Seifedine Kadry

Seifedine Kadry
Noroff University College · Department of Applied Data Science

PhD, HdR

About

714
Publications
473,620
Reads
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6,169
Citations
Introduction
Dr. Seifedine Kadry has a Bachelor degree in 1999 from Lebanese University, MS degree in 2002 from Reims University (France) and EPFL (Lausanne), PhD in 2007 from Blaise Pascal University (France), HDR degree in 2017 from Rouen University (France). At present his research focuses on Data Science, education using technology, system prognostics, stochastic systems, and applied mathematics. He is an ABET program evaluator for computing, and ABET program evaluator for Engineering Tech.
Additional affiliations
May 2017 - present
Beirut Arab University
Position
  • Faculty Member
September 2010 - March 2017
The American University of the Middle East
Position
  • Head of Department
March 2007 - September 2010
Lebanese University
Position
  • Professor (Assistant)
Education
March 2011 - December 2017
April 2004 - May 2007
Université Clermont Auvergne
Field of study
  • Applied Mathematics

Publications

Publications (714)
Article
This paper proposes a hybrid algorithm for capacity configuration optimization of a solar PV-battery based micro-grid. The hybrid algorithm (BAPSO) which is a combination of Particle Swarm Optimization (PSO) and Bat Algorithm (BA) is designed to optimize the solar generation location and capacity for efficient performance of a micro-grid. The algor...
Article
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Here, we use multi-type feature fusion and selection to predict COVID-19 infections on chest computed tomography (CT) scans. The scheme operates in four steps. Initially, we prepared a database containing COVID-19 pneumonia and normal CT scans. These images were retrieved from the Radiopaedia COVID-19 website. The images were divided into traini...
Article
One of the major challenges in designing an autonomous agent system is to achieve the objective of recreating human-like cognition by exploiting the growing pragmatic architectures that act intelligently and intuitively in vital fields. Consequently , this research addresses the general problem of designing an agent-based autonomous flight control...
Article
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Eye is an essential sensory organ in human physiological system and disease in eye severely affects the vision system. Age-related-macular-degeneration (AMD) is a common eye disease in elderly people (age > 60 years) and the untreated AMD will cause severe eye illness including permanent vision loss. This research work proposes a machine-learning-s...
Article
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Automated formulation of sketches from face photos has seen successive growth since the work of Wang and Tang in recent years. Each new methodology is, however, able to partially achieve its objective of sketch synthesis while using pairs of photos and viewed sketches as a training medium. The viewed sketches are also used as a testing medium to de...
Article
Surveillance Systems Application based on deep learning algorithms is speedily growing in a broad range of fields such as Facial Recognition, Real Time Attendance Systems etc. Identifying several appearances in a real time environment is very crucial due to its difficult and heterogenous environmental conditions and blocking effects. We used state-...
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Industry 5.0 provides resource-efficient solutions compared to Industry 4.0. Edge Computing (EC) allows data analysis on edge devices. Artificial intelligence (AI) has become the focus of interest in recent years, particularly in industrial applications. The coordination of AI at the edge will significantly improve industry performance. This paper...
Article
White blood cells (WBCs) are the important constituent of a blood cell. These blood cells are responsible for defending the body against infections. Abnormalities identified in WBC smears lead to the diagnosis of disease types such as leukocytosis, hepatitis, and immune system disorders. Digital image analysis for infection detection at an early st...
Article
In past decades, retinal diseases have become more common and affect people of all age grounds over the globe. For examining retinal eye disease, an artificial intelligence (AI) based multilabel classification model is needed for automated diagnosis. To analyze the retinal malady, the system proposes a multiclass and multi-label arrangement method....
Article
Knee osteoarthritis (KOA) is one of the deadliest forms of arthritis. If not treated at an early stage, it may lead to knee replacement. That is why early diagnosis of KOA is necessary for better treatment. Manually KOA detection is a time-consuming and error-prone task. Computerized methods play a vital role in accurate and speedy detection. There...
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COVID-19 has depleted healthcare systems around the world. Extreme conditions must be defined as soon as possible so that services and treatment can be deployed and intensified. Many biomarkers are being investigated in order to track the patient’s condition. Unfortunately, this may interfere with the symptoms of other diseases, making it more diff...
