Search results for: Ameur Ameur Abdelkader
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 105

Search results for: Ameur Ameur Abdelkader

105 The Effect of Dose of Pregnant Mare Serum Gonadotropin (PMSG) on Reproductive Efficiency in Ouled Djellal Ewes

Authors: Ameur Ameur Abdelkader, Boukherrouba Hadjira

Abstract:

The aim of the present study was to evaluate different doses of PMSG on reproductive performance in Ouled Djellal ewes synchronized during the breeding season period. A total of 200 ewes were used in this experiment, were divided in two groups, 100 uniparous (A) and 100 multiparous (B). All animals in both groups were divided equally into four groups homogeneous lots of then a single intramuscular (IM) injection of PMSG, Lot T1, A1 (400 IU), A2 (500 IU), A3 (600 IU) and (lot T2, B1 (400 IU), B2 (500UI), B3 (600UI), T1, and T2 are batch control groups received a single injection of progestin treatment without PMSG. The results showed that the fertility rate ranges from 79.16% to 92% with no significant difference (P > 0.05) between uniparous and multiparous ewes. The prolificity rate varies from 100% to 140% in uniparous ewes with the respective doses of 0 IU for the control group and 600 IU for lot A3. A significant difference between multiparous ewes prolificacy and uniparous receiving 500UI PMSG (respectively 142% vs 109%). The productivity rate has increased significantly among uniparous ewes with 82% for lot A1 to 112.5% for lot A3, as in multiparous ewes 66.66% for lot B1 to 133.33% for lot B3. At the same we recorded a positive correlation between the number of born products and increasing the dose of PMSG injected into the two categories of ewes (112.5% to 133.33% for multiparous uniparous VS 83% for and 66.66 uniparous % for multiparous).

Keywords: Ouled djellal ewe, PMSG, reproductive performance, Fertility

Procedia PDF Downloads 437
104 Preliminary Study on Milk Composition and Milk Protein Polymorphism in the Algerian Local Sheep's Breeds

Authors: A. Ameur Ameur, F. Chougrani, M. Halbouche

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In order to characterize the sheep's milk, we analyzed and compared, in a first stage of our work, the physical and chemical characteristics in two Algerian sheep breeds: Hamra race and race Ouled Djellal breeding at the station the experimental ITELV Ain Hadjar (Saïda Province). Analyses are performed by Ekomilk Ultra-analyzer (EON TRADING LLC, USA), they focused on the pH, density, freezing, fat, total protein, solids-the total dry extract. The results obtained for these parameters showed no significant differences between the two breeds studied. The second stage of this work was the isolation and characterization of milk proteins. For this, we used the precipitation of caseins phi [pH 4.6]. For this, we used the precipitation of caseins Phi (pH 4.6). After extraction, purification and assay, both casein and serum protein fractions were then assayed by the Bradford method and controlled by polyacrylamide gel electrophoresis (PAGE) in the different conditions (native, in the presence of urea and in the presence of SDS). The electrophoretic pattern of milk samples showed the presence similarities of four major caseins variants (αs1-, αs2-β-and k-casein) and two whey proteins (β-lactoglobulin, α-lactalbumin) of two races Hamra and Ouled Djellal. But compared to bovine milk, they have helped to highlight some peculiarities as related to serum proteins (α La β Lg) as caseins, including αs1-Cn.

Keywords: Hamra, Ouled Djellal, protein polymorphism, sheep breeds

Procedia PDF Downloads 556
103 Evaluation of the Safety Status of Beef Meat During Processing at Slaughterhouse in Bouira, Algeria

Authors: A. Ameur Ameur, H. Boukherrouba

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In red meat slaughterhouses a significant number of organs and carcasses were seized because of the presence of lesions of various origins. The objective of this study is to characterize and evaluate the frequency of these lesions in the slaughterhouse of the Wilaya of BOUIRA. On cattle slaughtered in 2646 and inspected 72% of these carcasses have been no seizures against 28% who have undergone at least one entry. 325 lung (44%), 164 livers (22%), 149 hearts (21%) are the main saisis.38 kidneys members (5%), 33 breasts (4%) and 16 whole carcasses (2%) are less seizures parties. The main reasons are the input hydatid cyst for most seized organs such as the lungs (64.5%), livers (51.8%), hearts (23.2%), hydronephrosis for the kidneys (39.4%), and chronic mastitis (54%) for the breasts. Then we recorded second-degree pneumonia (16%) to the lungs, chronic fascioliasis (25%) for livers. A significant difference was observed (p < 0.0001) by sex, race, origin and age of all cattle having been saisie.une a specific input patterns and So pathology was recorded based on race. The local breed presented (75.2%) of hydatid cyst, (95%) and chronic fascioliasis (60%) pyelonephritis, for against the improved breed presented the entire respiratory lesions include pneumonia (64%) the chronic tuberculosis (64%) and mastitis (76%). These results are an important step in the implementation of the concept of risk assessment as the scientific basis of food legislation, by the identification and characterization of macroscopic damage leading withdrawals in meat and to establish the level of inclusion of these injuries within the recommended risk assessment systems (HACCP).

