Search results for: Mais Haj Qasem

Authors: Mais Haj Qasem, Maen M. Al Assaf, Ali Rodan

Abstract:

Parallel hybrid storage systems consist of a hierarchy of different storage devices that vary in terms of data reading speed performance. As we ascend in the hierarchy, data reading speed becomes faster. Thus, migrating the application’ important data that will be accessed in the near future to the uppermost level will reduce the application I/O waiting time; hence, reducing its execution elapsed time. In this research, we implement trace-driven two-levels parallel hybrid storage system prototype that consists of HDDs and SSDs. The prototype uses data mining techniques to classify application’ data in order to determine its near future data accesses in parallel with the its on-demand request. The important data (i.e. the data that the application will access in the near future) are continuously migrated to the uppermost level of the hierarchy. Our simulation results show that our data migration approach integrated with data mining techniques reduces the application execution elapsed time when using variety of traces in at least to 22%.

Keywords: Data mining, hybrid storage system, recurrent neural network, support vector machine.

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Authors: Qasem M. Al-Mdallal

Abstract:

This paper presents results obtained from the numerical solution for the flow past an oscillating circular cylinder at Reynolds number of 200. The frequency of oscillation was fixed to the vortex shedding frequency from a fixed cylinder, f0, while the amplitudes of oscillations were varied from to 1.1a, where a represents the radius of the cylinder. The response of the flow through the fluid forces acting on the surface of the cylinder are investigated. The lock-on phenomenon is captured at low oscillation amplitudes.

Keywords: Lock-on; streamwise oscillation; transverse oscillation; fluid forces, combined motion

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Authors: Alessandra Agostini, Roberto Boselli, Flavio De Paoli, Riccardo Dondi

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The work presented in this paper focus on Knowledge Management services enabling CSCW (Computer Supported Cooperative Work) applications to provide an appropriate adaptation to the user and the situation in which the user is working. In this paper, we explain how a knowledge management system can be designed to support users in different situations exploiting contextual data, users' preferences, and profiles of involved artifacts (e.g., documents, multimedia files, mockups...). The presented work roots in the experience we had in the MILK project and early steps made in the MAIS project.

Keywords: Information Management Systems, InformationRetrieval, Knowledge Management, Mobile CommunicationSystems.

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Authors: Altayeb Qasem, Tarek Zayed, Zhi Chen

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Statistics Canada stated that the wastewater treatment facilities in most provinces are aging and passes 63% of their useful life in 2007 the highest ratio among public infrastructure assets. Currently, there is no standard condition rating system for wastewater treatment plants that give a specific rating index that describe the physical integrity of different infrastructure elements in the treatment plant and its environmental performance. The main objective of this study is to develop a condition-rating index for wastewater treatment plants mainly activated sludge systems. The proposed WWTP CRI, is based on dividing the treatment plant into its three treatment phases; primary phase, secondary phase and the tertiary phase. The condition-rating index will reflect the infrastructures state for each phase, mainly tanks, pipes, blowers and pumps.

Keywords: Condition rating index, Wastewater treatment plants, AHP- MUAT.

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Authors: Osama H. Ghazal, Isam H. Qasem , M.Riyad H. Abdelkader

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the intension in this work is to investigate the effect of different bending manifold pipes on engine performance for different engine speed. Power, Torque, and BSFC were calculated and presented to show the effect of varying bending pipes angles on them for all cases considered. A special program used to carry out the calculations. A simulation model for 4-cylinders spark ignition engine with turbocharger has been built and calculated. The analysis of the results shows that for 120o angle the torque increases about 40% at 3000 rpm and 25% at 4000 rpm without changing in fuel consumption. For 90o angle the increment in torque is about 10 %. For the same bending angle the increment in brake power is around 40% at 3000 rpm and 25% at 4000 rpm. The increment in fuel consumption is about 12% for 60o and 30% for 90o between (6000- 7000) rpm.

Keywords: bending pipes, inlet manifold, spark ignition engines, performance

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Authors: Qasem A. Al-Radaideh, Emad Abu-Shanab, Shaima Hamam, Hani Abu-Salem

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Online news websites are one of the main and wide areas of Mass Media. Since the nineties several Jordanian newspapers were introduced to the World Wide Web to reach various and large numbers of audiances. Examples of these newspapers that have online version are Al-Rai, Ad-Dustor and AlGhad. Other pure online news websites include Ammon and Rum. The main aim of this study is to evaluate online newspaper websites using two assessment measures; usability and web content. This aim is achieved by using a questionnaire based evaluation which is based on the definition of usability and web content in the ISO document as the standard number 9241-part 11. The results are obtained based on 204 audiences- responses. The results of the research showed that the usability factor is relatively good for all Jordanian online newspapers whereas the web content factor is moderate.

