5916 research outputs found
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Is hotel revenue performance effective for destination competitiveness? An assessment by wavelet coherence analysis
No full textHotel industry is crucial for destination competitiveness as part of quality tourist infrastructure. The high performance of the industry promises a positive effect on destination competitive. This study aims to develop a approach focusing on the hotel revenue-related performance data in the case of European cities (Istanbul, London, Madrid, Paris, and Rome). Wavelet coherence analysis was applied on revenue data of the years 2013–2022 from 4000+ hotels. Findings reveal time–frequency relationships between hotel revenue variables, highlighting consistent coherence in supply–demand relationships during the pandemic, except for Rome. Furthermore, the analysis detected differentiated patterns in supply–revenue coherence, with Istanbul’s market showing unique fluctuations. London is the city with higher revenue expertise. Key revenue performance indicators of hotels emerged as significant determinants of a city’s competitiveness. These insights present implications for policymakers, community stakeholders, and industry practitioners, emphasizing the pivotal role of adept revenue professionals in improving competitiveness in their destinations
Research article a detailed examination of faculty acceptance of artificial intelligence: Insights from key variables
No full textThe adoption and use of emerging technologies like artificial intelligence (AI) in universities can significantly impact educational and research processes. This study investigates the acceptance levels of AI technologies among university faculty members in Türkiye using a descriptive survey design. Data were collected via convenience sampling during the spring semester of the 2023-2024 academic year from 392 faculty members through an online questionnaire distributed by email. The AI Acceptance Scale, developed based on the Technology Acceptance Model, was employed to measure acceptance levels. Data analysis included descriptive statistics, normality tests, and non-parametric inferential analyses conducted via SPSS 26.0. Findings indicated a high level of AI acceptance overall, with sub-factors showing high scores for ease of use, perceived usefulness, attitude toward use, and intention to use. Age and duration of AI use were found to significantly affect acceptance levels. These results provide valuable insights for facilitating AI integration in higher education environments. © 2025, Duzce University, Faculty of Education. All rights reserved.Publisher versio
Efficient multi-cycle folded integer multipliers
No full textFast combinational multipliers with large bit widths can occupy significant silicon area, which also drives up power consumption. Area can be reduced through resource sharing (i.e., folding) at the expense of lower throughput, which is acceptable for some applications. This work explores multiple architectures for Multi-Cycle folded Integer Multiplier (MCIM) designs, which are based on Schoolbook and Karatsuba approaches. Applications sometimes require a fractional number of multiplications to be performed per cycle. For example, an algorithm may only require 3.5 multiplications per cycle. In such a case, 3 multipliers with a throughput of 1 plus an additional smaller multiplier with a throughput of 1/2 would be sufficient to maintain the algorithm's throughput. Our MCIM design generator offers customization in terms of throughput, latency, and clock frequency. MCIM designs were synthesized and verified for various parameter values using scripts. ASIC synthesis results show that MCIM designs with a throughput of 1/2 offer area savings of up to 44% for bit widths of 8 to 128 with respect to directly synthesizing the * operator. Additionally, MCIM designs can offer up to 33% energy savings and 65% average peak power reduction. © 2025 IEEE
Financial statement fraud detection via large language models
No full textWith the widespread adoption of Internet-based AI technologies, addressing financial fraud has become increasingly critical, particularly within the realm of machine learning. In this case, deep learning and natural language processing (NLP) techniques offer powerful means of detecting fraudulent activity by analyzing financial documents, thereby enhancing both the efficiency and precision of such assessments and supporting financial security. In this study, we introduce deep representation learning-based approaches relying mainly on large language models (LLMs) for identifying fraud in financial statements by examining temporal changes in the Management Discussion and Analysis (MD&A) sections of corporate disclosures. Departing from conventional techniques that rely only on word frequency analysis, we propose DeepFraud that combines time-evolving financial LLM embeddings, such as FinBERT, FinLlama, and FinGPT embeddings, of paragraphs and uses long short-term memory (LSTM) to predict frauds via historical textual embeddings. In addition to LLM embeddings, we also integrate (1) time-evolving word frequencies of words relevant to fraud detection, such as those expressing sentiment or uncertainty, and (2) time-evolving financial ratios. Trajectories of paragraph-level embeddings, frequencies, and ratios are used to construct a fraud detection model, which we evaluate against machine learning methods and deep time-series models. Using 30 years of financial report data (from 1995 to 2024), our experiments demonstrate that DeepFraud on average enhances fraud detection performance across a number of scenarios and on average outperforms the competing approaches as well as conventional word frequency approaches. Our framework introduces a novel direction for deep feature engineering in the field of financial statement fraud detection. © 2025 John Wiley & Sons Lt
Clinical applications of interpersonal acceptance-rejection theory (IPARTheory)
No full textInterpersonal acceptance-rejection theory (IPARTheory) is an evidence-based theory that studies the consequences, causes, and other correlates of interpersonal rejection. The theory has important correlates with clinical symptoms (both individual and relational). Clinical adaptations of IPARTheory measures exist for clinical assessment as do treatment manuals, protocols, and guidelines. To help facilitate its clinical applications, the current chapter examines clinical correlates and clinical adaptations of the theory's main tenets. Several therapy models and techniques are also discussed about how IPARTheory concepts can be incorporated into clinical practice
