Abstract:
The computer security has become a major challenge. Tools and mechanisms have been developed to ensure a level of compliance. These include the Intrusion De-tection Systems (IDS). The principle of conventional IDS is to detect attempts to attack a network and to identify abnormal activities and behaviors. The reasons, including the uncertainty in searching for types of attacks and the increasing com-plexity of advanced cyber-attacks, IDS calls for the need for integration of meth-ods such as Deep Neuron Networks (DNN) and Recurring Neuron Networks (RNN) more precisely long-term memory (LSTM). In this submission, DNN and LSTM were used to predict attacks against the Network Intrusion Detection Sys-tem (NIDS). In this memory, we used four hidden layers for all deep learning algo-rithms, forty-one layers of inputs and two layers of outputs and with 100 itera-tions. In fact, learning is kept constant at 0.01 while the other parameters are optimized. After that for DNN, the number of neurons of the first hidden layer was further increased to 1280 but did not give any appreciable increase in accuracy. Therefore, the number of neurons has been set to 1024 and the LSTM we set the number of neurons of all hidden layers to 32. The results were compared and con-cluded that a three-layer LSTM performs better than all other conventional ma-chine learning and deep learning algorithms.

Abstract:
This paper aims to study the influence of individual and perceptual characteristics on e-learning outcomes. A conceptual model, based on the social cognitive theory, technology acceptance theory and training evaluation model, is developed and tested on 410 trainees, in Tunisian context. Data analysis conducted by structural equations shows the importance of motivation to learn, perceptual usefulness and ease of use as factors that influence e-learning outcomes.

Abstract:
This paper introduces a notion of 2-orthogonality for a sequence of polynomials to give extended versions of the Meixner and Feinsilver characterization results based on orthogonal polynomials. These new versions subsume the Letac-Mora characterization of the real natural exponential families having cubic variance function.

Abstract:
Translation is a crucial step in gene expression. During translation, macromolecules called ribosomes "read" the mRNA strand in a sequential manner and produce a corresponding protein. Translation is known to consume most of the cell's energy. Maximizing the protein production rate in mRNA translation, subject to the bounded biomolecullar budget, is thus an important problem in both biology and biotechnology. We consider this problem using a mathematical model for mRNA translation called the ribosome flow model (RFM). For an mRNA strand with $n$ sites the RFM includes $n$ state-variables that encode the normalized ribosomal density at each site, and $n+1$ positive parameters: the initiation rate and elongation rates along the chain. An affine constraint on these rates is used to model the bounded cellular budget. We show that for a homogeneous constraint the rates that maximize the steady-state protein production rate have a special structure. They are symmetric with respect to the middle of the chain, and monotonically increase as we move towards the center of the chain. The ribosomal densities corresponding to the optimal rates monotonically decrease along the chain. We discuss some of the biological implications of these results.

Abstract:
We compute the cohomological space $\mathrm{H}^1_\mathrm{diff}\left(\mathfrak{sl}(2), \mathrm{D}_{\lambda,\mu}\right)$ where $\mu\in \mathbb{R}$, $\lambda=(\lambda_1,\dots,\lambda_n)\in\mathbb{R}^n$ and $\mathrm{D}_{\lambda,\mu}$ is the space of multilinear differential operators from $\cF_{\l_1}\otimes\cdots\otimes\cF_{\l_n}$ to $\cF_\mu$. The structure of these spaces was conjectured in [M. Ben Ammar et al. in International Journal of Geometric Methods in Modern Physics Vol. 9, No. 4 (2012) 1250033 (15 pages).]

Abstract:
Treatment
of Indigo dye (leuco form), reduced in the industrial conditions of the
SITEX (Textile Industrial Company), by a batch electrocoagulation using
aluminum electrodes. Response Surface Methodology (RSM) and Box-Behnken design
were used to optimize for Color Removal (CR(%)). Our results showed that the
quadratic second order equation provided the best correlation for the
decolorization of Indigo dye (CR(%)). On the other hand, the ANOVA analysis
proved the large interaction between the current intensity and the initial
concentration of the dye. Experiments were conducted to find the desired
conditions for removal of particular concentration of the dye and lower
Operation Cost. The results showed that CR(%) = 88.3% (R^{2}) of color
removal for initial dye concentration of 12.31 mg/l, with a current density of
2.81 A/m^{2}, solution concentration of NaCl of 2.67 g/l. Under these
conditions, Electrical Energy Consumption (EEC) and Electrode Consumption (EMC)
and Operation Cost were 0.01999 kWh/m^{3} (R^{2} = 93.1%),
0.00142768 Kg/m^{3} (R^{2} = 79.4%) and 0.000558 US$/m^{3},
respectively.

