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Phishing detectors trained on public benchmarks score highly in-domain yet miss scams aimed at university users. We audit TF-IDF, MiniLM and RoBERTa detectors with 5146 scams published by five U.S. universities, 594 scams posted since 2023, 2684 legi...

This study examines how travellers’ use of ChatGPT—a generative artificial intelligence system—relates to travel decision-making through perceived tone appropriateness, trust in non-human assistance, and perceived time efficiency. D...

Clustering algorithms have received increasing attention as methods for determining unknown quantum states and their potential application in quantum information processing. In particular, quantum k-means is a promising approach to this task; however...

Text-to-SQL data synthesis must expand semantic coverage without losing the relational structure of observed queries. Existing SQL offers evidence of plausible join and nesting patterns, but reusing queries alone limits the range of training examples...

Small and medium-sized enterprises (SMEs) moved much of their marketing to web channels after 2020. This review examines how research has described that change. Two Scopus searches supported bibliometric mapping in VOSviewer at two levels: a broad se...

Social media platforms have become central arenas for climate communication, shaping how climate-related issues are discussed, interpreted, and contested. While previous studies have examined online responses to predefined climate events, less is kno...

Digitizing the historical Chagatai manuscripts of the Gunnar Jarring Collection is severely hindered by cursive orthographic complexity and extreme data scarcity. This study establishes a rigorous empirical HTR benchmark, comparing two distinct parad...

Accurate regional short-term load forecasting is essential to the reliable operation and efficient energy scheduling of smart grids. However, the data needed for collaborative model training are often distributed across regional utilities and grid op...

Artificial intelligence (AI) agents need authenticated identities, bounded action scopes and evidence before receiving adaptive authority. We present a post-quantum trust, accountability and control (TAC) protocol composing signed requests, independe...

Agentic artificial intelligence (AI) extends conventional predictive and generative AI by enabling systems to pursue goals through reasoning, planning, information retrieval, memory, tool use, and interaction with clinical workflows. These capabiliti...

Aircraft walk-around inspection is a safety-critical task where human error plays a significant contributing role in maintenance-related incidents. Using immersive virtual reality (VR) for preparation has been suggested, but the effect of ergonomic c...

Municipal websites are a primary channel for communicating with residents and providing access to public information and services. Their front ends may combine resources retrieved from the base host with resources delivered from other hosts, creating...

Protein post-translational modifications (PTMs), particularly phosphorylation, regulate cellular signaling, drug response, and disease-associated pathway activity. However, existing PTM resources are largely static and do not capture how PTM regulati...

Algorithmic explanations may inform consumer evaluation, but understanding a rationale and trusting its source are distinct judgments. Drawing on Signaling Theory, this study develops a conditional framework in which explanations provide useful infor...

Falls require rapid assistance, but fall-like activities and domain shift complicate alarm control. We present a cross-dataset fall-detection framework combining red–green–blue (RGB) appearance, pose evidence and sequential decisions. A f...

Reliable multi-agent trajectory prediction is essential for autonomous vehicles to anticipate the future motion of surrounding agents in complex road environments. However, many existing methods encode motion dynamics implicitly from coordinate seque...

Authentic assessment in digital marketing faces important challenges due to students’ limited access to real audiences and budgets, as well as their lack of time, while generative AI may create refined artefacts without making student reasoning...

User stories are widely used in agile requirements engineering, but their informal, natural language-based structure can introduce ambiguity, incomplete information, excessive scope, and other flaws that affect subsequent development activities. This...

Tree-ensemble classifiers predict customer churn accurately but explain little, and small language models (SLMs) are increasingly proposed as a zero-shot narration layer on top of them. We test whether such SLMs add decision value or trustworthy expl...

Nowadays, academic paper search systems help researchers find related studies from a large number of publications. However, assessing whether each paper matches the user search query remains very difficult. Previously, we proposed a reference paper c...

Digital transformation in the public sector has intensified the need to demonstrate not only adoption of ICT governance frameworks but sustained compliance with governance requirements. This systematic multivocal literature review developed a concept...

Culturally inclusive large language models (LLMs) should adapt to heterogeneous value systems without conflating national survey aggregates with comprehensive intercultural competence. We introduce Prototype-driven Contrastive Cultural Alignment (Pro...

Good demand forecasts help with inventory control, replenishment and distribution planning. However, retail sales can change quickly due to promotions, seasonal effects, store-level differences and unexpected events. We propose the resilient demand f...

Critical-infrastructure protection must distinguish the detection capability of artificial intelligence (AI) from its permission to act on physical processes. This article proposes Risk-Driven Deployment and Forensic Readiness for Critical Infrastruc...

Life insurance lapse rates across the euro area have risen to the point of constituting a distinct supervisory risk category, making the early identification of policyholders at risk of termination a priority for insurers. Under Solvency II and the G...

