Information, Volume 15, Issue 11

Social network analysis (SNA), or the application of network analysis techniques to social media data, is an increasingly prominent approach used in computational public health research. We conducted a systematic review to investigate trends around S...

Standardisation has become imperative to retaining order and development in modern society. The simplest actions, such as train timings and the width of the railroad, would be very difficult to achieve without Standardisation. Standardisation also so...

Landslides cause significant human and financial losses in different regions of the world. A high-accuracy landslide susceptibility map (LSM) is required to reduce the adverse effects of landslides. Machine learning (ML) is a robust tool for LSM crea...

Previous studies indicate that increased healthcare access through Medicaid expansion and alleviation of socioeconomic stressors via higher minimum wages improved health outcomes. This study investigates the spatial relationships between the Medicaid...

Traffic stops represent a crucial point of interaction between citizens and law enforcement, with potential implications for bias and discrimination. This study performs a rigorously validated comparative machine learning model analysis, creating art...

Apart from being an economic struggle, migration is first of all a societal challenge; most migrants come from different cultural and social contexts, do not speak the language of the host country, and are not familiar with its societal, administrati...

The sparse matrix–vector product (SpMV) is a fundamental computational kernel utilized in a diverse range of scientific and engineering applications. It is commonly used to solve linear and partial differential equations. The parallel computati...

We propose two decoding algorithms for quasi-cyclic LDPC codes (QC-LDPC) and implement the more efficient one in this paper. These algorithms depend on the split row for the layered decoding method applied to the Min-Sum (MS) algorithm. We designate...

In the digital era, the need for precise and efficient search operations is paramount as users increasingly rely on online resources to access specific information. However, search accuracy is often hindered by errors in user queries, such as incompl...

As the digital environment progresses, the complexities of cyber threats also advance, encompassing both hostile cyberattacks and sophisticated cyber espionage. In the face of these difficulties, cooperative endeavours between state and non-state act...

Massive Open Online Courses (MOOCs) offer highly specialized online courses and have attracted nearly 10 million learners worldwide to participate in various educational programs. These platforms provide discussion forums that allow learners to engag...

The increasing demand for consumers to engage in e-commerce “anytime, anywhere” necessitates more advanced and integrated solutions. This paper presents a novel approach for integrating e-commerce platforms with the Internet of Things (Io...

The development of large language models (LLMs) has promoted a transformation of human–computer interaction (HCI) models and has attracted the attention of scholars to the evaluation of personality traits of LLMs. As an important interface for...

The dynamics underpinning the urban landscape change are primarily driven by social, economic, and environmental issues. Owing to the population’s fluctuating needs, a new and dual perspective of urban space emerges. The Artificial Intelligence...

Acoustic management is very important for detecting possible events in the context of a smart environment (SE). In previous works, we proposed a reflective middleware for acoustic management (ReM-AM) and its autonomic cycles of data analysis tasks, a...

(1) Background: The development of generative artificial intelligence (GAI) is transforming higher education. This systematic literature review synthesizes recent empirical studies on the use of GAI, focusing on its impact on teaching, learning, and...

Audio-driven facial animation is a rapidly evolving field that aims to generate realistic facial expressions and lip movements synchronized with a given audio input. This survey provides a comprehensive review of deep learning techniques applied to a...

This paper proposes a new benchmark specifically designed for in-sensor digital machine learning computing to meet an ultra-low embedded memory requirement. With the exponential growth of edge devices, efficient local processing is essential to mitig...

This paper presents software advances to easily exploit computer architectures consisting of a multi-core CPU and CPU+GPU to accelerate diverse types of high-performance computing (HPC) applications using a single code implementation. The paper descr...

Edge computing architectures promise increased quality of service with low communication delays by bringing cloud services closer to the end-users, at the distributed edge servers of the network edge. Hosting server capabilities at access nodes, ther...

In the dynamic and evolving tourism industry, engaging with stakeholders is essential for fostering innovation and improving service quality. However, tourism companies often struggle to meet expectations for customer satisfaction through interactivi...

Hands-on and virtual laboratory-based learning has been integrated into science education due to its potential positive impact on students’ knowledge and skills development. In this study, we explore the effect of the hands-on and virtual labor...

In this age of big data and natural language processing, to what extent can we leverage new technologies and new tools to make progress in organizing disparate biomedical data sources? Imagine a system in which one could bring together sequencing dat...

The two-parameter logistic (2PL) item response model is typically estimated using an unbounded distribution for the trait $\theta$. In this article, alternative specifications of the 2PL models are investigated that consider a bounded or a positively...

Certain methods for implementing chaotic maps can lead to dynamic degradation of the generated number sequences. To solve such a problem, we develop a method for generating pseudorandom number sequences based on multiple one-dimensional chaotic maps....

Legal knowledge involves multidimensional heterogeneous knowledge such as legal provisions, judicial interpretations, judicial cases, and defenses, which requires extremely high relevance and accuracy of knowledge. Meanwhile, the construction of a le...

We propose a method for automatically extracting new trends and best practices from the recent literature on online learning, aligned with the learning cycle perspective. Using titles and abstracts of research articles published in high ranked educat...

In this paper, we explore the approaches to the problem of cross-domain few-shot classification of sentiment aspects. By cross-domain few-shot, we mean a setting where the model is trained on large data in one domain (for example, hotel reviews) and...

MHealth strategies have been used in various health areas, and mobile apps have been used in the context of health self-management. They can be considered an adjuvant intervention in oral health literacy, mainly for people with special health needs....

Understanding and explaining legal systems is very challenging due to their complex structure, specialized terminology, and multiple interpretations. Legal AI models are currently undergoing drastic advancements due to the development of Large Langua...

The large amount of available data, generated every second via sensors, social networks, organizations, and so on, has generated new lines of research that involve novel methods, techniques, resources, and/or technologies. The development of big data...