Abstract: Groups where the discrete logarithm problem (DLP) is believed to be intractable have proved to be inestimable building blocks for cryptographic applications. They are at the heart of numerous protocols such as key agreements, public-key cryptosystems, digital signatures, identification schemes, publicly verifiable secret sharings, hash functions and bit commitments. The search for new groups with intractable DLP is therefore of great importance.The goal of this article is to study elliptic curves over the ring Fq[], with Fq a finite field of order q and with the relation n = 0, n ≥ 3. The motivation for this work came from the observation that several practical discrete logarithm-based cryptosystems, such as ElGamal, the Elliptic Curve Cryptosystems . In a first time, we describe these curves defined over a ring. Then, we study the algorithmic properties by proposing effective implementations for representing the elements and the group law. In anther article we study their cryptographic properties, an attack of the elliptic discrete logarithm problem, a new cryptosystem over these curves.
Abstract: The least mean square (LMS) algorithmis one of the
most well-known algorithms for mobile communication systems
due to its implementation simplicity. However, the main limitation
is its relatively slow convergence rate. In this paper, a booster
using the concept of Markov chains is proposed to speed up the
convergence rate of LMS algorithms. The nature of Markov
chains makes it possible to exploit the past information in the
updating process. Moreover, since the transition matrix has a
smaller variance than that of the weight itself by the central limit
theorem, the weight transition matrix converges faster than the
weight itself. Accordingly, the proposed Markov-chain based
booster thus has the ability to track variations in signal
characteristics, and meanwhile, it can accelerate the rate of
convergence for LMS algorithms. Simulation results show that the
LMS algorithm can effectively increase the convergence rate and
meantime further approach the Wiener solution, if the
Markov-chain based booster is applied. The mean square error is
also remarkably reduced, while the convergence rate is improved.
Abstract: In this paper, we propose a single sample path based
algorithm with state aggregation to optimize the average rewards of
singularly perturbed Markov reward processes (SPMRPs) with a
large scale state spaces. It is assumed that such a reward process
depend on a set of parameters. Differing from the other kinds of
Markov chain, SPMRPs have their own hierarchical structure. Based
on this special structure, our algorithm can alleviate the load in the
optimization for performance. Moreover, our method can be applied
on line because of its evolution with the sample path simulated.
Compared with the original algorithm applied on these problems of
general MRPs, a new gradient formula for average reward
performance metric in SPMRPs is brought in, which will be proved
in Appendix, and then based on these gradients, the schedule of the
iteration algorithm is presented, which is based on a single sample
path, and eventually a special case in which parameters only
dominate the disturbance matrices will be analyzed, and a precise
comparison with be displayed between our algorithm with the old
ones which is aim to solve these problems in general Markov reward
processes. When applied in SPMRPs, our method will approach a fast
pace in these cases. Furthermore, to illustrate the practical value of
SPMRPs, a simple example in multiple programming in computer
systems will be listed and simulated. Corresponding to some practical
model, physical meanings of SPMRPs in networks of queues will be
clarified.
Abstract: The importance of ensuring safe meat handling and
processing practices has been demonstrated in global reports on food
safety scares and related illness and deaths. This necessitated stricter
meat safety control strategies. Today, many countries have regulated
towards preventative and systematic control over safe meat
processing at abattoirs utilizing the Hazard Analysis Critical Control
Point (HACCP) principles. HACCP systems have been reported as
effective in managing food safety risks, if correctly implemented.
South Africa has regulated the Hygiene Management System (HMS)
based on HACCP principles applicable to abattoirs. Regulators utilise
the Hygiene Assessment System (HAS) to audit compliance at
abattoirs. These systems were benchmarked from the United
Kingdom (UK). Little research has been done them since inception as
of 2004. This paper presents a review of the two systems, its
implementation and comparison with HACCP. Recommendations are
made for future research to demonstrate the utility of the HMS and
HAS in assuring safe meat to consumers.
Abstract: Software testing is important stage of software development cycle. Current testing process involves tester and electronic documents with test case scenarios. In this paper we focus on new approach to testing process using automated test case generation and tester guidance through the system based on the model of the system. Test case generation and model-based testing is not possible without proper system model. We aim on providing better feedback from the testing process thus eliminating the unnecessary paper work.
