Mohd Yamani Idna Idris

• Phd
• Professor at University of Malaya

Maintaining visual and semantic consistency across frames is a key challenge in text-to-image storytelling. Existing training-free methods, such as One-Prompt-One-Story, concatenate all prompts into a single sequence, which often induces strong embedding correlation and leads to color leakage, background blending, and identity drift. We propose DeC...

Large multimodal models have enabled one-click storybook generation, where users provide a short description and receive a multi-page illustrated story. However, the underlying story state, such as characters, world settings, and page-level objects, remains implicit, making edits coarse-grained and often breaking visual consistency. We present Stor...

Generating coherent visual stories requires maintaining subject identity across multiple images while preserving frame-specific semantics. Recent training-free methods concatenate identity and frame prompts into a unified representation, but this often introduces inter-frame semantic interference that weakens identity preservation in complex storie...

Early disruption of Advanced Persistent Threat (APT) campaigns hinges on recognising the attackers’ tactics, techniques and procedures (TTPs), which remain stable even after individual indicators of compromise (IOC) are rotated. Most prior studies derive such patterns from vendor-curated cyber-threat-intelligence reports, sources that can reflect c...

In this paper, a novel bio-inspired optimization algorithm is proposed, called Bombardier Beetle Optimizer (BBO). This type of species is very intelligent, which has an ability to defense and escape from predators. The principles of the former one is inspired by the defense mechanism of Bombardier Beetle against the predators, which the Bombardier...

Breast cancer is one of the leading causes of cancer-related morbidity worldwide, underscoring the need for advanced diagnostic tools to improve early detection and treatment outcomes. This study introduces MammoSegNet, a novel convolutional neural network architecture optimized for precisely segmenting mammographic images. The proposed MammoSegNet...

Visual reasoning is critical for a wide range of computer vision tasks that go beyond surface-level object detection and classification. Despite notable advances in relational, symbolic, temporal, causal, and commonsense reasoning, existing surveys often address these directions in isolation, lacking a unified analysis and comparison across reasoni...

Quantitative remote sensing inversion aims to estimate continuous surface variables-such as biomass, vegetation indices, and evapotranspiration-from satellite observations, supporting applications in ecosystem monitoring, carbon accounting, and land management. With the evolution of remote sensing systems and artificial intelligence, traditional ph...

Hair artifacts in dermoscopic images significantly hinder the accurate diagnosis of melanoma and other skin conditions by obscuring critical lesion details. To address this challenge, we introduce DPA-HairNet, a novel Dual Encoder Attention-Based Network designed specifically for effective hair artifact removal while preserving lesion integrity. Th...

We introduce Layered Self-Supervised Knowledge Distillation (LSSKD) framework for training compact deep learning models. Unlike traditional methods that rely on pre-trained teacher networks, our approach appends auxiliary classifiers to intermediate feature maps, generating diverse self-supervised knowledge and enabling one-to-one transfer across d...

We propose SatelliteFormula, a novel symbolic regression framework that derives physically interpretable expressions directly from multi-spectral remote sensing imagery. Unlike traditional empirical indices or black-box learning models, SatelliteFormula combines a Vision Transformer-based encoder for spatial-spectral feature extraction with physics...

Cloud occlusion significantly hinders remote sensing applications by obstructing surface information and complicating analysis. To address this, we propose DC4CR (Diffusion Control for Cloud Removal), a novel multimodal diffusion-based framework for cloud removal in remote sensing imagery. Our method introduces prompt-driven control, allowing selec...

We present DanceText, a training-free framework for multilingual text editing in images, designed to support complex geometric transformations and achieve seamless foreground-background integration. While diffusion-based generative models have shown promise in text-guided image synthesis, they often lack controllability and fail to preserve layout...

Quantitative remote sensing inversion plays a critical role in environmental monitoring, enabling the estimation of key ecological variables such as vegetation indices, canopy structure, and carbon stock. Although vision foundation models have achieved remarkable progress in classification and segmentation tasks, their application to physically int...

