Search results for: Houssam Hijazi

Authors: Houssam Hijazi, Laurent Cantrel, Jean-François Paul

Abstract:

Periodic DFT calculations were performed to study the chemistry of CsI particles and the possible release of volatile iodine from CsI surfaces for nuclear safety interest. The results show that water adsorbs at low temperature associatively on the (011) surface of CsI, while water desorbs at higher temperatures. On the other hand, removing iodine species from the surface requires oxidizing the surface one time for each removed iodide atom. The activation energy of removing I₂ from the surface in the presence of two OH is 1,2 eV.

Keywords: aerosols, CSI, reactivity, DFT, water adsorption

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Authors: Tagreed Alzahrani

Abstract:

The syntax of quantifiers has received much attention by linguists, philosophers and logicians within different frameworks and in various languages. However, the syntax of Arabic quantifiers has received limited attention in the literature, especially in relation to floating quantifiers. There have been a few discussions of floating quantifiers in Modern Standard Arabic (henceforth, MSA), although the analysis and the properties of their counterparts in other Saudi dialects are rare. Therefore, the aim of the paper is to provide a clear description of floating quantifiers (FQs) in Hijazi dialect (henceforth, HA) by utilising the following approaches: the adverbial approach, and the derivational (stranding) analysis. For a long time, Linguists have tried to explain the floating quantifiers’ phenomenon, as exemplified in the following sentences: 1. All the friends have watched the movie. 2. The friends have all watched the movie. The adverbial approach assumes that the floating quantifier is a type of adverb, because it occupies the adverbial position next to the verb. Thus, the subject in the first example is all the friends and the subject in the second example is the friends with all becoming an adverb, as it is located in an adverbial position. However, in stranding analysis, it is argued that the floating quantifier becomes stranded when its complement has moved to a higher position in the sentence [SPEC, TP]. Therefore, both sentences have the same subject all the friends, although in second example the friends has moved to a higher position and has stranded the quantifier all. The paper will investigate the floating quantifiers in HA using both approaches. The analysis will show that neither view is entirely successful in providing a unified account for FQs in HA.

Keywords: floating quantifier, adverbial analysis, stranding approach, universal quantifier

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Authors: Houssam A. Toutanji, Meng Han

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This study focuses on the development of a fracture mechanics based-model that predicts the debonding behavior of FRP strengthened RC beams. In this study, a database includes 351 concrete prisms bonded with FRP plates tested in single and double shear were prepared. The existing fracture-mechanics-based models are applied to this database. Unfortunately the properties of adhesive layer, especially a soft adhesive layer, used on the specimens in the existing studies were not always able to found. Thus, the new model’s proposal was based on fifteen newly conducted pullout tests and twenty four data selected from two independent existing studies with the application of a soft adhesive layers and the availability of adhesive properties.

Keywords: carbon fiber composite materials, interface response, fracture characteristics, maximum shear stress, ultimate transferable load

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Authors: M. Hijazi, A. Zeki, A. Ismail

Abstract:

An enormous amount of valuable human knowledge is preserved in documents. The rapid growth in the number of machine-readable documents for public or private access requires the use of automatic text classification. Text classification can be defined as assigning or structuring documents into a defined set of classes known in advance. Arabic text classification methods have emerged as a natural result of the existence of a massive amount of varied textual information written in the Arabic language on the web. This paper presents a review on the published researches of Arabic Text Classification using classical data representation, Bag of words (BoW), and using conceptual data representation based on semantic resources such as Arabic WordNet and Wikipedia.

Keywords: Arabic text classification, Arabic WordNet, bag of words, conceptual representation, semantic relations

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Authors: Kamal Chafiq, Youssef Hadzine, Adel Elmekkaoui, Othmane Benlenda, Houssam Rajad, Soukaina Wakrim, Hicham Nassik

Abstract:

Guillain-Barré syndrome/Miller Fishe syndrome (GBS/MFS) overlap syndrome is an extremely rare variant of Guillain-Barré syndrome (GBS) in which Miller Fisher syndrome (MFS) coexists with other characteristics of GBS, such as limb weakness, paresthesia, and facial paralysis. We report the clinical case of a 12-year-old patient, with no pathological history, who acutely presents with ophthalmoplegia, areflexia, facial diplegia, and swallowing and phonation disorders, followed by progressive, descending, and symmetrical paresis affecting first the upper limbs and then the lower limbs. An albuminocytological dissociation was found in the cerebrospinal fluid study. Magnetic resonance imaging of the spinal cord showed enhancement and thickening of the cauda equina roots. The patient was treated with immunoglobulins with a favorable clinical outcome.

