Amany M Sarhan

• Full professor
• Head of Department at Tanta University

This work tackles the challenge of ranking-based machine reading comprehension (MRC), where a question answering (QA) system generates a ranked list of relevant answers for each question instead of simply extracting a single answer. We highlight the limitations of traditional learning methods in this setting, particularly under limited training dat...

This paper introduces a pioneering, effective data-hiding algorithm using different sizes of cover images and different types of secret data (image, txt, and audio). The proposed algorithm is based on a hybrid 1D chaotic map combined with a 2D composite chaotic map paired with optimization and Least Significant Bits (LSB) techniques. We employ chao...

This research presents an innovative approach to Egyptian car plate recognition using YOLOv8 and optical character recognition (OCR) technologies. Leveraging the powerful object detection capabilities of YOLOv8, the system efficiently detects car plates within images, videos, or real-time. Subsequently, OCR algorithms are applied to extract alphanu...

Nowadays, liver tumor segmentation has been widely applied for vital medical objectives such as illness diagnosis, treatment, and evaluation of liver function. In this work, we aim to improve the performance of hybrid convolution neural network (CNN) models for liver tumor segmentation. A new automatic design method is introduced to build a hybrid...

An ischemic stroke attack can cause permanent damage to healthy brain tissue, leading to a permanent loss of motor or sensory function. It can also result in disability or death if not diagnosed and treated promptly. Early prediction of the outcome of the first stroke, such as disability or death, can help many patients by administering appropriate...

Chronic kidney disease (CKD) is one of today’s most serious illnesses. Because this disease usually does not manifest itself until the kidney is severely damaged, early detection saves many people’s lives. Therefore, the contribution of the current paper is proposing three predictive models to predict CKD possible occurrence within 6 or 12 months b...

Search engines are now an essential part of our daily lives, providing us with immediate access to a vast amount of information on the internet. They have transformed the way we search for and acquire knowledge by simplifying the process of finding answers to our questions. Information Retrieval (IR) is a field of study that focuses on effectively...

Kouranal of Research Engineering, Vol. 7, Issue 1, 2023

Deep Neural Networks (DNNs) are widely regarded as the most effective learning tool for dealing with large datasets, and they have been successfully used in thousands of applications in a variety of fields. Based on these large datasets, they are trained to learn the relationships between various variables. The adaptive moment estimation (Adam) alg...

Facial expressions are caused by specific movements of the face muscles; they are regarded as a visible manifestation of a person's inner thought process, internal emotional states, and intentions. A smile is a facial expression that often indicates happiness, satisfaction, or agreement. Many applications use smile detection such as automatic image...

Nowadays, touchscreen mobile devices make up a larger share in the market, necessitating effective and robust methods to continuously authenticate touch-based device users. A classification framework is proposed that learns the touch behavior of a user and is able afterwards to authenticate users by monitoring their behavior in performing input tou...

The Internet of Things (IoT) and cloud technologies have been the main focus of recent research, allowing for the accumulation of a vast amount of data generated from this diverse environment. These data include without any doubt priceless knowledge if could correctly discovered and correlated in an efficient manner. Data mining algorithms can be a...

Blood clots in the brain are frequently caused by brain tumors. Early detection of these clots has the potential to significantly lower morbidity and mortality in cases of brain cancer. It is thus indispensable for a proper brain tumor diagnosis and treatment that tumor tissue magnetic resonance images (MRI) be accurately segmented. Several deep le...

The development of neural networks and machine learning techniques has recently been the cornerstone for many applications of artificial intelligence. These applications are now found in practically all aspects of our daily life. Predicting drowsiness is one of the most particularly valuable of artificial intelligence for reducing the rate of traff...

The SARS-CoV-2 virus has proliferated around the world and caused panic to all people as it claimed many lives. Since COVID-19 is highly contagious and spreads quickly, an early diagnosis is essential. Identifying the COVID-19 patients’ mortality risk factors is essential for reducing this risk among infected individuals. For the timely examination...

