The security is so important for both storing and transmitting the digital data, the choice of parameters is critical for a security system, that is, a weak parameter will make the scheme very vulnerable to attacks, for example the use of supersingular curves or anomalous curves leads to weaknesses in elliptic curve cryptosystems, for RSA cryptosystem there are some attacks for low public exponent or small private exponent. In certain circumstances the secret sharing scheme is required to decentralize the risk. In the context of the security of secret sharing schemes, it is known that for the scheme of Shamir, an unqualified set of shares cannot leak any information about the secret. This paper aims to show that the well-known Shamir’s secret sharing is not always perfect and that the uniform randomization before sharing is insufficient to obtain a secure scheme. The second purpose of this paper is to give an explicit construction of weak polynomials for which the Shamir’s (k, n) threshold scheme is insecure in the sense that there exist a fewer than k shares which can reconstruct the secret. Particular attention is given to the scheme whose threshold is less than or equal to 6. It also showed that for certain threshold k, the secret can be calculated by a pair of shares with the probability of 1/2. Finally, in order to address the mentioned vulnerabilities, several classes of polynomials should be avoided.

Graph matching is a comparison process of two objects represented as graphs through finding a correspondence between vertices and edges. This process allows defining a similarity degree (or dissimilarity) between the graphs. Generally, graph matching is used for extracting, finding and retrieving any information or sub-information that can be represented by graphs. In this paper, a new consistency rule is proposed to tackle with various problems of graph matching. After, using the proposed rule as a necessary and sufficient condition for the graph isomorphism, we generalize it for subgraph isomorphism, homomorphism and for an example of inexact graph matching. To determine whether there is a matching or not, a backtracking algorithm called CRGI2 is presented who checks the consistency rule by exploring the overall search space. The tree-search is consolidated with a tree pruning technique that eliminates the unfruitful branches as early as possible. Experimental results show that our algorithm is efficient and applicable for a real case application in the information retrieval field. On the efficiency side, due to the ability of the proposed rule to eliminate as early as possible the incorrect solutions, our algorithm outperforms the existing algorithms in the literature. For the application side, the algorithm has been successfully tested for querying a real dataset that contains a large set of e-mail messages.

This paper introduces a new approach of hybrid meta-heuristics based optimization technique for decreasing the computation time of the shortest paths algorithm. The problem of finding the shortest paths is a combinatorial optimization problem which has been well studied from various fields. The number of vehicles on the road has increased incredibly. Therefore, traffic management has become a major problem. We study the traffic network in large scale routing problems as a field of application. The meta-heuristic we propose introduces new hybrid genetic algorithm named IOGA. The problem consists of finding the k optimal paths that minimizes a metric such as distance, time, etc. Testing was performed using an exact algorithm and meta-heuristic algorithm on random generated network instances. Experimental analyses demonstrate the efficiency of our proposed approach in terms of runtime and quality of the result. Empirical results obtained show that the proposed algorithm outperforms some of the existing technique in term of the optimal solution in every generation.

Skin detection is very challenging because of the differences in illumination, cameras characteristics, the range of skin colours due to different ethnicities and many other variations. New effective and accurate methodologies are developed for skin colour detection to easily identify human’s skin colour threw databases which are specifically designed to assist research in the area of face recognition. One of these is the recently built SFA database that showed high accuracy for segmentation of face images. The approach described in this paper exploits skin and non-skin samples provided by SFA for skin segmentation on the basis of the well-known Euclidean and Manhattan distance metrics. Most importantly, the scheme proposed tries to segment facial colour images inside or outside SFA by means of skin samples belonging to SFA. Simulation results in both SFA and UTD colour face databases indicate that detection rates higher than 95% can be achieved with either measure.

The quasiparticle band structures and optical properties of ACdTS kesterite are investigated here on the basis of first-principles calculations, including the many-body effects theory, by using the GW plus Bethe-Salpeter equation. There were significant GW-quasiparticle corrections, over 0.9 eV, to the GGA-Kohn-Sham band gap. Our calculations also show that ACdTS kesterite had a small binding energy, exhibited optical absorption in the visible region, high minority carrier mobility, and large diffusion in length, rendering this material a promising candidate for solar cells. Based on these findings, we designed and implemented an ACdTS absorber in a thin-film solar cell (TFSC) structure. The new kesterite solar cell has a high efficiency of 11.6% with a low deficit in the output voltage. Moreover, a strategic combination between the particle swarm optimization approach and the ACdTS TFSC decorated with periodic nanowires is proposed to obtain significantly improved photovoltaic characteristics. The optimized design identifies a new pathway for a high conversion efficiency of 14%, far surpassing that provided by the conventional TFSC kesterite.

