Mechanism of acetic acid transfer from aqueous sodium chloride solutions to some orgranic solvents

Salting out of acetic acid from aqueous solutions containing various concentrations of sodium chloride into some organic solvents has been studied at various temperatures. The solvents include cyclohexane, carbon tetrachloride, 1,2-dichloroethane, isopropyl ether, 2-pentanone and 1-heptanol. The results are consistent with a transfer mechanism involving monomer partitioning, dimerization and dimer return to the aqueous phase. Factors favoring monomer partitioning such as rise in both temperature and salt level retard dimer return, a process which is found to be significant in dimerization-enhancing solvents. The sensitivity of various solvents towards salt effect increases in the order 1-heptanol < isopropylether < 1,2-dichloroethane < 2-pentanone < cyclohexane < carbon tetrachloride which generally parallels in the reverse order the extent of stabilization of the acid by various solvent interactions.     

On the Performance of FFT/DWT/DCT-based OFDM Systems with Chaotic Interleaving and Channel Estimation Algorithms

The efficiency of data transmission over fading channels in orthogonal frequency division multiplexing (OFDM) systems depends on the employed interleaving method. In this study, we propose an improved chaotic interleaving scheme which aims to improve the performance of OFDM system under fading channel. In the proposed scheme, the binary data is interleaved with chaotic Baker map prior to the modulation process. In the sequel, significant degree of encryption is being added during data transmission. The performance of the proposed approach is tested on the conventional fast Fourier transform OFDM, discrete wavelet transform OFDM, and discrete cosine transform OFDM with and without chaotic interleaving. Furthermore, an expectation–maximization (EM) algorithm is proposed for improving channel impulse response (CIR) estimation based on a maximum likelihood principle. The proposed scheme makes use of EM algorithm to update the channel estimates until convergence is reached. The simulation results show the efficiency of the proposed algorithms under Rayleigh fading environments where the symbol error rate essentially coincides with that of the perfect channel case after the fifth EM iteration.     

Nitrogen-doped reduced graphene oxide/Fe2O3 hybrid as efficient catalyst for ammonium nitrate

In this investigation, we successfully synthesized a hybrid material, N-rGO@Fe₂O₃, via a one-step hydrothermal process, comprising nitrogen-doped reduced graphene oxide and α-Fe₂O₃. Thorough characterization using diverse analytical methods validated its structure. Employing this hybrid composite as a catalyst, we studied its efficacy in the catalytic thermal decomposition of ammonium nitrate (AN). The N-rGO@Fe₂O₃/AN composite was prepared using a recurrent spray coating method with 3 % mass of the hybrid material. Thermo-gravimetric (TG) and differential scanning calorimetric (DSC) analyses were employed to investigate the catalytic effect. Computational assessment of Arrhenius parameters was conducted through isoconversional kinetic approaches. Results from the kinetic analysis allowed the determination of the critical ignition temperature. Furthermore, calorific values for pure AN and N-rGO@Fe₂O₃/AN were measured using an oxygen calorimetric bombe, revealing a 41 % reduction in activation energy barrier and a lowering of the critical ignition temperature from 292 °C to 283 °C upon incorporation of the hybrid material. Notably, the surface modification of AN with N-rGO@Fe₂O₃ resulted in an increase of 1440 J/g in the observed calorific values. These findings highlight the potential of N-rGO@Fe₂O₃ as an effective catalyst, offering promising implications for applications in enhancing ammonium nitrate thermal decomposition.     

ANN modeling of a smart MEMS-based capacitive humidity sensor

This paper presents a design of a smart humidity sensor. First we begin by the modeling of a Capacitive MEMS-based humidity sensor. Using neuronal networks and Matlab environment to accurately express the non-linearity, the hysteresis effect and the cross sensitivity of the output humidity sensor used. We have done the training to create an analytical model CHS “Capacitive Humidity Sensor”. Because our sensor is a capacitive type, the obtained model on PSPICE reflects the humidity variation by a capacity variation, which is a passive magnitude; it requires a conversion to an active magnitude, why we realize a conversion capacity/voltage using a switched capacitor circuit SCC. In a second step a linearization, by Matlab program, is applied to CHS response whose goal is to create a database for an element of correction “CORRECTOR”. After that we use the bias matrix and the weights matrix obtained by training to establish the CHS model and the CORRECTOR model on PSPICE simulator, where the output of the first is identical to the output of the CHS and the last correct its nonlinear response, and eliminate its hysteresis effect and cross sensitivity. The three blocks; CHS model, CORRECTOR model and the capacity/voltage converter, represent the smart sensor.     

