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LoRaWAN is an innovative and prominent communication protocol in the domain of Low Power Wide Area Networks (LPWAN), known for its ability to provide long-range communication with low energy consumption. However, the practical implementation of the ...

Quantitative characterizations and estimations of uncertainty are of fundamental importance for machine learning classification, particularly in safety-critical settings where continuous real-time monitoring requires explainable and reliable scoring. ...

From the perspective of telecommunications, next-generation networks or beyond 5G will inevitably face the challenge of a growing number of users and devices. Such growth results in high-traffic generation with limited network resources. Thus, the ...

We explore the landscape of modern data structures that employ two powerful scaling mechanisms simultaneously: (a) concurrency to harness the power of today’s multicore processors, and (b) learned queries – the operations employing machine learning ...

Postprandial blood glucose (PPBG) is the glucose level measured after a meal and it is one of the main factors for Type 2 Diabetes Mellitus (T2DM) management. This work aims to predict PPBG level of T2DM patients by addressing the problems of clinical ...

This study uses Word2Vec's word vector representation technology to finely capture the semantic relationships of vocabulary in legal texts through the Skip-gram model. By introducing Hierarchical Softmax optimization, a legal privacy protection model ...

The static control limits restrict self-healing capabilities and decision-making processes, impeding adaptability to the dynamic shifts in intricate industrial operations, frequently leading to suboptimal or anomalous conditions that undermine production ...

The continuous development of artificial intelligence (AI) theory has propelled this field to unprecedented heights, owing to the relentless efforts of scholars and researchers. In the medical realm, AI takes a pivotal role, leveraging robust machine ...

One of the most important factors that are associated with the quality and performance of textiles is the fineness of yarn. There is usually high demand for automated methods of yarn fineness measurement as the traditional methods are time consuming and ...

Dementia is a common neurological disorder that substantially impacts the global population. Primarily, it affects elderly individuals who experience a correlation between memory decline and cognitive function. Regrettably, no effective medications are ...

Embeddings in deep neural networks are essential for processing high-dimensional and categorical data by converting it into compact, low-dimensional vectors. This conversion enables the model to capture complex semantic relationships and improves its ...

Phishing has been a prevalent cyber threat that manipulates users into revealing sensitive private information through deceptive tactics, designed to masquerade as trustworthy entities. Over the years, proactively detection of phishing URLs (or websites) ...

In this paper, we provide the first systematic literature review of the intersection of two research areas, Multi-Label Learning (MLL) and Software Engineering (SE). We refer to this intersection as MLL4SE. In recent years, MLL problems have increased in ...

Automated debugging techniques have the potential to reduce developer effort in debugging. However, while developers want rationales for the provided automatic debugging results, existing techniques are ill-suited to provide them, as their ...

The use of Machine Learning to monitor old people is crucial in providing immediate assistance and potentially life-saving interventions. With the rapid innovation in the field of Artificial Intelligence and Computer Vision, fall detection has ...

The threat of fake news jeopardizing the credibility of online news platforms, particularly on social media, underscores the need for innovative solutions. This paper proposes a creative engine for detecting fake news, leveraging advanced machine ...

Journalists often face the daunting task of manually sifting through vast amounts of documents to uncover newsworthy story ideas. The Djinn platform, or “Data Journalism Interface for Newsgathering and Notifications”, developed by iTromsø, Visito, ...

This paper presents the development of a pixel-wise plastic waste identification system for multispectral remote sensing data, based on artificial intelligence methods. The system will be used as part of a two stage approach to identify and ...

Neural Networks are used in various fields such as research and development. Because it takes much time and cost to make high-performance models, we tune a trained model in order to make the model for our purpose more efficiently. Hence, it is ...

Malware detection traditionally relies on signature-based approaches, which suffer from limited generalization. To mitigate this issue, machine learning (ML)-based detection methods have been integrated with signature-based methods in recent ...