Interactive augmented reality (AR) glasses are increasingly used in museums to integrate digital interpretation with physical exhibitions. However, the relationships between AR-glasses system characteristics, visitor experience, perceived learning ou...

Scams targeting older adults increasingly combine social engineering with generative technology such as voice cloning, video deepfakes and text produced by large language models (LLMs). Adults aged 60 and over reported losses of USD 7.7 billion to th...

Recommender systems increasingly exploit sequential interactions, but higher-level process context is rarely used to organize model specialization. This study proposes a process-context-routed recommendation framework in which e-commerce interaction...

In multi-scenario Mobile Edge Computing (MEC), offloading and resource allocation for topologically heterogeneous Directed Acyclic Graph (DAG) tasks are NP-hard, while Federated Meta-Learning (FML) suffers from generalization degradation under non-in...

This application was developed as part of a dissertation project, motivated by direct professional experience in the field of statistics and by the growing need to make statistical data more accessible in today’s data-driven context. Despite th...

This article explores the serious ethical concerns surrounding machine translation (MT), particularly when applied to low-resource languages such as Arabic. While MT has immense influence on cross-lingual and cross-cultural communication, its ethical...

Retention campaigns depend on identifying the customers most likely to discontinue service, yet churn classifiers are usually deployed with the conventional decision threshold of one half, a rule that ignores both the rarity of churn and the unequal...

Generative artificial intelligence (GenAI) is reshaping media and communication, yet research on its semiotic role in meaning-making remains theoretically and methodologically fragmented. This systematic review examines semiotic frameworks, technolog...

Text-guided segmentation combines visual information with semantic descriptions, but semantic conditioning alone does not explicitly supervise the separation of foreground and background representations. We combine a VGG16-based encoder–decoder...

A search for a suitable experimental protocol using keywords may not lead to the most appropriate protocol, because the keywords may not include exactly the right terms. ProtocolNerd is a web-based interactive assistant that helps biologists and chem...

In recursive learning, model outputs can be reused in subsequent training, linking successive models through the reuse and transformation of observable information. Assessing these processes requires distinguishing changes in observable states from t...

Ancient literary evidence is commonly dispersed across works, editions, and citation systems, making passage-level thematic retrieval and aggregation difficult. This study presents SourceArchiveOnto, a lightweight application ontology for representin...

Exact-score retrieval returns the same ordered top-k and numerical scores as a specified exhaustive computation. Quantized vectors can screen candidates, but their approximation errors require safe upper bounds. We study a one-sided residual certific...

Retrieval-augmented generation (RAG), agentic systems, and human authors produce text with inline citations, but the cited sources do not always support the claims attributed to them. We present HallucinationNerd, a modular citation-verification engi...

Multi-hop RAG requires complementary facts from multiple documents to form a complete evidence chain. Relevance-based passage selection can miss bridging evidence, while adding more passages can introduce redundancy and distractors. Context compressi...

Chaos-based image encryption schemes are often motivated by the apparent randomness of chaotic sequences and by the nonlinear processing capability of convolutional neural networks (CNNs). However, these properties alone do not guarantee cryptographi...

This paper presents Relational Narrative Historiography (RNH) as a framework paper and testable research hypothesis, not as an empirical study. Historical accounts of the same event frequently diverge across archives, languages, and interpretive comm...

Fault diagnosis in induction motors is challenging when only a limited number of labeled infrared thermal images are available for training. Effective small-sample augmentation requires generated images to preserve class-related appearance patterns a...

Building dependable automatic speech recognition (ASR) for Karakalpak is hindered by the scarcity of transcribed speech. Whisper handles many languages well, but without adaptation its Karakalpak transcripts remain unreliable, largely because the lan...

Zero-inflated sparse count data are common in text analytics, where keyword frequencies contain many zeros and highly skewed positive values. This study proposes a systematic model-specific framework that treats predictor transformation and scaling a...

Designers may use learner personas to plan different content, feedback, or support for groups of students, but a clustering result alone does not establish that these groups represent distinct learner types. Whether such a categorical structure exist...

Background/Objectives: Acute kidney injury (AKI) is common in critical care, yet predictive artificial intelligence studies often differ in outcome definitions, validation, calibration, and interpretability. We developed and internally validated mach...

Chinese short-form dramas (duanju) drive a growing demand for automated Japanese dubbing that preserves each character’s voice. The decisive component is zero-shot cross-lingual voice cloning: synthesising Japanese speech from a short Chinese r...

Systematic literature reviews are essential for synthesizing scientific evidence but remain complex and resource-intensive processes that demand significant time and human effort. To reduce bias, they are usually conducted collaboratively and accordi...

Legal question answering is usually evaluated as if the law were static. In Kazakhstan, it changed twice within one year: a new Constitution replaced the 1995 text on 1 July 2026, and a new Tax Code replaced its predecessor on 1 January 2026, both re...