Université Amar Telidji Laghouat
  • Laghouat, Laghouat, Algeria
Recent publications
Latent heat materials are widely investigated and successfully used in a variety of important applications as in the building industry and thermal engineering systems. In this paper a comprehensive review on phase change material (PCM) in relatively recent potential application such as photovoltaic (PV) panel cooling, applications in food, automotive; asphalt, and textile industries. The review is divided into seven sections. The first two sections give a general overview of PCMs, their potential in integrating intermittent systems, PCM characterization and enhancement techniques. In the third and subsequent sections applications in the PV panels cooling, food, textile, automotive and asphalt applications are presented. The results showed that application of PCM RT42 in a BiCPV system reduced the temperature by about 3.8 °C and increased the electrical efficiency by 7.7 %. The use of finned enclosures enhanced the performance of PV panels. A finned enclosure decreased the operating temperature by 6.1 °C and increased the efficiency by 5.3 %.The use of nanoparticles (SiC) dispersed into paraffin based PCM showed good thermal performance and increased the electrical efficiency by 13.7 %. Similar benefits are found in the food industry. The use of PCM in food containers reduced the energy consumption, the operational cost, and the emission by 86.7, 91.6, and 78.5 %, respectively. Penetration of PCM in the textile industry is relatively small. Applications in the textile industry showed that for a temperature rise from 20 to 28 °C, common silk took 13 s, the Outlast/silk took 20 s, and the treated fabric took 37 s. Application of PCM in the car industry for cooling batteries, and thermal insulation is continuously growing. It is shown that using PCM decreased the maximum and minimum battery temperature from 56.8 and 48.3 °C to 38.9 and 36.0 °C, respectively. Other application showed that the use of coconut oil as PCM for the thermal control of a vehicle decreased the passenger's cabin temperature by an average of 13 °C, while application on the roof of a parked car during 1 h in a sunny day can reduce the temperature by about 33 °C. The inclusion of PCM in the asphalt mixture can eliminate the destructive bonds that cause aging of the asphalt mixture, contribute to the prevention of low-temperature cracking and decrease the temperature fluctuations in the asphalt binder. This review can be of great help for system designers, practice engineers and researchers in the area of thermal energy storage and PCM based systems. Trends for future research are highlighted.
This work is concerned with a full von Kármán beam in the presence of infinite-memory, Microtemperature and distributed delay terms. Firstly we establish the well posedness of the system. Secondly, by considered the kernel h : R + → R + satisfying h(t) ≤ ξ(t)H(h(t)), ∀t ∈ R + , where ξ and H are functions satisfying some specific properties, and under this very general hypothesis on the behavior of h at infinity, we prove the stability of the system.
This paper proposes rainfall-runoff models based on machine learning to estimate daily streamflows in Oued Sebaou Watershed, a Mediterranean Coastal Basin located in northern Algeria. Therefore, we applied Random Forest (RF), Artificial Neural Networks (ANN) - under different training algorithms -, and Local Weighted Linear Regression (LWLR) using as input combinations of current and past amounts of rainfalls and previous values of streamflow. We selected streamflow and rainfall records to calibrate and validate the stated approaches. The study considered Root Mean Square Error (RMSE) and Correlation Coefficient (R) to evaluate the accuracy of the models. Analyses of the results show that RF provided the best outcomes for both training (RMSE = 4.7458 and R = 0.9834) and validation (RMSE = 2.3617 and R = 0.9719). The ANN calibrated with the Levenberg-Marquardt algorithm presented the second-best result, outperforming its counterparts and LWLR.
