The direct power control of the doubly fed induction generator using conventional controllers is characterized by unsatisfactory performance: high ripples of stator powers and sensitivity to parametric variations. Among the most evoked control strategies adopted in this field to overcome these drawbacks presented in classical drive, it is worth mentioning the use of the higher law sliding mode developed on the super twisting algorithm associated with the fuzzy logic control in order to realize optimal command performance, Finally, the efficiency of the envisaged control scheme, is investigated against. The proposed regulation scheme is efficient in reducing the powers ripples; successfully suppress chatter and the effects of parametric variations that do not affect the performance of the regulation.

This paper proposes the fundamental aspects of hybrid nonlinear control which is composed of the super twisting algorithm (STA) based second order sliding mode control applying fuzzy logic method (FSOSMC), with pertinent simulation results for a doubly fed induction machine (DFIM) drive. To minimize chattering effect phenomenon due to Signum function employed in sliding mode algorithm, a new method is proposed. This technique consists in replacing the signum function by fuzzy switching function in the SOSMC to minimize flux and torque ripples. This FSOSMC is associated to the double direct torque control DDTC of the doubly fed induction machine (DFIM) by combining the advantages of fuzzy logic (FL) and the advantages of super-twisting sliding mode. The FSOSMC-DDTC strategy is compared with a PI-DDTC and SOSMC-DDTC. Simulation results demonstrate good efficiency and excellent robustness of the hybrid nonlinear controller.

This article investigates a non-equilibrium chaotic system in view of commensurate and incommensurate fractional orders and with only one signum function. By varying some values of the fractional-order derivative together with some parameter values of the proposed system, different dynamical behaviors of the system are explored and discussed via several numerical simulations. This system displays complex hidden dynamics such as inversion property, chaotic bursting oscillation, multistabilty, and coexisting attractors. Besides, by means of adapting certain controlled constants, it is shown that this system possesses a three-variable offset boosting system. In conformity with the performed simulations, it also turns out that the resultant hidden attractors can be distributively ordered in a grid of three dimensions, a lattice of two dimensions, a line of one dimension, and even arbitrariness in the phase space. Through considering the Caputo fractional-order operator in all performed simulations, phase portraits in two- and three-dimensional projections, Lyapunov exponents, and the bifurcation diagrams are numerically reported in this work as beneficial exit results.

In this work, we propose a new algorithm to improve existing techniques used in the field of spectroscopic data regression analysis. In particular, it combines the power of nonlinear kernel regressors (kernel ridge regression [KRR], kernel principal component regression [KPCR], and Gaussian process regression [GPR]) with an optimization based on nondominated sorting multi-objective genetic algorithm (NSGAII) to filter the residual outliers in the prediction space and leverage points in the features space. The proposed algorithm, contrary to most existing robust algorithms, simultaneously optimizes many complementary objectives for an automatic adaptation and thus a better outliers detection. It is well known that the elimination of outliers greatly improves the regression model. It is thus the aim of this work to develop a new robust regression algorithm. It has been applied on five different datasets, and the results are compared to both classical nonlinear regression methods and the commonly used robust regression methods robust continuum regression (RCR), partial robust M-regression (PRM), robust principal component regression (RPCR), robust PLSR (RSIMPLS), and locally weighted regression (LWR). They show that the proposed algorithm outperforms the classical nonlinear regression methods and is a promising competitor to the robust methods outperforming most of them. Even though the results obtained are only from five datasets, this algorithm can be considered an interesting contribution for improving data analysis in the field of chemometrics.

In this paper, the role of introducing Germanium (Ge)/IGZO heterostructure in enhancing the Infrared (IR) photodetection properties of thin-film phototransistor (Photo- TFT) is presented. Numerical models for the investigated device are developed using ATLAS device simulator. The influence of Ge photosensitive layer thickness on the sensor IR photoresponse is carried out. It is revealed that the optimized IR Photo-TFT based on p-Ge/IGZO heterojunction can offer improved IR responsivity of 4.1×10(exp2) A/W, and over 10(exp6) of sensitivity. These improvements are attributed to the role of the introduced p-Ge/IGZO heterostructure in promoting IR photodetection ability and improved separation and transfer mechanisms of photo-exited electron/hole pairs. The photosensor is then implemented in an optical inverter gate circuit in order to assess its switching capabilities. It is found that the proposed phototransistor shows an improved optical gain thus indicating its excellent performance. Therefore, providing high IR responsivity and low dark noise effects, the optimized Ge/IGZO IR Photo-TFT can be a potential alternative photosensor for designing optoelectronic systems with high-performance and ultralow power consumption.

