Nouar Aldahoul

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Verified

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• PHD in Machine Learning
• Postdoctoral Associate at New York University Abu Dhabi

recognizing human activities is one of the main goals of human-centered intelligent systems. Smartphone sensors produce a continuous sequence of observations. These observations are noisy, unstructured and high dimensional. Therefore, efficient features have to be extracted in order to perform an accurate classification. This paper proposes a combi...

This paper examines how decentralized energy systems can be enhanced using collaborative Edge Artificial Intelligence. Decentralized grids use local renewable sources to reduce transmission losses and improve energy security. Edge AI enables real-time, privacy-preserving data processing at the network edge. Techniques such as federated learning and...

Large Language Models (LLMs) are a transformational technology, fundamentally changing how people obtain information and interact with the world. As people become increasingly reliant on them for an enormous variety of tasks, a body of academic research has developed to examine these models for inherent biases, especially political biases, often fi...

Text-to-image generative AI models such as Stable Diffusion are used daily by millions worldwide. However, the extent to which these models exhibit racial and gender stereotypes is not yet fully understood. Here, we document significant biases in Stable Diffusion across six races, two genders, 32 professions, and eight attributes. Additionally, we...

Bias in news reporting significantly impacts public perception, particularly regarding crime, politics, and societal issues. Traditional bias detection methods, predominantly reliant on human moderation, suffer from subjective interpretations and scalability constraints. Here, we introduce an AI-driven framework leveraging advanced large language m...

Generative Artificial Intelligence (AI) is a cutting-edge technology capable of producing text, images, and various media content leveraging generative models and user prompts. Between 2022 and 2023, generative AI surged in popularity with a plethora of applications spanning from AI-powered movies to chatbots. This paper investigates the potential...

Accessing the internet in regions with expensive data plans and limited connectivity poses significant challenges, restricting information access and economic growth. Images, as a major contributor to webpage sizes, exacerbate this issue, despite advances in compression formats like WebP and AVIF. The continued growth of complex and curated web con...

The integration of Generative Artificial Intelligence (GenAI) into university-level academic writing presents both opportunities and challenges, particularly in relation to cognitive dissonance (CD). This work explores how GenAI serves as both a trigger and amplifier of CD, as students navigate ethical concerns, academic integrity, and self-efficac...

TikTok is a major force among social media platforms with over a billion monthly active users worldwide and 170 million in the United States. The platform's status as a key news source, particularly among younger demographics, raises concerns about its potential influence on politics in the U.S. and globally. Despite these concerns, there is scant...

License plate recognition (LPR) involves automated systems that utilize cameras and computer vision to read vehicle license plates. Such plates collected through LPR can then be compared against databases to identify stolen vehicles, uninsured drivers, crime suspects, and more. The LPR system plays a significant role in saving time for institutions...

The widespread dissemination of hate speech, harassment, harmful and sexual content, and violence across websites and media platforms presents substantial challenges and provokes widespread concern among different sectors of society. Governments, educators, and parents are often at odds with media platforms about how to regulate, control, and limit...

Hyper-personalized medicine represents an advanced approach to healthcare, integrating real-time lifestyle, environmental, genetic, and biological data to tailor medical interventions for individual needs. This approach transcends traditional genetic profiling by focusing on the dynamic interplay between personal habits, environmental conditions, a...

Personalized medicine (PM) promises to transform healthcare by providing treatments tailored to individual genetic, environmental, and lifestyle factors. However, its high costs and infrastructure demands raise concerns about exacerbating health disparities, especially between high-income countries (HICs) and low- and middle-income countries (LMICs...

Technologies for recognizing facial attributes like race, gender, age, and emotion have several applications, such as surveillance, advertising content, sentiment analysis, and the study of demographic trends and social behaviors. Analyzing demographic characteristics based on images and analyzing facial expressions have several challenges due to t...

The manner in which different racial and gender groups are portrayed in news coverage plays a large role in shaping public opinion. As such, understanding how such groups are portrayed in news media is of notable societal value, and has thus been a significant endeavour in both the computer and social sciences. Yet, the literature still lacks a lon...

In recent years, Advanced Persistent Threat (APT) attacks on network systems have increased through sophisticated fraud tactics. Traditional Intrusion Detection Systems (IDSs) suffer from low detection accuracy, high false-positive rates, and difficulty identifying unknown attacks such as remote-to-local (R2L) and user-to-root (U2R) attacks. This p...

Recent breakthroughs in Large Language Models (LLMs) have led to their adoption across a wide range of tasks, ranging from code generation to machine translation and sentiment analysis, etc. Red teaming/Safety alignment efforts show that fine-tuning models on benign (non-harmful) data could compromise safety. However, it remains unclear to what ext...

