Mohammed Zakariah

King Saud University | KKUH · College of Computer and Information Sciences

Brain signal analysis from electroencephalogram (EEG) recordings is the gold standard for diagnosing various neural disorders especially epileptic seizure. Seizure signals are highly chaotic compared to normal brain signals and thus can be identified from EEG recordings. In the current seizure detection and classification landscape, most models pri...

Federated learning (FL) is a popular method where edge devices work together to train machine learning models. This study introduces an efficient network for analyzing healthcare records. It uses VPN technology and applies a federated learning approach over a wireless backhaul network. The study compares different wireless backhaul channels, includ...

The security of the wireless sensor network-Internet of Things (WSN-IoT) network is more challenging due to its randomness and self-organized nature. Intrusion detection is one of the key methodologies utilized to ensure the security of the network. Conventional intrusion detection mechanisms have issues such as higher misclassification rates, incr...

This study describes improving network security by implementing and assessing an intrusion detection system (IDS) based on deep neural networks (DNNs). The paper investigates contemporary technical ways for enhancing intrusion detection performance, given the vital relevance of safeguarding computer networks against harmful activity. The DNN-based...

Intrusion detection systems (IDS) are essential in the field of cybersecurity because they protect networks from a wide range of online threats. The goal of this research is to meet the urgent need for small-footprint, highly-adaptable Network Intrusion Detection Systems (NIDS) that can identify anomalies. The NSL-KDD dataset is used in the study;...

Speech Emotion Recognition (SER) has advanced considerably during the past 20 years. Till date, various SER systems have been developed for monolingual, multilingual and cross corpus contexts. However, in a country like India where numerous languages are spoken and often humans converse in more than one language, a dedicated SER system for mixed-li...

Detecting plant leaf diseases accurately and promptly is essential for reducing economic consequences and maximizing crop yield. However, farmers’ dependence on conventional manual techniques presents a difficulty in accurately pinpointing particular diseases. This research investigates the utilization of the YOLOv4 algorithm for detecting and iden...

This paper investigates the potential of COVID-19 detection using cough, breathing, and voice patterns. Speech-based features, such as MFCC, zero crossing rate, spectral centroid, spectral bandwidth, and chroma STFT are extracted from audio recordings and evaluated for their effectiveness in identifying COVID-19 cases from Coswara dataset. The expl...

Machine learning algorithms have recently been increasingly used in medical data, particularly in healthcare areas where image processing techniques have played a crucial role. This study aims to utilize artificial intelligence (AI) techniques to forecast respiratory diseases by implementing a deep convolutional neural network (CNN) structure. The...

Monitoring student activity manually constantly is a laborious endeavor. Over the past few years, there has been a rapid expansion in the usage of cameras and the automatic identification of odd surveillance behavior. Different computer vision algorithms have been used to observe and monitor real-world activities. Most educational institutions are...

Multimodal emotion recognition is a developing field that analyzes emotions through various channels, mainly audio, video, and text. However, existing state-of-the-art systems focus on two to three modalities at the most, utilize traditional techniques, fail to consider emotional interplay, lack the scope to add more modalities, and aren’t efficien...

Protection against unwanted intrusions is crucial for preserving the integrity and security of connected devices in the context of Internet of Things (IoT) networks. The growing number of IoT devices has made several industries more vulnerable to cyberattacks and security breaches, including smart homes, industrial automation, and healthcare. In re...

Communication is essential for humanity today and in the past. However, some individuals lack verbal communication due to their innate disability and physical losses from accidents. There are sign-language communication methods developed for such people to communicate. Artificial intelligence solutions are offered to remove the disadvantaged situat...

The exponential expansion of the Internet of Things (IoT) has fundamentally transformed the way people, machines, and gadgets communicate, resulting in unparalleled levels of interconnectedness. Nevertheless, the growth of IoT has also brought up notable security obstacles, requiring the creation of strong intrusion detection systems to safeguard I...