In this paper, a new high-performance tunable band-selective (UV-Visible) photodetector (PD) based on RF sputtered a-SiC active layer is demonstrated. SiC thin-films were deposited on glass substrate by RF magnetron sputtering method at different sputter power values ranging from 60 W to 120 W. The samples morphological, structural, optical and photodetection properties were investigated by carrying out XRD, SEM, EDS, UV-Vis spectroscopy and photoresponse measurements. It was revealed that the sputtering power could modulate the optical behavior of a-SiC alloy, tuning favorable visible absorbance at high sputter power. This phenomenon is correlated with the influence of the RF power on the SiC film structural properties and compositions. Interestingly, measurements showed that a-SiC PD elaborated at 60 W of RF power can detect UV radiation with a high responsivity of 138 mA/W, low noise effects, superior detectivity of 7.8 × 1012 Jones, while maintaining the visible blindness property. On the other hand, the prepared device at high sputtering power exhibits extended photoresponse characteristics, yielding 426 mA/W and 77 mA/W of responsivity values over UV and visible ranges, respectively. Therefore, the present investigation can provide a new strategy for the design and fabrication of photodetector devices based on SiC platform with broadband and solar-blind adjustable sensing purposes according to the desired application.

In this work, an inverted PTB7:PC70BM bulk heterojunction solar cells with the configuration of ITO/ZnO/ PTB7:PC70BM / HTMs/Ag for various inorganic materials as a hole transport layer (ZnO, MoO3, NiO, PEDOT: PSS, V2O5 and Cu2O) are simulated by using the GPVDM software which is a free general-purpose tool for the simulation of opto-electronic devices. The influence of the thickness of both PTB7:PC70BM and HTMs layers on the performance of the solar cell are investigated. The obtained results indicated that on regardless on the type of the inorganic material constituted the Hole Transport Material (HTM), the solar cell parameters can be improved by reducing the HTM thickness while the active layer optimum thickness is around 90 nm. The performance of the device with all inorganic materials used as HTM reaches the same levels as the PEDOT/PSS for the lower thickness (10 nm). As the thickness is increased, the electrical parameters are significantly enhanced by inserting cuprous oxide (Cu2O) compared to the conventional PEDOT: PSS.

A new multispectral InGaZnO (IGZO) thin-film phototransistor (TF PT) based on a graded band-gap (GBG) SiGe capping layer with metallic nanoparticles (MNPs) is proposed. An accurate drain-current model is developed to investigate the device performances, where the optical characteristics under different light excitations (530 nm, 820 nm, and 1550 nm) are analyzed using the 3-D Finite-difference time-domain method (FDTD). It is found that the proposed device shows high photoresponse characteristics. Besides, it is revealed that the GBG configuration, MNPs spatial distribution and size can induce a complex behavior, which influences the device photoresponse over multiple spectral bands. Importantly, an iterative decision-maker framework based on the Multi-Objective Genetic Algorithm (MOGA) metaheuristic approach is implemented to design efficient multispectral IGZO TF PT. It is demonstrated that the proposed MOGA-based scheme paves the way for the designer to identify the appropriate GBG profile and MNPs spatial distribution for highly-responsive devices at selective Visible and IR wavelengths and to realize high-performance multispectral sensors. The proposed approach based on combining the proposed IGZO TF PT structure with MOGA metaheuristic computation opens up a new strategy for the design and experimental fabrication of high-performance multispectral optoelectronic devices.