Article
Network application classification (NAC) is a vital technology for intrusion detection, QoS-aware traffic engineering, traffic analysis, and network anomalies. Researchers have focused on designing algorithms using deep learning models based on statistical information to address the challenges of traditional payload and port-based traffic classific...
Article
Diabetic Retinopathy is a serious complication arising in diabetes afflicted patients. Its effective treatment depends on early detection, and the course of action varies decisively with the intensity of the affliction. Computer-aided diagnosis helps to detect not only the presence or absence of the disease but also the severity, making it easier f...
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Emerging technologies such as network function virtualization and software-defined networking (SDN) have made a phenomenal breakthrough in network management by introducing softwarization. The provision of assets to each virtualized network functions autonomously as well as efficiently and searching for an optimal pattern for traffic routing challe...
Article
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Nowadays, the relevance of women-only educational institutes is questionable due to various reasons that include social uplifting, ample opportunities, and a free mindset among the population. Though women colleges and universities bring many female students to the purview of the traditional education system every year, other activities like resear...
Article
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Data mining may enable healthcare organizations, with analysis of the different prospects and connection between seemingly unrelated information, to anticipate trends in the patient’s medical condition and behavior. Raw data are large and heterogeneous from healthcare organizations. It needs to be collected and arranged, and its integration enables...
Article
Semantic web technology is adapted to the internet of things (IoT) for web - based applications to globally connect the services. Web ontology language (OWL) domain ontology is a powerful machine - readable language for domain knowledge representation. The developer stored the IoT application relevant ontology in a repository or catalogue. Hence, I...
Article
In recent times, bacterial Antimicrobial Resistance (AMR) analyses becomes a hot study topic. The AMR comprises information related to the antibiotic product name, class name, subclass name, type, subtype, gene type, etc., which can fight against the illness. However, the tagging language used to determine the data is of free context. These context...
Article
Detection of arrhythmia of electrocardiogram (ECG) signals recorded within several sessions for each person is a challenging issue, which has not been properly investigated in the past. This arrhythmia detection is challenging since a classification model that is constructed and tested using ECG signals maintains generalization when dealing with un...
Article
The outbreak of novel coronavirus disease 2019, also called COVID-19, in Wuhan, China, began in December 2019. Since its outbreak, infectious disease has rapidly spread across the globe. The testing methods adopted by the medical practitioners gave false negatives, which is a big challenge. Medical imaging using deep learning can be adopted to spee...
Article
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An electrocardiogram (ECG) consists of five types of different waveforms or characteristics (P, QRS, and T) that represent electrical activity within the heart. Identification of time intervals and morphological appearance of the waves are the major measuring instruments to detect cardiac abnormality from ECG signals. The focus of this study is to...
Article
PendingIntent (PI) is an authority to use the sender’s permissions and identity by the receiver. Unprotected broadcast and PI s with an empty base intent are some of the vulnerable features that a malware utilizes to perform unauthorized access and privilege escalation (PE) attacks on the PI. To protect the PI from the above attacks, this paper pro...
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The 12 leads of electrocardiogram (ECG) signals show the heart activities from different angles of coronal and axial planes; hence, the signals of these 12 leads have functional dependence on each other. This paper proposes a novel method for fusing the data of 12-lead ECG signals to diagnose heart problems. In the first phase of the proposed metho...
Article
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Multiple sclerosis (MS) is an autoimmune disease that causes mild to severe issues in the central nervous system (CNS). Early detection and treatment are necessary to reduce the harshness of the disease in individuals. The proposed work aims to implement a convolutional neural network (CNN) segmentation scheme to extract the MS lesion in a 2D brain...
Article
Resource allocation and offloading in green Internet of Things (IoT) relies on the multi-level heterogeneous platforms. The energy expenses of the platform determine the reliability of green IoT based services and applications. This manuscript introduces a decisive energy management scheme for optimal resource allocation and offloading along with e...
Article
The Internet of things (IoT) is a network of technologies that support a wide variety of healthcare workflow applications to facilitate users' obtaining real-time healthcare services. Many patients and doctors' hospitals use different healthcare services to monitor their healthcare and save their records on the servers. Healthcare sensors are widel...
