According to a United Nations report, the proportion of the urban population living in informal houses worldwide had reached 23.5% in 2018, which means over 1 billion people have been living in slums, and an estimated 3 billion people will be requiring affordable housing by 2030. Slums are often linked to developing countries, where weak governance and misled socio-economic choices aggravate the situation and lead to continual conflict with the authorities. This research aims to model this conflict through Game Theory and shed the light on the different parameters that influence the decision-making process and finally propose a management model to limit the spread of this phenomenon as much as possible. This model will be applied in the city of Hassi Bahbah using ABM, the results of the game modeling allowed us to extract the delta threshold which will allow decision-makers to know when they have to make decisions. Our study aims to offer decision-makers a tool based on our model, allowing them to better manage and thus monitor the evolution of informal houses. The authors hope that the findings could provide means and insights for policies and strategic directions in land uses and planning systems.

Sedimentation of dam reservoirs is a complex problem with several dimensions, including filling rates and characteristics of accumulated sediments. Sediment supply from river basins is particularly high in this region because of its semi-arid climate and especially because of poor vegetation protection. The amount of silt accumulated annually since the construction of this dam is estimated at 330000 m³. This silt accumulation strongly limits its storage capacity and consequently its operating duration. The consequences of this serious problem have been catastrophic, including a considerable reduction of 43–84% of the storage capacity of the dams and a clear degradation of water quality that can cause the degradation of the ecosystem functioning and can lead to irreversible changes. The silt present in abundance in the Algerian dams can, thus, constitute a potential resource to be judiciously exploited towards the increase of the performances of the construction materials. The extraction of sediments accumulated in the dam reservoir is, therefore, imperative. These sediments have a great geotechnical value. The objective of this study is to assess the feasibility of the recovery of mud by studying the knowledge of the sediments of the dam of Koudiat Medouar. The results of the tests carried out in laboratory allowed us to identify the various sediments from a physical and geotechnical point of view. These materials must of course meet certain rigorous criteria in terms of mechanical strength and durability and environmental impact. The experimental approach that we adopted allowed us to determine the characteristics of the materials necessary for the realization of compressed earth bricks (BTC) in conformity with the recommendations of the technical guides of construction.

In this paper a H∞ control technique addresses the voltage regulation in distributed generation (DG) system connected to power converter under harmonic disturbances. The DG control technique combines a discrete sliding mode control (DSMC) in the current control and a Robust Servomechanism Problem (RSP) in the voltage control. Besides, a fractional Order Proportional-Integral-Derivative (FOPID) controller synthesized with an automatic calibration of adjustable fractional weights is formulated in this work. For performance and high robustness requirements, the parameters of FOPID are optimized through solving a multiobjective optimization problematic based on the automatic calibration of the weighted-mixed sensitivity problem. Furthermore, for ensuring an adequate calibration of parameters, the Integral of Time Weighted Absolute Error (ITAE) criterion with Genetic Algorithm (GA) are used to achieve better voltage regulation. The simulation results show that it can achieve trade-off between nominal performance (NP) and robust stability (RS) margins for the constrained uncertain plants in the large range frequencies. Also, the results validate the effectiveness of the proposed control at which both low total harmonic distortion (THD) and low tracking error.

The ongoing pandemic of COVID-19 is causing more health, economic and social issues worldwide. As of July 5, 2021, the world registered more than 184 million cases across 222 countries; more than 4 million have died from the deadly infection. The SARSCoV-2 continues spreading globally; new variants emerge randomly due to errors in the virus' gRNAs replication process. The present paper treats the new delta variant of concern, also known as B.1.617.2 lineage. The study highlights transmissibility, vaccine effectiveness, pathogenicity, and the likelihood of hospital admission related to delta variant infection based on a literature review of 10 indexed databases. The findings indicate high transmissibility of the B.1.617.2 lineage, approving it to be the dominant strain worldwide. Also, reduced vaccine effectiveness is confirmed. However, approved vaccines for emergency use remain valuable against COVID-19's delta variant. Finally, the risk of hospitalization seems to be twice in the case of delta variant infection. A combined approach of vaccination and nonpharmaceutical interventions is the leading way to contain the ongoing pandemic of COVID-19

The human color skin image database called SFA, specifically designed to assist research in the area of face recognition, constitutes a very important means particularly for the challenging task of skin detection. It has showed high performances comparing to other existing databases. SFA database provides multiple skin and non-skin samples, which in various combinations with each other allow creating new samples that could be useful and more effective. This particular aspect will be investigated, in the present paper, by creating four new representative skin samples according to the four rules of minimum, maximum, mean and median. The obtained samples will be exploited for the purpose of skin segmentation on the basis of the well-known Euclidean and Manhattan distance metrics. Thereafter, performances of the new representative skin samples versus performances of those skin samples, originally provided by SFA, will be illustrated. Simulation results in both SFA and UTD (University of Texas at Dallas) color face databases indicate that detection rates higher than 92% can be achieved with either measure.