With the enormous growth of sensing devices tending to the use of Internet of everything, data aggregated by these devices are the biggest data streams generated in the history of IT. Thus, aggregating such data in the cloud for leveraging powerful cloud computing processing and storage is essential, and it eventually led to the emergence of Sensor-Cloud concept. This has allowed aggregation of the sensors’ data to the cloud for further processing, storage, and visualization. Furthermore, virtualization makes the sensors accessible to other end-user applications that require such data. All of these features are expected to be provided by the Sensor-Cloud invisibly, without the end-user application developer being aware of the sensor location or hardware specifications. For these reasons, a simulation platform where Sensor-Cloud infrastructure agents and components may be modeled, scheduling policies defined, and execution time assessed is essential to assure performance and quality of service. The aim of this study is to develop such a platform by enhancing CloudSim, the most well-known and powerful simulation tool for cloud computing. A user-friendly Java Script Swing-based graphical user interface (GUI) has been carefully designed and implemented for this purpose. The user can then utilize the specific interface to define the Cloudlet type as well as the scheduling on a single virtual machine. Finally, a simulation study is carried out on the platform to demonstrate its efficiency and accuracy. We were able to fully model the needed scenarios and acquire real-time results, displaying good accuracy in terms of application response time with a mean absolute percentage error (MAPE) of 3.37%, demonstrating the increased proposed platform’s proper operation.
Recent advances in control, communication, and management systems, as well as the widespread use of renewable energy sources in homes, have led to the evolution of traditional power grids into smart grids, where passive consumers have become so-called prosumers that feed energy into the grid. On the other hand, the integration of blockchain into the smart grid has enabled the emergence of decentralized peer-to-peer (P2P) energy trading, where prosumers trade their energy as tokenized assets. Even though this new paradigm benefits both distribution grid operators and end users in many ways. Nevertheless, there is a conflict of interest between the two parties, as on the one hand, prosumers want to maximize their profit, while on the other hand, distribution system operators (DSOs) seek an optimal power flow (OPF) operating point. Due to the complexity of formulating and solving OPF problems in the presence of renewable energy sources, researchers have focused on mathematical modeling and effective solution algorithms for such optimization problems. However, the control of power generation according to a defined OPF solution is still based on centralized control and management units owned by the DSO. In this paper, we propose a novel, fully decentralized architecture for an OPF-based demand response management system that uses smart contracts to force generators to comply without the need for a central authority or hardware.
Industrial IoT has emerged as a new paradigm in the era of smart systems where interactions and transmission of messages among various entities in an industrial ecosystem are done autonomously. This includes manufacturing of products, shipment process, storage of records, and counting the data, to name a few. However, the involvement of multiple cyber threats that accompany the smart devices may lead the organizations on a heavy risk of profits. Even though number of cyber-security approaches have been proposed to ensure a secure and efficient communication mechanism in IIoT systems, the identification of cyber security issues in IIoT applications while exchanging the data is still at its early stage. The aim of this paper is to propose an efficient cyber-security communication mechanism using the trust evaluation system of each device to make a correct decision during communication. In addition, the evaluated trust of each device is further analyzed and monitored through a blockchain-based mechanism. The proposed approach is validated against an existing scheme in terms of various security metrics such as sensitivity of devices while communicating, convergence time of transmitting information and percentage and probability of malicious devices in terms of data delivery rate, false authentication and trust value computation.
Learner autonomy represents a consumed subject in the realm of English as a foreign language instruction. Nonetheless, the Algerian literature demonstrates a dearth of research on teachers' beliefs about learner autonomy in the Algerian Middle school setting. is paper, therefore, examines the beliefs of English as a Foreign Language (EFL) teachers about learner autonomy in Algeria. To this end, quantitative and qualitative data were collected from a sample of 129 Algerian middle school teachers of English as a foreign language. e study deployed a questionnaire in conjunction with an interview for data collection. e questionnaires' data were numerically analysed using Statistical Package for the Social Sciences (SPPS), while the interviews' data were analysed qualitatively using coding and theme generation. Findings reveal that teachers often view learner autonomy from psychological and technical orientations, implying that it encompasses the concepts of independence, choice, and collaboration. Additionally, the findings indicate a strong belief in teachers' roles in promoting learner autonomy as well as in the latter's role in enhancing the learning process. Furthermore, the findings indicated teachers' desirability to involve learners in decision-making and assist them in developing skills for learning how to learn outweighs their feasibility. e investigation concluded with some suggestions.