Keywords: slaughterhouses, meat safety, seizure patterns, HACCP

Procedia PDF Downloads 465
102 Predictive Analysis for Big Data: Extension of Classification and Regression Trees Algorithm

Authors: Ameur Abdelkader, Abed Bouarfa Hafida

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Since its inception, predictive analysis has revolutionized the IT industry through its robustness and decision-making facilities. It involves the application of a set of data processing techniques and algorithms in order to create predictive models. Its principle is based on finding relationships between explanatory variables and the predicted variables. Past occurrences are exploited to predict and to derive the unknown outcome. With the advent of big data, many studies have suggested the use of predictive analytics in order to process and analyze big data. Nevertheless, they have been curbed by the limits of classical methods of predictive analysis in case of a large amount of data. In fact, because of their volumes, their nature (semi or unstructured) and their variety, it is impossible to analyze efficiently big data via classical methods of predictive analysis. The authors attribute this weakness to the fact that predictive analysis algorithms do not allow the parallelization and distribution of calculation. In this paper, we propose to extend the predictive analysis algorithm, Classification And Regression Trees (CART), in order to adapt it for big data analysis. The major changes of this algorithm are presented and then a version of the extended algorithm is defined in order to make it applicable for a huge quantity of data.

Keywords: predictive analysis, big data, predictive analysis algorithms, CART algorithm

Procedia PDF Downloads 139
101 Ant System with Acoustic Communication

Authors: Saad Bougrine, Salma Ouchraa, Belaid Ahiod, Abdelhakim Ameur El Imrani

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Ant colony optimization is an ant algorithm framework that took inspiration from foraging behaviour of ant colonies. Indeed, ACO algorithms use a chemical communication, represented by pheromone trails, to build good solutions. However, ants involve different communication channels to interact. Thus, this paper introduces the acoustic communication between ants while they are foraging. This process allows fine and local exploration of search space and permits optimal solution to be improved.

Keywords: acoustic communication, ant colony optimization, local search, traveling salesman problem

Procedia PDF Downloads 584
100 CPPI Method with Conditional Floor: The Discrete Time Case

Authors: Hachmi Ben Ameur, Jean Luc Prigent

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We propose an extension of the CPPI method, which is based on conditional floors. In this framework, we examine in particular the TIPP and margin based strategies. These methods allow keeping part of the past gains and protecting the portfolio value against future high drawdowns of the financial market. However, as for the standard CPPI method, the investor can benefit from potential market rises. To control the risk of such strategies, we introduce both Value-at-Risk (VaR) and Expected Shortfall (ES) risk measures. For each of these criteria, we show that the conditional floor must be higher than a lower bound. We illustrate these results, for a quite general ARCH type model, including the EGARCH (1,1) as a special case.

Keywords: CPPI, conditional floor, ARCH, VaR, expected ehortfall

Procedia PDF Downloads 301
99 A Reduced Distributed Sate Space for Modular Petri Nets

Authors: Sawsen Khlifa, Chiheb AMeur Abid, Belhassan Zouari

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Modular verification approaches have been widely attempted to cope with the well known state explosion problem. This paper deals with the modular verification of modular Petri nets. We propose a reduced version for the modular state space of a given modular Petri net. The new structure allows the creation of smaller modular graphs. Each one draws the behavior of the corresponding module and outlines some global information. Hence, this version helps to overcome the explosion problem and to use less memory space. In this condensed structure, the verification of some generic properties concerning one module is limited to the exploration of its associated graph.

Keywords: distributed systems, modular verification, petri nets, state space explosition

Procedia PDF Downloads 113
98 Neural Network Monitoring Strategy of Cutting Tool Wear of Horizontal High Speed Milling

Authors: Kious Mecheri, Hadjadj Abdechafik, Ameur Aissa

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The wear of cutting tool degrades the quality of the product in the manufacturing processes. The online monitoring of the cutting tool wear level is very necessary to prevent the deterioration of the quality of machining. Unfortunately there is not a direct manner to measure the cutting tool wear online. Consequently we must adopt an indirect method where wear will be estimated from the measurement of one or more physical parameters appearing during the machining process such as the cutting force, the vibrations, or the acoustic emission etc. In this work, a neural network system is elaborated in order to estimate the flank wear from the cutting force measurement and the cutting conditions.