This study highlights the significance of using AT to enhance the writing skills. Then, this accommodation would help SVI to meet their educational needs. Besides, this study shows the major barriers that hinder VI learners in writing when they lack AT devices.

The Mio-Plio-Quaternary groundwater of Mchira-Teleghma suffers from an increasing rate of salinity especially in the northwestern part. To identify the reason for the water’s salinity and its aptitude for irrigation, physico-chemical analyses of 20 water samples, which were based on the different physical and chemical parameters (electric conductivity EC, pH, Ca²⁺, Mg²⁺, Na⁺, K⁺, HCO₃⁻, Cl⁻, SO₄²⁻, NO₃⁻ and Sr²⁺), were carried out during the period of October 2015. This study showed disquieting anomalies of electric conductivity that reached the value of 4376.14 µS cm⁻¹. The statistical analyses, the multivariate statistics: the principal component analysis, Q-mode cluster analyses, Sr²⁺/Ca²⁺ ratio and water type showed that the hydrochemistry of Mchira-Teleghma groundwater is controlled by the dissolution of carbonate rocks and the leaching of evaporite processes, which proved that these anomalies of the MPQ groundwater’s salinity of Mchira-Teleghma are mainly determined by the leaching of Triassic gypsum formations process. This hydrogeochemical process generates an unsuitable quality of water based on Wilcox’s and Water Quality Index’s methods, whereas Richard’s method classifies all water samples to C3S1 and C4S1 classes as they are recommended to be used with salt-tolerant species in well-drained and leached soils.

Optical burst switching (OBS) has become one of the best and widely used optical networking techniques. It offers more efficient bandwidth usage than optical packet switching (OPS) and optical circuit switching (OCS).However, it undergoes more attacks than other techniques and the Classical security approach cannot solve its security problem. Therefore, a new security approach based on machine learning and cloud computing is proposed in this article. We used the Google Colab platform to apply Support Vector Machine (SVM) and Extreme Learning Machine (ELM)to Burst Header Packet (BHP) flooding attack on Optical Burst Switching (OBS) Network Data Set.

This paper deals with the integration of a photovoltaic energy conversion system (PVECS) into a distribution network and cater for the energy needs of buildings. The main goals of this work are the reduction of the grid dependence, minimization of the energy cost and increasing the autonomy of the building’s energy. Two stages converters are used to ensure the maximum power point tracking (MPPT) and to control the power flow. A fuzzy MPPT control is proposed to maintain the power of the Photovoltaic panel at its optimal value despite climatic condition variations and building’s load changes. The grid side inverter is controlled by hysteresis regulators to transfer the total produced energy, with the aim to partially or completely replace energy provided from the Grid. The DC link voltage is also stabilized in order to improve the energy quality. The complete PVECS system is modelled and simulated in Matlab/Simulink, the controllers used are simple to implement and the simulation results show that the building’s energy demand can be satisfied, and the energy exceed is injected into the grid. The results confirm the good effectiveness of the proposed control.

Purpose The assessment of patient safety culture (PSC) is a major priority for healthcare providers. It is often realized using quantitative approaches (questionnaires) separately from qualitative ones (patient safety culture maturity model (PSCMM)). These approaches suffer from certain major limits. Therefore, the aim of the present study is to overcome these limits and to propose a novel approach to PSC assessment. Design/methodology/approach The proposed approach consists of evaluating PSC in a set of healthcare establishments (HEs) using the HSOPSC questionnaire. After that, principal component analysis (PCA) and K-means algorithm were applied on PSC dimensional scores in order to aggregate them into macro dimensions. The latter were used to overcome the limits of PSC dimensional assessment and to propose a quantitative PSCMM. Findings PSC dimensions are grouped into three macro dimensions. Their capitalization permits their association with safety actors related to PSC promotion. Consequently, a quantitative PSC maturity matrix was proposed. Problematic PSC dimensions for the studied HEs are “Non-punitive response to error”, “Staffing”, “Communication openness”. Their PSC maturity level was found underdeveloped due to a managerial style that favors a “blame culture”. Originality/value A combined quali-quantitative assessment framework for PSC was proposed in the present study as recommended by a number of researchers but, to the best of our knowledge, few or no studies were devoted to it. The results can be projected for improvement and accreditation purposes, where different PSC stakeholders can be implicated as suggested by international standards.

