Salt resistance studies have, unfortunately, mainly been focused on conventional crops, with very few studies being conducted on the potential of available halophytes as new crops in the future. Portulaca oleracea L. has been listed as one of the most used medicinal plants by the World Health Organization as an edible halophyte. It is a fast-growing herbaceous annual with high nutritional relevance. The present work was designed to determine the effect of six soluble salts (NaCl, Na2SO4, KCl, CaCl2, CaCO3, and MgCl2) on germination of P. oleracea seeds. The effect of salinity was tested on final germination percentage (FGP%), and germination tolerance index (GTI%) using five concentrations (0, 200, 300, 400, and 600 mM) of each salt. In addition, laboratory experiments were conducted to assess the effects of salinity on germination recovery from high saline conditions (600 mM). Salinity level and salt composition significantly influenced germination attributes. P. oleracea seeds were non-dormant, exhibited approximately 100% germination in distilled water. Both FGP and GTI gradually decreased with increasing salinity. This study showed that seeds of P. oleracea can germinate under 300 mM in all tested salts. The salts causing germination inhibition exhibited specificity, with an increasing trend observed in the following sequence: MgCl2 > Na2SO4 > NaCl > KCl > CaCl2 > CaCO3. Transferring ungerminated seeds from 600 mM to distilled water recovered their germination ability. Based on these results, we can conclude that P. oleracea is a high salt-tolerant species that can tolerate a variety of salts found in soil. Therefore, P. oleracea may be considered a promising species for improving ecological balance in saline soils.

This study aims to update the list of Nitidulidae species observed on date palms in Algeria (Ziban region), their spatial dynamics according to the development stages (larva, pupa, adult), and the effectiveness of the bagging operation. In 2020, we sampled and examined 1800 dates of the Deglet Nour variety from three palm groves managed with different protection modes: yellow bagging, white bagging, and no bagging. The results obtained mention the presence of nine species of Nitidulidae with five species reported for the first time on dates in Algeria. The highest relative abundance (RA) of Nitidulidae beetles was noted in the southern (28%) direction. However, the variation of infestation rate (IR) according to the direction was not very accentuated. The GLM analysis showed that, except for the adult stage, the direction presented a highly significant effect on the RA variation of the total Nitudilidae, the larva and pupa stages (p < 0.0001), but there was no significant effect of direction on the IR in all studied cases. The highest RA of total Nitidulidae was found on the white plastic-protected dates (RA = 42%), the IR of the total Nitidulidae was higher on dates protected by yellow plastic (IR = 38%). The unprotected dates recorded the lowest RA and IR for all studied cases and the effect of bagging type on the RA variation of Nitidulidae, in all studied cases, was statistically highly significant (p < 0.0001). This effect on the IR was very highly significant only for total Nitudilidae, larvae, and adults (p < 0.0001). So, the southern direction presents the best conditions for sheltering the largest numbers of Nitidulidae. The latter also has a marked preference for bunches covered by plastic bags rather than for those left uncovered. This implies the ineffectiveness of the operation of protecting dates with plastic bags, especially the yellow-coloured ones.

Wetlands are present within intricate ecological settings, exhibiting dynamic changes over time and across different areas with regard to their functional and structural diversity. Several approaches have been introduced for ecosystem analysis and management since 1990s, where Driver – Pressure – State – Impact – Response (DPSIR) framework is one of the widely used approaches for assessing and managing environmental problems. In this study, we proposed a DPSIR framework as a model in the Sebkhates of Aures wetland complex (SAWC, Northeast of Algeria), in order to create a regional wetland observatory to deliver ecosystem services within current state of changes resulted from socioeconomic drivers. DPSIR facilitates the identification of essential indicators to detect threats to the Sebkahtes of Aures wetlands complex (SAWC), influencing policymakers to enhance the protection and management of these wetlands. In line with the established DPSIR framework. This same approach and methodology could be applied to the other 15 wetlands complexes known in Algeria, culminating in the creation of a national wetland observatory. Furthermore, DPSIR can be employed as an analytical tool for policy making in the context of sustainable management of wetland ecosystems and can serve as a model in the establishment and development of various observatory programs in Algeria.