Air traffic controllers (ATC) play a critical role in ensuring aviation safety, but their demanding workload can lead to fatigue, potentially compromising their performance. This paper presents a study that investigates speech features responsible for detecting ATC fatigue and proposes an approach to predict the timestamp at which an ATC transition...

Privacy and trust are significant issues in intelligent transportation systems (ITS). Data security is critical in ITS systems since sensitive user data is communicated to another user over the internet through wireless devices and routes such as radio channels, optical fiber, and blockchain technology. The Internet of Things (IoT) is a network of...

Modern networks are at risk from a variety of threats as a result of the enormous growth in internet-based traffic. By consuming time and resources, intrusive traffic hampers the efficient operation of network infrastructure. An effective strategy for preventing, detecting, and mitigating intrusion incidents will increase productivity. A crucial el...

The prevalence of Internet of Things (IoT) technologies is on the rise, making the identification of anomalies in IoT systems crucial for ensuring their security and reliability. However, many existing approaches rely on static classifiers and immutable datasets, limiting their effectiveness. In this paper, we have utilized the UNSW-NB15 dataset, w...

Intrusion detection systems, also known as IDSs, are widely regarded as one of the most essential components of an organization’s network security. This is because IDSs serve as the organization’s first line of defense against several cyberattacks and are accountable for accurately detecting any possible network intrusions. Several implementations...

Modern technology frequently uses wearable sensors to monitor many aspects of human behavior. Since continuous records of heart rate and activity levels are typically gathered, the data generated by these devices have a lot of promise beyond counting the number of daily steps or calories expended. Due to the patient’s inability to obtain the necess...

Traditional firewalls and data encryption techniques can no longer match the demands of current IoT network security due to the rising amount and variety of network threats. In order to manage IoT network risks, intrusion detection solutions have been advised. Even though machine learning (ML) helps the widely used intrusion detection techniques cu...

The growth of biomedical engineering has made depression diagnosis via electroencephalography (EEG) a trendy issue. The two significant challenges to this application are EEG signals’ complexity and non-stationarity. Additionally, the effects caused by individual variances may hamper the generalization of detection systems. Given the association be...

Organizations and individuals worldwide are becoming increasingly vulnerable to cyberattacks as phishing continues to grow and the number of phishing websites grows. As a result, improved cyber defense necessitates more effective phishing detection (PD). In this paper, we introduce a novel method for detecting phishing sites with high accuracy. Our...

Brain tumor (BT) diagnosis is a lengthy process, and great skill and expertise are required from radiologists. As the number of patients has expanded, so has the amount of data to be processed, making previous techniques both costly and ineffective. Many academics have examined a range of reliable and quick techniques for identifying and categorizi...

The process of learning about a student’s knowledge and comprehension of a particular subject is referred to as student knowledge assessment. It helps to identify areas where students need additional support or challenge and can be used to evaluate the effectiveness of instruction, make important decisions such as on student placement and curriculu...

License Plate Recognition (LPR) is essential for the Internet of Vehicles (IoV) since license plates are a necessary characteristic for distinguishing vehicles for traffic management. As the number of vehicles on the road continues to grow, managing and controlling traffic has become increasingly complex. Large cities in particular face significant...

The construction of an automatic voice pathology detection system employing machine learning algorithms to study voice abnormalities is crucial for the early detection of voice pathologies and identifying the specific type of pathology from which patients suffer. This paper’s primary objective is to construct a deep learning model for accurate spee...

Student engagement is a flexible, complicated concept that includes behavioural, emotional, and cognitive involvement. In order for the instructor to understand how the student interacts with the various activities in the classroom, it is essential to predict their participation. The current work aims to identify the best algorithm for predicting s...

Current anti-malware technologies have exposed its glaring vulnerabilities as a result of a signature-based approach as more sophisticated malware has been appearing in recent years, particularly in the android operating system. The state-of-the-art literature offers a wide range of possibilities, but none of them are flawless in terms of providing...