In this paper, we present a novel scheme for enhancing the security of speech information in communication systems. We build a hybridization of three approaches: Chaotic logistic and tent maps for generating an arbitrary vector by some primarily initiated values to be joined in the original speech signal, an integrated watermark image within the encrypted signal in order to verify, through decryption process, that the encrypted signal is authentic as well as does not suffer from eventual attacks, and the third approach is using an Arnold scrambling key (cat map) to spread signal samples by means of a secret key, then recuperate the original signal from samples which is not possible without this key. Obtained correlation value in the proposed scheme is closer to null which proves that original and encrypted signals are completely dissimilar. Moreover, we recovered the original speech without disturbing the quality. Numerical results of the Signal to Noise Ratio (SNR) and Correlation Coefficient (CC) reported below, and the comparison between the proposed approach to seven recently published works, also reported, reveal the superiority of the proposed scheme and validate our design to be considered amongst the best methods compared to other recently existing strong approaches.
The objective of this study was to detect helminths in sheep on farms in three different zones of the Laghouat region, and to examine relationships between the prevalence of these parasites and the factors of age, sex, and area. The study was carried out over a period of four months (March to June 2019) on 77 faecal samples taken from 77 sheep. For this purpose, we used both a qualitative technique (flotation) and a quantitative technique (Mac Master). These two techniques allowed us to isolate helminths and determine the degree of infestation of sheep in the steppe region, specifically the Laghouat region. The results showed that the sheep flock studied overall was negative, with the exception of eight subjects infected with Nematodirus or Strongyloides at a rate of 7.49% each. The helminth parasite prevalence was 10.40%. Statistical analysis of the influence of specific factors revealed no significant effect (P˃0.05) for sex, though the effects of age and area were significant (P<0.05). This parasite prevalence must be taken seriously to avoid its detrimental effect on animal health and the zootechnical performance of sheep flocks.
In this work, a transparent metasurface absorber/emitter (TMAE) is proposed based on the transparent metal of indium tin oxide (ITO) and substrate layer consisting of (ZnS). This design can achieve the highest absorption of 99% and remains higher than 90% when the incident angle is less than 70° under TE/TM polarization waves. According to Kirchhoff’s law, this design can exhibit adequate shapes of emissivity for a commonly used PV cell under a temperature range extended from 300 to 1500 °C, with thermal stability for optimal thermal transfer efficiency over 95 % under different operating temperatures, and solar concentration ratios can be featured. This TMAE potentially can be used efficaciously in the combined solar/thermal conversion with highly beneficial under various operating conditions.
Nanoparticles (NPs) synthesized by the co-precipitation technique show many attractive properties such as small particle size, high crystallinity, high average pore diameter and high specific surface area. However, numerous reports show that some characteristics of the Ni-doped ZnO (NZO) NPs remain controversial such as optical bandgap (Eg), surface morphology and defect level. In this study, pure ZnO and NZO NPs at different Ni contents (x) were successfully prepared using the co-precipitation method. Phase analysis confirms the hexagonal wurtzite crystallinity of the samples. XRD peak shows that the Ni may substituted ZnO structure as the peaks shift toward higher angles with increasing x. Meanwhile, the formation of NiO secondary phases was significant at 12.50% Ni content. Densely packed spherical shaped structures with nanoparticle agglomeration are observed at low x, while some nanorod shaped structures appear at higher x. The stretching vibrations of the Zn–O bond are observed in the NZO NPs. The absorption edge shifts to higher wavelengths with the increase in x. This study provides consistent results in the phase analysis, morphology and structural parameters. The decrease in Eg agrees with the photoluminescence measurements. The emission spectra confirm the presence of interstitial zinc and singly ionized oxygen vacancies.