Wetlands are present within intricate ecological settings, exhibiting dynamic changes over time and across different areas with regard to their functional and structural diversity. Several approaches have been introduced for ecosystem analysis and management since 1990s, where Driver – Pressure – State – Impact – Response (DPSIR) framework is one of the widely used approaches for assessing and managing environmental problems. In this study, we proposed a DPSIR framework as a model in the Sebkhates of Aures wetland complex (SAWC, Northeast of Algeria), in order to create a regional wetland observatory to deliver ecosystem services within current state of changes resulted from socioeconomic drivers. DPSIR facilitates the identification of essential indicators to detect threats to the Sebkahtes of Aures wetlands complex (SAWC), influencing policymakers to enhance the protection and management of these wetlands. In line with the established DPSIR framework. This same approach and methodology could be applied to the other 15 wetlands complexes known in Algeria, culminating in the creation of a national wetland observatory. Furthermore, DPSIR can be employed as an analytical tool for policy making in the context of sustainable management of wetland ecosystems and can serve as a model in the establishment and development of various observatory programs in Algeria.

Le présent article met en jeu un objectif bien précis, celui de nous interroger sur le rôle des questions argumentatives et de cerner leurs relations avec l’évolution argumentative des thèmes mis en délibération onusienne. Le corpus d’analyse est un recueil de comptes rendus analytiques « textes officiels » qui ont été récoltés sur le site officiel des Nations Unies. Notre travail s’inscrit dans la conception de l’interaction argumentative telle qu’elle a été définie par Christian Plantin. Ce modèle s’accorde parfaitement avec une analyse du dialogue onusien. Dans ce travail nous visons à présenter le statut argumentatif et interactionnel de la question argumentative. This article brings in a very precise objective that allows us to interrogate the role of argumentative questions, and to identify their relations with the argumentative evolution of themes provided in the United Nations’ deliberation. The corpus of analysis is a collection of analytic reports “official texts”, which were collected from the UN’s official website. Our work falls under to the conception of argumentative interaction such as the one defined by Christian Plantin. This model corresponds perfectly with the UN’s dialogue analysis. In this work, we aim to present the argumentative and interactional statuses of argumentative questions.

An effective Food Traceability System (FTS) in a Food Supply Chain (FSC) should adequately provide all necessary information to the consumer(s), meet the requirements of the relevant agencies, and improve food safety as well as consumer confidence. New information and communication technologies are rapidly advancing, especially after the emergence of the Internet of Things (IoT). Consequently, new food traceability systems have become mainly based on IoT. Many studies have been conducted on food traceability. They mainly focused on the practical implementation and theoretical concepts. Accordingly, various definitions, technologies, and principles have been proposed. The “traceability” concept has been defined in several ways and each new definition has tried to generalize its previous ones. Nevertheless, no standard definition has been reached. Furthermore, the architecture of IoT-based food traceability systems has not yet been standardized. Similarly, used technologies in this field have not been yet well classified. This article presents an analysis of the existing definitions of food traceability, and thus proposes a new one that aims to be simpler, general, and encompassing than the previous ones. We also propose, through this article, a new architecture for IoT-based food traceability systems as well as a new classification of technologies used in this context. We do not miss discussing the applications of different technologies and future trends in the field of IoT-based food traceability systems. Mainly, an FTS can make use of three types of technologies: Identification and Monitoring Technologies (IMT), Communication Technologies (CT), and Data Management Technologies (DMT). Improving a food traceability system requires the use of the best new technologies. There is a variety of promising technologies today to enhance FTS, such as fifth-generation (5G) mobile communication systems and distributed ledger technology (DLT).

In this paper, we present a novel hybrid meta-heuristic by enhancing the Basic Bees Algorithm through the integration of a local search method namely Simulated Annealing and Variable Neighbourhood Search like algorithm. The resulted hybrid bees algorithm (BASA) is used to solve the Single Machine Scheduling Problem with Early/Tardy jobs, where the generated outcomes are compared against the Basic Bees Algorithm (BA), and against some stat-of-the-art meta-heuristics. Computational results reveal that our proposed framework outperforms the Basic Bees Algorithm, and demonstrates a competitive performance compared with some algorithms extracted from the literature.