In recent years, we witnessed great progress in different tasks of natural language understanding using machine learning. Question answering is one of these tasks which is used by search engines and social media platforms for improved user experience. Arabic is the language of the Holy Qur'an; the sacred text for 1.8 billion people across the world...

Nowadays, age estimation systems have become a pressing need in several vital fields such as security services and health systems. Over the past decade, there have been introduced several efforts to build accurate and robust age estimation systems, where deep networks have proved to be the superior leader of machine learning tools. From this point,...

Mixed reality (MR) is one of the technologies with many challenges in the design and implementation phases, especially the problems associated with time-sensitive applications. The main objective of this paper is to introduce a conceptual model for MR application that gives MR application a new layer of interactivity by using Internet of things/Int...

As most real world systems are significantly nonlinear in nature, developing robust controllers have attracted many researchers for decades. Robust controllers are the controllers that are able to cope with the inherent uncertainties of the nonlinear systems. Many control methods have been developed for this purpose. Sliding mode control (SMC) is o...

In recent years, channel state information (CSI) in WiFi 802.11n has been increasingly used to collect data pertaining to human activity. Such raw data are then used to enhance human activity recognition. Activities such as lying down, falling, walking, running, sitting down, and standing up can now be detected with the use of information collected...

Over the past decade, the computer vision community has given increased attention to the development of age estimation systems. Several approaches to more accurate and robust facial age estimation have been introduced. Apparent age datasets are typically collected from uncontrolled environments, leading to a number of challenges. In this paper, a c...

The wide prevalence of brain tumors in all age groups necessitates having the ability to make an early and accurate identification of the tumor type and thus select the most appropriate treatment plans. The application of convolutional neural networks (CNNs) has helped radiologists to more accurately classify the type of brain tumor from magnetic r...

Chaos-based cryptography has become a major interest for providing effective, fast and secure encryption in the recent few years. Chaos-based encryption applies basically repetitive steps of more than one chaotic map to increase the strength of the security. However, this repetition unfortunately increases the processing time especially for videos....

Image encryption has become the essential way to secure image information with the high frequency of multimedia information exchange on the Internet. In this paper, an effective chaotic color/grayscale image encryption algorithm is proposed. The algorithm uses a hybrid 2D composite chaotic map combined with a sine–cosine cross-chaotic map for the t...

This paper introduces a multi-server searchable symmetric encryption (SSE) scheme called the Multi-Server Searchable Data Crypt "MS-SDC" that works on achieving a trade-off between efficiency/functionality and security. The proposed scheme has the merits of dividing the uploaded file in an encrypted form into blocks and distributing them across sev...

Corona Virus Disease (COVID-19) has been announced as a pandemic and is spreading rapidly throughout the world. Early detection of COVID-19 may protect many infected people. Unfortunately, COVID-19 can be mistakenly diagnosed as pneumonia or lung cancer, which with fast spread in the chest cells, can lead to patient death. The most commonly used di...

Lip reading is typically regarded as visually interpreting the speaker’s lip movements during the speaking. This is a task of decoding the text from the speaker’s mouth movement. This paper proposes a lip-reading model that helps deaf people and persons with hearing problems to understand a speaker by capturing a video of the speaker and inputting...

Facial expressions demonstrate the presence and degree of pain of humans, which is a vital topic in E-health care domain especially for elderly people or patients with special needs. The main objective of this paper is to present a framework for pain detection, pain classification, and face recognition using Gabor filter for feature extraction, Rel...

Fog computing is a developing computing approach to extend and assist cloud computing. Fog computing platforms have several characteristics help providing the services for the users in a reduced time manner and thus improve the QoS of the IoT devices such as being close to edge-users, being open platform, and its support for mobility. Thus, it is b...

Object detection and tracking have been extensively used in many applications including security and surveillance. This chapter addresses the problem of human detection and tracking in surveillance videos with noise. The system proposed deals with video processing utilizing Kalman filtering to enhance the process in the presence of challenging weat...

As a result of what happened to the world during the past and current year of the spread of the Covid-19 epidemic, it was necessary to have a reliable health care system for remote observation, especially in care homes for the elderly. There are many research works have been done in this field, but still have limitations in terms of latency, securi...