Named Data Networking (NDN) is a prominent realization of the vision of Information-Centric Networking. The NDN architecture adopts name-based routing and location-independent data retrieval. Among other important features, NDN integrates security mechanisms and focuses on protecting the content rather than the communications channels. Along with a new architecture come new threats and NDN is no exception. NDN is a potential target for new network attacks such as Interest Flooding Attacks (IFAs). Attackers take advantage of IFA to launch (D)DoS attacks in NDN. Many IFA detection and mitigation solutions have been proposed in the literature. However, there is no comprehensive review study of these solutions that has been proposed so far. Therefore, in this paper, we propose a survey of the various IFAs with a detailed comparative study of all the relevant proposed solutions as counter-measures against IFAs. We also review the requirements for a complete and efficient IFA solution and pinpoint the various issues encountered by IFA detection and mitigation mechanisms through a series of attack scenarios. Finally, in this survey, we offer an analysis of the open issues and future research directions regarding IFAs.
Optimum conditions for ultrasonic‐assisted extraction UAE of total phenolic and total flavonoid compounds (TPC & TFC) and antioxidant activity from aerial parts of Saccocalyx satureioides have been investigated using response surface methodology RSM. The Box–Behnken design was used to investigate the effects of three independent variables: time, temperature and solvent/matter “mL/g d.w.”) ratio. In this study, total phenolics and total flavonoids extracts were investigated for their antioxidant activity using two different and complementary assays: the DPPH• (2,2‐diphenyl‐1‐picrylhydrazyl) free radical scavenging and the FRAP (Ferric Reducing Antioxidant Power). Optimized conditions of UAE extraction were determined for TPC, TFC and antioxidant capacity (DPPH, FRAP) at once. The results suggested that extraction with absolute methanol to dry matter ratio of 70/1 mL/g for 40.0 min at 43.21°C were the optimal conditions for this combination of variables. Hence, the optimal solution results for the investigated variables were: TPC = 2.416 g/100g, TFC = 0.440 g/100g, DPPH (IC50 = 0.022 mg/mL), FRAP (IC50 = 0.760 mg/mL). The experimental values agreed with those predicted within a 95% confidence level, thus indicating the suitability of RSM in optimizing the UAE of phenolic compounds from S. satureioides. The results indicate also that optimization of extraction conditions in this plant is critical for precise quantification of antioxidant phenolics and its further utilization in industry.
Smart social systems are ones where a number of individuals share and interact with each other via various networking devices. There exist a number of benefits to including smart-based systems in networks such as religions, economy, medicine, and other networks. However, the involvement of several cyber threats leads to adverse effects on society in terms of finance, business, liability, economy, psychology etc. The aim of this paper is to present a secure and efficient medical Internet of Things communication mechanism by preventing various cyber threats. The proposed framework uses Artificial Intelligence-based techniques such as Levenberg–Marquardt (LM) and Viterbi algorithms to prevent various social cyber threats during interaction and sharing of messages. The proposed mechanism is simulated and validated with various performance metrics compared with the traditional mechanism.
