Networking continues to increase day by day to invest increasingly our daily, creating huge volume of various and precise data: it is not easy to collect content, especially in crisis times. We focus on Smart Education proposed as primary tool of a hybrid of Deep Convolutional Neural Networks (CNN)-Long Short-Term Memory (LSTM)-based model to retrieving content efficiently: CNN is used to extract meaningful features from multiple sources, enabling to have qualitative and sure information, notably with an efficient fake news security, and LSTM is used to maintain long-term dependencies in the extracted features with recurrent connections. This model has been compared to previous approaches to the performance of a publicly available dataset to demonstrate its highly satisfactory performance. This new approach makes it possible to integrate artificial intelligence technologies, deep learning, social media and detecting or avoiding fake news into the crisis management model. It is based on an extension of our previous approach, namely disaster management based on short-term memory and education: this experience constitutes a background for this model. It combines representation training with awareness and education, while retrieving pattern information by combining various search results from multiple sources. We have extended it to improve our disaster management model and evaluate it in the case of Covid-19 while obtaining promising results, through past programs and experience that have shown overwhelmingly positive effects of education for vulnerability reduction and disaster risk management, in the pusuit of Environmental Sustainability.
The electrical conductivity of Ca-doped Co 1-xO single crystals was measured as a function of oxygen partial pressure, over the temperature range 1273–1673 K. The results were analyzed using Seebeck coefficient measurements, microstructural characterizations, EELS and X-ray diffraction experiments. From this set of results, we have shown that the influence of calcium on the thermodynamic and transport properties of cobaltous oxide is due to the reducing behavior of these solute cations, leading to both the shift of the Co/CoO phase boundary to higher PO2 and the formation of singly ionized cobalt cations (Co⁺) in the stability range of CoO.
The primary concern of an air traffic controller is to ensure the safety and fluidity of ever-increasing air traffic. This requires effective training through practical work supervised by instructors. Based on certain rules called separation rules, the trainee must find a solution to a traffic configuration defined by flight plans (FPL) initially containing a number of conflicts. This solution will then be compared to the one proposed by the instructor. The purpose of this article is to replace the instructor with a Geographical Information System (GIS) solution combined with a genetic algorithm which, from a set of FPLs, will find the best solution to ensure on the one hand the safety of the aircraft but also minimizing the distance and the changes to be made. The application will use the GAMA platform, very suitable for this and a set of tests composed of actual exercises will be performed to validate the work.
The volume of network and Internet traffic is increasing extraordinarily fast daily, creating huge data. With this volume, variety, speed, and precision of data, it is hard to collect crisis information in such a massive data environment. This paper proposes a hybrid of deep convolutional neural network (CNN)-long short-term memory (LSTM)-based model to efficiently retrieve crisis information. Deep CNN is used to extract significant characteristics from multiple sources. LSTM is used to maintain long-term dependencies in extracted characteristics while preventing overfitting on recurring connections. This method has been compared to previous approaches to the performance of a publicly available dataset to demonstrate its highly satisfactory performance. This new approach allows integrating artificial intelligence technologies, deep learning and social media in managing crisis model. It is based on an extension of our previous approach namely long short-term memory-based disaster management and education: this experience forms a background for this model. It combines representation training with situational awareness and education, while retrieving template information by combining various search results from multiple sources. We have extended it to improve our managing disaster model and evaluate it in the case of the coronavirus disease 2019 (COVID-19) while achieving promising results.