In this paper, the leaky acoustic microwaves (LAW) in a piezoelectric substrate (Lithium Niobate LiNbO3 Cut Y-X) were studied. The main method for this research was classification using a probabilistic neural network (PNN).The originality of this method is in the accurate values it provides. In our case, this technique was helpful in identifying undetectable waves, which are difficult to identify by classical methods. Moreover, all the values of the real part and the imaginary part of the coefficient attenuation with the acoustic velocity were classified in order to build a model from which we could easily note the Leaky waves. Accurate values of the coefficient attenuation and acoustic velocity for Leaky waves were obtained. Hence, in this study, the focus was on the interesting modeling and realization of acoustic microwave devices (radiating structures) based on the propagation of acoustic microwaves

This paper presents the second-order sliding mode controller (SOSMC) of a micro-positioning stage piezoelectric model actuator (PEA), where the C-H model parameters are adopted to describe the hysteresis behavior and identified through particle swarm optimization. In this technique, two control algorithms are developed. The first one is the so-called twisting algorithm (TA). The control appears explicitly in the second surface derivative, and in a discontinuous control action that ensures a sliding regime mode. The second one, the super twisting algorithms (STA) has been developed and analyzed for systems. The use of both algorithms gives a significant reduction in chattering as compared to the standard sliding mode control. It is shown that the STA case offers better performances than TA. Simulation results are presented to demonstrate the advantage of SOSMC over SMC.

In this work, the modeling and the sliding mode control of a self-excited asynchronous generator integrated in a wind energy conversion system is studied. The dc-link voltage and frequency output by the wind turbine depend on the wind intensity applied to the turbine and load. The goal of the study is to increase energy quality and to achieve a stabilization of dc-link voltage and frequency values based on sliding mode control. This method offers stability and robustness against external disturbances. However, this method is based in the power converter to improve the excellent dynamic of wind energy conversion system to meet the connection to the main grid. The simulation results show the efficiency and reliability of the proposed control method.

The Mexa and Bougous dams were built to control river floods and supply crop-irrigation and drinking water. This study aimed to characterize the hydrogeochemical state in the region containing the dams, which influences the quality of the waters and thus their suitability for agricultural use, given the extent of the river networks that naturally transport sediments and pollutants into the reservoirs via streams. Thus, some physicochemical and organic parameters, including electrical conductivity, calcium, magnesium, sodium, potassium, chloride, bicarbonate, sulfate, biological oxygen demand, nitrite, ammonium, and phosphate, were used as benchmarks to examine the stiffness of the water pollution. Sampling was carried out during May and September of 2011 and 2012. The obtained results showed that, according to the Stiff diagram, the dominant hydrogeochemical facies is calcium bicarbonate in waters that do not have calcium levels in excess of 3 meq/l and bicarbonate levels in excess of 2.4 meq/l. The organic pollution index disclosed that the waters have evolved from a moderate to a high degree of organic pollution due to the accumulation of pollutants and nutrients from waste disposal and fertilizers. The samples fell into the C2-S1 class in the Richards diagram; this implies that the waters are suitable for plants that are salt tolerant, but that the use of these waters can cause problems for clay soils. However, in the long term, irrigation with the dam waters may pose difficulties for agriculture due to the resulting increase in the electrical conductivity of the soil. This study concludes that water salinity and alkalinity affect crop suitability, meaning that the temporal monitoring of water quality is needed to avoid adverse consequences for crop production.

The relative scarcity of water resources in Algeria and their unequal distribution induce a rational use of available resources. The Zana-Gadaïne plain appears as an exemplary case study, where the difficulties posed by the problem of crop water needs versus the availability of water resources appear. This article, based on field surveys and in-situ measurements, aims to identify the pressure of irrigation on water resources and the optimization of their use in an agricultural area, where irrigated agriculture represents 85% of the water consumption of the Zana-Gadaïne plain. The piezometric study in correlation with hydrogeological data reveals that groundwater resources are limited, aggravated by wastage resulting in a consequent drawdown of 24 meters over 11 years. The analysis of interannual climate variability has enabled us to draw rainfall maps characteristic of the evolution of rainfall over the past decades where we observe a net deficit in precipitation. We calculated the evapotranspiration and the requirements in irrigation water for each crop in order to compare them with the available hydric resources and the establishment of irrigation schedules for the principal irrigated crops. The analysis of interannual climate variability has enabled us to draw rainfall maps characteristic of the evolution of rainfall over the past decades where we observe a net deficit in precipitation. We calculated the evapotranspiration and the requirements in irrigation water for each crop in order to compare them with the available hydric resources and the establishment of irrigation schedules for the principal irrigated crops.