Wind energy is a valuable renewable resource that plays a significant role in electricity generation process. Predicting wind speed (W.S.) is critical for effectively managing wind energy and producing power. This study proposes an improved multi-layer perceptron (MLP) model for W.S. prediction that incorporates a novel optimization algorithm namel...

Large language models (LLMs) demonstrate impressive zero-shot and few-shot reasoning capabilities. Some propose that such capabilities can be improved through self-reflection, i.e., letting LLMs reflect on their own output to identify and correct mistakes in the initial responses. However, despite some evidence showing the benefits of self-reflecti...

Over two-thirds of the U.S. population uses YouTube, and a quarter of U.S. adults regularly receive their news from it. Despite the massive political content available on the platform, to date, no classifier has been proposed to classify the political leaning of YouTube videos. The only exception is a classifier that requires extensive information...

Laparoscopic videos are tools used by surgeons to insert narrow tubes into the abdomen and keep the skin without large incisions. The videos captured by a camera are prone to numerous distortions such as uneven illumination, motion blur, defocus blur, smoke, and noise which have impact on visual quality. Automatic detection and identification of di...

Electrocardiogram (ECG) signal analysis and processing are crucial in the diagnosis of cardiovascular diseases which are considered as one of the leading causes of mortality worldwide. However, the traditional rule-based analysis of large volumes of ECG data is time-consuming, labor-intensive, and prone to human errors. With the advancement of the...

Internet has become a main source of information for people in numerous areas. However, internet can be useful or harmful according to types of contents exposed. When the visual sexual and violent contents are available, the danger targets children and youths and causes a damage in their mental health. Consequently, content moderators are required...

Natural calamities like droughts have harmed not just humanity throughout history but also the economy, food, agricultural production, flora, animal habitat, etc. A drought monitoring system must incorporate a study of the geographical and temporal fluctuation of the drought characteristics to function effectively. This study investigated the space...

Due to excessive streamflow (SF), Peninsular Malaysia has historically experienced floods and droughts. Forecasting streamflow to mitigate municipal and environmental damage is therefore crucial. Streamflow prediction has been extensively demonstrated in the literature to estimate the continuous values of streamflow level. Prediction of continuous...

Today, network security is crucial due to the rapid development of network and internet technologies, as well as the continuous growth in network threats. Detecting network anomalies is one of the approaches that may be used to safeguard a network's security. Recent research has focused extensively on techniques for identifying abnormalities. Using...

Intestinal parasitic infections (IPIs) caused by protozoan and helminth parasites are among the most common infections in humans in low-and-middle-income countries. IPIs affect not only the health status of a country, but also the economic sector. Over the last decade, pattern recognition and image processing techniques have been developed to autom...

With over two billion monthly active users, YouTube currently shapes the landscape of online political video consumption, with 25% of adults in the United States regularly consuming political content via the platform. Considering that nearly three quarters of the videos watched on YouTube are delivered via its recommendation algorithm, the propensi...

Vidos from a first-person or egocentric perspective offer a promising tool for recognizing various activities related to daily living. In the egocentric perspective, the video is obtained from a wearable camera, and this enables the capture of the person’s activities in a consistent viewpoint. Recognition of activity using a wearable sensor is chal...

Machine learning techniques have been used widely to analyze videos that have scenes of violence for censorship or surveillance purposes. Violence detection is an essential act to prevent underage and teenagers from being exposed to violent acts that have harmful impact on viewers’ behavioral and mental health. Automatic identification of violent s...

Content moderation software was found to automate the reviewing and editing process. Big companies such as Microsoft Azure and Amazon Web Services (AWS) created their own content moderators that can be employed in websites, video sharing platforms, social media, broadcast media, advertising, and e-commerce situations to detect inappropriate visual...

Today, network security is crucial due to the rapid development of network and internet technologies, as well as the continuous growth in network threats. Detecting network anomalies is one of the approaches that may be used to safeguard a network's security. Recent research has focused extensively on techniques for identifying abnormalities. Using...

The water is the main pivotal sources of irrigation in agricultural activities and affects human daily activities such as drinking. The water quality has a significant impact on various aspects and thus this review aims to addresses existing problems related to water quality prediction methods that have been found in the literature. We explore nume...

Electrocardiogram (ECG) signal analysis and processing are crucial in the diagnosis of cardiovascular diseases which are considered as one of the leading causes of mortality worldwide. However, the traditional rule-based analysis of large volumes of ECG data is time-consuming, labor-intensive, and prone to human errors. With the advancement of the...