Keywords: Guillain-Barré syndrome, Miller Fisher syndrome, overlap syndrome, anti-GQ1b antibodies

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Authors: Huy Hieu Pham, Houssam Salmane, Louahdi Khoudour, Alain Crouzil, Pablo Zegers, Sergio Velastin

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We present a deep learning-based multitask framework for joint 3D human pose estimation and action recognition from color video sequences. Our approach proceeds along two stages. In the first, we run a real-time 2D pose detector to determine the precise pixel location of important key points of the body. A two-stream neural network is then designed and trained to map detected 2D keypoints into 3D poses. In the second, we deploy the Efficient Neural Architecture Search (ENAS) algorithm to find an optimal network architecture that is used for modeling the Spatio-temporal evolution of the estimated 3D poses via an image-based intermediate representation and performing action recognition. Experiments on Human3.6M, Microsoft Research Redmond (MSR) Action3D, and Stony Brook University (SBU) Kinect Interaction datasets verify the effectiveness of the proposed method on the targeted tasks. Moreover, we show that our method requires a low computational budget for training and inference.

Keywords: human action recognition, pose estimation, D-CNN, deep learning

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Authors: Amanda M. Tadini, Houssam Hajjoul, Gustavo Nicolodelli, Stéphane Mounier, Célia R. Montes, Débora M. B. P. Milori

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Soil organic matter (SOM) plays an important role in maintaining soil productivity and accounting for the promotion of biological diversity. The main components of the SOM are the humic substances which can be fractionated according to its solubility in humic acid (HA), fulvic acids (FA) and humin (HU). The determination of the chemical properties of organic matter as well as its interaction with metallic species is an important tool for understanding the structure of the humic fractions. Fluorescence spectroscopy has been studied as a source of information about what is happening at the molecular level in these compounds. Specially, soils of Amazon region are an important ecosystem of the planet. The aim of this study is to understand the molecular and structural composition of HA samples from Spodosol of Amazonia using the fluorescence Emission-Excitation Matrix (EEM) and Time Resolved Fluorescence Spectroscopy (TRFS). The results showed that the samples of HA showed two fluorescent components; one has a more complex structure and the other one has a simpler structure, which was also seen in TRFS through the evaluation of each sample lifetime. Thus, studies of this nature become important because it aims to evaluate the molecular and structural characteristics of the humic fractions in the region that is considered as one of the most important regions in the world, the Amazon.

Keywords: Amazonian soil, characterization, fluorescence, humic acid, lifetime

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Authors: Ali J. Ghandour, Houssam A. Krayem, Abedelkarim A. Jezzini

Abstract:

High-resolution satellite images and remote sensing can provide global information in a fast way compared to traditional methods of data collection. Under such high resolution, a road is not a thin line anymore. Objects such as cars and trees are easily identifiable. Automatic vehicles enumeration can be considered one of the most important applications in traffic management. In this paper, autonomous vehicle detection and classification approach in highway environment is proposed. This approach consists mainly of three stages: (i) first, a set of preprocessing operations are applied including soil, vegetation, water suppression. (ii) Then, road networks detection and delineation is implemented using built-up area index, followed by several morphological operations. This step plays an important role in increasing the overall detection accuracy since vehicles candidates are objects contained within the road networks only. (iii) Multi-level Otsu segmentation is implemented in the last stage, resulting in vehicle detection and classification, where detected vehicles are classified into cars and trucks. Accuracy assessment analysis is conducted over different study areas to show the great efficiency of the proposed method, especially in highway environment.