Keywords: flank wear, cutting forces, high speed milling, signal processing, neural network

Procedia PDF Downloads 392
97 Evaluation of Photovoltaic System with Different Research Methods of Maximum Power Point Tracking

Authors: Mehdi Ameur, Ahmed Essadki, Tamou Nasser

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The purpose of this paper is the evaluation of photovoltaic system with MPPT techniques. This system is developed by combining the models of established solar module and DC-DC converter with the algorithms of perturbing and observing (P&O), incremental conductance (INC) and fuzzy logic controller (FLC). The system is simulated under different climate conditions and MPPT algorithms to determine the influence of these conditions on characteristic power-voltage of PV system. According to the comparisons of the simulation results, the photovoltaic system can extract the maximum power with precision and rapidity using the MPPT algorithms discussed in this paper.

Keywords: fuzzy logic controller, FLC, hill climbing, HC, incremental conductance (INC), perturb and observe (P&O), maximum power point, MPP, maximum power point tracking, MPPT

Procedia PDF Downloads 510
96 Analysis and Modeling of Photovoltaic System with Different Research Methods of Maximum Power Point Tracking

Authors: Mehdi Ameur, Ahmed Essakdi, Tamou Nasser

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The purpose of this paper is the analysis and modeling of the photovoltaic system with MPPT techniques. This system is developed by combining the models of established solar module and DC-DC converter with the algorithms of perturb and observe (P&O), incremental conductance (INC) and fuzzy logic controller(FLC). The system is simulated under different climate conditions and MPPT algorithms to determine the influence of these conditions on characteristic power-voltage of PV system. According to the comparisons of the simulation results, the photovoltaic system can extract the maximum power with precision and rapidity using the MPPT algorithms discussed in this paper.

Keywords: photovoltaic array, maximum power point tracking, MPPT, perturb and observe, P&O, incremental conductance, INC, hill climbing, HC, fuzzy logic controller, FLC

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95 Investigation of the Mechanism, Régio and Sterioselectivity Using the 1,3-Dipolar Cycloaddition Reaction of Fused 1h-Pyrrole-2,3-Diones with Nitrones: Molecular Electron Density Theory Study

Authors: Ameur Soukaina, Zeroual Abdellah, Mazoir Noureddine

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Molecular Electron Density Theory (MEDT) elucidates the regioselectivity of the [4+2] cycloaddition reaction between 3-aroylpyrrolo[1,2-α]quinoxaline-1,2,4(5H)-trione and butyl vinyl ether Regioselectivity and stereoselectivity. The regioselectivity mechanisms of these reactions were investigated by evaluating potential energy surfaces calculated for cycloaddition processes and DFT density-based reactivity indices. These methods have been successfully applied to predict preferred regioisomers for different method alternatives. Reactions were monitored by performing transition state optimizations, calculations of intrinsic reaction coordinates, and activation energies. The observed regioselectivity was rationalized using DFT-based reactivity descriptors such as the Parr function. Solvent effects were also investigated in 1,4-dioxane solvent using a field model for self-consistent reactions. The results were compared with experimental data to find good agreement.

Keywords: cycloaddition, DFT, ELF, MEDT, parr, stereoselectivité

Procedia PDF Downloads 107
94 Image Compression Based on Regression SVM and Biorthogonal Wavelets

Authors: Zikiou Nadia, Lahdir Mourad, Ameur Soltane

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In this paper, we propose an effective method for image compression based on SVM Regression (SVR), with three different kernels, and biorthogonal 2D Discrete Wavelet Transform. SVM regression could learn dependency from training data and compressed using fewer training points (support vectors) to represent the original data and eliminate the redundancy. Biorthogonal wavelet has been used to transform the image and the coefficients acquired are then trained with different kernels SVM (Gaussian, Polynomial, and Linear). Run-length and Arithmetic coders are used to encode the support vectors and its corresponding weights, obtained from the SVM regression. The peak signal noise ratio (PSNR) and their compression ratios of several test images, compressed with our algorithm, with different kernels are presented. Compared with other kernels, Gaussian kernel achieves better image quality. Experimental results show that the compression performance of our method gains much improvement.