The aim of this paper is to propose a new family of codes.  We define this family over the ring R=∑4s=0vs5A4R=∑s=04v5sA4, with v55=v5v55=v5.  We derive its properties, a generator matrix and Gray images.  This new family of codes is illustrated by three applications.

From the 1990s, urban policy in Algeria underwent significant upheavals, including authoritarian management, which was replaced by participatory management. Following the example of Algerian cities, the city of Batna adheres with this new vision, hence the implementation of a partnership program that involves various stakeholders including the citizen. The latter is present within multiple associations. The objective of this work is to highlight the activism of neighborhood associations as a representative element of civil society and their determining role in the management of different situations. To report on this issue, a field survey was conducted in the form of semi-directive interviews addressed to the three local actors: associations, citizens and elected officials.

Introduction. Budget constraints in a world ravenous for electrical power have led utility companies to operate generating stations with full power and sometimes at the limit of stability. In such drastic conditions the occurrence of any contingency or disturbance may lead to a critical situation starting with poorly damped oscillations followed by loss of synchronism and power system instability. In the past decades, the utilization of supplementary excitation control signals for improving power system stability has received much attention. Power system stabilizers (PSS) are used to generate supplementary control signals for the excitation system in order to damp low-frequency oscillations caused by load disturbances or short-circuit faults.

Problem. Adaptive power system stabilizers have been proposed to adequately deal with a wide range of operating conditions, but they suffer from the major drawback of requiring parameter model identification, state observation and on-line feedback gain computation. Power systems are nonlinear systems, with configurations and parameters that fluctuate with time that which require a fully nonlinear model and an adaptive control scheme for a practical operating environment. A new nonlinear adaptive fuzzy approach based on synergetic control theory which has been developed for nonlinear power system stabilizers to overcome above mentioned problems.

Aim. Synergetic control theory has been successfully applied in the design of power system stabilizers is a most promising robust control technique relying on the same principle of invariance found in sliding mode control, but without its chattering drawback. In most of its applications, synergetic control law was designed based on an asymptotic stability analysis and the system trajectories evolve to a specified attractor reaching the equilibrium in an infinite time. In this paper an indirect finite time adaptive fuzzy synergetic power system stabilizer for damping local and inter-area modes of oscillations for power systems is presented. 

Methodology. The proposed controller design is based on an adaptive fuzzy control combining a synergetic control theory with a finite-time attractor and Lyapunov synthesis. Enhancing existing adaptive fuzzy synergetic power system stabilizer, where fuzzy systems are used to approximate unknown system dynamics and robust synergetic control for only providing asymptotic stability of the closed-loop system, the proposed technique procures finite time convergence property in the derivation of the continuous synergetic control law. Analytical proofs for finite time convergence are presented confirming that the proposed adaptive scheme can guarantee that system signals are bounded and finite time stability obtained. 

Results. The performance of the proposed stabilizer is evaluated for a single machine infinite bus system and for a multi machine power system under different type of disturbances. Simulation results are compared to those obtained with a conventional adaptive fuzzy synergetic controller.

Introduction. Constant increases in power consumption by both industrial and individual users may cause depletion of fossil fuels and environmental pollution, and hence there is a growing interest in clean and renewable energy resources. Photovoltaic power generation systems are playing an important role as a clean power electricity source in meeting future electricity demands.

 Problem. All photovoltaic systems have two problems; the first one being the very low electric-power generation efficiency, especially under low-irradiation states; the second resides in the interdependence of the amount of the electric power generated by solar arrays and the ever changing weather conditions. Load mismatch can occur under these weather varying conditions such that maximum power is not extracted and delivered to the load. This issue constitutes the so-called maximum power point tracking problem. 