Precipitation plays a critical role in the Earth's hydrological cycle, directly affecting ecosystems, agriculture, and water resource management. Accurate precipitation estimation and prediction are crucial for understanding climate dynamics, disaster preparedness, and environmental monitoring. In recent years, artificial intelligence (AI) has gain...

The International Journal of Artificial Intelligence for Science (IJAI4S) is established to address the growing role of artificial intelligence (AI) in scientific research. As AI technologies continue to advance, they are increasingly applied across various scientific domains, including physics, chemistry, biology, medicine, environmental science,...

This paper proposes a new hybrid algorithm, combining FA, SSO, and the N-R method to accelerate convergence towards global optima, named the Hybrid Firefly Algorithm and Sperm Swarm Optimization with Newton-Raphson (HFASSON). The performance of HFASSON is evaluated using 23 benchmark functions from the CEC 2017 suite, tested in 30, 50, and 100 dime...

Forests serve as vital carbon reservoirs, reducing atmospheric CO2 and mitigating climate change. Monitoring carbon stocks typically combines ground-based data with satellite remote sensing, yet accuracy remains a challenge. This study analyzes Huize County, China, using GF-1 WFV and Landsat TM images and introduces the Quantitative Remote Sensing...

Pollen grains play a critical role in environmental, agricultural, and allergy research despite their tiny dimensions. The accurate classification of pollen grains remains a significant challenge, mainly attributable to their intricate structures and the extensive diversity of species. Traditional methods often lack accuracy and effectiveness, prom...

Organizations are adopting the Bring Your Own Device (BYOD) concept to enhance productivity and reduce expenses. However, this trend introduces security challenges, such as unauthorized access. Traditional access control systems, such as Attribute-Based Access Control (ABAC) and Role-Based Access Control (RBAC), are limited in their ability to enfo...

Fruits are mature ovaries of flowering plants that are integral to human diets, providing essential nutrients such as vitamins, minerals, fiber and antioxidants that are crucial for health and disease prevention. Accurate classification and segmentation of fruits are crucial in the agricultural sector for enhancing the efficiency of sorting and qua...

The worldwide prevalence of thyroid disease is on the rise, representing a chronic condition that significantly impacts global mortality rates. Machine learning (ML) approaches have demonstrated potential superiority in mitigating the occurrence of this disease by facilitating early detection and treatment. However, there is a growing demand among...

The Internet of Things (IoT) is a fast-growing technology that enable existing systems to communicate with one another by using new devices such as sensors and other smart devices. The IoT devices such as wireless sensors and other smart devices are often very cheap, very small, and have limited power sources, memories, and processing capabilities....

The rapid advancement of information technology (IT) has given rise to a new era of efficient and fast communication and transactions. However, the increasing adoption of and reliance on IT has led to the exposure of personal and sensitive information online. Safeguarding this information against unauthorized access remains a persistent challenge,...

The energy of sensor nodes in the network consumes more energy due to the sending and receiving of data among them before being forwarded to the server or the sink. Therefore, the remains energy of nodes is one of the main concerns in Wireless Sensor Networks (WSNs) that should be addressed and improved. Many approaches and methods are proposed to...

The number of devices connected within organisational networks through ”Bring Your Own Device” (BYOD) initiatives has steadily increased. BYOD security risks have resulted in significant privacy and security issues impacting organisational security. Many researchers have reviewed security and privacy issues in BYOD policies. However, not all of the...

Organisations are adopting new IT strategies such as “Bring Your Own Device” (BYOD) and remote working. These trends are highly beneficial both for enterprise owners and employees in terms of increased productivity and reduced costs. However, security issues such as unauthorised access as well as privacy concerns pose significant obstacles. These c...

In earlier years, most malware attacks were against Android smartphones. Unfortunately, for the past few years, the trend has shifted towards attacks against the Apple iOS smartphone. Consequently, an in-depth analysis of the malware and iOS architecture is important to identify the best mitigation solution against malware exploitation. Hence, this...

Flying Ad hoc Network (FANET) is a self-organizing wireless network that constitutes swarms of flying nodes, namely Unmanned Aerial Vehicles (UAV), and communicates in close proximity. It has various distinguishing characteristics that set it apart from other ad hoc networks, posing some issues, particularly in routing. UAVs are highly dynamic and...