Keywords: image compression, 2D discrete wavelet transform (DWT-2D), support vector regression (SVR), SVM Kernels, run-length, arithmetic coding

Procedia PDF Downloads 380
93 Numerical Study of Natural Convection Heat Transfer Performance in an Inclined Cavity: Nanofluid and Random Temperature

Authors: Hicham Salhi, Mohamed Si-Ameur, Nadjib Chafai

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Natural convection of a nanofluid consisting of water and nanoparticles (Ag or TiO2) in an inclined enclosure cavity, has been studied numerically, heated by a (random temperature, based on the random function). The governing equations are solved numerically using the finite-volume. Results are presented in the form of streamlines, isotherms, and average Nusselt number. In addition, a parametric study is carried out to examine explicitly the volume fraction effects of nanoparticles (Ψ= 0.1, 0.2), the Rayleigh number (Ra=103, 104, 105, 106),the inclination angle of the cavity( égale à 0°, 30°, 45°, 90°, 135°, 180°), types of temperature (constant ,random), types of (NF) (Ag andTiO2). The results reveal that (NPs) addition remarkably enhances heat transfer in the cavity especially for (Ψ= 0.2). Besides, the effect of inclination angle and type of temperature is more pronounced at higher Rayleigh number.

Keywords: nanofluid, natural convection, inclined cavity, random temperature, finite-volume

Procedia PDF Downloads 284
92 A High Compression Ratio for a Losseless Image Compression Based on the Arithmetic Coding with the Sorted Run Length Coding: Meteosat Second Generation Image Compression

Authors: Cherifi Mehdi, Lahdir Mourad, Ameur Soltane

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Image compression is the heart of several multimedia techniques. It is used to reduce the number of bits required to represent an image. Meteosat Second Generation (MSG) satellite allows the acquisition of 12 image files every 15 minutes and that results in a large databases sizes. In this paper, a novel image compression method based on the arithmetic coding with the sorted Run Length Coding (SRLC) for MSG images is proposed. The SRLC allows us to find the occurrence of the consecutive pixels of the original image to create a sorted run. The arithmetic coding allows the encoding of the sorted data of the previous stage to retrieve a unique code word that represents a binary code stream in the sorted order to boost the compression ratio. Through this article, we show that our method can perform the best results concerning compression ratio and bit rate unlike the method based on the Run Length Coding (RLC) and the arithmetic coding. Evaluation criteria like the compression ratio and the bit rate allow the confirmation of the efficiency of our method of image compression.

Keywords: image compression, arithmetic coding, Run Length Coding, RLC, Sorted Run Length Coding, SRLC, Meteosat Second Generation, MSG

Procedia PDF Downloads 351
91 Exploratory Study of the Influencing Factors for Hotels' Competitors

Authors: Asma Ameur, Dhafer Malouche

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Hotel competitiveness research is an essential phase of the marketing strategy for any hotel. Certainly, knowing the hotels' competitors helps the hotelier to grasp its position in the market and the citizen to make the right choice in picking a hotel. Thus, competitiveness is an important indicator that can be influenced by various factors. In fact, the issue of competitiveness, this ability to cope with competition, remains a difficult and complex concept to define and to exploit. Therefore, the purpose of this article is to make an exploratory study to calculate a competitiveness indicator for hotels. Further on, this paper makes it possible to determine the criteria of direct or indirect effect on the image and the perception of a hotel. The actual research is used to look into the right model for hotel ‘competitiveness. For this reason, we exploit different theoretical contributions in the field of machine learning. Thus, we use some statistical techniques such as the Principal Component Analysis (PCA) to reduce the dimensions, as well as other techniques of statistical modeling. This paper presents a survey covering of the techniques and methods in hotel competitiveness research. Furthermore, this study allows us to deduct the significant variables that influence the determination of hotel’s competitors. Lastly, the discussed experiences in this article found that the hotel competitors are influenced by several factors with different rates.