Keywords: remote sensing, object identification, vehicle and road extraction, vehicle and road features-based classification

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Authors: Ghadeer Jalloul, Nour Hijazi, Cassia Boyadjian, Hussein Awala, Mohammad N. Ahmad, ‎Ahmad Albadarin

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In this study, we applied Fe-sensitized TiO₂ supported over embryonic Beta zeolite (BEA) zeolite ‎for the photocatalytic degradation of Tetracycline (TC) antibiotic under visible light. Four different ‎samples having 20, 40, 60, and 100% w/w as a ratio of TiO₂/BEA were prepared. The ‎immobilization of solgel TiO₂ (33 m²/g) over BEA (390 m²/g) increased its surface area to (227 ‎m²/g) and enhanced its adsorption capacity from 8% to 19%. To expand the activity of TiO₂ ‎photocatalyst towards the visible light region (λ>380 nm), we explored two different metal ‎sensitization techniques with Iron ions (Fe³⁺). In the ion-exchange method, the substitutional cations ‎in the zeolite in TiO₂/BEA were exchanged with (Fe³⁺) in an aqueous solution of FeCl₃. In the ‎doping technique, solgel TiO₂ was doped with (Fe³⁺) from FeCl₃ precursor during its synthesis and ‎before its immobilization over BEA. (Fe-TiO₂/BEA) catalysts were characterized using SEM, XRD, ‎BET, UV-VIS DRS, and FTIR. After testing the performance of the various ion-exchanged catalysts ‎under blue and white lights, only (Fe-TiO₂/BEA 60%) showed better activity as compared to pure ‎TiO₂ under white light with 100 ppm initial catalyst concentration and 20 ppm TC concentration. As ‎compared to ion-exchanged (Fe-TiO₂/BEA), doped (Fe-TiO₂/BEA) resulted in higher photocatalytic ‎efficiencies under blue and white lights. The 3%-Fe-doped TiO₂/BEA removed 92% of TC ‎compared to 54% by TiO₂ under white light. The catalysts were also tested under real solar ‎irradiations. This improvement in the photocatalytic performance of TiO₂ was due to its higher ‎adsorption capacity due to BEA support combined with the presence of Iron ions that enhance the ‎visible light absorption and minimize the recombination effect by the charge carriers. ‎

Keywords: Tetracycline, photocatalytic degradation, immobilized TiO₂, zeolite, iron-doped TiO₂, ion-exchange

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Authors: Jamil Hijazi, Stirling Howieson

Abstract:

Reducing energy consumption and CO₂ emissions are probably the greatest challenge now facing mankind. From considerations surrounding global warming and CO₂ production, it has to be recognized that oil is a finite resource and the KSA like many other oil-rich countries will have to start to consider a horizon where hydro-carbons are not the dominant energy resource. The employment of hybrid ground-cooling pipes in combination with the black body solar collection and radiant night cooling systems may have the potential to displace a significant proportion of oil currently used to run conventional air conditioning plant. This paper presents an investigation into the viability of such hybrid systems with the specific aim of reducing cooling load and carbon emissions while providing all year-round thermal comfort in a typical Saudi Arabian urban housing block. Soil temperatures were measured in the city of Jeddah. A parametric study then was carried out by computational simulation software (DesignBuilder) that utilized the field measurements and predicted the cooling energy consumption of both a base case and an ideal scenario (typical block retro-fitted with insulation, solar shading, ground pipes integrated with hypocaust floor slabs/stack ventilation and radiant cooling pipes embed in floor). Initial simulation results suggest that careful ‘ecological design’ combined with hybrid radiant and ground pipe cooling techniques can displace air conditioning systems, producing significant cost and carbon savings (both capital and running) without appreciable deprivation of amenity.

Keywords: cooling load, energy efficiency, ground pipe cooling, hybrid cooling strategy, hydronic radiant systems, low carbon emission, passive designs, thermal comfort

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Authors: Jamil Hijazi, Stirling Howieson

Abstract:

Over one-quarter of the Kingdom of Saudi Arabia’s total oil production (2.8 million barrels a day) is used for electricity generation. The built environment is estimated to consume 77% of the total energy production. Of this amount, air conditioning systems consume about 80%. Apart from considerations surrounding global warming and CO2 production it has to be recognised that oil is a finite resource and the KSA like many other oil rich countries will have to start to consider a horizon where hydro-carbons are not the dominant energy resource. The employment of hybrid ground cooling pipes in combination with black body solar collection and radiant night cooling systems may have the potential to displace a significant proportion of oil currently used to run conventional air conditioning plant. This paper presents an investigation into the viability of such hybrid systems with the specific aim of reducing carbon emissions while providing all year round thermal comfort in a typical Saudi Arabian urban housing block. At the outset air and soil temperatures were measured in the city of Jeddah. A parametric study then was carried out by computational simulation software (Design Builder) that utilised the field measurements and predicted the cooling energy consumption of both a base case and an ideal scenario (typical block retro-fitted with insulation, solar shading, ground pipes integrated with hypocaust floor slabs/ stack ventilation and radiant cooling pipes embed in floor).Initial simulation results suggest that careful ‘ecological design’ combined with hybrid radiant and ground pipe cooling techniques can displace air conditioning systems, producing significant cost and carbon savings (both capital and running) without appreciable deprivation of amenity.