Android malware security tools that can swiftly identify and categorize various malware classes to create rapid response strategies have been trendy in recent years. Although many application fields have demonstrated the usefulness of implementing Machine Learning and deep learning methods to provide automation and self-learning services, the scarc...

The paper describes the creation, analysis and validation of a multilingual Dementia Speech dataset for Indic languages. Three popular Indian languages viz. Telugu, Tamil and Hindi are considered for the pilot study. Dementia and associated Alzheimers disease affect a large section of Asian population. Though there are promising studies in dementia...

Skin cancer is one of the most severe forms of the disease, and it can spread to other parts of the body if not detected early. Therefore, diagnosing and treating skin cancer patients at an early stage is crucial. Since a manual skin cancer diagnosis is both time-consuming and expensive, an incorrect diagnosis is made due to the high similarity bet...

Devices which are part of the Internet of Things (IoT) have strong connections; they generate and consume data, which necessitates data transfer among various devices. Smart gadgets collect sensitive information, perform critical tasks, make decisions based on indicator information, and connect and interact with one another quickly. Securing this s...

Dementia affects the patient’s memory and leads to language impairment. Research has demonstrated that speech and language deterioration is often a clear indication of dementia and plays a crucial role in the recognition process. Even though earlier studies have used speech features to recognize subjects suffering from dementia, they are often used...

COVID-19 has remained a threat to world life despite a recent reduction in cases. There is still a possibility that the virus will evolve and become more contagious. If such a situation occurs, the resulting calamity will be worse than in the past if we act irresponsibly. COVID-19 must be widely screened and recognized early to avert a global epide...

Sign language is essential for deaf and mute people to communicate with normal people and themselves. As ordinary people tend to ignore the importance of sign language, which is the mere source of communication for the deaf and the mute communities. These people are facing significant downfalls in their lives because of these disabilities or impair...

Because underlying cognitive and neuromuscular activities regulate speech signals, biomarkers in the human voice can provide insight into neurological illnesses. Multiple motor and nonmotor aspects of neurologic voice disorders arise from an underlying neurologic condition such as Parkinson's disease, multiple sclerosis, myasthenia gravis, or ALS....

Diseases of internal organs other than the vocal folds can also affect a person’s voice. As a result, voice problems are on the rise, even though they are frequently overlooked. According to a recent study, voice pathology detection systems can successfully help the assessment of voice abnormalities and enable the early diagnosis of voice pathology...

Emotions play an essential role in human relationships, and many real-time applications rely on interpreting the speaker’s emotion from their words. Speech emotion recognition (SER) modules aid human-computer interface (HCI) applications, but they are challenging to implement because of the lack of balanced data for training and clarity about which...

Human-computer interaction (HCI) has seen a paradigm shift from textual or display-based control toward more intuitive control modalities such as voice, gesture, and mimicry. Particularly, speech has a great deal of information, conveying information about the speaker’s inner condition and his/her aim and desire. While word analysis enables the spe...

Sign language is the native language of deaf people, which they use in their daily life, and it facilitates the communication process between deaf people. The problem faced by deaf people is targeted using sign language technique. Sign language refers to the use of the arms and hands to communicate, particularly among those who are deaf. This varie...

Several speaker recognition algorithms failed to get the best results because of the wildly varying datasets and feature sets for classification. Gender information helps reduce this effort since categorizing the classes based on gender may help lessen the impact of gender variability on the retrieved features. This study attempted to construct a p...

Brain tumor classification is a very important and the most prominent step for assessing life-threatening abnormal tissues and providing an efficient treatment in patient recovery. To identify pathological conditions in the brain, there exist various medical imaging technologies. Magnetic Resonance Imaging (MRI) is extensively used in medical imagi...

In experimental analysis and computer-aided design sustain scheme, segmentation of cell liver and hepatic lesions by an automated method is a significant step for studying the biomarkers characteristics in experimental analysis and computer-aided design sustain scheme. Patient to patient, the change in lesion type is dependent on the size, imaging...