Introduction: Modern approaches to Occupational Health and Safety have acknowledged the important contribution that continuous improvements to working conditions can make to the motivation of employees, their subsequent performance, and therefore to the competitiveness of the company. Despite this fact, organizational change initiatives represent a path less traveled by employees. Specialized literature has drawn on the fact that employees’ satisfaction presents both the foundation and catalyst for effective implementation of improvements to working conditions. Method: This paper conceptualizes the alignment of employees through measurement of job satisfaction and uses the Bayesian Network to assess the influence of human factors, particularly the cognitive, emotional, and behavioral aspects. Toward this aim, the Bayesian Network is evaluated through a cross-validation process, and a sensitivity analysis is then conducted for each influential dimension: emotional, cognitive, and behavioral. Results: The results reveal that these three dimensions are interrelated and have a direct influence on job satisfaction and employees’ alignment during the organization change. Further, they suggest that the best strategy for enhanced alignment and smooth conduct of organizational changes is simultaneous enhancement of the three dimensions. Practical applications: This study shows the influence of emotional, cognitive, and behavioral dimensions on job satisfaction and employees’ alignment during the organizational change. Furthermore, it elaborates the way to develop efficient and effective strategies for a successful change implementation and sustained alignment.

This paper presents a decision-making support system for situation risk assessment associated with critical alarms conditions in a gas facility. The system provides a human operator with advice on the confirmation and classification of occurred alarm. The input of the system comprises uncertain and incomplete information. In the light of uncertain and incomplete information, different uncertainties laws have been associated with the probabilistic assessment of the system loops which combine data of several sources to reach the ultimate classification. The implemented model used Observe-Orient-Decide-Act loop (OODA) combined with Bayesian networks. Results show that the system can classify the alarms system.

Purpose The increasing complexity of industrial systems is at the heart of the development of many fault diagnosis methods. The artificial neural networks (ANNs), which are part of these methods, are widely used in fault diagnosis due to their flexibility and diversification which makes them one of the most appropriate fault diagnosis methods. The purpose of this paper is to detect and locate in real time any parameter deviations that can affect the operation of the blowout preventer (BOP) system using ANNs. Design/methodology/approach The starting data are extracted from the tables of the HAZOP (HAZard and OPerability) method where the deviations of the parameters of normal BOP operating (pressure, flow, level and temperature) are associated with an initial rule base for establishing cause and effect of relationships between the causes of deviations and their consequences; these data are used as a database for the neural network. Three ANNs were used, the multi-layer perceptron network (MLPN), radial basis functions network (RBFN) and generalized regression neural networks (GRNN). These models were trained and tested, then, their comparative performances were presented. The respective performances of these models are highlighted following their application to the BOP system. Findings The performances of the models are evaluated using determination coefficient (R2), root mean square error (RMSE) and mean absolute error (MAE) statistics and time execution. The results of this study show that the RMSE, MAE and R2 values of the GRNN model are better than those corresponding to the RBFN and MLPN models. The GRNN model can be applied with better performance, to establish a diagnostic model that can detect and to identify the different causes of deviations in the parameters of the BOP system. Originality/value The performance of the trained network is found to be satisfactory for the real-time fault diagnosis. Therefore, future studies on modeling the BOP system with soft computing techniques can be concentrated on the ANNs. Consequently, with the use of these techniques, the performance of the BOP system can be ensured performing only a limited number of monitoring operations, thus saving engineering effort, time and funds.

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.

Various facilities are used in mineral processing to prepare raw material. Practically, two types of balls are used, cast balls and forged balls. They are respectively made from high chromium cast iron and forged steel and are supplied in different sizes and chemical compositions. The cast and forged balls have different microstructures and consequently display dissimilar wear behavior. The target aimed in this work is to achieve a comparative study taking into account the type of microstructure, mechanical properties, and wear behavior of these two kinds of materials. Specimens have undergone chemical, metallographic and XRD characterizations. Subsequently, these samples were subjected to hardness measurements, abrasion and friction tests in order to evaluate their wear behaviour. Tribological tests, under unlubricated environment, are carried out on both types of grinding balls in order to study the wear system. Corrosion tests are also performed on forged steel and high chromium cast iron ball samples. The obtained results reveal a large difference in terms of chemical composition and microstructural components. Chromium cast iron balls are more resistant to friction, whereas forged balls are more resistant to abrasion. Additionally, the corrosion tests reveal a narrow discrepancy in corrosion behaviour between the studied materials.

