The Hierarchical Navigable Small World (HNSW) algorithm is widely used for approximate nearest neighbor (ANN) search, leveraging the principles of navigable small-world graphs. However, it faces some limitations. first local optima problem, which arises from algorithm's greedy search strategy, selecting neighbors based solely on proximity at each step. This often leads to cluster disconnections. second limitation that HNSW frequently fails achieve logarithmic complexity, particularly in...

Object Tracking is essential for many computer vision applications, such as autonomous navigation, surveillance, and robotics. Unlike Passive (POT), which relies on static camera viewpoints to detect track objects across consecutive frames, Active (AOT) requires a controller agent actively adjust its viewpoint maintain visual contact with moving target in complex environments. Existing AOT solutions are predominantly single-agent-based, struggle dynamic scenarios due limited information...

The widespread use of Multi-layer perceptrons (MLPs) often relies on a fixed activation function (e.g., ReLU, Sigmoid, Tanh) for all nodes within the hidden layers. While effective in many scenarios, this uniformity may limit networks ability to capture complex data patterns. We argue that employing same at every node is suboptimal and propose leveraging different functions each increase flexibility adaptability. To achieve this, we introduce Local Control Networks (LCNs), which leverage...

Decentralized Multi-Agent Reinforcement Learning (Dec-MARL) has emerged as a pivotal approach for addressing complex tasks in dynamic environments. Existing (MARL) methodologies typically assume shared objective among agents and rely on centralized control. However, many real-world scenarios feature with individual goals limited observability of other agents, complicating coordination hindering adaptability. Dec-MARL strategies prioritize either communication or coordination, lacking an...

Next-frame prediction in videos is crucial for applications such as autonomous driving, object tracking, and motion prediction. The primary challenge next-frame lies effectively capturing processing both spatial temporal information from previous video sequences. transformer architecture, known its prowess handling sequence data, has made remarkable progress this domain. However, transformer-based models face notable issues: (a) multi-head self-attention (MHSA) mechanism requires the input...

Neural Architecture Search (NAS) aims to automate the design of deep neural networks. However, existing NAS techniques often focus on maximising accuracy, neglecting model efficiency. This limitation restricts their use in resource-constrained environments like mobile devices and edge computing systems. Moreover, current evaluation metrics prioritise performance over efficiency, lacking a balanced approach for assessing architectures suitable constrained scenarios. To address these...

Assessing learners’ understanding and competency in video-based digital learning is time-consuming very difficult for educators, as it requires the generation of accurate valid questions from pre-recorded videos. This paper demonstrates VideoDL, a framework powered by Artificial Intelligence (AI) that supports automatic question answer assessment VideoDL comprises various AI algorithms, an interactive web-based user interface (UI) developed using principles human-centred design. Our...

Several approaches have applied Deep Reinforcement Learning (DRL) to Unmanned Aerial Vehicles (UAVs) do autonomous object tracking. These methods, however, are resource intensive and require prior knowledge of the environment, making them difficult use in real-world applications. In this paper, we propose a Lightweight Vision (LDVRL) framework for dynamic tracking that uses camera as only input source. Our employs several techniques such stacks frames, segmentation maps from simulation,...

Human values such as integrity, privacy, curiosity, security, and honesty are guiding principles for what people consider important in life. Such human may be violated by mobile software applications (apps), the negative effects of value violations can seen various ways society. In this work, we focus on honesty. We present a model to support automatic identification from app reviews an end-user perspective. Beyond detection apps, also aim better understand different categories expressed...

Research interest in autonomous agents is on the rise as an emerging topic. The notable achievements of Large Language Models (LLMs) have demonstrated considerable potential to attain human-like intelligence agents. However, challenge lies enabling these learn, reason, and navigate uncertainties dynamic environments. Context awareness emerges a pivotal element fortifying multi-agent systems when dealing with situations. Despite existing research focusing both context-aware systems, there...