Article
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In the current era, the incidence rate of the cancer is gradually rising due to various causes and early screening and treatment is necessary to reduce the mortality rates. Skin Cancer (SC) is one of the cancers and listed under top 5 groups in 2020 report of World Health Organisation (WHO). The proposed research aims to propose a CNN framework to...
Article
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The possibility neutrosophic hypersoft set (pNHs-set) is a generalized version of the possibility neutrosophic soft set (pNs-set). It tackles the limitations of the pNs-set regarding the use of the multi-argument approximate function. This function maps sub-parametric tuples to a power set of the universe. It emphasizes the partitioning of each att...
Article
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Brain tumor is an active research topic in the area of medical imaging due to only 36% survival rate. The malignant tumor is a more dangerous type of tumor. The recent facts and figures show that 700,000 American are living in brain tumor and from them, 30.25% tumors are malignant. The diagnosis at the initial stage can help to minimize the human m...
Chapter
Recent advancements in networking and communication systems helped to enhance various domains, including healthcare. The invention of cloud computing, the Internet of medical things (IoMT), and artificial intelligence (AI) invented Healthcare 4.0, which supports the monitoring and examination of a variety of medical information using digital techni...
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These days, fog computing is an emerging paradigm that offers ubiquitous and omnipresent latency-aware services to delay applications. However, due to the mobility features of applications, the resource allocation to the workload of applications in distributed dynamic fog networks is becoming a challenging problem. This paper investigates the resou...
Article
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Background and objectives Over the past two decades, medical imaging has been extensively apply to diagnose diseases. Medical experts continue to have difficulties for diagnosing diseases with a single modality owing to a lack of information in this domain. Image fusion may be use to merge images of specific organs with diseases from a variety of m...
Article
Pre-COVID-19, most of the supply chains functioned with more capacity than demand. However, COVID-19 changed traditional supply chains' dynamics, resulting in more demand than their production capacity. This article presents a multiobjective and multiperiod supply chain network design along with customer prioritization, keeping in view price discou...
Article
Breast cancer has now overtaken lung cancer as the world's most commonly diagnosed cancer, with thousands of new cases per year. Early detection and classification of breast cancer are necessary to overcome the death rate. Recently, many deep learning-based studies have been proposed for automatic diagnosis and classification of this deadly disease...
Article
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Signet Ring Cell (SRC) Carcinoma is among the dangerous types of cancers, and has a major contribution towards the death ratio caused by cancerous diseases. Detection and diagnosis of SRC carcinoma at earlier stages is a challenging, laborious, and costly task. Automatic detection of SRCs in a patient's body through medical imaging by incorporating...
Article
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A brain tumor is an abnormal enlargement of cells if not properly diagnosed. Early detection of a brain tumor is critical for clinical practice and survival rates. Brain tumors arise in a variety of shapes, sizes, and features, with variable treatment options. Manual detection of tumors is difficult, time-consuming, and error-prone. Therefore, a si...
Article
A Deep Learning Algorithm for Detection of Long-Term Sepsis Using Bidirectional Gated Recurrent Unit
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For autonomous navigation, three main functions are essential: finding the location, creating the mapping, and getting the optimum path. Since Human operators study the map and correlate it to aerial pictures to locate target locations, consistent localization and mapping concurrently are challenging tasks. Light detection and ranging (LiDAR) can c...
Article
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An eye disease affects the entire sensory operation, and an unrecognized and untreated eye disease may lead to loss of vision. The proposed work aims to develop an automated Age-Related Macular Degeneration (AMD) detection system using a Deep-Learning (DL) scheme with serially concatenated deep and handcrafted features. The research includes the fo...
Article
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Medical images play a fundamental role in disease screening, and automated evaluation of these images is widely preferred in hospitals. Recently, Convolutional Neural Network (CNN) supported medical data assessment is widely adopted to inspect a set of medical imaging modalities. Extraction of the leukocyte section from a thin blood smear image is...
Article
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Globally, data security and privacy over the Internet of Things (IoT) are necessary due to its emergence in daily life. As the IoT will soon invade each part of our lives, attention to IoT security is significant. The nature of attacks is dynamic, and addressing this requires designing dynamic methods and a self-adaptable scheme to discover securit...
Preprint
Dispensing errors in community pharmacies are common reasons for a patient’s injury and harm. Therefore, to improve patient safety in relation to the use of medicine in the primary care setting, the study sought to determine the attitude and perception of community pharmacists towards dispensing errors. A survey-based cross-sectional study consiste...