Purpose

The objectives of this paper are the application of sensitivity analysis (SA) methods in atmospheric dispersion modeling to the emission dispersion model (EDM) to study the prediction of atmospheric dispersion of NO₂ generated by an industrial fire, whose results are useful for fire safety applications. The EDM is used to predict the level concentration of nitrogen dioxide (NO₂) emitted by an industrial fire in a plant located in an industrial region site in Algeria.

Design/methodology/approach

The SA was defined for the following input parameters: wind speed, NO₂ emission rate and viscosity and diffusivity coefficients by simulating the air quality impacts of fire on an industrial area. Two SA methods are used: a local SA by using a one at a time technique and a global SA, for which correlation analysis was conducted on the EDM using the standardized regression coefficient.

Findings

The study demonstrates that, under ordinary weather conditions and for the fields near to the fire, the NO₂ initial concentration has the most influence on the predicted NO₂ levels than any other model input. Whereas, for the far field, the initial concentration and the wind speed have the most impact on the NO₂ concentration estimation.

Originality/value

The study shows that an effective decision-making process should not be only based on the mean values, but it should, in particular, consider the upper bound plume concentration.

Mining itemsets for association rule generation is a fundamental data mining task originally stemming from the traditional market basket analysis problem. However, enumerating all frequent itemsets, especially in a dense dataset, or with low support thresholds, remains costly. In this paper, a novel theorem builds the relationship between frequent closed itemsets (FCIs) and frequent generator itemsets (FGIs) and proves that the process of mining FCIs is equivalent to mining FGIs, unified with their full-support and extension items. On the basis of this theorem, a generator-based algorithm for mining FCIs, called GrAFCI⁺, is proposed and explained in details including its correctness. The comparative effectiveness of the algorithm in terms of scalability is first investigated, along with the compression rate—a measure of the interestingness of a given FIs representation. Extensive experiments are further undertaken on eight datasets and four state-of-the-art algorithms, namely DCI_CLOSED*, DCI_PLUS, FPClose, and NAFCP. The results show that the proposed algorithm is more efficient regarding the execution time in most cases as compared to these algorithms. Because GrAFCI⁺ main goal is to address the runtime issue, it paid a memory cost, especially when the support is too small. However, this cost is not high since GrAFCI⁺ is seconded by only one competitor out of four in memory utilization and for large support values. As an overall assessment, GrAFCI⁺ gives better results than most of its competitors.

In this  study, we have studied the length-weight relationship, condition factor (Kr), gonado-somatic index (GSI) and size at first maturity of two Cichlidae species (Tilapia zillii and Hemichromis bimaculatus) from two lakes (Megarine and Temacine) of the northern Sahara (Algeria). Some 159 specimens of H. bimaculatus and 52 T. zillii were sampled between September 2012 and July 2013. The length-weight relationship revealed an isometric value b (3.0) for H. bimaculatus from Lake Megarine, while there was no significant difference for T. zillii from Lake Temacine. We noted a negative allometric growth pattern (b<3) of males and females of H. bimaculatus. Both sexes of T. zillii grew isometrically. The Kr did not differ significantly between months for the two studied species. It was less than 1 only in November and July for H. bimaculatus. For T. zillii, the monthly mean of Kr was always greater than 1 for all the studied period. The first sexual maturity of 50% of males was observed at 52.75mm in H. bimaculatus and 61mm in T. zillii. The smallest mature female had a total length of 60.26mm and 66mm for H. bimaculatus and T. zillii respectively. The reproduction period of H. bimaculatus and T. zillii begins in March with an extended spawning period. The overall sex ratio was in favor of females (1: 0.7) in H. bimaculatus, and in favor of males in T. zillii (1: 1.33). For both species, the sex ratio varied according to months and size classes.

The health systems in many countries are still unable to control the evolution and persistence of the COVID-19 pandemic despite the large mobilisation of national resources. International attention has focussed on finding a cure, and preventive measures and national and international strategies to be adopted and implemented with regard to other future pandemics have been neglected despite their predictability and high probability of occurrence. This work aims to anticipate a reading on experience feedback in light of the current pandemic situation, and to identify the main spatial elements of vulnerability in Batna, Algeria, which seems to control the ability of an urban area to prevent the spread of the COVID-19 virus. We used a digital model based on a multi-criteria approach implemented in a geo-decisional GIS database to serve as a decision support tool for dealing with an epidemiological situation as a preventive or curative action. The results from the model seem to adequately reflect the reality of confirmed incidents in Batna. In addition, the results of the analysis of the spatiotemporal evolution of the virus clearly confirm that the urban sectors characterised by high vulnerability are those that have recorded an increasing number of confirmed COVID-19 incidents since the start of the epidemic until December 2020.