Aim. Many methods have been developed to determine the maximum power point under all conditions. There are various methods, in most of them based on the well-known principle of perturb and observe. In this method, the operating point oscillates at a certain amplitude, no matter whether the maximum power point is reached or not. That is, this oscillation remains even in the steady state after reaching the maximum power point, which leads to power loss. This is an essential drawback of the previous method. In this paper, a cascade sliding mode maximum power point tracking control for a photovoltaic system is proposed to overcome above mentioned problems. 

Methodology. The photovoltaic system is mainly composed of a solar array, DC/DC boost converter, cascade sliding mode controller, and an output load. Two sliding mode control design strategies are joined to construct the proposed controller. The primary sliding mode algorithm is designed for maximum power point searching, i.e., to track the output reference voltage of the solar array. This voltage is used to manipulate the setpoint of the secondary sliding mode controller, which is used via the DC-DC boost converter to achieve maximum power output. 

Results. This novel approach provides a good transient response, a low tracking error and a very fast reaction against the solar radiation and photovoltaic cell temperature variations. The simulation results demonstrate the effectiveness of the proposed approach in the presence of environmental disturbances.

This paper deals with the design and optimization of a 1.2 MVA medium-voltage (MV) power electronic traction transformer (PETT) for an AC 15 kV/16.7 Hz railway grid, in which a simple two-stage multi-cell PETT topology consisting of a bidirectional 170 kW, 2.5 kV AC rms to 6 kV DC power factor corrected (PFC) converter stage followed by a bidirectional isolated 46 kHz, 6 kV to 1.5 kV series resonant DC/DC converter for each cell is presented. This paper presents a methodology that maximizes the converter"s efficiency and minimizes the converter"s size and weight. Accordingly, the first stage employs 10 kV SiC MOSFETs based on the integrated Triangular Current Mode (iTCM). The second stage uses 10 kV SiC MOSFETs on the MV-side, 3.3 kV SiC MOSFETs on the LV-side, and a medium frequency (MF) MV transformer operating at 46 kHz. MF transformers offer a way to reduce weight and improve energy efficiency, particularly in electric multiple-unit applications. The MF MV transformer requires power electronic converters, which invert and rectify the voltages and currents at the desired operating frequency. The development of high voltage SiC MOSFETs, which can be used instead of Si IGBTs in PETT topologies, increases the operating frequency without reducing the converter"s efficiency. The designed MV PETT achieves 98.95% efficiency and 0.76 kVA/kg power density.

This work proposes a new modeling framework based on combining graded band-gap (GBG) engineering and metaheuristic optimization to improve the Cd-Free ZnMgO/CIGS solar cell performances. Analytical and numerical calculations are carried out to assess the influence of band-gap profiles of both buffer and active layers on the electronic and optical properties of the studied solar cell. This investigation shows a great improvement of solar cell efficiency by increasing the optoelectronic figures of merit through tuning and optimizing the band-gap profiles and the conduction band offset at the ZnMgO/CIGS interface. Moreover, metaheuristic-based optimization models are developed to optimize the GBG profiles and enhance the optical and electrical performances of the solar cell. In this context, we recorded very satisfactory results, where the optimized design with GBG paradigm offers a high efficiency of 31.88% compared to 23.35% provided by the conventional CdS/CIGS solar cell. Therefore, this study provides a new strategy in enhancing the efficiency of thin-film solar cells by exploiting the graded band-gap engineering combined with metaheuristic optimization approach.

Iris texture is one of the most secure biometric characteristics used for person recognition, where the most significant step in the iris identification process is effective features extraction. Deep Convolutional Neural network models have been achieved massive success in the features extraction field in recent years, but several of these models have tens to hundreds of millions of parameters, which affect the computational time and resources. A lot of systems proposed in the iris recognition field extract features from normalized iris images after applying many pre-processing steps. These steps affect the quality and computational efficiency of these systems; also, occlusion, reflections, blur, and illumination variation affect the quality of features extracted. This paper proposed a new robust approach for iris recognition that locates the iris region based on the YOLOv4-tiny, then it extracts features without using iris images’ pre-processing, which is a delicate task. In addition, we have proposed an effective model that accelerated the feature extraction process by reducing the architecture of the Inception-v3 model. The obtained results on four benchmark datasets validate the robustness of our approach, where we achieved average accuracy rates of 99.91%, 99.60%, 99.91%, and 99.19% on the IITD, CASIA-Iris-V1, CASIA-Iris-Interval, and CASIA-Iris-Thousand datasets, respectively.

