drying condition on
volatile compounds in berries and new volatile compound formation.
Abstract: A gradient learning method to regulate the trajectories
of some nonlinear chaotic systems is proposed. The method is
motivated by the gradient descent learning algorithms for neural
networks. It is based on two systems: dynamic optimization system
and system for finding sensitivities. Numerical results of several
examples are presented, which convincingly illustrate the efficiency
of the method.
Abstract: When faced with stochastic networks with an uncertain
duration for their activities, the securing of network completion time
becomes problematical, not only because of the non-identical pdf of
duration for each node, but also because of the interdependence of
network paths. As evidenced by Adlakha & Kulkarni [1], many
methods and algorithms have been put forward in attempt to resolve
this issue, but most have encountered this same large-size network
problem. Therefore, in this research, we focus on network reduction
through a Series/Parallel combined mechanism. Our suggested
algorithm, named the Activity Network Reduction Algorithm
(ANRA), can efficiently transfer a large-size network into an S/P
Irreducible Network (SPIN). SPIN can enhance stochastic network
analysis, as well as serve as the judgment of symmetry for the Graph
Theory.
Abstract: This interdisciplinary research aims to distinguish universal scale-free and field-like fundamental principles of selforganization observable across many disciplines like computer science, neuroscience, microbiology, social science, etc. Based on these universal principles we provide basic premises and postulates for designing holistic social simulation models. We also introduce pervasive information field (PIF) concept, which serves as a simulation media for contextual information storage, dynamic distribution and organization in social complex networks. PIF concept specifically is targeted for field-like uncoupled and indirect interactions among social agents capable of affecting and perceiving broadcasted contextual information. Proposed approach is expressive enough to represent contextual broadcasted information in a form locally accessible and immediately usable by network agents. This paper gives some prospective vision how system-s resources (tangible and intangible) could be simulated as oscillating processes immersed in the all pervasive information field.
Abstract: In an emergency, combining Wireless Sensor Network's data with the knowledge gathered from various other information sources and navigation algorithms, could help safely guide people to a building exit while avoiding the risky areas. This paper presents an emergency response and navigation support architecture for data gathering, knowledge manipulation, and navigational support in an emergency situation. At normal state, the system monitors the environment. When an emergency event detects, the system sends messages to first responders and immediately identifies the risky areas from safe areas to establishing escape paths. The main functionalities of the system include, gathering data from a wireless sensor network which is deployed in a multi-story indoor environment, processing it with information available in a knowledge base, and sharing the decisions made, with first responders and people in the building. The proposed architecture will act to reduce risk of losing human lives by evacuating people much faster with least congestion in an emergency environment.
Abstract: Internet is one of the major sources of information for
the person belonging to almost all the fields of life. Major language
that is used to publish information on internet is language. This thing
becomes a problem in a country like Pakistan, where Urdu is the
national language. Only 10% of Pakistan mass can understand
English. The reason is millions of people are deprived of precious
information available on internet. This paper presents a system for
translation from English to Urdu. A module LESSA is used that uses
a rule based algorithm to read the input text in English language,
understand it and translate it into Urdu language. The designed
approach was further incorporated to translate the complete website
from English language o Urdu language. An option appears in the
browser to translate the webpage in a new window. The designed
system will help the millions of users of internet to get benefit of the
internet and approach the latest information and knowledge posted
daily on internet.
Abstract: In this research, STNEP is being studied considering network adequacy and limitation of investment cost by decimal codification genetic algorithm (DCGA). The goal is obtaining the maximum of network adequacy with lowest expansion cost for a specific investment. Finally, the proposed idea is applied to the Garvers 6-bus network. The results show that considering the network adequacy for solution of STNEP problem is caused that among of expansion plans for a determined investment, configuration which has relatively lower expansion cost and higher adequacy is proposed by GA based method. Finally, with respect to the curve of adequacy versus expansion cost it can be said that more optimal configurations for expansion of network are obtained with lower investment costs.
Abstract: This paper presents an evolutionary method for designing
electronic circuits and numerical methods associated with
monitoring systems. The instruments described here have been used
in studies of weather and climate changes due to global warming, and
also in medical patient supervision. Genetic Programming systems
have been used both for designing circuits and sensors, and also for
determining sensor parameters. The authors advance the thesis that
the software side of such a system should be written in computer
languages with a strong mathematical and logic background in order
to prevent software obsolescence, and achieve program correctness.