Keywords: energy efficiency, ground pipe, hybrid cooling, radiative cooling, thermal comfort

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Authors: Laura Micheli, Majd Hijazi, Mahmoud Faytarouni

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The damage reported by oil and gas industrial facilities revealed the utmost vulnerability of steel liquid storage tanks to seismic events. The failure of steel storage tanks may yield devastating and long-lasting consequences on built and natural environments, including the release of hazardous substances, uncontrolled fires, and soil contamination with hazardous materials. It is, therefore, fundamental to reliably predict the damage that steel liquid storage tanks will likely experience under future seismic hazard events. The seismic performance of steel liquid storage tanks is usually assessed using vulnerability curves obtained from the numerical simulation of a tank under different hazard scenarios. However, the computational demand of high-fidelity numerical simulation models, such as finite element models, makes the vulnerability assessment of liquid storage tanks time-consuming and often impractical. As a solution, this paper presents a surrogate model-based strategy for predicting seismic-induced damage in steel liquid storage tanks. In the proposed strategy, the surrogate model is leveraged to reduce the computational demand of time-consuming numerical simulations. To create the data set for training the surrogate model, field damage data from past earthquakes reconnaissance surveys and reports are collected. Features representative of steel liquid storage tank characteristics (e.g., diameter, height, liquid level, yielding stress) and seismic excitation parameters (e.g., peak ground acceleration, magnitude) are extracted from the field damage data. The collected data are then utilized to train a surrogate model that maps the relationship between tank characteristics, seismic hazard parameters, and seismic-induced damage via a data-driven surrogate model. Different types of surrogate algorithms, including naïve Bayes, k-nearest neighbors, decision tree, and random forest, are investigated, and results in terms of accuracy are reported. The model that yields the most accurate predictions is employed to predict future damage as a function of tank characteristics and seismic hazard intensity level. Results show that the proposed approach can be used to estimate the extent of damage in steel liquid storage tanks, where the use of data-driven surrogates represents a viable alternative to computationally expensive numerical simulation models.

Keywords: damage prediction , data-driven model, seismic performance, steel liquid storage tanks, surrogate model

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Authors: Ayman Hijazi, Witold Kwapinski, J. J. Leahy

Abstract:

Finding a sustainable alternative energy to fossil fuel is an urgent need as various environmental challenges in the world arise. Therefore, formic acid (FA) decomposition has been an attractive field that lies at the center of biomass platform, comprising a potential pool of hydrogen energy that stands as a new energy vector. Liquid FA features considerable volumetric energy density of 6.4 MJ/L and a specific energy density of 5.3 MJ/Kg that qualifies it in the prime seat as an energy source for transportation infrastructure. Additionally, the increasing research interest in FA decomposition is driven by the need of in-situ H2 production, which plays a key role in the hydrogenation reactions of biomass into higher value components. It is reported elsewhere in literature that catalytic decomposition of FA is usually performed in poorly designed setup using simple glassware under magnetic stirring, thus demanding further energy investment to retain the used catalyst. it work suggests an approach that integrates designing a novel catalyst featuring magnetic property with a robust setup that minimizes experimental & measurement discrepancies. One of the most prominent active species for dehydrogenation/hydrogenation of biomass compounds is palladium. Accordingly, we investigate the potential of engrafting palladium metal onto functionalized magnetic nanoparticles as a heterogeneous catalyst to favor the production of CO-free H2 gas from FA. Using ordinary magnet to collect the spent catalyst renders core-shell magnetic nanoparticles as the backbone of the process. Catalytic experiments were performed in a jacketed batch reactor equipped with an overhead stirrer under inert medium. Through a novel approach, FA is charged into the reactor via high-pressure positive displacement pump at steady state conditions. The produced gas (H2+CO2) was measured by connecting the gas outlet to a measuring system based on the amount of the displaced water. The novelty of this work lies in designing a very responsive catalyst, pumping consistent amount of FA into a sealed reactor running at steady state mild temperatures, and continuous gas measurement, along with collecting the used catalyst without the need for centrifugation. Catalyst characterization using TEM, XRD, SEM, and CHN elemental analyzer provided us with details of catalyst preparation and facilitated new venues to alter the nanostructure of the catalyst framework. Consequently, the introduction of amine groups has led to appreciable improvements in terms of dispersion of the doped metals and eventually attaining nearly complete conversion (100%) of FA after 7 hours. The relative importance of the process parameters such as temperature (35-85°C), stirring speed (150-450rpm), catalyst loading (50-200mgr.), and Pd doping ratio (0.75-1.80wt.%) on gas yield was assessed by a Taguchi design-of-experiment based model. Experimental results showed that operating at lower temperature range (35-50°C) yielded more gas while the catalyst loading and Pd doping wt.% were found to be the most significant factors with a P-values 0.026 & 0.031, respectively.