Modelling approaches for the estimation of irreducible water saturation and heterogeneities of the commercial Ashtart reservoir from the Gulf of Gabès, Tunisia

Oil production based on reserves in place in the Ashtart oilfield required the precise knowledge of the main reservoir parameters including porosity, permeability and irreducible water saturation. The reservoir series is comprised of Nummulitid but heterogeneous limestones of the El Garia Formation, the petrofacies texture, geometry and petrophysical parameters of which were apprehended using seismic profiles; gamma-ray and sonic lateral logs, as well as cores and cuttings taken in drillwells. The evaluation of residual oil saturation, multiphase flow and oil production techniques from the Ashtart reservoir also depend on variations and zoning of the irreducible water saturation. Estimation of the initial water saturation and hence variations in the capillary pressure in the reservoir, required compilations of porosity data measured on cores, supplemented by additional but computed porosities based on acoustic log diagrams. Furthermore, Gamma Ray, Sonic log, and well to well correlations tied to core results and well cuttings, help recognize the layered lithologies within the El Garia flat lying but stratified, Ypresian in origin reservoir rocks. Abundant permeability and porosity values compiled in the light of seismic sequence and Gamma Ray and Sonic log details, were integrated in an empirical approach using the Leverett J function, to model the irreducible water saturation depending on the capillary pressure distribution in the whole reservoir. Variations of this principal hydraulic parameter in a wide range (S_wir: 12 to 40%) compared to the preceding lithostratigraphic, petrographical and petrophysical results help recognize four main rock pore types in the commercial Ashtart reservoir. These vary from (1) a zone with a rock pore type showing an irreducible water saturation as low as 12%, and a fairly good reservoir character in the lower third part of the lithologic column which is thought to channelize a multiphase fluid flow in the global oilfield, (2) to those zones built-up of rock pore types with higher initial water saturation amounts which in certain cases tend to indicate zones of degraded reservoir. Our study suggests that diagenesis prevalently controls porosity, due to operative dissolutions of the Nummulitid tests/bioclasts, and cementation; moreover, diagenesis exerts effects on permeability by interconnecting intergranular and intratest pore spaces. In contrast, microfracturing enhances permeability of the reservoir. This is notably the case in the fairly permeable central zone in the Ashtart reservoir with excellent petrophysical parameters, but which were found to degrade gradually towards its peripheries.     

On-line resources allocation for ATM networks with rerouting

This paper presents an application we developed for France Telecom R&D to solve a difficult real-life network problem. The problem takes place in an Asynchronous Transfer Mode (ATM) network administration context and consists in planning demands of connection over a period of 1 year. A new demand is accepted if both bandwidth and Quality of Service (QoS) requirements are satisfied. Demands are not known prior to the assignment and must be performed on-line according to their arrival. Moreover, the acceptance or the reject of a demand must be decided within a given time of 1 min.     

A multi-level conceptual data reduction approach based on the Lukasiewicz implication

Starting from fuzzy binary data represented as tables in the fuzzy relational database, in this paper, we use fuzzy formal concept analysis to reduce the tables size to only keep the minimal rows in each table, without losing knowledge (i.e., association rules extracted from reduced databases are identical at given precision level). More specifically, we develop a fuzzy extension of a previously proposed algorithm for crisp data reduction without loss of knowledge. The fuzzy Galois connection based on the Lukasiewicz implication is mainly used in the definition of the closure operator according to a precision level, which makes data reduction sensitive to the variation of this precision level.     

Some experiments with the interpretation strategy of a modular computer vision system

This paper is concerned with the general problem of computer vision. That is, given a colored input picture, design a system which segments the objects in the scene and interprets them appropriately. During the past few years, we have been engaged in the development of a modular, data-driven computer vision system to achieve this goal. The details have appeared elsewhere, so here we have primarily emphasized the mechanism for updating the hypothesized region interpretations. This is achieved by means of a relaxation labeling process which has continuous access to a scene model describing the picture under consideration.