Keywords: competitiveness, e-reputation, hotels' competitors, online hotel’ review, principal component analysis, statistical modeling

Procedia PDF Downloads 117
90 Meteosat Second Generation Image Compression Based on the Radon Transform and Linear Predictive Coding: Comparison and Performance

Authors: Cherifi Mehdi, Lahdir Mourad, Ameur Soltane

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Image compression is used to reduce the number of bits required to represent an image. The Meteosat Second Generation satellite (MSG) allows the acquisition of 12 image files every 15 minutes. Which results a large databases sizes. The transform selected in the images compression should contribute to reduce the data representing the images. The Radon transform retrieves the Radon points that represent the sum of the pixels in a given angle for each direction. Linear predictive coding (LPC) with filtering provides a good decorrelation of Radon points using a Predictor constitute by the Symmetric Nearest Neighbor filter (SNN) coefficients, which result losses during decompression. Finally, Run Length Coding (RLC) gives us a high and fixed compression ratio regardless of the input image. In this paper, a novel image compression method based on the Radon transform and linear predictive coding (LPC) for MSG images is proposed. MSG image compression based on the Radon transform and the LPC provides a good compromise between compression and quality of reconstruction. A comparison of our method with other whose two based on DCT and one on DWT bi-orthogonal filtering is evaluated to show the power of the Radon transform in its resistibility against the quantization noise and to evaluate the performance of our method. Evaluation criteria like PSNR and the compression ratio allows showing the efficiency of our method of compression.

Keywords: image compression, radon transform, linear predictive coding (LPC), run lengthcoding (RLC), meteosat second generation (MSG)

Procedia PDF Downloads 418
89 Tool Wear Monitoring of High Speed Milling Based on Vibratory Signal Processing

Authors: Hadjadj Abdechafik, Kious Mecheri, Ameur Aissa

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The objective of this study is to develop a process of treatment of the vibratory signals generated during a horizontal high speed milling process without applying any coolant in order to establish a monitoring system able to improve the machining performance. Thus, many tests were carried out on the horizontal high speed centre (PCI Météor 10), in given cutting conditions, by using a milling cutter with only one insert and measured its frontal wear from its new state that is considered as a reference state until a worn state that is considered as unsuitable for the tool to be used. The results obtained show that the first harmonic follow well the evolution of frontal wear, on another hand a wavelet transform is used for signal processing and is found to be useful for observing the evolution of the wavelet approximations through the cutting tool life. The power and the Root Mean Square (RMS) values of the wavelet transformed signal gave the best results and can be used for tool wear estimation. All this features can constitute the suitable indicators for an effective detection of tool wear and then used for the input parameters of an online monitoring system. Although we noted the remarkable influence of the machining cycle on the quality of measurements by the introduction of a bias on the signal, this phenomenon appears in particular in horizontal milling and in the majority of studies is ignored.

Keywords: flank wear, vibration, milling, signal processing, monitoring

Procedia PDF Downloads 596
88 Jeddah’s Hydraulic Protection Systems and the Management of Flood: An Assessment

Authors: Faouzi Ameur, Atef Belhaj Ali

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Located in the South-west of Saudi Arabia, Jeddah is more than a harbor. It is a big city of the Red Sea and the second town of Saudi Arabia, after Riyadh the capital. Jeddah profits from several economic assets due especially to its transit position towards the high sacred places of Islam like Mecca and Medina. During summer, this metropolis is transformed into a political capital and a tourist resort for foreigners and Saudis alike. The city of Jeddah was affected by serious sudden floods; two great ones took place in 2009, and in 2011. The human and material tools were considerable, since these events caused the death to hundreds of people, damaged thousands of buildings built on basins slopes, which, however had the authorizations necessary. To cope with these natural disasters, several urban hydraulic measures were undertaken like building dams and canals to collect surface waters. These urban measures aimed at the protection of inhabitants and belongings against the risks of floods as well as the interception and the drainage of streams. Although these protection measures are important, expensive, and effective, they are no longer enough or effective to cope with the evolution of the natural disasters that the city of Jeddah is constantly exposed to. These protective hydraulic measures did not make it possible to reach risk zero situations. They transferred the damages towards other zones. This paper purports to study the protection network systems in Jeddah and to understand their various impacts during floods on the city and on its inhabitants.

Keywords: Jeddah, Saudi Arabia, urbanization, hydraulic protection

Procedia PDF Downloads 248
87 Transferring World Athletic Championship-Winning Principles to Entrepreneurship: The Case of Abdelkader El Mouaziz

Authors: Abderrahman Hassi, Omar Bacadi, Khaoula Zitouni

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Abdelkader El Mouaziz is a Moroccan long-distance runner with a career-best time of 2:06:46 in the Chicago Marathon. El Mouaziz is a winner of the Madrid Marathon in 1994, the London Marathon in 1999 and 2001, as well as the New York Marathon in 2001. While he was playing for the Moroccan national team, he used to train in the Ifrane-Azrou region owing to its altitude, fresh forests, non-polluted air and quietness. After winning so many international competitions and retiring, he left his native Casablanca and went back to the Ifrane-Azrou region and started a business that employs ten people. In March 2010, El Mouaziz opened a bed and breakfast called Tourtite with a nice view on the mountain near the city of Ifrane in the way to Azrou. He wanted to give back to the region that helped him become a sport legend. His management style is not different than his sport style: performance and competitiveness combined with fair play. The objective of the present case study is to further enhance the understanding of the dynamics of transferring athletic championship-winning principles to entrepreneurial activities. The case study is a real-life situation and experience designed to provoke and stimulate reflections about a particular approach of management, especially for start-up businesses.

