Mohammad Alsmirat

Jordan University of Science and Technology | Just · Department of Computer Science

Collaborative filtering methods are often utilized in the industry of recommender systems. They work by identifying users with similar tastes and recommending items for each active user. Besides, clustering techniques are extensively utilized to create systems based on collaborative filtering recommendation in the context of big data. Nevertheless,...

In the recent years, recommender systems have begun to attract the attention of many online-based companies. While these systems are being developed to provide users with better recommendations, they suffer from the lack of explain-ability. The explainable recommendation systems are developed to solve the problem of why certain products or services...

Computer-aided diagnosis (CAD) systems have been the focus of many researchers in both computer and medical fields. In this paper, we build two convolutional neural network (CNN) based CAD systems for diagnosing lumbar disk herniation from Magnetic Resonance Imaging (MRI) axial scans. The first one is a disk herniation detection CAD system which is...

This article studies and analyzes the use of 3D models, built from magnetic resonance imaging (MRI) axial scans of the lumbar intervertebral disk, that are needed for the diagnosis of disk herniation. We study the possibility of assisting radiologists and orthopedists and increasing their quality of experience (QoE) during the diagnosis process. Th...

Sinuses disorders are among the most common disorders that affect people's lives worldwide. Diagnosing such disorders requires highly skilled specialists to carefully inspect Computed Tomographic (CT) scans of the patient. The diagnosis process is time-consuming and very costly. To build a machine learning based computer system for the diagnosis pr...

In this project, a sinonasal diseases dataset is created with the help of Ear, Nose, and Throat (ENT) specialists at King Abdullah University Hospital (KAUH), Jordan. This dataset is then used to experiment with different features extraction and selection methods and different machine learning classification methods. The work can be summarized as f...

Advancement of the prediction models used in a variety of fields is a result of the contribution of machine learning approaches. Utilizing such modeling in feature engineering is exceptionally imperative and required. In this research, we show how to utilize machine learning to save time in research experiments, where we save more than five thousan...

The wide spread of motion sensors has encouraged the creation of many useful applications. In this chapter, the authors use Human Activity Recognition (HAR) application as a case study to make it more useful and more applicable in real life by tolerating the heterogeneity of the types of devices. This chapter investigates the ability of Recurrent N...

This paper studies the problem of clinical MRI analysis in the field of lumbar intervertebral disk herniation diagnosis. It discusses the possibility of assisting radiologists in reading the patient's MRI images by constructing a 3D model for the region of interest using simple computer vision methods. We use axial MRI slices of the lumbar area. Th...

The interest in large scale automated video surveillance systems and the interest in using cloud in supporting such systems has increased dramatically. Unfortunately, building such a large system requires huge resources (for processing and storage) and very high network bandwidth. This paper, proposes a framework for resources efficient intelligent...

Many applications in intelligent transportation systems are demanding an accurate vehicle Global Position System (GPS) location prediction. In this study, we satisfy this demand by designing an automated GPS location prediction system based on the well known traditional Auto-Regressive Integrated Moving Average (ARIMA). To increase the proposed mod...

Technically Co-Sponsored by IEEE France Section FMEC 2020 CFP: Cloud computing provides large range of services and virtually unlimited available resources for users. New applications, such as virtual reality and smart building control, have emerged due to the large number of resources and services brought by cloud computing. However, the delay-sen...

Next generation cloud systems will require a paradigm shift in how they are constructed and managed. Conventional control and management platforms are facing considerable challenges regarding flexibility, dependability and security that next generation systems will require. The cloud computing paradigm has gone part of the way towards alleviating s...

16th ACS/IEEE International Conference on Computer Systems and Applications AICCSA 2019

The purposeful acts of bioterrorism and the emergence of new pathogens call for developing efficient biosurveillance systems that are capable of detecting health security threats and localizing their origins. For this sake, several biosurveillance systems have been developed and deployed in different regions around the world. The objectives of thes...

Acceptable error rate, low quality assessment, and time complexity are the major problems in image segmentation, which needed to be discovered. A variety of acceleration techniques have been applied and achieve real time results, but still limited in 3D. HMM is one of the best statistical techniques that played a significant rule recently. The prob...

