Economic growth in leading tourist destinations faces challenges requiring investment, technological advancement, and resource management. This study examines the impact of tourism, Fintech, FDI, digitalization on economic Austria, France, Germany, Greece, Italy, Mexico, Spain, Turkey, UK, USA. These countries, identified by UNWTO for 2022, represent 46% global tourism market. Utilizing yearly data from 2010 to 2022 sources like World Bank, Crunchbase, UNWTO, we apply Pooled OLS, PCSEs,...

This article presents a study using ResNet-50, GRU, and transfer learning to construct marketing decision-making model predict consumer behavior. Deep algorithms address the scale complexity of data in information age. Traditional methods may not capture patterns effectively, while deep excels at extracting features from large datasets. The research aims leverage build ResNet-50 analyzes data, visual for decisions. GRU temporal dynamics, capturing elements like purchase sequences. Transfer...

Abstract The integration of AI‐based platforms, such as Poe and Gemini, into language instruction has garnered increasing attention for their potential to enhance writing skills. Despite this interest, little is known about effects on EFL learners' positive emotions (PEs), academic self‐efficacy boredom in writing. Addressing gap, the present study investigated effectiveness Gemini developing skills explored impact PEs, among learners at upper‐intermediate level. For purpose, a total 519...

Festivals and events as social gatherings have become an increasingly important sector of the tourism leisure industries. The present study applied identity theory to examine causal relationship between three mental stages experienced by event visitors: categorization (fundamental hedonic values), identification (social identity), comparison (self-esteem), well another two consequential factors (revisit intention electronic word-of-mouth). Data were collected at Harbin Ice Snow Sculpture...

Transportation accounts for more than a quarter of the greenhouse gas emissions that are causing climate change. Carpooling is subset sharing economy, in which individuals share their vehicle with commuters to save travel expenses. In recent decades, carpooling has been promoted as feasible alternative car ownership potential alleviate traffic congestion, parking demand, and environmental problems. Unstable economic conditions, cultural norms, lack infrastructure make exchange activities...

This study's objective is to analyze ecological footprints that exist among China's economic growth, energy consumption, carbon dioxide emissions, and the revenue generated from tourism in other countries. The years 1995 through 2020 are focus of this particular research endeavor. relationship between emissions has been discovered by a large number researchers; nevertheless, findings have inconsistent do not give clear picture situation. We can only hope results study will improve existing...

Interactions involving children span a wide range of important domains from learning to clinical diagnostic and therapeutic contexts. Automated analyses such interactions are motivated by the need seek accurate insights offer scale robustness across diverse wide-ranging conditions. Identifying speech segments belonging child is critical step in modeling. Conventional child-adult speaker classification typically relies on audio modeling approaches, overlooking visual signals that convey...

Keyword spotting (KWS) is an important speech processing component for smart devices with voice assistance capability. In this paper, we investigate if Kolmogorov-Arnold Networks (KAN) can be used to enhance the performance of KWS. We explore various approaches integrate KAN a model architecture based on 1D Convolutional Neural (CNN). find that effective at modeling high-level features in lower-dimensional spaces, resulting improved KWS when integrated appropriately. The findings shed light...

Speech foundation models, trained on vast datasets, have opened unique opportunities in addressing challenging low-resource speech understanding, such as child speech. In this work, we explore the capabilities of models child-adult speaker diarization. We show that exemplary can achieve 39.5% and 62.3% relative reductions Diarization Error Rate Speaker Confusion Rate, respectively, compared to previous diarization methods. addition, benchmark evaluate results with varying input audio window...

Speech foundation models, trained on vast datasets, have opened unique opportunities in addressing challenging low-resource speech understanding, such as child speech. In this work, we explore the capabilities of models child-adult speaker diarization. We show that exemplary can achieve 39.5% and 62.3% relative reductions Diarization Error Rate Speaker Confusion Rate, respectively, compared to previous diarization methods. addition, benchmark evaluate results with varying input audio window...

Automating child speech analysis is crucial for applications such as neurocognitive assessments. Speaker diarization, which identifies ``who spoke when'', an essential component of the automated analysis. However, publicly available child-adult speaker diarization solutions are scarce due to privacy concerns and a lack annotated datasets, while manually annotating data each scenario both time-consuming costly. To overcome these challenges, we propose data-efficient solution by creating...

Autism spectrum disorder (ASD) is a neurodevelopmental condition characterized by challenges in social communication, repetitive behavior, and sensory processing. One important research area ASD evaluating children's behavioral changes over time during treatment. The standard protocol with this objective BOSCC, which involves dyadic interactions between child clinicians performing pre-defined set of activities. A fundamental aspect understanding behavior these automatic speech understanding,...

Large Language Models (LLMs) have shown significant potential in understanding human communication and interaction. However, their performance the domain of child-inclusive interactions, including clinical settings, remains less explored. In this work, we evaluate generic LLMs' ability to analyze child-adult dyadic interactions a clinically relevant context involving children with ASD. Specifically, explore LLMs performing four tasks: classifying utterances, predicting engaged activities,...

Access to accurate depth information is important for a wide variety of oceanographic science applications. For example, it crucial in the creation 3D models. Currently, divers are manually measuring by using dive watches, but this method inconsistent because variable readings caused changing wave heights and human errors. To combat these problems, we created Depth-Sensor Enclosed Application (D-SEA) automatically collect average pressure data while displaying calculated underwater. use...

Speech processing techniques are useful for analyzing speech and language development in children with Autism Spectrum Disorder (ASD), who often varied delayed acquiring these skills. Early identification intervention crucial, but traditional assessment methodologies such as caregiver reports not adequate the requisite behavioral phenotyping. Natural Language Sample (NLS) analysis has gained attention a promising complement. Researchers have developed benchmarks spoken capabilities ASD,...

The establishment of an intelligent, comprehensive, and all-encompassing information system for tourism management is the current trend in informatization as a result continual development modern technology. Significant advancements field VRGIS its usage research have been made use to categorize, assess, plan, manage resources. analysis recent resource first section this work. This study examines implements mobile, computerized, intelligent service that gives visitors sense surrounding...

This article mainly discusses how to extract the interested information from massive amounts of micro-blogs and recommend right user, which is a hot research area in recommendation systems social networks, too.To solve this problem, model called Multi-tags Latent Dirichlet Allocation proposed.Using model, topics paid attention by users can be mined effectively defect low degree differentiation for short blog content settled.Experiments showed that tags user's micro-blog figured out with...

Image mosaic is an important research content in digital image processing, and could be used to solve the problem of observing large objects with narrow view, such as 360 degree panorama stitching.Microscopic observation liver biopsy a commonly method diagnosing diseases, which are always rely on whole slice.Therefore, pathological microscopic best way formulate it.This paper proposes mosaicing system based scale invariant feature transform point set matching method, includes selection...