The purpose of this study was to investigate the effects of polluted Soummam River and unpolluted Agrioun River on sperm parameters and oxidative stress status of Barbus callensis spermatozoa during the spawning season in natural condition. The experimental design consisted to activate alternatively fish sperm of the two sites with the polluted (Soummam River, S) and unpolluted water (Agrioun River, A). Sperm motility duration (SMD) was measured using a stopwatch. Gametes straight line velocity (VSL), average path velocity (VAP), curvilinear velocity (VCL), spermatozoa concentration (SC), straightness (STR) and linearity (LIN) were measured by a CASA. Oxidative stress biomarkers were evaluated by measuring total antioxidant status (TAS) and catalase (CAT) activity. The results showed that the SMD and spermatozoa velocity were significantly higher in (Sm, S) than in (Ag, A) with SMD = 52 versus 42s, VSL = 23 versus 16 µm/s, VAP = 35 versus 25 µm/s, and VCL = 52 versus 35 µm/s, respectively. However, SC, STR and LIN were significantly higher in (Ag, A) than in (Sm, S) with SC = 37.5x10 ⁹ versus 27x10 ⁹ spz/ml, STR = 52 versus 40% and LIN = 35 versus 26%. Likewise, the oxidative status of fish spermatozoa was significantly affected by the quality activating water; TAS and CAT were significantly higher in (Ag, A) than in (Sm, S); 7.5 to 0.5 and 120 to 28 µmol/min/ml, respectively. The current investigation showed that Barbus callensis sperm motility parameters, particularly spermatozoa concentration, straightness and linearity are good bioindicators of water pollution.
Background Nowadays, the function of information construction in construction project quality supervision and management is increasingly prominent, and it has become a task that cannot be ignored by administrative departments. Objective To supervise and manage engineering safety data effectively and display the system construction more intuitively, a method based on computer network technology is proposed. Methods K-means clustering, random forest, neural network, and other artificial intelligence algorithms were used for data modelling, and classification model evaluation, regression model evaluation, and other evaluation tools were used to evaluate the quality of the built model, and the power engineering monitoring system was established. The functions of engineering safety supervision and management, data storage and query, deformation graphical display, data analysis and forecast, results report output, and so on are realized. Results The results showed that the mean square error of K-means was 7.74, the mean square error of random forest was 27.5, and the error of neural network was 4.4. Conclusion Neural network has the smallest error and the closest data. The establishment of the system provides a new research platform for power engineering safety supervision and management.
In this paper, we use a new technique to improve the gain and the bandwidth of a small size ultra-wide-band (UWB) circular microstrip antenna. The technique is based on a non-uniform microstrip line feed width and using a partial rectangular ground plane. The compact structure is printed on the economical FR4 substrate material with a relative permittivity 4.4 and loss tangent 0.02 with a degree of miniaturization 39.3×30×1.6 mm3 compatible with the integration technology of components in communications systems architecture. The proposed antenna is simulated and optimized using electromagnetic simulators high frequency structure simulator, results show a good characteristics and radiating behavior within the UWB frequency. The simulated results established that our design has a very important gain (10 dB), and huge bandwidth: from 2.74 to 76.83 GHz for return loss S11<-10 dB and covered multi-band for many applications such as: wireless fidelity system, wireless local area network: operate within the UWB band, worldwide interoperability for microwave access, the 5th generation mobile network (5G). The measured antenna parameters are presented and discussed, confirming the simulation results in the interval [0.1, 20]GHz using ZNB 20 vector network analyser 100 KHz–20 GHz.
This investigation presented presents the drying characteristics, and aimed to predict the drying kinetics of tomato slices (Lycopersicon esculentum MILL.) using convection and microwave methods. Hot air drying was carried out in a ventilated oven at 50, 60, 80, and 100°C temperatures and microwave drying was performed in domestic microwave using 300, 500, 800, and 900 W powers. Twenty‐two mathematical models were undertaken to predict the drying kinetics and the best model was chosen based on the highest R2 values and the lowest root mean square error (RMSE) and χ2 values. Drying kinetics, drying rate variation, diffusivity and energy consumption of both methods were evaluated. Fernando and Amarasinghe model and Sledz model were the best models for convective and microwave drying processes, respectively. Effective moisture diffusivity varied from 0.28 × 10−9 to 2.81 × 10−9 and from 1.32 × 10−9 to 21.52 × 10−9, while the activation energy was 27.64 kJ/mol and 5.71 W/g for convective and microwave drying processes, respectively. The energy consumption increases with increasing temperature or power, the reverse was observed for energy efficiency. Microwave drying process has the advantage of drying time reduction, low‐energy consumption, and high‐drying efficiency at a moderate high‐power level (900 W). Hence, it is recommended to apply this innovative process for drying tomato slices. In this study by using more than 20 models, for the first time, we demonstrated that microwave‐assisted drying of tomato slices was more effective than forced convection drying. It revealed a shorter drying time, high‐drying rates, and high diffusivity with low‐energy consumption.