Let A, A_{1},  A_{2}, B, B_{1}, B_{2}, C_{1} and C_{2} be linear bounded operators on Hilbert spaces. In this paper, by using generalized inverses, we establish necessary and sufficient conditions for the existence of a common solution and give the form of the general common solution of the operator equations A_{1}XB_{1}=C_{1} and A_{2}XB_{2}=C_{2}, we apply this result to determine new necessary and sufficient conditions for the existence of Hermitian solutions  and give the form of the general Hermitian solution to the operator equation AXB=C. As a consequence, we give necessary and sufficient condition for the existence of Hermitian solution to the operator equation AXA^{*}+BYB^{*}=C.

In wireless sensor networks (WSNs), multi-channel communication represents an attractive field due to its advantage in improving throughput and delivery rate. However, the major challenge that faces WSNs is the energy constraint. To overcome the channel assignment problem in an energy-efficient way, reinforcement learning (RL) approach is used. Though, RL requires several iterations to obtain the best solution, creating a communication overhead and time-wasting. In this paper, a heuristically accelerated reinforcement learning approach for channel assignment (HARL CA) in WSNs is proposed to reduce the learning iterations. The proposal considers the selected channel by the neighboring sender nodes as external information, used to accelerate the learning process and to avoid collisions, while the bandwidth of the used channel is regarded as an important factor in the scheduling process to increase the delivery rate. The results of extensive simulation experiments show the effectiveness of our approach in improving the network lifetime and performance.

The design and the evaluation of communication protocols in WSNs is a crucial issue. Generally, researchers use simulation methods to evaluate them. However, formal modelling and analysis techniques are an efficient alternative to simulation methods. Indeed, these techniques allow performance evaluation and model verification. In this paper, a formal approach is proposed to modelling and to evaluating the Carrier Sense Multiple Access with Collision Avoidance (CSMA/CA) MAC protocol with a star topology. Moreover, the proposed approach deals with some properties that are not stated in most existing works. The approach uses Hierarchical Timed Coloured Petri Nets (HTCPNs) formalism to model the protocol and exploits the CPN-Tools to analyse the generated models. HTCPNs provide timed aspect which facilitates the consideration of time constraints inherent to the CSMA/CA protocol.

The objective of this study was to evaluate the effect of food supply in garbage dumps on the reproductive fitness of Cattle Egret Bubulcus ibis and offspring losses. A total of 236 nests were monitored during two distinct periods of 2 years for each: 146 nests during a period without food supply in dumps (1998–1999) and 90 with food supply in dumps (2007–2008). The study was carried out in the colony of El-Kseur in the Lower Soummam Valley (northeast Algeria). For the entire study period, the mean of clutch size, average number of hatched chicks, productivity, and breeding success varied significantly between years (Kruskal–Wallis test: p < .05). Also, the average calculated losses for eggs, chicks, and total offspring vary significantly (Chi2 test: p > .0001). The clutch size and the number of hatched chicks per nest were highest during the period with food supply in garbage dump (respectively: 3.46 ± 0.86; 2.85 ± 1.11), compared to the period when cattle egrets feed in natural or agricultural habitats (3.04 ± 0.87; 2.54 ± 1.03). However, productivity and breeding success were highest during the period without food supply (respectively: 2.11 ± 1.16 fledging’s/nest; 0.70 ± 0.35) than in the period with food supply (1.14 ± 0.91; 0.35 ± 0.30). While egg losses were substantially similar between the two study periods, chick’s mortality (59.9%) and total offspring losses (36.7%) were higher during the period with food supply. The generalized linear mixed model (GLMM) analysis indicated a large negative effect of food supply in dumps on the productivity, on the chick’s losses; and a positive effect on the total offspring losses (p < .001). Also, feed in dump garbage revealed a significant negative effect on the breeding success linear mixed model (LMM, p = .01). However, no significant effects (GLMM, p > .05) of food supply in dumps were noted on average clutch size, the mean number of hatched chicks per nest, and egg losses.