In data mining, outlier detection is a major challenge as it has an important role in many applications such as medical data, image processing, fraud detection, intrusion detection, and so forth. An extensive variety of clustering based approaches have been developed to detect outliers. However they are by nature time consuming which restrict their...

IoT field is continuously evolving to cope with the tremendous number of applications that satisfy the user needs. IoT is implemented by physical objects with virtual representations and services. Augmented reality provides the user with a simple interacting interface to applications. The merge between IoT and augmented reality is a realistic conse...

This article discusses the design of a hybrid fuzzy variable structure control algorithm combined with genetic algorithm (GA) optimization technique to improve the adaptive proportional‐integral‐derivative (PID) continuous second‐order sliding mode control approach (APID2SMC), recently published in our previous article in the literature. In this ar...

In Wireless Local Area Networks (WLAN), portable devices such as notebooks, tabs, and smart phones are powered by batteries with limited energy. With the great increase of using such portable devices, energy efficiency becomes one of the most important issues in wireless networks that are based on IEEE 802.11b standard. Although, IEEE 802.11b stand...

In Wireless Local Area Networks (WLAN), portable devices such as notebooks, tabs, and smart phones are powered by batteries with limited energy. With the great increase of using such portable devices, energy efficiency becomes one of the most important issues in wireless networks that are based on IEEE 802.11b standard. Although, IEEE 802.11b stand...

This paper addresses the task-space robust trajectory tracking control problem for robot manipulators in the presence of uncertainties and external disturbances. First, a discontinuous sliding-mode controller-based inverse dynamics control strategy (IDSMC) with discontinuous robust control action is synthesized. Second, an adaptive inverse dynamics...

Developing IoT projects from scratch requires a lot of knowledge and expertise; moreover, it takes a very long time to be developed. It can be hard for starters and even senior developers to perfect every aspect of an IoT project in a timely manner. These aspects include hardware, communication, data storage, security, integration, application, dat...

Healthcare informatics is undergoing a revolution because of the availability of safe, wearable sensors at low cost. Smart hospitals have exploited the development of the Internet of Things (IoT) sensors to create Remote Patients monitoring (RPM) models that observe patients at their homes. RPM is one of the Ambient Assisted Living (AAL) applicatio...

In this paper an adaptive neural network (NN)-based nonlinear controller is proposed for trajectory tracking of uncertain nonlinear systems. The adopted control algorithm combines a continuous second-order sliding mode control (CSOSMC), the radial basis function neural network (RBFNN) and the adaptive control methodology. First, a second-order slid...

Abstract Cognitive radio networks (CRNs) have been introduced as a promising solution to optimize the use of available radio-frequency spectrum. The key idea in CRNs is the proper selection of available sensed channels. In this paper, an intelligent distributed channel selection strategy is proposed for cognitive radio ad-hoc networks aiming to ass...

The embracing of the Internet of Things (IoT) and Cloud Computing technologies gives excellent opportunities to develop smart healthcare services that have great prediction capabilities. This paper proposes a Hybrid Real-time Remote Monitoring (HRRM) framework, which remote-monitors patients continuously. This smart framework predicts the real heal...

Despite the success achieved in the metadata models matching area, large-scale matching does not preserve high match quality and efficiency at the same time. To deal with these challenges, we introduce a generic matching framework, called MetMat, to identify and discover corresponding entities across XML schemas and/or ontologies (metadata models)....

Nowadays, WSNs have received great importance because they are the best solutions that can be used in harsh environments. The main limitation in WSNs is the node power because the sensor node is battery powered and charging or replacing this battery is not applicable. Moreover, in mission-critical applications, sensor nodes can sense important data...

In the current decade, ambient assisted living is attracting widespread interest due to the rapidly aging global population. The cloud-based Internet of things (IoT) healthcare systems are facing many barriers to handle the big healthcare data that IoT generates. Edge of things computing is one of the promising solutions. Accordingly, this paper pr...

This paper proposes an intelligent hybrid context-aware model for patients under supervision at home that adopts a hybrid architecture with both local and cloud-based components. The cloud-based portion of the model facilitates storing and processing the big data generated by ambient assisted living systems that are used to monitor patients sufferi...