Authenticated Encryption (AE) protects confidentiality and integrity at the same time. The sponge construction is based on an iterated permutation or transformation that can be used to implement hashing, and AE schemes, among others. Sponge-based AE schemes offer desirable characteristics like parallelizability and incrementality. In addition, they...

Modeling individual’s variation in speech pattern can be challenging in Automatic Speech Recognition (ASR). In Classical Arabic (CA) language, 20 Quranic accents are permitted for Quranic recitation. An ASR system for CA with accent detection requires a modeling method that can capture speech pattern changes. Here, we study the accentual influences...

In developing an efficient battery management system (BMS), accurate battery state estimation is always required. However, the trade-off between computational efficiency and accuracy of state estimation is hard to maintain. This work proposes the comprehensive co-estimation method for battery states, maximum available capacity, and maximum availabl...

Quality of Service (QoS)-aware service composition plays an increasingly important role in various computational paradigms and delivery models, predominantly cloud computing. The proliferation of services with expanding quality attributes navigates this problem towards big service compositions, which fall under the umbrella of NP-hard. Within the r...

Underwater wireless sensor networks have grown considerably in recent years and now contribute substantially to ocean surveillance applications, marine monitoring and target detection. However, the existing deployment solutions struggle to address the deployment of mobile underwater sensor nodes as a stochastic system. The system faces internal and...

Taken from: https://doi.org/10.1007/s00521-021-05880-4

Skin cancer is the most common type of cancer in many parts of the world. As skin cancers start as skin lesions, it is important to identify precancerous skin lesions early. In this paper we propose an image based skin lesion identification to classify seven different classes of skin lesions. First, Multi Resolution Empirical Mode Decomposition (MR...

“Extremely High Frequency (EHF)” and “Very high frequency (VHF)” bands are mainly utilized with “Underwater Wireless Sensor Networks (UWSNs)” for communication purposes. However, duo to the mobility of underwater sensor in water because the water tide, the EHF/VHF signals may attenuate, loss or fade depending on the condition of the water. There...

As the range of security attacks increases across diverse network applications, intrusion detection systems are of central interest. Such detection systems are more crucial for the Internet of Things (IoT) due to the voluminous and sensitive data it produces. However, the real-world network produces imbalanced traffic including different and unknow...

This research addresses the problem of redundant data transmission and improves load-balance routing in wireless sensor network (WSN). Redundant data generates higher data transfer and additional traffic loads, which degrade the network performance. The sub-clustering approach is used to minimize redundant transmissions by grouping overlapped or cl...

Communication in vehicular ad hoc networks (VANETs) is significantly increased due to several services such as location-based service (LBS), traffic management, road safety, and vehicle privacy. Authentication is one of the backbones for communication in the vehicular network to protect the whole system, and guarantee the unforgeability and effecti...

In the current age, the wide use of digital images has led to the manipulations of content that misrepresent information with malicious goals. This issue demands the requirement of digital image investigation to authenticate the source and certify the trustworthiness of images. One image manipulation technique is called copy-move forgery (CMF), whi...

In developing an efficient battery management system (BMS), an accurate and computationally efficient battery states estimation algorithm is always required. In this work, the highly accurate and computationally efficient model-based state of X (SOX) estimation method is proposed to concurrently estimate the different battery states such as state o...

In recent years, wireless sensor networks (WSNs) have been growing rapidly because of their ability to sense data, communicate wirelessly, and compute data efficiently. These networks contain small and low-powered sensor nodes that organize and configure themselves to carry out their functions. Even though WSNs are cheap, easy to deploy, flexible,...

Background: Walking recovery post stroke can be slow and incomplete. Determining effective stroke rehabilitation frequency requires the assessment of neuroplasticity changes. Neurobiological signals from electroencephalogram (EEG) can measure neuroplasticity through incremental changes of these signals after rehabilitation. However, changes seen w...