The exploitation of fossil fuels is causing global warming whose negative effects have recently been felt all over the world. Therefore, the search for new sources of energy, renewable and respectful of the environment is crucial for manufacturers. The concept of Best Available Techniques (BAT) presents an adequate solution for manufacturers, for the control, elimination or reduction of the harmful impacts of their activities on the environment. This concept, known as Integrated Pollution Prevention and Control (IPPC), was introduced and imposed from 1996 in Europe. This paper aims to introduce the possibility of transferring the IPPC approach and BAT concepts to Algeria. Therefore, the main objective is to propose some recommendations to optimize the technical and environmental performance of hybrid solar-gas systems, by treating as a case study the first hybrid solar-gas power plant SPPI (Solar Power Plant One) near Hassi R’mel in the south of Algeria. A gap analysis of the Algerian environmental policy compared to the IPPC system, and an assessment of technical and environmental performance of the “SPPI” plant in terms of regulation and BAT are developed in our study.

The assessment of Patient Safety Culture (PSC) is often conducted using a quantitative approach based on questionnaires or a qualitative one focused on the deployment of Patient Safety Culture Maturity Models (PSCMM). These two approaches suffer from a number of limitations and their resolution is only possible by exploiting the possible complementarity that exists between them. Indeed, to overcome their inherent limits, it is imperative to merge the two PSC approaches in a single approach called quali-quantitative evaluation of PSC. This article fits into this context and aims to materialise the merger of PSC approaches through their co-deployment. This will make it possible to capitalise the scores of the HSOPSC dimensions in terms of PSC maturity levels.

Improvements to health and safety at work constantly involve organizational changes (OCs). However, the OC initiatives often fail at achieving their intended goals despite efforts to draw knowledge from various disciplines, such as sociology, psychology and information sciences, to guide the change implementation. This paper proposes a temporality approach to manage the resistance during an OC project based on the capitalization of the actors’ behaviors (i.e. alignment/resistance) for successful OC implementation.Employees in an industrial company (N = 186) undergoing an OC answered a questionnaire survey. The statistical analysis approach was used to measure the influence of the constructs of the proposed temporality capitalization approach on the OC conduct.Results indicate that the considered constructs have positive and significant correlations with OC development. It has also been found that the employees’ alignment is highly correlated with the opportunities they might gain from the OC.The proposed temporality capitalization approach shows that providing the employees with clear objectives is not sufficient to support the change, and it is suggested that the change management has to move a step further and seek to target the perspectives of the employees to energize them around the OC and maximize their alignment.In this paper, change management is approached through the temporality capitalization that confirms the importance of monitoring the change development through the alignment. In other terms, the curve of the adaptation of the change receivers matters and should attract more attention rather than the change implementation speed.

يهدف البحث الى التعرف على اثر تطبيق تقنية الواقع المعزز في تدريس مادة الثقافة البدنية لطلبة السنة الثانية ليسانس، في جامعة باتنة 2 خلال الموسم الجامعي الحالي2020/2021، و تم استخدام المنهج الشبه التجريبي. على عينة تتكون من 20طالب، مقسمة الى مجموعتين، وتوصلنا الى ان هناك فروق بين نتائج الطلبة في الاختبارين النظري والتطبيقي وان لاستخدام تقنية الواقع المعزز بواسطة تطبيقEyeJack أثر كبير على اكتساب الطلبة في مادة الثقافة البدنية على المستويين النظري والتطبيقي.

أصبحنا نرى في الآونة الاخيرة ان الكثير من الاشخاص اصبحت تنموا لديهم الرغبة في حرق الدهون الزائدة في الجسم والتي تعود الى عديد الاسباب وتختلف من شخص الى اخر ومن مجتمع الى اخر تبعا الى نمط وطريقة المعيشة. لكن الكثير منهم يصطدم بعلامة استفهام كبيرة هل الحل يكمن في تمارين الكارديو ام يكمن في الرياضات الخاصة برفع الاثقال والأوزان في صورة رياضة كمال الاجسام؟ لذا أردنا ان نقوم بهذه الدراسة الاستقصائية للتوصل الى أكثر معلومات حول هذا الموضوع كون هاتين الطريقتين هما الاكثر شعبية بين الممارسين الراغبين في الحصول على الجسم المثالي والخالي من الدهون الزائدة.