Oral contrast-enhanced ultrasonographic features and radiomics analysis to predict NIH risk stratification for gastrointestinal stromal tumors by Fan Yang, Fan Yang, Fan Yang, Fan Yang, Chun-wei Liu, Dai Zhang, Dai Zhang, Dai Zhang, Dai Zhang, Hai-Ling Wang, Hai-Ling Wang, Hai-Ling Wang, Hai-Ling Wang, Xi Wei, Xi Wei, Xi Wei, Xi Wei, Mo Yang, Mo Yang, Mo Yang

“…The clinical profiles, oral contrast-enhanced ultrasonography (CEUS), and endoscopic ultrasound (EUS) imaging data were collected. 105 patients with high-risk and moderate-risk GISTs were classified into the high-risk group, while 99 patients with low-risk and very-low-risk GISTs were classified into the low-risk group. …”
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On Remoteness Functions of <i>k</i>-NIM with <i>k</i> + 1 Piles in Normal and in Misère Versions by Vladimir Gurvich, Vladislav Maximchuk, Georgy Miheenkov, Mariya Naumova

“…For <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mi>n</mi><mo>=</mo><mn>5</mn><mo>,</mo><mn>6</mn></mrow></semantics></math></inline-formula>, a polynomial algorithm computing P-positions was obtained for the normal version. …”
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Standardised packaging, minimum excise tax, and RYO focussed tax rise implications for UK tobacco pricing. by Rosemary Hiscock, Nicole H Augustin, J Robert Branston, Anna B Gilmore

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Classical Benchmarks for Variational Quantum Eigensolver Simulations of the Hubbard Model by Antonios M. Alvertis, Abid Khan, Thomas Iadecola, Peter P. Orth, Norm Tubman

“…While these algorithms have been shown to reproduce the qualitative features of the Hubbard model, their quantitative accuracy in terms of producing true ground state energies and other properties, and the dependence of this accuracy on the system size and interaction strength, the choice of variational ansatz, and the degree of spatial inhomogeneity in the model, remains unknown. …”
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Multi-Objective Performance Evaluation Framework for Integrated Fiber-Reinforced Shading Systems by Salman Oukati Sadegh, Emad Tabadkani, Mahmoud Oukati Sadegh

“…The proposed framework benefits from integrating Multi-objective Evolutionary Algorithms (MOEAs). Such algorithms have proven to address conflicting parameters effectively while providing a range of different solutions to problems. …”
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Hybrid Filtering Technique for Accurate GNSS State Estimation by Jahnvi Verma, Nischal Bhattarai, Thejesh N. Bandi

“…For the real-world dynamic dataset, our method also provides a better fit to the measurements than the classical algorithms.…”
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Can Knowledge Distillation Enable Seismic Interpolation, Super-Resolution, and Denoising Simultaneously? by Benwen Zhang, Linrong Wang

“…For comparison, we combine three interpolation algorithms with three super-resolution algorithms and select the one with the best performance. …”
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Pharmacotherapeutic Options for Ophthalmic Conjunctivitis by A. D. van Eyk

“…Herpes simplex and Herpes zoster are the infective organisms also responsible for conjunctivitis while seasonal pollens are usually the cause for allergic conjunctivitis. …”
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A network intrusion detection method designed for few-shot scenarios by Weichen HU, Congyuan XU, Yong ZHAN, Guanghui CHEN, Siqing LIU, Zhiqiang WANG, Xiaolin WANG

“…Existing intrusion detection techniques often require numerous malicious samples for model training.However, in real-world scenarios, only a small number of intrusion traffic samples can be obtained, which belong to few-shot scenarios.To address this challenge, a network intrusion detection method designed for few-shot scenarios was proposed.The method comprised two main parts: a packet sampling module and a meta-learning module.The packet sampling module was used for filtering, segmenting, and recombining raw network data, while the meta-learning module was used for feature extraction and result classification.Experimental results based on three few-shot datasets constructed from real network traffic data sources show that the method exhibits good applicability and fast convergence and effectively reduces the occurrence of outliers.In the case of 10 training samples, the maximum achievable detection rate is 99.29%, while the accuracy rate can reach a maximum of 97.93%.These findings demonstrate a noticeable improvement of 0.12% and 0.37% respectively, in comparison to existing algorithms.…”
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An optimized elliptic curve digital signature strategy for resource-constrained devices by Nawras H. Sabbry, Alla Levina