Discovery of service is one of the main challenge in Internet of Things due to the increasing of services and applications, which is especially tricky for the lookup of service (or set of services). Therefore , in this paper , we propose a new distributed discovering algorithm based on Grey Wolf Optimizer ( GWO ) for IoT . GWO is one of recent metaheuristic , the field of swarm intelligence to solve combinatorial optimization problem. To show the different effective performances of GWO in accurate discovering of services, The simulation results show that GWO can achieve a high discovery success with small number of hops used to discover service. Our approach maintains their performance and achieve good scalability as the number of object in decentralized approach for IoT .
This study aims to optimize the factors influencing the removal of textile dyes by a physicochemical treatment, coagulation-flocculation, using an experimental design. By carrying out the tests and analysing the data, the screening of the factors made it possible to identify the optimum conditions necessary to obtain better elimination. These operating conditions are pH, coagulant dose, the concentration of initial solutions, and stirring speed. Our study demonstrated the importance of applying the design of experiments methodology, particularly the response surface methodology (RSM). A full factorial design allowed the optimization of operational parameters affecting flocculation coagulation. The factors influencing the removal of textile dyes by a physicochemical treatment have been studied.A full factorial design allowed the optimization of operational parameters affecting flocculation coagulation.A full factorial design allowed the optimization of operational parameters affecting flocculation coagulation. The factors influencing the removal of textile dyes by a physicochemical treatment have been studied. A full factorial design allowed the optimization of operational parameters affecting flocculation coagulation. A full factorial design allowed the optimization of operational parameters affecting flocculation coagulation.
The development in industrial systems leads to the augmentation in the consumption of the power. Therefore, this development makes use of multiphase machines. The use of multiphase machines caused several problems and defects. Electrical energy is mainly distributed in a three-phase system to provide the electrical power necessary for the electrical engineering equipment and materials. The sinusoidal aspect of the required original voltage primarily preserves its essential qualities for transmitting useful power to terminal equipment. When the voltage waveform is no longer sinusoidal, perturbations are encountered, which generate malfunctions and overheating of the receivers and the equipment connected to the same electrical supply network. The main disturbing phenomena are harmonics, voltage fluctuations, voltage unbalances, electromagnetic fields, and electrostatic discharges. This present work aims to study the effects of harmonic pollution and voltage unbalance on the five-phase permanent magnet synchronous machine using spectrum current analysis and wavelet transform.
Radio communication systems are very widely present in our current smart lifestyles. It consists of two ends, which can carry the transmitter’s information to the receptor. Before installing any radio communication system, it is necessary to analyze the link resources. Hence, this analysis allows the determination of the received radio communication strength to prove if it is sufficient for the link to work correctly and assure a high quality of service. For this reason, new services and technologies are integrated. The objective of the present work is to improve the performance of the radio communication link of 4G systems. The study is based on real measurements using the drive test. The data collected by the drive test are analyzed to increase the performance of the radio communication. Based on this data analysis, recommendations and suggestions are issued for improving the radio communication link. The obtained results indicate a significant amelioration in the performance of the radio communication link.
Aim To propose a set of dynamic model generation algorithm DPGA, the algorithm can generate parameter models and service models based on user scenarios. Background Buildings in the traditional sense have become increasingly unable to meet modern humans’ pursuit of high-quality living and working environments, with the pace of urban development, modern buildings have gradually entered people's lives Objective Research on Electronic Data Energy Consumption Monitoring System Based on the Construction of Internet of Things Method The author made two definitions of the communication format between the middleware and the wireless sensor network, the author has designed the software and hardware functions of the nodes of the system's wireless sensor network, the author implements part of the node. Finally, the author describes the specific implementation of the application program interface and data interface between the modules of the middleware system, and take the internal environment of a typical office building as an example, the author discussed the deployment plan of system nodes in specific environments and the division of similar areas. Result It has been verified that the platform is committed to strict monitoring and management of energy-consuming equipment Conclusion Realize the reasonable distribution of energy consumption, energy saving, and humanized and automated energy consumption monitoring functions in the office area of large office buildings in modern cities.
