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As computer network and internet technologies advance more quickly today, the importance of network security is widely acknowledged. This research intends to introduce a new security platform for SaaS framework, which comprises two major phases: (1) ...

In the age of the internet of things (IoT), ensuring security is crucial to protect the interconnected devices and systems. The capacity to identify cyberattacks is essential for IoT security, hence many academics have focused their efforts on developing ...

Histopathological images play a significant role in selecting effective therapeutics and identifying disorders like cancer. Digital histopathology is a crucial advancement in contemporary medicine. The growth and spread of cancer cells within the body ...

We present a six-phase skin cancer classification model based on improved deep joint segmentation (IDJS) in this work. The pre-processed image is segmented using IDJS in the second phase, after contrast enhancement with assistance from contrast limited ...

Coronavirus disease has raised serious health concern across the globe. Identification of severe acute respiratory syndrome corona virus 2 (SARS-CoV-2) variants are indeed a concern in controlling its spread. SARS-CoV-2 variants are classified based on ...

The centralized nature of software‐defined networks (SDN) makes them a suitable choice for vehicular networks. This enables numerous vehicles to communicate within an SD‐vehicular network (SDVN) through vehicle‐to‐vehicle (V2V) and with road‐...

Given a weighted, ordered query set \(Q\) and a partition of \(Q\) into classes, we study the problem of computing a minimum-cost decision tree that, given any query \(q\in Q\), uses equality tests and less-than tests to determine \(q\)’s class. ...

Emotional expressions are a fundamental aspect of human communication, with speech being one of the most natural modes of interaction. Speech Emotion Recognition (SER) is a significant research topic in Natural Language Processing (NLP), aimed at ...

We present a method for prediction of a person’s hairstyle from a single image. Despite growing use cases in user digitization and enrollment for virtual experiences, available methods are limited, particularly in the range of hairstyles they can capture. ...

Audio deepfakes represent a rising threat to trust in our daily communications. In response to this, the research community has developed a wide array of detection techniques aimed at preventing such attacks from deceiving users. Unfortunately, the ...

Deep learning-based approaches have shown great achievement in 3D point analysis. Due to the irregular and unordered data structure, point cloud analysis is still very challenging. Most existing work uses the convolution, graph, or attention ...

Machine-assisted photo identification processes require significant amounts of data for each member of a population of interest but offer the possibility to alleviate a significant amount of manual effort. Gathering such data is time consuming and ...

Yoga, with a history spanning hundreds of years, is often referred to as a “treasure of the world.” As global emphasis on health and fitness increases, yoga, which integrates physical, mental, and spiritual practices, has gained significant ...

Data from multi-modal sensors, such as Red-Green-Blue (RGB) cameras, thermal cameras, microphones, and mmWave radars, have gradually been adopted in various classification problems for better accuracy. Some sensors, like RGB cameras and microphones, ...

There is increasing interest in the adoption of large language models (LLMs) in HCI research. However, LLMs may often be regarded as a panacea because of their powerful capabilities with an accompanying oversight on whether they are suitable for their ...

Association in-between features has been demonstrated to improve the representation ability of data. However, the original association data reconstruction method may face two issues: the dimension of reconstructed data is undoubtedly higher than ...

Research on data annotation for artificial intelligence (AI) has demonstrated that biases, power, and culture impact the ways that annotators apply labels to data and subsequently affect downstream AI systems. However, annotators can only apply labels ...

Dyslexia, a specific learning disorder, poses challenges in reading and language processing. Traditional diagnostic methods often rely on subjective assessments, leading to inaccuracies and delays in intervention. This work proposes classifying ...

Software maintenance is a challenging and laborious software management activity, especially for open‐source software. The bugs reports of such software allow tracking maintenance activities and were used in several empirical studies to better ...

The key findings of the conducted empirical study are as follows: The best performances were achieved by SVM, RT, and kNN techniques, while MNB technique gave low performance. Instance selection algorithms improved the performance of original classifiers,...

Role classification of players according to their uniform or playing kit in unseen soccer game scenes remains a challenging problem. While multiple methods have being proposed for this task, both handcrafted and deep learning methods have been designed ...