With the aim of reducing duplicate records in databases, duplicate record detection (DRD) ensures the integrity of data. Its role is to identify records signifying same entities either in the same or in different compared to database. A diversity of indexing techniques has been proposed to support DRD. Q-gram is one of the common techniques used to...

Due to the rapid use of Internet technology, a need for security mechanisms has appeared to protect the information. Cryptography is one of the most effective techniques used to protect and secure information. Triple Data encryption standard is a cryptography system that provides security in the commercial enterprise. A lot of research has been mad...

This issue includes the following articles; P1121606475, Author="M. AbdelDayem and H. Hemeda and A. Sarhan", Title="Enhanced User Authentication through Keystroke Biometrics for Short-Text and Long-Text Inputs" P1121602462, Author="Eslam Mahmoud and Ahmed M. Elmogy and Amany Sarhan", Title="Enhancing Grid Local Outlier Factor Algorithm for better O...

This issue includes the following articles; P1121606475, Author="M. AbdelDayem and H. Hemeda and A. Sarhan", Title="Enhanced User Authentication through Keystroke Biometrics for Short-Text and Long-Text Inputs" P1121602462, Author="Eslam Mahmoud and Ahmed M. Elmogy and Amany Sarhan", Title="Enhancing Grid Local Outlier Factor Algorithm for better O...

This issue includes the following articles; P1121606475, Author="M. AbdelDayem and H. Hemeda and A. Sarhan", Title="Enhanced User Authentication through Keystroke Biometrics for Short-Text and Long-Text Inputs" P1121602462, Author="Eslam Mahmoud and Ahmed M. Elmogy and Amany Sarhan", Title="Enhancing Grid Local Outlier Factor Algorithm for better O...

This issue includes the following articles; P1121606475, Author="M. AbdelDayem and H. Hemeda and A. Sarhan", Title="Enhanced User Authentication through Keystroke Biometrics for Short-Text and Long-Text Inputs" P1121602462, Author="Eslam Mahmoud and Ahmed M. Elmogy and Amany Sarhan", Title="Enhancing Grid Local Outlier Factor Algorithm for better O...

This issue includes the following articles; P1121606475, Author="M. AbdelDayem and H. Hemeda and A. Sarhan", Title="Enhanced User Authentication through Keystroke Biometrics for Short-Text and Long-Text Inputs" P1121602462, Author="Eslam Mahmoud and Ahmed M. Elmogy and Amany Sarhan", Title="Enhancing Grid Local Outlier Factor Algorithm for better O...

In this paper, a communication load balanced dynamic topology management algorithm (CLB-AODV) is proposed to extend the wireless sensor network (WSN) lifetime via managing the participation in communication process among all nodes in the network. The idea is that, each time there is a failure in the network topology; the topology is adjusted only o...

The main objective of the work is to improve the clustering efficiency and performance when we deal with very big datasets. This paper aims to improve the quality of XML data clustering by exploiting more features extracted from source schemas. In particular, it proposes clustering approach that gathers both content and structure of XML documents t...

This paper introduces a secure chaos-based model for ciphering and deciphering of digital images. The proposed approach is composed of successive confusion and diffusion stages. The confusion stage is repeated n rounds using a different key in each round. The output of the confusion stage is subjected to diffusion stage which is repeated m rounds w...

Detecting outliers in a large data set is a major data mining task. The existing approaches in this field are categorized into two main categories which are distance-based and density-based outlier detection approaches. Although, Local Outlier Factor (LOF) is considered as the most popular density-based algorithm, it still has some problems related...

Vision-based registration methods for augmented reality systems recently have been the subject of intensive research due to their potential to accurately align virtual objects with the real world. The drawbacks of these vision-based approaches, however, are their high computational cost and lack of robustness. Motion blur and partial occlusion are...

Traditionally in Web crawling, the required features are extracted from the whole contents of HTML pages. However, the position which a word is located inside the HTML tags indicates its importance in the web page. This research proposes two ideas concerning the Feature Selection stage in HTML web pages. The first idea reduces the features by simpl...