Purpose: The present study aimed to estimate the prevalence and molecular characterization of Cryptosporidium spp. in six different fish species both from marine and freshwater environments. Methods: During a period of 2 years (2018-2020), a total of 415 fecal samples and 565 intestinal scrapings were collected in seven provinces from the central and eastern Algeria. From those, 860 fish belonged to six different species, two of which are cultured marine and four are wild freshwater fish. All samples were screened for Cryptosporidium spp. presence using molecular techniques. Nested PCR approach was performed to amplify partial sequences of the small subunit ribosomal RNA (SSU rRNA) and 60-kDa glycoprotein (GP60) genes for Cryptosporidium genotyping and subtyping. Detailed statistical analysis was performed to assess the prevalence variation of Cryptosporidium infection according to different risk factors. Results: Nested PCR analysis of SSU gene revealed 173 Cryptosporidium positive fish, giving an overall prevalence of 20.11% (17.5-23.0). Cryptosporidium spp. was detected in 8.93% (42/470) of cultured marine fish and 33.58% (131/390) of wild freshwater fish. Overall, the prevalence was affected by all studied risk factors, except the gender. Molecular characterization and subtyping of Cryptosporidium isolates showed occurrence of IIaA16G2R1 and IIaA17G2R1 subtypes of C. parvum in the fish species Sparus aurata. Conclusion: The present study provides the first epidemiological data on the prevalence and associated risk factors of Cryptosporidium spp. in farmed marine and wild freshwater fish and the first molecular data on the occurrence of zoonotic C. parvum in fish from North Africa (Algeria).
In this paper, we study a viscoelastic flexible satellite under unknown distributed disturbances during attitude maneuvering. The system composed of a rigid central hub that represents the spacecraft with two symmetrical viscoelastic Euler–Bernoulli beams and subject to undesirable vibrations. The problem can be modeled by a set of partial differential equations (PDEs) taking into account therefore the dynamic boundary condition. The well‐posedness of the closed‐loop system is discussed. By applying a control force at the center body of the spacecraft, we shall suppress these vibrations; namely, we establish stability results of the system under appropriate assumptions imposed on the relaxation function. These new results generalize and improve many results in the literature. Our results are obtained by using the multiplier technique. Numerical simulation results show the effectiveness of the proposed control scheme.
The prediction of displacements in earthen dams after seismic loading is necessary to ensure their proper functioning. In this study, the finite element software plaxis 2D is used to model the nonlinear dynamic behavior (elasto-plastic) of the embankment dam solicited by real seismic records. The earth dam considered in our case study is the Taksebt dam located in the north-east of Algeria. The main steps of the modeling are the following: first the dam of Taksebt was analyzed under seismic stresses without water (empty). Then the dam of Taksebt is subjected to the same seismic records with water (full). The comparison of the study cases allows us to estimate the displacements in the two main directions (horizontal and vertical).The results obtained show the ability to estimate the displacements in an embankment dam under seismic excitation. In addition, the analysis time will be reduced considerably by considering the two extreme cases of seismic loading.
Our study focuses on the study of the phosphorus efficiency on the mineral nutrition of a leguminous plant; to study this efficiency, we tested the effect of increasing doses of phosphorus on the mineral nutrition of faba bean and on the concentration of Nt (total nitrogen), Pi (available phosphorus), KE (exchangeable potassium), C (organic carbon), and the organic matter (OM) rate in the rhizospheric soil after harvest, as well as the concentration of N, P, K, Na, and Ca in the roots, stems, leaves, and seeds of faba bean. The faba bean crop was subjected to four phosphorus doses (P0 = 0 kg/ha; P1 = 70 kg/ha; P2 = 140 kg/ha; P3 = 210 kg/ha). The main results obtained showed that the concentration of the mineral elements in the different faba bean parts reacted differently to the phosphorus treatments. Regarding the dosage of nutrients in the different parts of the faba bean, the results obtained highlight that Pi deficiency in the soil does not only affect phosphate nutrition but can also affect the absorption of other mineral elements, a synergy is recorded between the K concentration in the roots and in the stems with the organic carbon in the soil, and an antagonism between K and Na in the different parts of the plant. All the results obtained in this work show that a phosphate fertilization for doses between 70 kg/ha and 140 kg/ha of P2O5 improves the microbial life of soil microorganisms.
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