On the enhanced cryogenic strength of a dual-phase trip-assisted high entropy alloy
No full textThis study investigates the influence of deformation temperature on the microstructural evolution and mechanical performance of a dual-phase high-entropy alloy subjected to cold rolling after annealing at 750 °C for 30 min. Unlike the homogenized alloy, which exhibits a single-phase face-centered cubic structure, the processed condition develops a dual-phase microstructure with the inclusion of body-centered cubic phases. Uniaxial tensile experiments were conducted across a wide temperature range to evaluate the mechanical response. These results were correlated with microstructural observations to elucidate the underlying deformation mechanisms and guide property optimization. While the coarse-grained homogenized condition exhibited no phase transformation during deformation, the refined dual-phase structure demonstrated strain-induced phase transformation with its extent strongly dependent on the deformation temperature. Notably, the microstructure obtained after thermomechanical processing demonstrated enhanced transformation-induced plasticity effect at lower temperatures, achieving a tensile strength exceeding 1600 MPa and a failure elongation of approximately 18% under cryogenic conditions. © The Author(s) under exclusive licence to The Korean Institute of Metals and Materials 2025.Bilim Akademis
Red pill leadership behaviours and discourse ethics
No full textRed Pill ideology, an online ecosystem that frames men as victims of feminist progress, has moved well beyond fringe forums to shape leadership norms in corporate and political arenas. Scholars have charted its spread across the manosphere, yet we know little about how these narratives crystallise into day-to-day leadership behaviours that undermine workplace ethics and equity. This study conceptualises Red Pill leadership behaviours as a distinctive, discourse-driven form of toxic leadership and examines how they distort organisational decision-making. Grounded in Habermasian discourse ethics and extended with Fraser's critique of power asymmetries, we investigate how Red Pill leaders subvert open deliberation and justify exclusion. Employing critical netnography and thematic analysis, we analyse a multi-source dataset comprising 66 keynote speeches and high-profile interviews, 227 social media artefacts posted by 34 executives, 23 corporate case files, 20 investigative media articles, and 13 podcast episodes, produced between 2018 and 2024. Our findings identify three interlocking behaviour clusters: (1) exploitative influence and manipulation; (2) control, supremacy, and suppression of dissent; and (3) dehumanisation with harmful outcomes that normalise male supremacist grievance, delegitimise diversity initiatives, and marginalise opposing voices. By theorising these behaviours and mapping their communicative tactics, we show how Red Pill leadership manufactures legitimacy, monetises grievance, and embeds misogyny in workplace culture. We conclude by outlining multilevel policy and organisational interventions that promote ethical deliberation, critical reflexivity, and inclusive governance.Publisher versio
Supporting preschool children’s executive functions: Evidence from a group-based play intervention
No full textThe current study endeavors to assess the impact of the Preschool Executive Functions Intervention Program (PEFIP) on children's executive functions. A quasi-experimental design was employed, encompassing both pre-test and post-test assessments within a control group, complemented by follow-up evaluations over a 5-week period. The sample comprises 76 children ranging in age from 54 to 72 months, with 42 in the experimental group and 34 in the control group. Teachers provided assessments of the children's executive functions through the Childhood Executive Functions Inventory, while independent researchers employed the Head–Toes–Knees–Shoulders task to evaluate the executive functions of the children. The play-based PEFIP sessions were administered to the experimental group children twice a week for a duration of 10 weeks. Results from the two-way repeated measures analysis of variance (ANOVA) indicated that children in the experimental group exhibited higher levels of teacher-reported working memory, inhibitory control, and performance-based executive function compared to their counterparts in the control group. Furthermore, this improvement in the children persisted in the follow-up assessment conducted 5 weeks after the program's completion. These outcomes underscore the efficacy of play-based interventions in bolstering children's executive functions
Fragile Lives under the Shadow of the Parthenon: Armenian Orphans and Refugees in Interwar Greece
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Physicochemical properties, volatile compounds and basic spherification of hibiscus (Hibiscus sabdariffa L.) kombucha beverage
No full textKombucha is a fermented beverage with a slightly acidic taste, flavor, and natural carbonation. It has gained popularity due to its health benefits. Traditional kombucha is prepared by fermentation of black tea and sucrose. Today, kombucha products do not have a standard composition and there is a growing demand. Therefore, the purpose of this research was to produce kombucha with hibiscus and two different sweeteners (apple juice concentrate and sucrose), to examine physicochemical properties, ethanol and vitamin B12 contents, to identify volatiles, and to study its compatibility in spherification. Fermentation resulted in a pH drop. Decrease in brix of kombucha with apple juice concentrate was seen whereas brix of kombucha with sucrose did not change. While density and fermentation rate of apple juice concentrate containing sample were higher than those of the sucrose containing one, beverage yields were similar. Negligible color changes were encountered during fermentation. Ethanol, vitamin B12, and carbon dioxide levels were determined as 1.08–1.12 g/L, 0.054–0.071 µg cyanocobalamin/100 g, and 0.40–0.43 g/L, respectively. Decanoic acid, octanoic acid, and lauric acid were the major volatiles. Kombucha spheres with apple juice concentrate had higher diameter and weight whereas spheres with sucrose had more uniform surface and less color change.Ozyegin Universit