Thisarticleconcernstheinverse problem of the recoveryof unknown potential coefficient for the Schrödinger equation, in a bounded domain of Rn with non-homogeneous Neumann boundary condition from a time-dependent Dirich let boundary measurement. We prove uniqueness and Lipschitz stability for this inverse problem under certain convexity hypothesis on the geometry of the spatial domain and under weak regularity requirements on the data. The proof is based on aCarleman estimate in [12] for Schrödinger equations and its resulting implication, a continuous observability inequality. Mathematics Subject Classification. 35R30, 35Q40, 49K20.

This research uses the stability radius approach to investigate the robust stability of an infinite-dimensional linear discrete-time system subjected to stochastic perturbations. First, we characterize the stability radius in terms of a Lyapunov equation. These characterizations improve a computational formula for calculating the stability radius. The second goal is to study how state feedback can maximize the stability radius. We characterize the maximum attainable stability radius using an infinite-dimensional discrete-time Riccati equation. Examples are provided to demonstrate the achieved outcomes.

Most road crashes at work are caused by Driver Behavioral Drift (DBD). This DBD has become a recurring issue on congested road sections. In this context, this study proposes a method called (MASOCU-DBD) which allows to analyze this DBD problem in two steps: assessment of the dynamics of DBD occurrence using a model called BM-NSA and analysis of DCC using a Cost-Benefit Analysis (CBA) weighted by the Analysis Hierarchical Process (AHP). The application of the MASOCU-DBD on a road section of an Algerian city’s entry highlighted the problem of the DBD in terms of its occurrence and uselessness in the studied section. The merit of the proposed method is that it uses multi-criteria analysis tools (AHP and CBA) as well as a mathematical model (BM-NSA) to analyze professional drivers’ behavioral deviations.

Liquefied petroleum gas (LPG) storage fires and explosions occur due to uncontrolled gas leaks and the gradual breakdown of associated safety barriers. By installing an effective safety barrier, these accidents can be greatly reduced. However, this study assesses the probability of failure of emergency safety barriers (ESBs) to help decision makers understand how they can support decisions to reduce the risks associated with LPG storage. In this context, an extension of the event tree analysis is proposed named emergency event tree analysis (EETA). The aim of this paper is to develop an integrated approach that uses interval type-2 fuzzy sets and Analytic Hierarchy Process (AHP) method and emergency event tree analysis to handle uncertainty in the failure probability assessment of emergency safety barriers (ESBs). In addition, a case study on the failure probability assessment of the emergency safety barriers of the LPG plant in Algeria based on the proposed methodology is provided and carried out to illustrate its effectiveness and feasibility. The results demonstrated the ability of interval type-2 fuzzy sets and the AHP method to provide highly reliable results and to evaluate the failure probability of emergency safety barriers in emergencies situations. However, the classical event tree analysis (CETA) does not take into account the possibility of assessing the emergency consequences of different accident scenarios. Consequently, it only allows you to estimate the occurrence probability of accident scenarios. The results of this study show that the value of the probability of failure of the emergency safety barriers can be used to estimate the probability of occurrence of emergency consequences under different accident scenarios, improved the reliability and help prioritize emergency improvement measures. The study provides scientific and operational references for analyzing emergency consequences of the various accident scenarios in all fields such as petrochemical, maritime industry, and health occupational.