The phytochemical profile obtained from LC-ESI-MS/MS analysis of then-butanol extract (BEHL) from the North African endemic plantHyacinthoides lingulata (Poir.) Rothm. brought about the identification of ten glycosylated derivatives of apigenin and luteolin flavones. For the same plant extract,in vitro anti-inflammatory (hypotonic induced hemolysis and heat induced haemolysis assay) and antioxidant (DPPH andβ-Carotene) activities were evaluated observing high inflammatory inhibition by protecting membrane stability of erythrocyte in both heat (84.70 ± 0.24%) and hypotonic induced hemolysis (79.45 ± 0.12%). A remarkable hemostatic effect was also established by measuring the coagulation time (15.95 ± 1.05 s at a dose of 1 mg/mL) of decalcified plasma related to its phytochemical content. It is the first report on combined chemical components and biological evaluation of this specific plant.

β-lactams and colistin resistance in Enterobacterales is a global public health issue. In this study we aimed to investigate the occurrence and genetic determinants of Extended-Spectrum β-lactamases, carbapenemases and mcr-encoding-genes in Enterobacterales isolates recovered from the migratory bird species Ciconia ciconia in an Algerian city. A total of 62 faecal samples from white storks were collected. Samples were then subjected to selective isolation of β-lactams and colistin-resistant-Enterobacterales. The representative colonies were identified using Matrix-Assisted Laser Desorption-Ionisation Time-of-Flight Mass Spectrometry. Susceptibility testing was performed using the disk-diffusion method. ESBL, carbapenemases, and colistin resistance determinants were searched for by PCR and sequencing. The clonality relationships of the obtained isolates were investigated by multilocus sequence typing assays. Mating experiments were carried out to evaluate the transferability of the carbapenemase and mcr-genes. Forty-two isolates were identified as follows: Escherichia coli (n = 33), Klebsiella pneumoniae (n = 4), Proteus mirabilis (n = 4) and Citrobacter freundii (n = 1). Molecular analysis showed that twelve isolates carried the bla_ESBL genes alone, fifteen E. coli isolates were positive for the bla_OXA-48 gene, six isolates were NDM-5-carriers (two P. mirabilis, two K. pneumoniae and two E. coli) and eight E. coli strains were positive for the mcr-1 gene. MLST results showed a high clonal diversity, where NDM-5-producing strains were assigned to two sequence types (ST167 for E. coli and ST198 for K. pneumoniae), whereas the mcr-1 positive E. coli isolates belonged to ST58, ST224, ST453, ST1286, ST2973, ST5542, ST9815 and the international high-risk resistant lineage ST101. To the best of our knowledge, this is the first report of bla_NDM-5 gene in white storks and also the first describing the mcr-1 gene in white storks in Algeria. This study underlines the important role of migratory white storks as carriers of high-level drug-resistant bacteria, allowing their possible implication as indicators and sentinels for antimicrobial resistance surveillance.

This paper presents the development of a multi-coil eddy current (EC) sensor that uses an axial rotating magnetic field for the measurement of electrical resistance to determine the electrical conductivity tensor of stratified carbon fiber reinforced polymer (CFRP) materials. The sensor consists of an identical planar racetrack multi-coil, excited by two-phase sinusoidal current sources that are 90° apart in phase to generate an axial rotating magnetic field and eliminate the need for mechanical rotation. Each sensor's coil's resistance variation is measured using a developed experimental prototype unit and computed using a 3D finite element method (FEM) based on the (A, V–A) formulation. The inverse problem technique that minimizes the difference between the calculated and measured resistances is then used to identify the electrical conductivity tensor components using the particle swarm optimization (PSO) algorithm. The comparison between the computed resistances and the measured ones shows an excellent concordance.