Despite the large body of work on fingerprint identification systems, most of it focused on using specialized devices. Due to the high price of such devices, some researchers directed their attention to digital cameras as an alternative source for fingerprints images. However, such sources introduce new challenges related to image quality. Specific...

Big data is becoming bigger every day. Even for simple applications such as the Digital Bibliography & Library Project (DBLP) database, the data is becoming unmanageable using the conventional databases because of its size. Applying big data processing methods such as Hadoop and Spark is becoming more popular because of that. In this work, we inves...

This paper develops a cross-layer optimization solution for video streaming from multiple sources to a central proxy station over a wireless network. The proposed solution manages the application rates and transmission opportunities of various video sources based on the dynamic network conditions in such a way that minimizes the overall video disto...

The unprecedented trend of using public cloud computing services by increasing number of customers motivates cloud services providers to optimize their resources usage and management to the limit. This is including managing cloud user's virtual machines (VM) running on one or more of the thousands of hosting servers or physical machines (PMs) of th...

Cloud computing's seemingly limitless scalability lies in part, in the ability for cloud consumers to instantiate virtual resources when demand scales up, and terminate them when demand recedes. Cloud consumers access resources on-demand and with minimum upfront investments into the infrastructure, making cloud cost effective. Central to the cloud...

FMEC 2018 Call for Papers: Cloud computing provides large range of services and virtually unlimited available resources for users. New applications, such as virtual reality and smart building control, have emerged due to the large number of resources and services brought by cloud computing. However, the delay-sensitive applications face the problem...

Computer-aided diagnosis (CAD) systems have been the focus of many research endeavors. We consider the problem of building a CAD system for diagnosing lumbar disk herniation from MRI axial scans. Like other typical image based CAD systems, the CAD system we consider consists of several stages: image acquisition, region of interest (ROI) extraction...

Computer-aided diagnosis systems have been the focus of many research endeavors. They are based on the idea of processing and analyzing various types of inputs (such as patients medical history, physical examination results, images of different parts of the human body, etc.) to help physicians reach a quick and accurate diagnosis. In addition to be...

The wide spread of digital devices and tools causes the simplification of the manipulation of any digital multimedia content. As a result, digital videos and photos are not trusted to be used as evidence in courts. This fact raises the need for finding techniques to ensure the authenticity of digital multimedia contents. Experts in digital-signal p...

Utilizing cloud services in running large-scale video surveillance systems is not uncommon. However, special attention should be given to data security and privacy because, typically, data travels over insecure public networks. In this work, we propose an end-to-end security framework for a cloud-based video surveillance system that supports a larg...

Mobile Edge Computing (MEC) enables ubiquitous and efficient cloud services to mobile users which facilitates mobile cloud computing (MCC) more easily by providing storage and processing capacity within the access range of the mobile devices. To achieve the goals of MEC, Mobile Edge (ME) servers are co-placed with the mobile network base station (a...

Modern electronic devices(such as TVs, laptops, and mobile devices) come with a huge variety in screen sizes, resolutions, and aspect ratios. Image retargeting is a technique to retarget or (resize) an image to better utilize the viewing device screen and to protect the main content of the image. Different retargeting techniques have been proposed...

In the past years, surveillance systems have attracted both industries and researchers due to its importance for security. Automated Video Surveillance (AVS) systems are established to automatically monitor objects in real-time. Employing wireless communication in an AVS system is an attractive solution due to its convenient installation and config...

Underwater Wireless Sensor Network (UWSNs) have been proposed to monitor underwater regions such as seas and oceans. A typical example of an UWSN consists of a set of underwater sensor nodes and a set of sink nodes that are deployed at the sea surface. Using acoustic transmission, the sensors send their collected data to at least one of the sinks i...

With the emanation of educational data mining field, it is being increasingly connected to a number of research areas such as adaptive and intelligent web-based tutors, intelligent educational applications and other accommodating online educational data mining systems. The applications of educational data mining takes into account the system academ...

String matching problems such as sequence alignment is one of the fundamental problems in many computer since fields such as natural language processing (NLP) and bioinformatics. Many algorithms have been proposed in the literature to address this problem. Some of these algorithms compute the edit distance between the two strings to perform the matc...