Article
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Coronavirus disease 2019 (COVID-19) is a novel disease that affects healthcare on a global scale and cannot be ignored because of its high fatality rate. Computed tomography (CT) images are presently being employed to assist doctors in detecting COVID-19 in its early stages. In several scenarios, a combination of epidemiological criteria (contact d...
Conference Paper
COOT algorithm is a recent metaheuristic algorithm that simulates American coot birds when moving in the sea. However, the COOT algorithm like other metaheuristic techniques may be stuck in local regions. In this study, a modified COOT algorithm called (mCOOT) is presented which is based on 2 techniques: Opposition-based Learning (OBL) & Orthogonal...
Article
Full-text available
Worldwide, more than 1.5 million deaths are occur due to liver cancer every year. The use of computed tomography (CT) for early detection of liver cancer could save millions of lives per year. There is also an urgent need for a computerized method to interpret, detect and analyze CT scans reliably, easily, and correctly. However, precise segmentati...
Article
In modern networks and cloud evolution, as new nodes to internetwork growing rapidly and use of gaming and video streaming over the network require high availability with very small latency rate. 5G networks provides muchfaster services than 4G but link failure occurrence can affect the quality of service. In 5G networks environmentalfactors also a...
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The work devises the Blockchain-Enabled Federated Learning Algorithm Framework (DLEBAF) with different strategies. The first strategy is deadline-efficient task sequencing and scheduling (DETS), which allocates all applications (workloads) according to their deadline. The second strategy is latency-efficient task scheduling (LETS) to minimize the l...
Article
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The electroencephalogram (EEG) introduced a massive potential for user identification. Several studies have shown that EEG provides unique features in addition to typical strength for spoofing attacks. EEG provides a graphic recording of the brain’s electrical activity that electrodes can capture on the scalp at different places. However, selecting...
Article
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Air pollution is increasing profusely in Indian cities as well as throughout the world, and it poses a major threat to climate as well as the health of all living things. Air pollution is the reason behind degraded indoor air quality (IAQ) in urban buildings. Carbon dioxide (CO 2) is the main contributor to indoor pollution as humans themselves are...
Article
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In a network architecture, an intrusion detection system (IDS) is one of the most commonly used approaches to secure the integrity and availability of critical assets in protected systems. Many existing network intrusion detection systems (NIDS) utilize stand-alone classifier models to classify network traffic as an attack or as normal. Due to the...
Article
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This research work highlight the newly developed concept of Rosseland approximation and gyrotactic microorganisms in steady, two-dimensional, incompressible flow of Walter's-B nanofluid (non-Newtonian) over a stretch-able surface of sheet. Buongiorno nanofluid model, which represents seven important slip mechanisms (i.e., Brownian motion, inertia,...
Article
Nowadays, data privacy is an important consideration in machine learning. This paper provides an overview of how Federated Learning can be used to improve data security and privacy. Federated Learning is made up of three distinct architectures that ensure that privacy is never jeopardised. Federated learning is a type of collective learning in whic...
Article
Visual analysis of fashion images gain much attention in the fashion industry due to its commercial and social importance. In recent years, deep learning techniques offer overwhelming progress in improving the accuracy of fine‐grained apparel segmentation with accurate bounding box prediction. The baseline pixel‐based masking techniques show excell...
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The early prediction of Alzheimer's disease (AD) can be vital for the endurance of patients and establishes as an accommodating and facilitative factor for specialists. The proposed work presents a robotized predictive structure, dependent on machine learning (ML) methods for the forecast of AD. Neuropsychological measures (NM) and magnetic resonan...
Article
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Human gait recognition (HGR) has received a lot of attention in the last decade as an alternative biometric technique. The main challenges in gait recognition are the change in in-person view angle and covariant factors. The major covariant factors are walking while carrying a bag and walking while wearing a coat. Deep learning is a new machine lea...
Article
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Biomedical imaging technologies are designed to offer functional, anatomical, and molecular details related to the internal organs. Photoacoustic imaging (PAI) is becoming familiar among researchers and industrialists. The PAI is found useful in several applications of brain and cancer imaging such as prostate cancer, breast cancer, and ovarian can...