Strengthening production plants and process control functions contribute to a global improvement of manufacturing systems because of their cross-functional characteristics in the industry. Companies established various innovative and operational strategies; there is increasing competitiveness among them and increasing companies’ value. Machine learning (ML) techniques become an intelligent enticing option to address industrial issues in the current manufacturing sector since the emergence of Industry 4.0 and the extensive integration of paradigms such as big data and high computational power. Implementing a system able to identify faults early to avoid critical situations in the production line and its environment is crucial. Therefore, powerful machine learning algorithms are performed for fault diagnosis, real-time data classification, and predicting the state of functioning of the production line. Random forests proved to be a better classifier with an accuracy of 97%, compared to the SVM model’s accuracy which is 94.18%. However, the K-NN model’s accuracy is about 93.83%. An accuracy of 80.25% is achieved by the logistic regression model. About 83.73% is obtained by the decision tree’s model. The excellent experimental results reached on the random forest model demonstrated the merits of this implementation in the production performance, ensuring predictive maintenance and avoiding wasting energy.

In the context of the industrial process safety, the domino effect has become a topical issue for scientists and managers of companies given the diversity of factors that contributed to the aggravation of this phenomenon such as; proximity to industrial facilities, transport networks, development of industrial complexes, storage of hazardous substances and population growth. The purpose of this article is the MICDE method (Method of Identification and Characterization of Domino Effects) application on industrial zone of LPG storage in SONATRACH-Algeria Group for analyzes the domino effects caused by a major industrial accident.

Our study is adopted on the MICDE method which constitutes an aid in the integration of the domino effects problem in hazard studies and safety studies. In our application, it aims to formalize the points relating to the domino effects due to the BLEVE (Boiling Liquid Expanding Vapor Explosion) phenomenon of an LPG storage sphere.

The results obtained show that the hazardous equipment in the vicinity is seriously affected by the thermal and overpressure effect of the main accident, and may be seats in a new accident. The MICDE method is a promising method can be applied in several fields since it studies the phenomenon. This method facilitates decision-making in the prevention of domino effects for the sustainability facilities

Sebkha soils are defined as problem soils located in arid, semi-arid, and coastal areas. Generally, they are fine soil, composed of silt, sand, and clay, which are cemented by different salts (e.g., halite, gypsum, and calcite). In nature, sebkha saline soils are exposed to different drying and wetting (D-W) cycles. However, these cycles have a significant effect on the mechanical behavior of these soils. This study aims to characterize the chemical, mineralogical, and geotechnical properties of sebkha soil using an experimental approach. We focus on the effects of D-W cycles on the unconfined compressive strength (UCS) and salinity of sebkha soils from Ain M'Lila, Algeria. In addition, these D-W cycles were applied to the samples dried in the open air to achieve the targeted water content (water content values of 7%, 11.4%, and 13%). The results obtained show that the UCS increases with decrease in water content and decreases with an increase in the number of D-W cycles. In addition, these cycles affect the salinity of the sebkha soil. Indeed, a significant decrease in soil salinity was recorded with an increase in the number of D-W cycles. Finally, a relationship was found between the salinity of the soil and UCS. The latter decreases with a decrease in soil salinity; this relationship becomes very significant for low water content values of 7% or less.

Antibiotic-resistant bacteria can leave hospitals and therefore contaminate the environment and, most likely, humans and animals, through different routes, among which wastewater discharge is of great importance. This study aims to assess the possible role of hospital sewage as reservoir and dissemination pathway of carbapenem-resistant Gram-negative bacilli (GNB). Carbapenem-resistant GNB were selectively isolated from wastewater collected from a public hospital in Batna, Algeria. Species identification was carried out using matrix-assisted laser desorption and ionization time-of-flight mass spectrometry, and antibiotic susceptibility was evaluated by the disc diffusion method. β-Lactamase production was investigated phenotypically using the double-disk synergy assay and the modified CarbaNP test, then the molecular mechanisms of β-lactam-resistance were studied by PCR and sequencing. Ten Enterobacteriaceae and 14 glucose-nonfermenting GNB isolates were obtained. All Enterobacteriaceae isolates were positive for OXA-48 and TEM-1D β-lactamases, where seven of them coproduced an extended-spectrum β-lactamase. VIM-2 carbapenemase was detected in six glucose-nonfermenting GNB isolates. However, three Pseudomonas aeruginosa, one Comamonas jiangduensis and one Acinetobacter baumannii isolates were positive for VIM-4 variant. In addition, NDM-1 enzyme was detected in four A. baumannii isolates. Our findings highlight the potential impact of hospital wastewater in the spread of drug resistance mechanisms outside of hospitals.