Large-scale video surveillance systems are among the necessities for securing our life these days. The high bandwidth demand and the large storage requirements are the main challenges in such systems. To face these challenges, the system can be deployed as a multi-tier framework that utilizes different technologies. In such a framework, technologie...

Medical image processing is one of the most famous image processing fields in this era. This fame comes because of the big revolution in information technology that is used to diagnose many illnesses and saves patients lives. There are many image processing techniques used in this field, such as image reconstructing, image segmentation and many mor...

This paper develops an accuracy-based cross-layer optimization solution for wireless automated video surveillance systems, in which multiple sources stream videos to a central proxy station. The proposed solution manages the application rates and transmission opportunities of various video sources based on the dynamic network conditions in such a w...

Metamorphic malware are able to change their appearance to evade detection by traditional anti-malware software. One of the ways to help mitigate the threat of new metamorphic malware is to determine their origins, i.e., the families to which they belong. This type of metamorphic malware analysis is not typically handled by commercial software. Mor...

Since security vulnerabilities represent one of the grand challenges of the Internet of Things (IoT), researchers have proposed what is known as the Internet of Biometric Things (IoBT), which mixes traditional biometric technologies with context-aware authentication techniques. One of the most famous biometric technologies is electronic fingerprint...

Purpose The purpose of this paper is to propose, a new multi-path routing protocol that distributes packets over the available paths between a sender and a receiver in a multi-hop ad hoc network. We call this protocol Geometric Sequence Based Multipath Routing Protocol (GMRP). Design/methodology/approach GMRP distributes packets according to the g...

Breast cancer is the most lethal type of cancer affecting women in the world. To improve the life quality of women, an early detection of this malignancy is always promising because this cancer is one of the cancers that can be managed and treated easily if it is detected earlier. Mammography is the standard screening method to diagnose breast canc...

The use of vehicular networks for collision avoidance increased significantly in the last decade. In particular, governments are employing DSRC-based communication for this purpose. One of the main challenges for DSRC-based vehicular networks is congestion control. Many solutions are proposed in the literature to solve this problem. Recently, EDCA...

Computer-aided diagnosis systems have been the focus of many research endeavors. They are based on the idea of processing and analyzing various types of input (such as patients medical history, physical examination results, images of different parts of the human body, etc.) to generate a quick and accurate diagnosis. In this work, we propose a syst...

In this work we investigate the problem of video streaming in cognitive radio networks from a cognitive radio video source to a set of cognitive radio destinations using multicasting. Our objective is to improve the overall quality of the received video by all destinations. To achieve this, we propose a cross layer approach to multicast the video p...

This paper develops a cross-layer optimization framework for video streaming from multiple sources to a central proxy station over a wireless network. The proposed framework manages the application rates and transmission opportunities of various video sources based on the dynamic network conditions in such a way that minimizes the overall distortio...

Providing video streaming users with expected waiting times enhances their perceived quality-of-service (QoS) and encourages them to wait. In the absence of any waiting-time feedback, users are more likely to defect because of the uncertainty as to when their services will start. We analyze waiting-time predictability in scalable video streaming. W...

The number of on-demand video streams that can be supported concurrently is highly constrained by the stringent requirements of real-time playback and high transfer rates. To address this problem, stream merging techniques utilize the multicast facility to increase resource sharing. The achieved resource sharing depends greatly on how the waiting r...

Motivated by the impressive performance of cost-based scheduling for media streaming, we investigate its effectiveness in detail and analyze opportunities for further tunings and enhancements. Guided by this analysis, we propose a highly efficient enhancement technique that optimizes the scheduling decisions to increase the number of requests servi...

We propose a scheduling policy, called Predictive Cost-Based Scheduling (PCS) for scalable video streaming. PCS schedules the waiting requests based on their required delivery costs, predicts future system state, and uses the prediction results to possibly alter the scheduling decisions. We also present two alternative implementations of PCS and an...

Providing video streaming users with expected waiting times enhances their perceived quality-of-service (QoS) and encourages them to wait. In the absence of any waiting-time feedback, users are more likely to defect because of the uncertainty as to when they will start to receive services. In this paper, we analyze waiting-time predictability in sc...