Skin diseases are considered the fourth most common disease, with melanoma and non-melanoma skin cancer as the most common type of cancer in Caucasians. The alarming increase in Skin Cancer cases shows an urgent need for further research to improve diagnostic methods, as early diagnosis can significantly improve the 5-year survival rate. Machine Le...

Blood cell counting plays a crucial role in clinical diagnosis to evaluate the overall health condition of an individual. Traditionally, blood cells are manually counted using a hemocytometer; however, this task has been found to be time-consuming and error-prone. Recently, machine learning-based approaches have been employed to effectively automat...

Space situational awareness (SSA) system requires recognition of space objects that are varied in sizes, shapes, and types. The space images are challenging because of several factors such as illumination and noise and thus make the recognition task complex. Image fusion is an important area in image processing for various applications including RG...

Space situational awareness (SSA) systems play a significant role in space navigation missions. One of the most essential tasks of this system is to recognize space objects such as spacecrafts and debris for various purposes including active debris removal, on-orbit servicing, and satellite formation. The complexity of object recognition in space i...

Hormone receptor status is determined primarily to identify breast cancer patients who may benefit from hormonal therapy. The current clinical practice for the testing using either Allred score or H-score is still based on laborious manual counting and estimation of the amount and intensity of positively stained cancer cells in immunohistochemistry...

The demand for nudity and pornographic content detection is increasing due to the prevalence of media products containing sexually explicit content with Internet being the main source. Recent literature has proved the effectiveness of deep learning techniques for adult image and video detection. However, the requirement for a huge dataset with labe...

IPIs caused by protozoan and helminth parasites are among the most common infections in humans in LMICs. They are regarded as a severe public health concern, as they cause a wide array of potentially detrimental health conditions. Researchers have been developing pattern recognition techniques for the automatic identification of parasite eggs in mi...

Many species have gone extinct as a result of human neglect and various environmental influences. Monitoring these species has proven to be a challenge due to their small population, remote habitats, and evasiveness, among other reasons. Nonetheless, they can be routinely tracked by using CCTV cameras. This project made use of a transfer learning a...

The perceptual quality of video surveillance footage has impacts on several tasks involved in the surveillance process, such as the detection of anomalous objects. The videos captured by a camera are prone to various distortions such as noise, smoke, haze, low or uneven illumination, blur, rain, and compression, which affect visual quality. Automat...

Differentiating white blood cells has been a fundamental part of medical diagnosis as it allows the assessment of the state of health of various organ systems in an animal. However, the examination of blood smears is time-consuming and is dependent on the level of the health professional’s expertise. With this, automated computer-based systems have...

Many species have gone extinct as a result of human neglect and various environmental influences. Monitoring these species has proven to be a challenge due to their small population, remote habitats, and evasiveness, among other reasons. Nonetheless, they can be routinely tracked by using CCTV cameras. This project made use of a transfer learning a...

IPIs caused by protozoan and helminth parasites are among the most common infections in humans in LMICs. They are regarded as a severe public health concern, as they cause a wide array of potentially detrimental health conditions. Researchers have been developing pattern recognition techniques for the automatic identification of parasite eggs in mi...

Optical Character Recognition (OCR) has been investigated widely to recognize characters in images for various applications including license plate recognition. Several limitations and distortions are available in images such as noise, blurring, and closed characters (alphabet and numbers) which makes the task of recognition more complex. This pape...

Human detection and activity recognition (HDAR) in videos plays an important role in various real-life applications. Recently, object detection methods have been used to detect humans in videos for subsequent decision-making applications. This paper aims to address the problem of human detection in aerial captured video sequences using a moving cam...

The suspended sediment load (SSL) is one of the major hydrological processes affecting the sustainability of river planning and management. Moreover, sediments have a significant impact on dam operation and reservoir capacity. To this end, reliable and applicable models are required to compute and classify the SSL in rivers. The application of mach...

The Visayan warty pig is one of the endemic species of the Philippines that have been listed as "critically endangered." Conservation actions and efforts, such as health assessments, are being carried out to preserve the population. However, there is limited information about the normal hematological and biochemical profile of the species. The stud...

Recognition of space objects including spacecraft and debris is one of the main components in the space situational awareness (SSA) system. Various tasks such as satellite formation, on-orbit servicing, and active debris removal require object recognition to be done perfectly. The recognition task in actual space imagery is highly complex because t...

Floods are the most frequent type of natural disaster. It destroys wildlife habitat, damages bridges, railways, roads, properties, and puts millions of people at risk. As such, flood detection systems have been developed to monitor the changes of water level and raise an alarm should there be imminent danger. River water level prediction is a signi...