Abstract: This paper presents the source extraction system which can extract only target signals with constraints on source localization in on-line systems. The proposed system is a kind of methods for enhancing a target signal and suppressing other interference signals. But, the performance of proposed system is superior to any other methods and the extraction of target source is comparatively complete. The method has a beamforming concept and uses an improved time-frequency (TF) mask-based BSS algorithm to separate a target signal from multiple noise sources. The target sources are assumed to be in front and test data was recorded in a reverberant room. The experimental results of the proposed method was evaluated by the PESQ score of real-recording sentences and showed a noticeable speech enhancement.
Abstract: The aim of this work was to investigate the potential of soil microorganisms and the burhead plant, as well as the combination of soil microorganisms and plants to remediate monoethylene glycol (MEG), diethylene glycol (DEG), and triethylene glycol (TEG) in synthetic wastewater. The result showed that a system containing both burhead plant and soil microorganisms had the highest efficiency in EGs removal. Around 100% of MEG and DEG and 85% of TEG were removed within 15 days of the experiments. However, the burhead plant had higher removal efficiency than soil microorganisms for MEG and DEG but the same for TEG in the study systems. The removal rate of EGs in the study system related to the molecular weight of the compounds and MEG, the smallest glycol, was removed faster than DEG and TEG by both the burhead plant and soil microorganisms in the study system.
Abstract: Distributed Generation (DG) in the form of renewable
power generation systems is currently preferred for clean power
generation. It has a significant impact on the distribution systems.
This impact may be either positively or negatively depending on the
distribution system, distributed generator and load characteristics. In
this works, an overview of DG is briefly introduced. The technology
of DG is also listed while the technical impacts and economic
impacts are explained.
Abstract: In gas lifted oil fields, the lift gas should be distributed optimally among the wells which share gas from a common source to maximize total oil production. One of the objectives of the paper is to show that a linear MPC consisting of a control objective and an economic objective can be used both as an optimizer and a controller for gas lifted systems. The MPC is based on linearized model of the oil field developed from first principles modeling. Simulation results show that the total oil production is increased by 3.4%. Difficulties in accurately measuring the bottom hole pressure using sensors in harsh operating conditions can be resolved by using an Unscented Kalman Filter (UKF) for estimation. In oil fields where input disturbance (total supply of gas) is not measured, UKF can also be used for disturbance estimation. Increased total oil production due to optimization leads to increased profit.
Abstract: This paper explores how Critical Systems Thinking and Action Research can be used to improve student performance in Networking. When describing a system from a systems thinking perspective, the following aspects can be identified: the total system performance, the systems environment, the resources, the components and the management of the system. Following the history of system thinking we observe three emerged methodologies namely, hard systems, soft systems, and critical systems. This paper uses Critical Systems Thinking (CST) which describes systems in terms of contradictions and conflict. It demonstrates how CST can be used in an Action Research (AR) project to improve the performance of students. Intervention in terms of student assessment is discussed and the impact of the intervention is discussed.
Abstract: In this paper we present an efficient system for
independent speaker speech recognition based on neural network
approach. The proposed architecture comprises two phases: a
preprocessing phase which consists in segmental normalization and
features extraction and a classification phase which uses neural
networks based on nonparametric density estimation namely the
general regression neural network (GRNN). The relative
performances of the proposed model are compared to the similar
recognition systems based on the Multilayer Perceptron (MLP), the
Recurrent Neural Network (RNN) and the well known Discrete
Hidden Markov Model (HMM-VQ) that we have achieved also.
Experimental results obtained with Arabic digits have shown that the
use of nonparametric density estimation with an appropriate
smoothing factor (spread) improves the generalization power of the
neural network. The word error rate (WER) is reduced significantly
over the baseline HMM method. GRNN computation is a successful
alternative to the other neural network and DHMM.