Keywords: sport, winning principles, entrepreneurship, Abdelkader El Mouaziz

Procedia PDF Downloads 276
86 Neural Networks Models for Measuring Hotel Users Satisfaction

Authors: Asma Ameur, Dhafer Malouche

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Nowadays, user comments on the Internet have an important impact on hotel bookings. This confirms that the e-reputation issue can influence the likelihood of customer loyalty to a hotel. In this way, e-reputation has become a real differentiator between hotels. For this reason, we have a unique opportunity in the opinion mining field to analyze the comments. In fact, this field provides the possibility of extracting information related to the polarity of user reviews. This sentimental study (Opinion Mining) represents a new line of research for analyzing the unstructured textual data. Knowing the score of e-reputation helps the hotelier to better manage his marketing strategy. The score we then obtain is translated into the image of hotels to differentiate between them. Therefore, this present research highlights the importance of hotel satisfaction ‘scoring. To calculate the satisfaction score, the sentimental analysis can be manipulated by several techniques of machine learning. In fact, this study treats the extracted textual data by using the Artificial Neural Networks Approach (ANNs). In this context, we adopt the aforementioned technique to extract information from the comments available in the ‘Trip Advisor’ website. This actual paper details the description and the modeling of the ANNs approach for the scoring of online hotel reviews. In summary, the validation of this used method provides a significant model for hotel sentiment analysis. So, it provides the possibility to determine precisely the polarity of the hotel users reviews. The empirical results show that the ANNs are an accurate approach for sentiment analysis. The obtained results show also that this proposed approach serves to the dimensionality reduction for textual data’ clustering. Thus, this study provides researchers with a useful exploration of this technique. Finally, we outline guidelines for future research in the hotel e-reputation field as comparing the ANNs with other technique.

Keywords: clustering, consumer behavior, data mining, e-reputation, machine learning, neural network, online hotel ‘reviews, opinion mining, scoring

Procedia PDF Downloads 136
85 Power Quality Improvement Using Interval Type-2 Fuzzy Logic Controller for Five-Level Shunt Active Power Filter

Authors: Yousfi Abdelkader, Chaker Abdelkader, Bot Youcef

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This article proposes a five-level shunt active power filter for power quality improvement using a interval type-2 fuzzy logic controller (IT2 FLC). The reference compensating current is extracted using the P-Q theory. The majority of works previously reported are based on two-level inverters with a conventional Proportional integral (PI) controller, which requires rigorous mathematical modeling of the system. In this paper, a IT2 FLC controlled five-level active power filter is proposed to overcome the problem associated with PI controller. The IT2 FLC algorithm is applied for controlling the DC-side capacitor voltage as well as the harmonic currents of the five-level active power filter. The active power filter with a IT2 FLC is simulated in MATLAB Simulink environment. The simulated response shows that the proposed shunt active power filter controller has produced a sinusoidal supply current with low harmonic distortion and in phase with the source voltage.

Keywords: power quality, shunt active power filter, interval type-2 fuzzy logic controller (T2FL), multilevel inverter

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84 Digimesh Wireless Sensor Network-Based Real-Time Monitoring of ECG Signal