Keywords: formic acid decomposition, green catalysis, hydrogen, mesoporous silica, process optimization, nanoparticles

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Authors: Ayman Hijazi, Witold Kwapinski, J. J. Leahy

Abstract:

Finding a sustainable alternative energy to fossil fuel is an urgent need as various environmental challenges in the world arise. Therefore, formic acid (FA) decomposition has been an attractive field that lies at the center of the biomass platform, comprising a potential pool of hydrogen energy that stands as a distinct energy vector. Liquid FA features considerable volumetric energy density of 6.4 MJ/L and a specific energy density of 5.3 MJ/Kg that qualifies it in the prime seat as an energy source for transportation infrastructure. Additionally, the increasing research interest in FA decomposition is driven by the need for in-situ H₂ production, which plays a key role in the hydrogenation reactions of biomass into higher-value components. It is reported elsewhere in the literature that catalytic decomposition of FA is usually performed in poorly designed setups using simple glassware under magnetic stirring, thus demanding further energy investment to retain the used catalyst. Our work suggests an approach that integrates designing a distinct catalyst featuring magnetic properties with a robust setup that minimizes experimental & measurement discrepancies. One of the most prominent active species for the dehydrogenation/hydrogenation of biomass compounds is palladium. Accordingly, we investigate the potential of engrafting palladium metal onto functionalized magnetic nanoparticles as a heterogeneous catalyst to favor the production of CO-free H₂ gas from FA. Using an ordinary magnet to collect the spent catalyst renders core-shell magnetic nanoparticles as the backbone of the process. Catalytic experiments were performed in a jacketed batch reactor equipped with an overhead stirrer under an inert medium. Through a distinct approach, FA is charged into the reactor via a high-pressure positive displacement pump at steady-state conditions. The produced gas (H₂+CO₂) was measured by connecting the gas outlet to a measuring system based on the amount of the displaced water. The uniqueness of this work lies in designing a very responsive catalyst, pumping a consistent amount of FA into a sealed reactor running at steady-state mild temperatures, and continuous gas measurement, along with collecting the used catalyst without the need for centrifugation. Catalyst characterization using TEM, XRD, SEM, and CHN elemental analyzer provided us with details of catalyst preparation and facilitated new venues to alter the nanostructure of the catalyst framework. Consequently, the introduction of amine groups has led to appreciable improvements in terms of dispersion of the doped metals and eventually attaining nearly complete conversion (100%) of FA after 7 hours. The relative importance of the process parameters such as temperature (35-85°C), stirring speed (150-450rpm), catalyst loading (50-200mgr.), and Pd doping ratio (0.75-1.80wt.%) on gas yield was assessed by a Taguchi design-of-experiment based model. Experimental results showed that operating at a lower temperature range (35-50°C) yielded more gas, while the catalyst loading and Pd doping wt.% were found to be the most significant factors with P-values 0.026 & 0.031, respectively.

Keywords: formic acid decomposition, green catalysis, hydrogen, mesoporous silica, process optimization, nanoparticles

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