Abstract: Capacity and efficiency of any refrigerating system
diminish rapidly as the difference between the evaporating and
condensing temperature is increased by a reduction in the evaporator
temperature. The single stage vapour compression refrigeration
system using various refrigerants are limited to an evaporator
temperature of -40 0C. Below temperature of -40 0C the either
cascade refrigeration system or multi stage vapour compression
system is employed. Present work describes thermal design of
condenser (HTS), cascade condenser and evaporator (LTS) of
R404A-R508B and R410A-R23 cascade refrigeration system. Heat
transfer area of condenser, cascade condenser and evaporator for
both systems are compared and the effect of condenser and
evaporator temperature on heat-transfer area for both systems is
studied under same operating condition. The results shows that the
required heat-transfer area of condenser and cascade condenser for
R410A-R23 cascade system is lower than the R404A-R508B cascade
system but heat transfer area of evaporator is similar for both the
system. The heat transfer area of condenser and cascade condenser
decreases with increase in condenser temperature (Tc), whereas the
heat transfer area of cascade condenser and evaporator increases with
increase in evaporator temperature (Te).
Abstract: The paper makes part from a complex research project
on Romanian Grey Steppe, a unique breed in terms of biological and
cultural-historical importance, on the verge of extinction and which
has been included in a preservation programme of genetic resources
from Romania. The study of genetic polymorphism of protean
fractions, especially kappa-casein, and the genotype relations of
these lactoproteins with some quantitative and qualitative features of
milk yield represents a current theme and a novelty for this breed. In
the estimation of the genetic parameters we used R.E.M.L.
(Restricted Maximum Likelihood) method.
The main lactoprotein from milk, kappa - casein (K-cz),
characterized in the specialized literature as a feature having a high
degree of hereditary transmission, behaves as such in the nucleus under
study, a value also confirmed by the heritability coefficient (h2 = 0.57
%). We must mention the medium values for milk and fat quantity
(h2=0.26, 0.29 %) and the fat and protein percentage from milk
having a high hereditary influence h2 = 0.71 - 0.63 %.
Correlations between kappa-casein and the milk quantity are
negative and strong. Between kappa-casein and other qualitative
features of milk (fat content 0.58-0.67 % and protein content 0.77-
0.87%), there are positive and very strong correlations. At the same
time, between kappa-casein and β casein (β-cz), β lactoglobulin (β-
lg) respectively, correlations are positive having high values (0.37 –
0.45 %), indicating the same causes and determining factors for the
two groups of features.
Abstract: The existence of maximal durations drastically modifies the performance evaluation in Discrete Event Systems (DES). The same particularity may be found on systems where the associated constraints do not concern the time. For example weight measures, in chemical industry, are used in order to control the quantity of consumed raw materials. This parameter also takes a fundamental part in the product quality as the correct transformation process is based upon a given percentage of each essence. Weight regulation therefore increases the global productivity of the system by decreasing the quantity of rejected products. In this paper we present an approach based on mixing different characteristics theories, the fuzzy system and Petri net system to describe the behaviour. An industriel application on a tobacco manufacturing plant, where the critical parameter is the weight is presented as an illustration.
Abstract: In the past decade, because of wide applications of
hybrid systems, many researchers have considered modeling and
control of these systems. Since switching systems constitute an
important class of hybrid systems, in this paper a method for optimal
control of linear switching systems is described. The method is also
applied on the two-tank system which is a much appropriate system
to analyze different modeling and control techniques of hybrid
systems. Simulation results show that, in this method, the goals of
control and also problem constraints can be satisfied by an
appropriate selection of cost function.
Abstract: In this study a clustering technique has been implemented which is K-Means like with hierarchical initial set (HKM). The goal of this study is to prove that clustering document sets do enhancement precision on information retrieval systems, since it was proved by Bellot & El-Beze on French language. A comparison is made between the traditional information retrieval system and the clustered one. Also the effect of increasing number of clusters on precision is studied. The indexing technique is Term Frequency * Inverse Document Frequency (TF * IDF). It has been found that the effect of Hierarchical K-Means Like clustering (HKM) with 3 clusters over 242 Arabic abstract documents from the Saudi Arabian National Computer Conference has significant results compared with traditional information retrieval system without clustering. Additionally it has been found that it is not necessary to increase the number of clusters to improve precision more.