Keywords: Communication and mass media, Jordanian online news websites, website content, website usability.

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Authors: Sultan Noman Qasem

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This paper presents an evolutionary algorithm for solving multi-objective optimization problems-based artificial neural network (ANN). The multi-objective evolutionary algorithm used in this study is genetic algorithm while ANN used is radial basis function network (RBFN). The proposed algorithm named memetic elitist Pareto non-dominated sorting genetic algorithm-based RBFN (MEPGAN). The proposed algorithm is implemented on medical diseases problems. The experimental results indicate that the proposed algorithm is viable, and provides an effective means to design multi-objective RBFNs with good generalization capability and compact network structure. This study shows that MEPGAN generates RBFNs coming with an appropriate balance between accuracy and simplicity, comparing to the other algorithms found in literature.

Keywords: Radial basis function network, Hybrid learning, Multi-objective optimization, Genetic algorithm.

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Authors: Qasem Qananwah, Ahmad Dagamseh, Hiam AlQuran, Khalid Shaker Ibrahim

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Blood pressure helps the physicians greatly to have a deep insight into the cardiovascular system. The determination of individual blood pressure is a standard clinical procedure considered for cardiovascular system problems. The conventional techniques to measure blood pressure (e.g. cuff method) allows a limited number of readings for a certain period (e.g. every 5-10 minutes). Additionally, these systems cause turbulence to blood flow; impeding continuous blood pressure monitoring, especially in emergency cases or critically ill persons. In this paper, the most important statistical features in the photoplethysmogram (PPG) signals were extracted to estimate the blood pressure noninvasively. PPG signals from more than 40 subjects were measured and analyzed and 12 features were extracted. The features were fed to principal component analysis (PCA) to find the most important independent features that have the highest correlation with blood pressure. The results show that the stiffness index means and standard deviation for the beat-to-beat heart rate were the most important features. A model representing both features for Systolic Blood Pressure (SBP) and Diastolic Blood Pressure (DBP) was obtained using a statistical regression technique. Surface fitting is used to best fit the series of data and the results show that the error value in estimating the SBP is 4.95% and in estimating the DBP is 3.99%.

Keywords: Blood pressure, noninvasive optical system, PCA, continuous monitoring.

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Authors: Mais Nijim, Rama Devi Chennuboyina, Waseem Al Aqqad

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Advances in spatial and spectral resolution of satellite images have led to tremendous growth in large image databases. The data we acquire through satellites, radars, and sensors consists of important geographical information that can be used for remote sensing applications such as region planning, disaster management. Spatial data classification and object recognition are important tasks for many applications. However, classifying objects and identifying them manually from images is a difficult task. Object recognition is often considered as a classification problem, this task can be performed using machine-learning techniques. Despite of many machine-learning algorithms, the classification is done using supervised classifiers such as Support Vector Machines (SVM) as the area of interest is known. We proposed a classification method, which considers neighboring pixels in a region for feature extraction and it evaluates classifications precisely according to neighboring classes for semantic interpretation of region of interest (ROI). A dataset has been created for training and testing purpose; we generated the attributes by considering pixel intensity values and mean values of reflectance. We demonstrated the benefits of using knowledge discovery and data-mining techniques, which can be on image data for accurate information extraction and classification from high spatial resolution remote sensing imagery.

Keywords: Remote sensing, object recognition, classification, data mining, waterbody identification, feature extraction.

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Authors: Abobaker Mohammed Qasem Farhan, Shangming Yang, Mohammed Al-Nehari

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Pneumonia is a kind of lung disease that creates congestion in the chest. Such pneumonic conditions lead to loss of life due to the severity of high congestion. Pneumonic lung disease is caused by viral pneumonia, bacterial pneumonia, or COVID-19 induced pneumonia. The early prediction and classification of such lung diseases help reduce the mortality rate. We propose the automatic Computer-Aided Diagnosis (CAD) system in this paper using the deep learning approach. The proposed CAD system takes input from raw computerized tomography (CT) scans of the patient's chest and automatically predicts disease classification. We designed the Hybrid Deep Learning Algorithm (HDLA) to improve accuracy and reduce processing requirements. The raw CT scans are pre-processed first to enhance their quality for further analysis. We then applied a hybrid model that consists of automatic feature extraction and classification. We propose the robust 2D Convolutional Neural Network (CNN) model to extract the automatic features from the pre-processed CT image. This CNN model assures feature learning with extremely effective 1D feature extraction for each input CT image. The outcome of the 2D CNN model is then normalized using the Min-Max technique. The second step of the proposed hybrid model is related to training and classification using different classifiers. The simulation outcomes using the publicly available dataset prove the robustness and efficiency of the proposed model compared to state-of-art algorithms.