Cyber threat became one of the most serious problem for both economics and national security in the 21st century. Therefore, we need a focused research on developing efficient techniques, technologies and tools to deal with this stimulating problem. The growing dimension and complexity of spatiotemporal data generated on daily basis and from variet...

C yber threat became one of the most serious problem for both economics and national security in the 21st century. Therefore, we need a focused research on developing efficient techniques, technologies and tools to deal with this stimulating problem. The growing dimension and complexity of spatiotemporal data generated on daily basis and from varie...

Congestion is a significant problem that faces streaming media applications in Wireless Sensor Networks (WSN). This problem occurs when the sensor receives traffic that exceeds its maximum forwarding rate causing more packet loss, more delay and overall quality degradation. The Datagram Congestion Control Protocol (DCCP) is a congestion control pro...

Outlier detection is an important issue in the realm of data mining. Several applications relay on outlier detection such as intrusion detection, fraud detection, medical and public health data, image processing, etc. Clustering-based outlier detection algorithms are considered as the most important outlier detection approaches. They provide high d...

The explosive growth of webpage number on the Web has brought up some problems in the search process. One of these problems is that the general purpose search engines often return too many irrelevant results when users are searching for specific information on a given topic. Another problem is the massive increase in the number of pages to be index...

Sharing data between organizations has growing importance in many data mining projects. Data from various heterogeneous sources often has to be linked and aggregated in order to improve data quality. The importance of data accuracy and quality has increased with the explosion of data size. The first step to ensure the data accuracy is to make sure...

When clustering objects to be allocated on a number of nodes, most researches focus only on either the communication cost between clusters or the balancing of the workload on the nodes. Load balancing is a technique to distribute workload evenly across two or more computers, network links, CPUs, hard drives or other resources, in order to, get opti...

Cloud service composition is usually long term based and economically driven. Services in cloud computing can be categorized into two groups: Application services and Computing Services. Compositions in the application level are similar to the Web service compositions in Service-Oriented Computing. Compositions in the computing level are similar to...

A database system includes a set of different hardware and software resources with a large number of configuration parameters that affect and control the performance of database systems. Tuning these parameters within their diverse and complex environments requires a lot of expertise and it is a time-consuming, and often a misdirected process. Furt...

Electronic Voting (e-voting) system has to achieve some basic security aspects in order to satisfy the confidence of the voters. Although e-voting is expected to be more efficient than the current traditional voting, e-voting is not used in a large scope. The main reason is the lack of the voter trust. It is a difficult challenge to design trustwor...

The increasing demand for World Wide Web (WWW) services has led to a considerable increase in the amount of Internet traffic. As a result, the network becomes highly prone to congestion which increases the load on servers, resulting in increasing the access times of WWW documents. Thus, web caching is crucial for reducing the load on network, short...

E[ectronic Voting (e-voting) s y stem has to achieve some basic securit y aspects in order to satisf y the confidence of the voters. Althou g h e-votin g is expected to be more efficient than the current traditional votin g , e-votin g is not used in a lar g e scope. The main reason is the lack of the voter trust. It is a difficult challen g e to d...

An important issue in the analysis of two-dimensional electrophoresis images is the detection and quantification of protein spots. The main challenges in the segmentation of 2DGE images are to separate overlapping protein spots correctly and to find the abundance of weak protein spots. To enable comparison of protein patterns between different samp...

The increasing size and the widespread use of XML data and different types of ontologies result in the big challenge of how to integrate these data. A critical step towards building this integration is to identify and discover semantically corresponding elements across heterogeneous data sets. This identification process becomes more and more chall...

In this paper, the authors investigate trust of the online auctions one of most e-commerce fields used today, with online auctions; users could buy/sell items all over the world. Compared to traditional auctions, online auctions bring greater convenience while dramatically decreasing the transaction cost., Participants' trust more important one, th...

Schema matching represents a critical step to integrate heterogeneous e-Business and shared-data applications. Most existing schema matching approaches rely heavily on similarity-based techniques, which attempt to discover correspondences based on various element similarity measures, each computed by an individual base matcher. It has been accepted...