Authors: Sahraoui Halima, Dahani Ameur, Tigrine Abedelkader

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DigiMesh technology represents a pioneering advancement in wireless networking, offering cost-effective and energy-efficient capabilities. Its inherent simplicity and adaptability facilitate the seamless transfer of data between network nodes, extending the range and ensuring robust connectivity through autonomous self-healing mechanisms. In light of these advantages, this study introduces a medical platform harnessed with DigiMesh wireless network technology characterized by low power consumption, immunity to interference, and user-friendly operation. The primary application of this platform is the real-time, long-distance monitoring of Electrocardiogram (ECG) signals, with the added capacity for simultaneous monitoring of ECG signals from multiple patients. The experimental setup comprises key components such as Raspberry Pi, E-Health Sensor Shield, and Xbee DigiMesh modules. The platform is composed of multiple ECG acquisition devices labeled as Sensor Node 1 and Sensor Node 2, with a Raspberry Pi serving as the central hub (Sink Node). Two communication approaches are proposed: Single-hop and multi-hop. In the Single-hop approach, ECG signals are directly transmitted from a sensor node to the sink node through the XBee3 DigiMesh RF Module, establishing peer-to-peer connections. This approach was tested in the first experiment to assess the feasibility of deploying wireless sensor networks (WSN). In the multi-hop approach, two sensor nodes communicate with the server (Sink Node) in a star configuration. This setup was tested in the second experiment. The primary objective of this research is to evaluate the performance of both Single-hop and multi-hop approaches in diverse scenarios, including open areas and obstructed environments. Experimental results indicate the DigiMesh network's effectiveness in Single-hop mode, with reliable communication over distances of approximately 300 meters in open areas. In the multi-hop configuration, the network demonstrated robust performance across approximately three floors, even in the presence of obstacles, without the need for additional router devices. This study offers valuable insights into the capabilities of DigiMesh wireless technology for real-time ECG monitoring in healthcare applications, demonstrating its potential for use in diverse medical scenarios.

Keywords: DigiMesh protocol, ECG signal, real-time monitoring, medical platform

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83 Nasopharyngeal Cancer in Children and Adolescents: Experience of Emir Abdelkader Cancer Center of Oran Algeria

Authors: Taleb L., Benarbia M., Brahmi M., Belmiloud H., Boukerche A.

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Introduction and purpose of the study: Cavum cancer in children and adolescents is rare and represents 8% of all nasopharyngeal cancers treated in our department. Our objective is to study its epidemiological, clinical, therapeutic, and evolutionary particularities. Material and methods: Retrospective study of 39 patients under 20 years old, treated for undifferentiated non-metastatic carcinoma of the nasopharynx at the Emir Abdelkader Cancer Center between 2014 and 2020. Results and statistical analysis: Median age was 14 years [7-19 years], with a sex ratio of 2.9. The median time to diagnosis was 5.6 months [1 to 14 months], the circumstances of the discovery of which were dominated by lymph node syndrome in 43.6% of cases (n=17) followed by a rhinological syndrome in 30.8% of cases (n=13). The tumor stage was T1 for two patients (5.1%), T2 for 8 (20.5%), T3 for 9 (23.1%), T4 for 20 (51.3%), N0 for 2 (5 .1%) N1 for 4 (10.3%), N2 for 28 (71.8%) and N3 for 5 (12.8%). All patients received induction chemotherapy followed by concomitant radiotherapy with cisplatin. The dose of irradiation delivered to the cavum and adenopathies was 66 Gy with fractionation of 2 Gy per session in 69.2% of cases (n=27) and 1.8 Gy in 30.8% of cases (n=12). With a median follow-up of 51 months (15 to 97 months), the locoregional, metastatic, specific, and overall relapse-free survival rates at five years were 91.1%, 73.5%, 66.1%, and 68.4, respectively. Conclusion: Chemotherapy and radiotherapy treatment of cavum cancer in children and adolescents has allowed excellent locoregional control despite the advanced stage of the disease. However, the frequency of metastatic relapses could justify the possible use of systemic maintenance treatment.

Keywords: cancer, nasopharynx, radiotherapy, chemotherapy, survival

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82 Phosphorous Acid: An Efficient and Recyclable Liquid Catalyst for the Synthesis of α-Aminophosphonates

Authors: Hellal Abdelkader, Chafaa Salah, Touafri Lasnouni

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A simple, efficient and general method has been developed for the high diastereoselective synthesis of diethyl α-aminophosphonates in water through “one-pot” three-component reaction of aromatic aldehydes, aminophenols and dialkyl phosphites in the presence of a low catalytic amount (10mol%) of phosphorous acid as highly stable catalyst is described.

Keywords: DFT, HOMO-LUMO, phosphonic acid, aminophenols

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81 Place of Radiotherapy in the Treatment of Intracranial Meningiomas: Experience of the Cancer Center Emir Abdelkader of Oran Algeria

Authors: Taleb L., Benarbia M., Boutira F. M., Allam H., Boukerche A.