“…Abstract Ensuring robust security in resource-constrained environments, such as microcontrollers used in Unmanned Vehicle systems (UVS), poses significant challenges due to the computational and memory demands of cryptographic algorithms. This research addresses these challenges by proposing an optimized ECC digital signature method designed for such environments. …”
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From PGC to UGC to AIGC: Change of content paradigm by Gao Ao

“…The study also points out that the development of AIGC technology relies on the support of algorithms, meta-universes and blockchain technology, while also sparking discussions on intellectual property, copyright, ethics and other issues. …”
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Advancements in Multipath Mitigation for GNSS Receivers: Review of Channel Estimation Techniques by Pedro Miguel Coelho Pereira, Hélder David Malheiro da Silva, Carlos Manuel Gregório Santos Lima

“…An analysis of adaptive algorithms is conducted for multipath mitigation applications.…”
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Pharmacotherapeutic Options for Ophthalmic Conjunctivitis by A. D. van Eyk

“…Herpes simplex and Herpes zoster are the infective organisms also responsible for conjunctivitis while seasonal pollens are usually the cause for allergic conjunctivitis. …”
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Research on the Application of Artificial Intelligence in Quantitative Investment: Implementation Scenarios, Practical Challenges, and Future Trends by Chen Boshan

“…First, the paper reviews the evolutionary trajectory of AI technologies, spanning from early expert systems to contemporary deep reinforcement learning, while analyzing breakthrough developments in specialized financial AI tools and core technical capabilities. …”
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Navigating the Dilemma of AI Integration for Organisational Performance: Insights for Contemporary Business Strategists by Jeanette Owusu, Isaac Sardello Kodzo Agbesi

“…In this literature review, the author examines how businesses can effectively implement AI to improve decision-making, productivity, and customer experience while addressing data privacy, algorithmic bias, and ethical implications. …”
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Ghost in the Machine: Daily Interaction with Ephemeral Computing by Sofia Pirandello

“…To realise this project of ubiquitous “spatial computing”, technology companies are converging on the development of wearable tools, mostly augmented reality (AR) glasses. While wearing them, users manipulate responsive but intangible objects that they “evoke” and that can appear ghostly from a distance. …”
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A Comparative Analysis of Artificial Intelligence Regulatory Law in Asia, Europe, and America by Alfiani Francisca Romana Nanik, Santiago Faisal

“…While the regulatory approaches differ across these regions, they share a common goal: ensuring that AI benefits society while minimizing negative impacts.…”
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Audit Program on Artificial Intelligence (AI)-driven Credit Risk Models by Valeria Anna De Palma, Alessandro Di Maria, Daniele Foschini, Vincenzo Frasca, Dario Girardi

“…From an Internal Audit perspective, the integration of Artificial Intelligence (AI) into credit risk modelling through Machine Learning (ML) algorithms presents significant challenges due to the complexity and multidimensional nature of these models. …”
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Fast-converging decentralized alternating direction method of multipliers for consensus optimization by Jeannie He, Ming Xiao, Mikael Skoglund

“…Through theoretical analysis, we have shown that our algorithms inherit the well-established convergence properties of the classical centralized ADMM while keeping the computational and communication complexity for each node at $${\mathcal {O}}(1)$$ O ( 1 ) . …”
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Increasing load factor in logistics and evaluating shipment performance with machine learning methods: A case from the automotive industry by Raziye Kılıç Sarıgül, Burak Erkayman, Bilal Usanmaz

“…To solve this problem, both supervised and unsupervised learning algorithms were applied. First, unsupervised clustering algorithms were used to group the shipment performance based on similarities. …”
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