Authenticated encryption (AE) is a cryptographic construction that simultaneously protects confidentiality and integrity. A considerable amount of research has been devoted to the area since its formal inception in 2000. Different lines of research have been proposed to enhance the available schemes in terms of security, efficiency, and design and...

Increasing the forecasting accuracy of photovoltaic (PV)-generated power is currently an important topic, particularly in the maintenance of the stability and reliability of modern electric grid systems. In this study, a model based on a particle swarm optimization (PSO)-optimized support vector regression (SVR) is proposed for the accurate forecas...

Since its birth in 2000, authenticated encryption (AE) has been a hot research topic, and many new features have been proposed to boost its security or performance. The Block cipher was the dominant primitive in constructing AE schemes, followed by stream ciphers and compression functions until the sponge construction emerged in 2011. Sponge-based...

A good exploration ability can ensure that the method jumps out of local optimum in multimodal problems and a good exploitation can ensure an algorithm converge faster to global optimum values. So, this paper proposes a new hybrid sperm swarm optimization and genetic algorithm to obtain global optimal solutions termed HSSOGA which is developed base...

With the advent of Service-Oriented Architecture (SOA), services can be registered, invoked, and combined by their identical Quality of Services (QoS) attributes to create a new value-added application that fulfils user requirements. Efficient QoS-aware service composition has been a challenging task in cloud computing. This challenge becomes more...

Industrial internet of things (IIoT) is the usage of internet of things (IoT) devices and applications for the purpose of sensing, processing and communicating real-time events in the industrial system to reduce the unnecessary operational cost and enhance manufacturing and other industrial-related processes to attain more profits. However, such Io...

Feature-based retinal fundus image registration (RIR) technique aligns fundus images according to geometrical transformations estimated between feature point correspondences. To ensure accurate registration, the feature points extracted must be from the retinal vessels and throughout the image. However, noises in the fundus image may resemble retin...

For the advancement of an effective energy management system for an electric vehicle (EV) application, it is constantly needed to utilize a precise battery state of energy (SOE) estimation method. In this study, two different data- driven SOE estimation methods using deep neural network (DNN) and support vector regression (SVR) are compared. The el...

The vehicular network is a collection of vehicles and other components facilitated with versatile sensors to communicate, which is backboned by authentication. Present authentication protocols focus on either the lightweight feature or security. On the other hand, privacy during authentication is essential. Moreover, existing schemes are dependent...

In this article, a Host-Based Intrusion Detection System (HIDS) using a Modified Vector Space Representation (MVSR) N-gram and Multilayer Perceptron (MLP) model for securing the Internet of Things (IoT), based on lightweight techniques and using Fog Computing devices, is proposed. The Australian Defence Force Academy Linux Dataset (ADFA-LD), which...

A substantial number of authentication protocols are designed to safeguard vehicular ad-hoc network (VANET) communication from potential attacks; however, they experienced an inability to provide a balance between lightweight and security. Existing security and privacy-preserving based authentication protocols in vehicular networks mostly rely on t...

A proficient battery management system (BMS) is constantly expected to make an electric vehicle (EV) more dependable. The battery states like state of charge (SOC) and state of health (SOH) estimation are one of the significant functions of BMS. However, the accuracy of the model-based state estimation strategy is profoundly affected by the exhibit...

Internet of Drones (IoD) is a decentralized network and management framework that links drones’ access to the controlled airspace and provides inter-location navigation services. The interconnection of drones in the IoD network is through the Internet of Things (IoT). Hence the IoD network is vulnerable to all the security and privacy threats that...

The implementation of efficient security mechanisms for Radio Frequency Identification (RFID) system has always been a continuous challenge due to its limited computing resources. Previously, hash-based, symmetric-key cryptography-based and elliptic curve cryptography based security protocols were proposed for RFID system. However, these protocols...

Security and privacy are among the most critical challenges on the internet of drones (IoD) network. The communication entities of the IoD network can communicate securely with the use of authenticated key agreement (AKA) based techniques. However, the design of such techniques must be balanced with security and lightweight features. Recently, Chen...