Keywords: CT scans, COVID-19, deep learning, image processing, pneumonia, lung disease.

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Authors: Mousa Bani Baker, Maria Elektorowicz, Adel Hanna, Altayeb Qasem

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Liners are made to protect the groundwater table from the infiltration of leachate which normally carries different kinds of toxic materials from landfills. Although these liners are engineered to last for long period of time; unfortunately these liners fail; therefore, toxic materials pass to groundwater. This paper focuses on the changes of the hydraulic conductivity of a sand-bentonite liner due to the infiltration of biofuel and ethanol fuel. Series of laboratory tests were conducted in 20-cm-high PVC columns. Several compositions of sand-bentonite liners were tested: 95% sand: 5% bentonite; 90% sand: 10% bentonite; and 100% sand (passed mesh #40). The columns were subjected to extreme pressures of 40 kPa, and 100 kPa to evaluate the transport of alternative fuels (biofuel and ethanol fuel). For comparative studies, similar tests were carried out using water. Results showed that hydraulic conductivity increased due to the infiltration of alternative fuels through the liners. Accordingly, the increase in the hydraulic conductivity showed significant dependency on the type of liner mixture and the characteristics of the liquid. The hydraulic conductivity of a liner (subjected to biofuel infiltration) consisting of 5% bentonite: 95% sand under pressure of 40 kPa and 100 kPa had increased by one fold. In addition, the hydraulic conductivity of a liner consisting of 10% bentonite: 90% sand under pressure of 40 kPa and 100 kPa and infiltrated by biofuel had increased by three folds. On the other hand, the results obtained by water infiltration under 40 kPa showed lower hydraulic conductivities of 1.50×10-5 and 1.37×10-9 cm/s for 5% bentonite: 95% sand, and 10% bentonite: 90% sand, respectively. Similarly, under 100 kPa, the hydraulic conductivities were 2.30×10-5 and 1.90×10-9 cm/s for 5% bentonite: 95% sand, and 10% bentonite: 90% sand, respectively.

Keywords: Biofuel, Ethanol; Hydraulic conductivity Landfill, Leakage, Liner failure, Liner performance Fine-grained soils, Particle size, Sand-bentonite.

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Authors: Z. A. Ahmad Noor Syukri, A. J. Nawal Aswan, S. V. Wong

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The motorcycle has become one of the most common type of vehicles used on the road, particularly in the Asia region, including Malaysia, due to its size-convenience and affordable price. This study focuses only on crashes involving motorcycles with passenger cars consisting 43 real world crashes obtained from in-depth crash investigation process from June 2016 till July 2017. The study collected and analyzed vehicle and site parameters obtained during crash investigation and injury information acquired from the patient-treating hospital. The investigation team, consisting of two personnel, is stationed at the Emergency Department of the treatment facility, and was dispatched to the crash scene once receiving notification of the related crashes. The injury information retrieved was coded according to the level of severity using the Abbreviated Injury Scale (AIS) and classified into different body regions. The data revealed that weekend crashes were significantly higher for the night time period and the crash occurrence was the highest during morning hours (commuting to work period) for weekdays. Bad weather conditions play a minimal effect towards the occurrence of motorcycle – passenger vehicle crashes and nearly 90% involved motorcycles with single riders. Riders up to 25 years old are heavily involved in crashes with passenger vehicles (60%), followed by 26-55 year age group with 35%. Male riders were dominant in each of the age segments. The majority of the crashes involved side impacts, followed by rear impacts and cars outnumbered the rest of the passenger vehicle types in terms of crash involvement with motorcycles. The investigation data also revealed that passenger vehicles were the most at-fault counterpart (62%) when involved in crashes with motorcycles and most of the crashes involved situations whereby both of the vehicles are travelling in the same direction and one of the vehicles is in a turning maneuver. More than 80% of the involved motorcycle riders had sustained yellow severity level during triage process. The study also found that nearly 30% of the riders sustained injuries to the lower extremities, while MAIS level 3 injuries were recorded for all body regions except for thorax region. The result showed that crashes in which the motorcycles were found to be at fault were more likely to occur during night and raining conditions. These types of crashes were also found to be more likely to involve other types of passenger vehicles rather than cars and possess higher likelihood in resulting higher ISS (>6) value to the involved rider. To reduce motorcycle fatalities, it first has to understand the characteristics concerned and focus may be given on crashes involving passenger vehicles as the most dominant crash partner on Malaysian roads.

Keywords: Motorcycle crash, passenger vehicle, in-depth crash investigation, injury mechanism.

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