Industrial systems are becoming more sophisticated, and their failure can result in significant losses for the company in terms of production loss, maintenance costs, fines, image loss, etc. Conventional approaches to modeling and evaluating the failure mechanisms of these systems do not consider certain important aspects, such as the interdependencies between failure modes (FMs) with information and data containing uncertainties as they are generally collected from experts’ judgments. These restrictions may lead to improper decision-making. The use of more advanced techniques to model and assess the interdependencies among components’ failures under uncertainties seems to be more than necessary to overcome these deficiencies. It is in this context that the proposed approach fits. It consists of proposing a hybrid multicriteria decision-aking (MCDM) approach that combines several techniques for a better selection of maintenance strategies. Using the failure mode and effects analysis (FMEA) technique, the potential FMs of components, along with their causes and effects, are identified. The relative importance (or weight) of these FMs is determined using the fuzzy simple additive weighing (FSAW) method based on how they affect the system’s goals. The causal relationships between FMs and their final weights are determined by the fuzzy cognitive maps (FCM) method and the nonlinear Hebbian learning and differential evolution (NHL-DE) algorithm. Finally, based on the final FM weights provided by the FCM, the simple additive weighing (SAW) method is used to select the optimal maintenance strategies. The results of applying the proposed approach to an operating compressor lubrication and sealing oil system demonstrate its importance and usefulness in assisting system operators to efficiently allocate the optimal maintenance strategies, considering the strong correlation between FMs and their effects on system performance while accounting for the uncertainties associated with experts’ judgments. These correlation effects have led to changes in the assigned weights of the selected FMs. Specifically, the FM related to the low output of the lube/seal oil pump, which was initially assigned a lower priority, and with the correlation effects has become the first critical FM. This shift in prioritization emphasizes the need to address this particular FM promptly. By focusing on addressing these high-priority FMs, maintenance efforts can be optimized to prevent or mitigate more severe consequences. Among the various maintenance strategies evaluated, it was determined that the combination of condition-based maintenance (CBM) and precision maintenance (PrM) yields the most favorable outcome in terms of mitigating the impact of accidental failures and undesired events on the selected system.

Purpose This study aims to improve the reliability of emergency safety barriers by using the subjective safety analysis based on evidential reasoning theory in order to develop on a framework for optimizing the reliability of emergency safety barriers. Design/methodology/approach The emergency event tree analysis is combined with an interval type-2 fuzzy-set and analytic hierarchy process (AHP) method. In order to the quantitative data is not available, this study based on interval type2 fuzzy set theory, trapezoidal fuzzy numbers describe the expert’s imprecise uncertainty about the fuzzy failure probability of emergency safety barriers related to the liquefied petroleum gas storage prevent. Fuzzy fault tree analysis and fuzzy ordered weighted average aggregation are used to address uncertainties in emergency safety barrier reliability assessment. In addition, a critical analysis and some corrective actions are suggested to identify weak points in emergency safety barriers. Therefore, a framework decisions are proposed to optimize and improve safety barrier reliability. Decision-making in this framework uses evidential reasoning theory to identify corrective actions that can optimize reliability based on subjective safety analysis. Findings A real case study of a liquefied petroleum gas storage in Algeria is presented to demonstrate the effectiveness of the proposed methodology. The results show that the proposed methodology provides the possibility to evaluate the values of the fuzzy failure probability of emergency safety barriers. In addition, the fuzzy failure probabilities using the fuzzy type-2 AHP method are the most reliable and accurate. As a result, the improved fault tree analysis can estimate uncertain expert opinion weights, identify and evaluate failure probability values for critical basic event. Therefore, suggestions for corrective measures to reduce the failure probability of the fire-fighting system are provided. The obtained results show that of the ten proposed corrective actions, the corrective action “use of periodic maintenance tests” prioritizes reliability, optimization and improvement of safety procedures. Research limitations/implications This study helps to determine the safest and most reliable corrective measures to improve the reliability of safety barriers. In addition, it also helps to protect people inside and outside the company from all kinds of major industrial accidents. Among the limitations of this study is that the cost of corrective actions is not taken into account. Originality/value Our contribution is to propose an integrated approach that uses interval type-2 fuzzy sets and AHP method and emergency event tree analysis to handle uncertainty in the failure probability assessment of emergency safety barriers. In addition, the integration of fault tree analysis and fuzzy ordered averaging aggregation helps to improve the reliability of the fire-fighting system and optimize the corrective actions that can improve the safety practices in liquefied petroleum gas storage tanks.