The use of machine learning algorithms for facial expression recognition and patient monitoring is a growing area of research interest. In this study, we present a technique for facial expression recognition based on deep learning algorithm: convolutional neural network (ConvNet). Data were collected from the FER2013 dataset that contains samples o...

Classification of indoor environments is a challenging problem. The availability of low-cost depth sensors has opened up a new research area of using depth information in addition to color image (RGB) data for scene understanding. Transfer learning of deep convolutional networks with pairs of RGB and depth (RGB-D) images has to deal with integratin...

Segmentation of cell liver and hepatic lesions through the automatic process is the important procedure for analyzing the biomarkers features in experimental analysis and Computer-aided design sustain scheme. The difference in the lesion type depends upon the size, imaging equipment such as setting dissimilarity technique, and timing which differ f...

Automatic recognition of human emotions in a continuous dialog model remains challenging where a speaker’s utterance includes several sentences that may not always carry a single emotion. Limited work with standalone speech emotion recognition (SER) systems proposed for continuous speech only has been reported. In the recent decade, various effecti...

Automated grading of colon biopsy images across all magnifications is challenging because of tailored segmentation and dependent features on each magnification. This work presents a novel approach of robust magnification-independent colon cancer grading framework to distinguish colon biopsy images into four classes: normal, well, moderate, and poor...

Currently, distracted driving is among the most important causes of traffic accidents. Consequently, intelligent vehicle driving systems have become increasingly important. Recently, interest in driver-assistance systems that detect driver actions and help them drive safely has increased. In these studies, although some distinct data types, such as...

Citation Information: Aldakheel, E.A., & Zakariah, M. (2021). Digital transformation challenges in healthcare and its effect on the patient–physician relationship. Journal of Management Information and Decision Sciences, 24(S6), 1-11. Digital transformation challenges in healthcare and its effect on the patient-physician relationship. ABSTRACT Heal...

Citation Information: Aldakheel, E.A., & Zakariah, M. (2021). Mobile devices and cybersecurity issues authentication techniques with machine learning. Journal of Management Information and Decision Sciences, 24(S6), 1-15. Cybersecurity is the most important and hot research topic, especially at this time. As people are getting more dependent on dig...

Citation Information: Aldakheel, E.A., & Zakariah, M. (2021). Detection of targeted region using deep learning-based multiscale alexnet cnn scheme for hyperspectral satellite image. Journal of Management Information and Decision Sciences, 24(S6), 1-15. Detection of targeted region using deep learning-based multiscale alexnet cnn scheme for hyperspe...

An algorithm for a potentially non-obtrusive speech production system was developed and characterized. The algorithm is primarily based on the articulation of the human tongue referred as tongue articulatory system (TAS) and was cascaded with a previously developed laryngeal model. We developed and optimized statistical formulae for formants of vow...

In the past decade, research for improving man–machine communication has focused on emotion recognition using audio cues. Several effective monolingual, multilingual, and cross-corpus speech emotion recognition (SER) systems have been developed; however, they are limited to recognizing emotions from databases of monolingual discourse, primarily in...

Background Infections of Salmonella typhimurium (S. typhimurium) are major threats to health, threats include diarrhoea, fever, acute intestinal inflammation, and cancer. Nevertheless, little information is available about the involvement of S. typhimurium in colon cancer etiology. Methods The present study was designed to predict nuclear targetin...

An edge detection is a critical tool under image processing and computer vision. It is used for security and reliability purposes to provide enhanced information about an object and recognize the contents of the image for the applications of object recognition in computer vision. The most prominent application may be pedestrian detection, face dete...

We propose a hybrid network-based learning framework for speaker-adaptive vocal emotion conversion, tested on three different datasets (languages), namely, EmoDB (German), IITKGP (Telugu), and SAVEE (English). The optimized learning model introduced is unique because of its ability to synthesize emotional speech with an acceptable perceptive qualit...