Background Over-consumption of foods high in purines like seafood, red meat, and alcoholic beverages leads to hyperuricemia causing gout attacks. Xanthine oxidase was reported responsible for the overproduction of uric acid. Material and methods We intend to test in silico and in vitro, the inhibition effect of four vitamins against bovine milk xanthine oxidase (BXO). We performed Molecular docking with GOLD v4.0, and the biological activity prediction with the PASS server. The best-selected vitamins were chosen based on their best PLPchem score. The BXO constant Km and Vmax were determined in vitro, and then the vitamins were tested for their inhibition effect to BXO. Furthermore, the inhibition constant Ki of each inhibitor were determined using Dixon method, the vitamins chosen were vitamin E, vitamin B9, vitamin D3, and vitamin C. Results The in silico results show that the tested vitamins were the best inhibitors model with PLPchem scores up to 70 comparing to the control. The in vitro results show that BXO have a Km value of 163.55 μM with Vmax of 37 U, vitamins B9, E, C, and D3 were potent inhibitors to BXO with an IC50 of 34.10 ± 0.21, 36.68 ± 1.50, 39.01 ± 0.02, and 100.28 ± 0.33 μM, respectively comparing to the control (32.03 ± 0.73 μM). The kinetic study shows that all tested vitamins were Non-competitive inhibitors, the Ki values were 15 ± 1.76 μM, 29 ± 1.06 μM, 12 ± 1.41 μM, and 20 ± 0.71 μM, for respectively vitamins B9, E, C, and D3. Conclusion The obtained results promise an excellent strategy using vitamins to enhance immunity, treat hyperuricemia, and minimize the usual drug side effects.
In this manuscript, the behavior of a Herschel-Bulkley uid has been discussed in a thin layer in R 3 associated with a nonlinear stationary, nonisothermal, and incompressible model. Furthermore, the limit problem has been considered, and the studied problem in Ω ε is transformed into another problem de ned in Ω ε without the parameter Ω ε (ε is the parameter representing the thickness of the layer tend to zero is studied). We also investigated the convergence of the unknowns which are the velocity, pressure, and the temperature of the uid. In addition, we established the limit problem and the speci c Reynolds equation.
To combat the problem of illegal access to a service, several location proof strategies have been proposed in the literature. In blockchain-based decentralized applications, transactions can be issued by IoT nodes or other automated smart devices. Key pair encryption and private key signing have been defined mainly for human identification in blockchain applications, where users are personally and responsibly concerned about the confidentiality of their private key. These methods are not suitable for computing nodes whose private key is implemented in the software they run. Ensuring that transactions are issued by a legitimate sender with the proper credentials is a bigger concern in applications with financial stakes. This is the case with blockchain energy trading platforms, where prosumers are credited with tokens in exchange for their contributions of energy. The tokens are issued by smart meter nodes installed at fixed locations to monitor the energy inputs and outputs of a given prosumer and claim energy tokens on its behalf from a defined smart contract in exchange for the energy it feeds into the grid. To this end, we have developed a decentralized Proof-of-Location (PoL) system tailored to blockchain applications for energy trading. It ensures that automated transactions are issued by the right nodes by using smart contract-based random selection and a game-theoretic scenario suitable for blockchain energy trading.
First-principles total energy calculations were performed to study the stability of Rh2TMSn (TM=Cr, Mn and Fe) toward different magnetic ordering, ferromagnetic (FM), antiferromagnetic type I (AFM-I) and antiferromagnetic type II (AFM-II). We studied the effects of electron correlation on the magnetic stability of the compounds in both cubic and tetragonal structures using density functional theory (DFT) within the generalized gradient approximation (GGA) and GGA+U. The results show that the electron correlation has an important role in determining the magnetic stability of the compounds. The magnetic stability obtained from GGA+U agrees well with the available experimental results. The thermodynamic stability of the three compounds shows that all the compounds are stable in both cubic and tetragonal structures. Using the energy difference method, we were able to calculate the exchange interactions and estimate the Curie temperature of the Rh2MnSn compound in the cubic structure. The phonon dispersion curves were investigated for the first time using the linear-response approach in the context of density functional perturbation theory. The results show that all the compounds are dynamically stable in their predicted phases.
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1,122 members
Djekidel Rabah
  • Department of Electrical Engineering
Makhloufi Zoubir
  • Engineering Department
Goual Idriss
  • Department of Civil Engineering
Mohammed Belkheiri
  • Department of Electronics
Khedidja Benarous
  • Department of Biology
BP 37G, Route de GHARDAIA, 03000, Laghouat, Laghouat, Algeria
Head of institution
Phd.Benbertal Djamal
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