Abstract:

Introduction and purpose of the study: Meningiomas are the most common non-glial intracranial tumors in adults, accounting for approximately 30% of all central nervous system tumors. The aim of our study is to determine the epidemiological, clinical, therapeutic, and evolutionary characteristics of a cohort of patients with intracranial meningioma treated with radiotherapy at the Emir Abdelkader Cancer Center in Oran. Material and methods: This is a retrospective study of 44 patients during the period from 2014 to 2020. The overall survival and relapse-free survival curves were calculated using the Kaplan-Meier method. Results and statistical analysis: The median age of the patients was 49 years [21-76 years] with a clear female predominance (sex ratio=2.4). The average diagnostic delay was seven months [2 to 24 months], the circumstances of the discovery of which were dominated by headaches in 54.5% of cases (n=24), visual disturbances in 40.9% (n=18), and motor disorders in 15.9% (n=7). The seat of the tumor was essentially at the level of the base of the skull in 52.3% of patients (n=23), including 29.5% (n=13) at the level of the cavernous sinus, 27.3% (n=12) at the parasagittal level and 20.5% (n=9) at the convexity. The diagnosis was confirmed surgically in 36 patients (81.8%) whose anatomopathological study returned in favor of grades I, II, and III in respectively 40.9%, 29.5%, and 11.4% of the cases. Radiotherapy was indicated postoperatively in 45.5% of patients (n=20), exclusive in 27.3% (n=12) and after tumor recurrence in 27.3% of cases (n=18). The irradiation doses delivered were as follows: 50 Gy (20.5%), 54 Gy (65.9%), and 60 Gy (13.6%). With a median follow-up of 69 months, the probabilities of relapse-free survival and overall survival at three years are 93.2% and 95.4%, respectively, whereas they are 71.2% and 80.7% at five years. Conclusion: Meningiomas are common primary brain tumors. Most often benign but can also progress aggressively. Their treatment is essentially surgical, but radiotherapy retains its place in specific situations, allowing good tumor control and overall survival.

Keywords: diagnosis, meningioma, surgery, radiotherapy, survival

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80 Control and Automation of Sensors in Metering System of Fluid

Authors: Abdelkader Harrouz, Omar Harrouz, Ali Benatiallah

Abstract:

This paper is to present the essential definitions, roles and characteristics of automation of metering system. We discuss measurement, data acquisition and metrological control of a signal sensor from dynamic metering system. After that, we present control of instruments of metering system of fluid with more detailed discussions to the reference standards.

Keywords: communication, metering, computer, sensor

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79 Agglomerative Hierarchical Clustering Using the Tθ Family of Similarity Measures

Authors: Salima Kouici, Abdelkader Khelladi

Abstract:

In this work, we begin with the presentation of the Tθ family of usual similarity measures concerning multidimensional binary data. Subsequently, some properties of these measures are proposed. Finally, the impact of the use of different inter-elements measures on the results of the Agglomerative Hierarchical Clustering Methods is studied.

Keywords: binary data, similarity measure, Tθ measures, agglomerative hierarchical clustering

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78 Investigation Of Eugan's, Optical Properties With Dft

Authors: Bahieddine. Bouabdellah, Benameur. Amiri, Abdelkader.nouri

Abstract:

Europium-doped gallium nitride (EuGaN) is a promising material for optoelectronic and thermoelectric devices. This study investigates its optical properties using density functional theory (DFT) with the FP-LAPW method and MBJ+U correction. The simulation substitutes a gallium atom with europium in a hexagonal GaN lattice (6% doping). Distinct absorption peaks are observed in the optical analysis. These results highlight EuGaN's potential for various applications and pave the way for further research on rare earth-doped materials.

Keywords: eugan, fp-lapw, dft, wien2k, mbj hubbard

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77 Intelligent Control Design of Car Following Behavior Using Fuzzy Logic

Authors: Abdelkader Merah, Kada Hartani

Abstract:

A reference model based control approach for improving behavior following car is proposed in this paper. The reference model is nonlinear and provides dynamic solutions consistent with safety constraints and comfort specifications. a robust fuzzy logic based control strategy is further proposed in this paper. A set of simulation results showing the suitability of the proposed technique for various demanding cenarios is also included in this paper.

Keywords: reference model, longitudinal control, fuzzy logic, design of car

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76 Global Optimization: The Alienor Method Mixed with Piyavskii-Shubert Technique

Authors: Guettal Djaouida, Ziadi Abdelkader

Abstract:

In this paper, we study a coupling of the Alienor method with the algorithm of Piyavskii-Shubert. The classical multidimensional global optimization methods involves great difficulties for their implementation to high dimensions. The Alienor method allows to transform a multivariable function into a function of a single variable for which it is possible to use efficient and rapid method for calculating the the global optimum. This simplification is based on the using of a reducing transformation called Alienor.

Keywords: global optimization, reducing transformation, α-dense curves, Alienor method, Piyavskii-Shubert algorithm

Procedia PDF Downloads 499