Ozone (O3) is one of the common air pollutants. An increase in the ozone concentration can adversely affect public health and the environment such as vegetation and crops. Therefore, atmospheric air quality monitoring systems were found to monitor and predict ozone concentration. Due to complex formation of ozone influenced by precursors of ozone (...

Background: Laparoscopy is a surgery performed in the abdomen without making large incisions in the skin and with the aid of a video camera, resulting in laparoscopic videos. The laparoscopic video is prone to various distortions such as noise, smoke, uneven illumination, defocus blur, and motion blur. One of the main components in the feedback loo...

Diabetes is one of the top ten causes of death among adults worldwide. People with diabetes are prone to suffer from eye disease such as diabetic retinopathy (DR). DR damages the blood vessels in the retina and can result in vision loss. DR grading is an essential step to take to help in the early diagnosis and in the effective treatment thereof, a...

Spacecraft recognition is a significant component of space situational awareness (SSA), especially for applications such as active debris removal, on-orbit servicing, and satellite formation. The complexity of recognition in actual space imagery is caused by a large diversity in sensing conditions, including background noise, low signal-to-noise ra...

From a public health perspective, this opinion article discusses the necessity to push for telehealth in the Philippines as a mode of healthcare delivery, based on lessons from other Southeast Asian countries. With the recent pandemic, the Philippines has witnessed the potential of telehealth to cater to the healthcare needs of the public. Teleheal...

Laparoscopic surgery is a surgical procedure performed by inserting narrow tubes into the abdomen without making large incisions in the skin. It is done with the aid of a video camera. Laparoscopic videos are affected by various distortions during surgery which lead to loss of visual quality. Identification of these distortions is the primary requ...

Network Anomaly Detection is still an open challenging task that aims to detect anomalous network traffic for security purposes. Usually, the network traffic data are large-scale and imbalanced. Additionally, they have noisy labels. This paper addresses the previous challenges and utilizes million-scale and highly imbalanced ZYELL’s dataset. We pro...

From a public health perspective, this opinion article discusses why it is necessary to integrate Artificial Intelligence (AI) in the mental health practices in the Philippines. The use of AI systems is an optimum solution to the rising demand for more accessible, cost-efficient, and inclusive healthcare. With the recent developments, the Philippin...

Violence detection has been investigated extensively in the literature. Recently, IOT based violence video surveillance is an intelligent component integrated in security system of smart buildings. Violence video detector is a specific kind of detection models that should be highly accurate to increase the model’s sensitivity and reduce the false a...

Detection of adult contents such as pornography, sex, and nudity has been investigated extensively in the literature. Recently, content moderator is a significant component for social platforms to be integrated in their software applications and services. Cartoon content moderator is a specific kind of moderators that should be highly accurate to r...

Pornographic and nudity content detection in videos is gaining importance as Internet grows to become a source for exposure to such content. Recent literature involved pornography recognition using deep learning techniques such as convolutional neural network, object detection models and recurrent neural networks, as well as combinations of these m...

Foul language exists in films, video-sharing platforms, and social media platforms, which increase the risk of a viewer to be exposed to large number of profane words that have negative personal and social impact. This work proposes a CNN-based spoken Malay foul words recognition to establish the base of spoken foul terms detection for monitoring a...

Rivers carry suspended sediments along with their flow. These sediments deposit at different places depending on the discharge and course of the river. However, the deposition of these sediments impacts environmental health, agricultural activities, and portable water sources. Deposition of suspended sediments reduces the flow area, thus affecting...

Inappropriate visual content on the internet has spread everywhere, and thus children are exposed unintentionally to sexually explicit visual content. Animated cartoon movies sometimes have sensitive content such as pornography and sex. Usually, video sharing platforms take children’s e-safety into consideration through manual censorship, which is...

Given the excessive foul language identified in audio and video files and the detrimental consequences to an individual’s character and behaviour, content censorship is crucial to filter profanities from young viewers with higher exposure to uncensored content. Although manual detection and censorship were implemented, the methods proved tedious. I...

Video pornography and nudity detection aim to detect and classify people in videos into nude or normal for censorship purposes. Recent literature has demonstrated pornography detection utilising the convolutional neural network (CNN) to extract features directly from the whole frames and support vector machine (SVM) to classify the extracted featur...

Content filtering is gaining popularity due to easy exposure of explicit visual contents to the public. Excessive exposure of inappropriate visual contents can cause devastating effects such as the growth of improper mindset and rise of societal issues such as free sex, child abandonment and rape cases. At present, most of the broadcasting media si...

Excessive content of profanity in audio and video files has proven to shape one’s character and behavior. Currently, conventional methods of manual detection and censorship are being used. Manual censorship method is time consuming and prone to misdetection of foul language. This paper proposed an intelligent model for foul language censorship thro...