Abstract:
Mesh technology has captured the interest of university research and industry, because of its capacity to meet at the same time the requirements of Internet service provider and users. But, its architecture and configuration do not ensure a protection against the unauthorized use of the network since the used basic security measures do not include the concept of mobility. Our endeavor in this paper is to introduce a re-authentication scheme for secure handoff based on an efficient mobility management. First, we have treated the mobility aspect. Indeed, we applied the Mobility Notification Message procedure to support an environment which manages handoff in effective way. Then, using this technique, we have defined a new scheme to provide security during handoff. Our study shows that the proposed protocol can provide more protected network and more effective re-authentication scheme in term of minimized handoff latency as well as reduced blocking and loss rates.

Abstract:
The asymmetric simple exclusion process (ASEP) is an important model from statistical physics describing particles that hop randomly from one site to the next along an ordered lattice of sites, but only if the next site is empty. ASEP has been used to model and analyze numerous multiagent systems with local interactions ranging from ribosome flow along the mRNA to pedestrian traffic. In ASEP with periodic boundary conditions a particle that hops from the last site returns to the first one. The mean field approximation of this model is referred to as the ribosome flow model on a ring (RFMR). We analyze the RFMR using the theory of monotone dynamical systems. We show that it admits a continuum of equilibrium points and that every trajectory converges to an equilibrium point. Furthermore, we show that it entrains to periodic transition rates between the sites. When all the transition rates are equal all the state variables converge to the same value. Thus, the RFMR with homogeneous transition rates is a nonlinear consensus algorithm. We describe an application of this to a simple formation control problem.

Abstract:
The Ribosome Flow Model (RFM) describes the unidirectional movement of interacting particles along a one-dimensional chain of sites. As a site becomes fuller, the effective entry rate into this site decreases. The RFM has been used to model and analyze mRNA translation, a biological process in which ribosomes (the particles) move along the mRNA molecule (the chain), and decode the genetic information into proteins. Here we propose the RFM as an analytical framework for modeling and analyzing linear communication networks. In this context, the moving particles are data-packets, the chain of sites is a one dimensional set of ordered buffers, and the decreasing entry rate to a fuller buffer represents a kind of decentralized backpressure flow control. For an RFM with homogeneous link capacities, we provide closed-form expressions for important network metrics including the throughput and end-to-end delay. We use these results to analyze the hop length and the transmission probability (in a contention access mode) that minimize the end-to-end delay in a multihop linear network, and provide closed-form expressions for the optimal parameter values.

Abstract:
Gene translation is the process in which intracellular macro-molecules, called ribosomes, decode genetic information in the mRNA chain into the corresponding proteins. Gene translation includes several steps. During the elongation step, ribosomes move along the mRNA in a sequential manner and link amino-acids together in the corresponding order to produce the proteins. The homogeneous ribosome flow model(HRFM) is a deterministic computational model for translation-elongation under the assumption of constant elongation rates along the mRNA chain. The HRFM is described by a set of n first-order nonlinear ordinary differential equations, where n represents the number of sites along the mRNA chain. The HRFM also includes two positive parameters: ribosomal initiation rate and the (constant) elongation rate. In this paper, we show that the steady-state translation rate in the HRFM is a concave function of its parameters. This means that the problem of determining the parameter values that maximize the translation rate is relatively simple. Our results may contribute to a better understanding of the mechanisms and evolution of translation-elongation. We demonstrate this by using the theoretical results to estimate the initiation rate in M. musculus embryonic stem cell. The underlying assumption is that evolution optimized the translation mechanism. For the infinite-dimensional HRFM, we derive a closed-form solution to the problem of determining the initiation and transition rates that maximize the protein translation rate. We show that these expressions provide good approximations for the optimal values in the n-dimensional HRFM already for relatively small values of n. These results may have applications for synthetic biology where an important problem is to re-engineer genomic systems in order to maximize the protein production rate.