Dental impression tray is frequently used in dentistry to record the patient’s oral structure for clinical oral diagnosis and treatment planning. Manual procedure of taking impressions is costly, time-consuming, and additionally, no research has been done on selecting dental impression tray from dental arch images using computer vision in real-life...

BACKGROUND Walking recovery post-stroke can be slow and incomplete. Determining effective stroke rehabilitation frequency requires assessment of neuroplasticity changes. Neurobiological signals from electroencephalogram (EEG) can measure neuroplasticity through incremental changes of these signals after rehabilitation. However, changes seen with di...

Increased in college/university populations, resulting in insufficient public transportation facilities. Staff members mostly prefer to use their own vehicles to commute to any event or meeting inside the campus rather than an alternative method. This leads to the problem such as an increasing number of vehicles traffic, parking problems, fuel comb...

A hot spot problem is a problem where cluster nodes near to the base station (BS) tend to drain their energy much faster than other nodes due to the need to perform more communication. Unequal clustering methods such as unequal clustering routing (UDCH) and energy‐efficient fuzzy logic for unequal clustering (EEFUC) have been proposed to address th...

A hot spot problem is a problem where cluster nodes near to the base station (BS) tend to drain their energy much faster than other nodes due to the need to perform more communication. Unequal clustering methods such as unequal clustering routing (UDCH) and energy-efficient fuzzy logic for unequal clustering (EEFUC) have been proposed to address th...

With the increasing demand for Lithium-ion batteries in an electric vehicle (EV), it is always crucial to develop a highly accurate and low-cost state estimation method for the battery management system (BMS). Presently, the dual extended Kalman filter (DEKF) is extensively utilized for online SOC estimation. However, the problem of battery model p...

To build up a proficient battery management system, it is required to accurately estimate the state of charge (SOC) of the electric vehicle (EV) battery. Generally, the accuracy of the conventional extended Kalman Filter (CEKF) algorithm is exceptionally affected by the method used to update the noise covariance matrices under running conditions. I...

Vehicle monitoring and positioning become an essential factor in road management to secure and safeguard the vehicular network, which influences the coupling of reliability on the advanced automobile technologies. Furthermore, to predict the exact location of a car in a given time is challenging, because it depends on a myriad number of elements. M...

Internet of Things (IoT) facilitates the integration between objects and different sensors to provide communication among them without human intervention. However, the extensive demand for IoT and its various applications has continued to grow, coupled with the need to achieve foolproof security requirements. IoT produces a vast amount of data unde...

In this work we introduce Multi-Resolution Empirical Mode Decomposition (MREMD) as an image decomposition method that simplifies the implementation of Empirical Mode Decomposition (EMD) for bidimensional data. The proposed method is used in conjunction with the local binary pattern (LBP) to classify the images of six types of defects that can be fo...

To optimize the energy storage management system of an electric vehicle (xEVs), the accurate monitoring of battery states are needed. In this paper, the simple combined state of charge (SOC) and state of energy (SOE) estimation method is proposed. By using this method, the battery SOC and SOE both can be estimated at a low cost of computational com...

The domain of underwater wireless sensor networks (UWSNs) had received a lot of attention recently due to its significant advanced capabilities in the ocean surveillance, marine monitoring and application deployment for detecting underwater targets. However, the literature have not compiled the state-of-the-art along its direction to discover the r...

Recently, the use of electric batteries has reached great heights due to the invention of electric vehicles (EVs). Many lithium-ion battery cells are usually connected in series to meet the voltage requirements. The voltages of the entire series-connected battery cells in a battery pack should be equal. However, such result is impossible due to som...

This work is based on the vehicle positioning system using the statistical approaches. Moreover, the method does not depend on the real time devices such as GPS, or networking technologies.

This work is based on the vehicle positioning system using the statistical approaches. Moreover, the method does not depend on the real time devices such as GPS, or networking technologies.

The inefficient waste collection system has resulted in environmental pollution and large consumption of sources of energy. This is because of inefficient waste collection systems result in smell pollution, unpleasant views, breading of insects, animal scavengers and rodents which also giving rise to a range of diseases when some waste bins are lef...