Abstract Recent technological advancements have led to a significant increase in digital documents. A document’s key information is generally represented by the keyphrases that provide abstract description contained therein. With traditional keyphrase techniques, however, it difficult identify relevant based on context. Several studies literature explored graph-based unsupervised extraction techniques for automatic extraction. However, there only limited existing work embeds contextual To...

The rapid growth of both the Industrial Internet Things (IIoT) and Artificial Intelligence (AI) results in a high demand for AI applications devices. To achieve levels accuracy, typically require large amount annotated data. Accessing such data is challenging various as healthcare, finance information security. Federated learning (FL) one strategies that was proposed to overcome this challenge. Specifically, FL enables model centralized system be trained without any prior knowledge on Recent...

Abstract Human values such as honesty, social responsibility, fairness, privacy, and the like are things considered important by individuals society. Software systems, including mobile software applications (apps), may ignore or violate values, leading to negative effects in various ways for While some works have investigated different aspects of human engineering, this mixed-methods study focuses on honesty a critical value. In particular, we studied (i) how detect violations apps, (ii)...

Finding experts drives successful collaborations and high-quality product development in academic research domains. To contribute to the expert finding community, we have developed ExpFinder which is a novel ensemble model for by integrating an N-gram vector space (nVSM) graph-based (μCO-HITS). This paper provides descriptions of ExpFinder's architecture, key components, functionalities, illustrative examples. effective competitive finding, significantly outperforming number models as...

Human values such as integrity, privacy, curiosity, security, and honesty are guiding principles for what people consider important in life. Such human may be violated by mobile software applications (apps), the negative effects of value violations can seen various ways society. In this work, we focus on honesty. We present a model to support automatic identification from app reviews an end-user perspective. Beyond detection apps, also aim better understand different categories expressed...

Machine reading comprehension (MRC) is a challenging task in natural language processing that demonstrates the understanding of machine. An approach to tackle this challenge requires machine answer question about given context when needed and abstain from answering there no answer. Recent works attempted solve with various comprehensive neural network architectures for sequences such as SAN, U-Net, EQuANt, others were trained on SQuAD 2.0 dataset containing unanswerable questions. However,...

Human values such as honesty, social responsibility, fairness, privacy, and the like are things considered important by individuals society. Software systems, including mobile software applications (apps), may ignore or violate values, leading to negative effects in various ways for While some works have investigated different aspects of human engineering, this mixed-methods study focuses on honesty a critical value. In particular, we studied (i) how detect violations apps, (ii) types (iii)...

Financial advice is given by a registered financial adviser (RFA) in the form of statement (SoA) document.To limit liability, advisor groups periodically assess SoA documents for compliance with legal regulations, internal policies, and best practices.However, this manual process that often subjective, time-consuming tedious.In paper, we propose, implement evaluate Risk Auditor (SRAuditor), natural language processing (NLP) framework to automatically audit documents.SRAuditor consists two...

In many real-world applications such as the inspection of powerlines, automated detection anomalies can minimise damage and reduce costs that result from presence unknown anomalies. Technologies LiDAR scans obtained Unmanned Aerial Vehicles (UAV) are becoming prominent due to data depth they provide. context powerline transmission, investigators must search for anomalous elements line defects or obstructions. Such occurrences not always apparent detecting them requires extensive analysis...

There has been a recent and rapid shift to digital learning hastened by the pandemic but also influenced ubiquitous availability of tools platforms now, making ever more accessible. An integral one most difficult part scaling teaching is be able assess learner's knowledge competency. educator can record lecture or create content that delivered thousands learners assessing extremely time consuming. In paper, we propose an Artificial Intelligence (AI)-based solution namely VidVersityQG for...

Finding an expert plays a crucial role in driving successful collaborations and speeding up high-quality research development innovations. However, the rapid growth of scientific publications digital expertise data makes identifying right experts challenging problem. Existing approaches for finding given topic can be categorised into information retrieval techniques based on vector space models, document language graph-based models. In this paper, we propose $\textit{ExpFinder}$, new...