Introduction: Traditional medicine has an important place in human history and this since antiquity. Indeed, during Egyptian and Chinese civilization era, many detailed manuscripts, describing the therapeutic effect of plants, were found which suggest that folk medicine is the basis of the actual medicine. Objective: To investigate the phytochemical and pharmacological properties of the n-butanol (n-BuOH) and ethyl acetate (EA) extracts of the aerial part of Centaurea tougourensis. Methods: The phytochemical evaluation was done based on HPLC-DAD approach. The antioxidant activity was determined by DPPH and cupric ion reducing antioxidant capacity (CUPRAC), while the hemostatic effect was performed using plasma recalcification time (PRT) method. The antidiabetic capacity was investigated by alpha-amylase inhibition assay and the photoprotective test was evaluated by the measurement of sun protection factor (SPF). Results: 13 phenolic compounds were identified in both extracts of C. tougourensis. These extracts showed antioxidant, haemostatic, antidiabetic and photoprotective properties with a dose-dependent manner. Amounts of n-BuOH activities were found higher, with a respective IC50 value of 0.72±0.07 μg/ml in DPPH assay, an A0.50 value lower than 3.125 μg/ml in CUPRAC assay besides a shortening rate percentage of coagulation (86.71%) in haemostatic assay, a moderate inhibition effect on alpha amylase activity with an IC50 value of (711.5±0.03 μg/ml) and a maximum sun protection factor of (56.035). These results were mostly found highly significant (p<0.001) when compared to respective standards. Conclusion: This study demonstrated some pharmacological effects of C. tougourensis which suggests that our plant could be a good candidate to treat some illnesses related to oxidative stress, bleeding or skin cancer.

In this paper, we address the integration of a two-level supply chain with multiple items. This two-level production-distribution system features a capacitated production facility supplying several retailers located in the same region. If production does occur, this process incurs a fixed setup cost and unit production costs. Besides, deliveries are made from the plant to the retailers by a limited number of capacitated vehicles, routing costs incurred. This work aims to implement a minimization solution that reduces the total costs in both the production facility and retailers. The methodology adopted based on a hybrid heuristic, greedy and genetic algorithm uses strong formulation to provide a suitable solution of a guaranteed quality that is as good or better than those provided by the MIP optimizer. The results demonstrate that the proposed heuristics are effective and performs impressively in terms of computational efficiency and solution quality.

In recent years, some efforts have been devoted to nonlinear dynamics of fractional discrete-time systems. A number of papers have so far discussed results related to the presence of chaos in fractional maps. However, less results have been published to date regarding the presence of hyperchaos in fractional discrete-time systems. This paper aims to bridge the gap by introducing a new three-dimensional fractional map that shows, for the first time, complex hyperchaotic behaviors. A detailed analysis of the map dynamics is conducted via computation of Lyapunov exponents, bifurcation diagrams, phase portraits, approximated entropy and Co complexity. Simulation results confirm the effectiveness of the approach illustrated herein.

Most of the papers published so far on fractional discrete systems are related to theoretical results on their chaotic behaviors or to applications based on the mathematical modeling of the chaotic phenomena. No paper has been published to date regarding the hardware implementation of hyperchaotic fractional maps. This manuscript makes a contribution to the topic by presenting the first example of hardware implementation of hyperchaotic fractional maps. In particular, by exploiting the Grunwald–Letnikov difference operator, the paper introduces a new version of the fractional Grassi–Miller map. The system dynamics are analyzed via bifurcation diagrams and Lyapunov exponents, showing that the conceived map is hyperchaotic when the fractional order � belongs to the interval [0.966,1]. Finally, a hardware implementation of the fractional map is illustrated, with the aim to concretely highlight the presence of hyperchaos in physical systems described by fractional difference equations. Arduino, an open-source platform, has been used to illustrate the simplicity as well as the feasibility of the implementation.

Tunnel FETisone of thealternativedevicefor low power electronics having steep subthreshold swing and lower leakage current than conventional MOSFET. In this research work, we have implemented the idea of high -k gate dielectric ondouble gate Tunnel FET, DG-TFETfor improvement of device features.An extensive investigation for the analog/RF and linearity feature of DG-TFET has been donehere for low power circuit and system development.Several essential analog/RF and linearity parameters like transconductance(gm), transconductance generation factor (gm/IDS) its high-order derivatives (gm2, gm3), cut-off frequency (fT), gain band width product (GBW), transconductance generation factor (gm/IDS) has been investigated for low power RF applications.The VIP2, VIP3, IMD3, IIP3, distortion characteristics (HD2, HD3), 1- dB the compression point, delay and power delay product performancehave also been throughly studied.It has been observed that the device features discussed for circuitry applications are found to be sensitiveto of gate materials, design configuration and input signals.