Search Results - "algorithm"

A Deep Learning-Based Echo Extrapolation Method by Fusing Radar Mosaic and RMAPS-NOW Data by Shanhao Wang, Zhiqun Hu, Fuzeng Wang, Ruiting Liu, Lirong Wang, Jiexin Chen

“…Furthermore, as the extrapolation time increases, the smoothing effect inherent to convolution operations leads to increasingly blurred predictions. To address the algorithmic limitations of deep learning-based echo extrapolation models, this study introduces three major improvements: (1) A Deep Convolutional Generative Adversarial Network (DCGAN) is integrated into the ConvLSTM-based extrapolation model to construct a DCGAN-enhanced architecture, significantly improving the quality of radar echo extrapolation; (2) Considering that the evolution of radar echoes is closely related to the surrounding meteorological environment, the study incorporates specific physical variable products from the initial zero-hour field of RMAPS-NOW (the Rapid-update Multiscale Analysis and Prediction System—NOWcasting subsystem), developed by the Institute of Urban Meteorology, China. …”
Get full text

MAPPING GENERATIVE AI'S ETHICAL ISSUES IN HIGHER EDUCATION: A FELT-GUIDED SYSTEMATIC REVIEW [PEMETAAN ISU ETIKA GENERATIVE AI DI PENDIDIKAN TINGGI: TINJAUAN SISTEMATIS BERPANDUAN... by okky barus, Achmad Nizar Hidayanto, Imairi Eitiveni

“…The SLR revealed seven prominent ethical concerns: (1) academic integrity and plagiarism, highlighting issues of unauthorized assistance and false authorship; (2) bias and fairness, manifested through algorithmic and linguistic biases; (3) data privacy and security, concerning unauthorized access and re-identification risks; (4) impact on critical thinking and learning outcomes, fostering over-reliance; (5) authorship, intellectual property, and copyright ambiguities; (6) misinformation, hallucinations, and deepfakes, eroding trust; and (7) broader environmental and labor impacts. …”
Get full text

INTERNATIONAL FORUM “OLD AND NEW MEDIA: ALONG THE PATH TOWARDS A NEW AESTHETICS” / МЕЖДУНАРОДНЫЙ ФОРУМ «СТАРЫЕ И НОВЫЕ МЕДИА: ПУТИ К НОВОЙ ЭСТЕТИКЕ»... by BOGATYRYOVA ELENA A.

“…Notice was made of alarming tendencies of transforming consciousness into that of “gamers,” reacting in correlations with certain algorithms, and a transference from discourse and substantiations towards reactions and evaluations. …”
Get full text

ARTS AND MACHINE CIVILIZATION INTERNATIONAL SCIENTIFIC CONFERENCE / МЕЖДУНАРОДНАЯ НАУЧНАЯ КОНФЕРЕНЦИЯ «ИСКУССТВО И МАШИННАЯ ЦИВИЛИЗАЦИЯ»... by DUKOV YEVGENY V. / ДУКОВ Е.В., EVALLYO VIOLETTA D. / ЭВАЛЛЬЕ В.Д.

“…The purpose of the conference was to comprehend the artistic practices in the era of machine civilization, get acquainted with current hypotheses, publish new facts and discuss modern terminologies (law of spontaneity, law of semantic uncertainty, algorithmic apophenia, post-opera, artificial life and new vitality). …”
Get full text

Interpretable Machine Learning for Legume Yield Prediction Using Satellite Remote Sensing Data by Theodoros Petropoulos, Lefteris Benos, Remigio Berruto, Gabriele Miserendino, Vasso Marinoudi, Patrizia Busato, Chrysostomos Zisis, Dionysis Bochtis

“…Subsequently, six ML models were evaluated representing different algorithmic strategies. Among them, XGBoost showed the best performance (<inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><msup><mi>R</mi><mn>2</mn></msup></mrow></semantics></math></inline-formula> = 0.8756) and low error values across <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mi>M</mi><mi>A</mi><mi>E</mi></mrow></semantics></math></inline-formula>, <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mi>M</mi><mi>S</mi><mi>E</mi></mrow></semantics></math></inline-formula>, and <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mi>R</mi><mi>M</mi><mi>S</mi><mi>E</mi></mrow></semantics></math></inline-formula> metrics. …”
Get full text

Multi-Focus Image Fusion Based on Dual-Channel Rybak Neural Network and Consistency Verification in NSCT Domain by Ming Lv, Sensen Song, Zhenhong Jia, Liangliang Li, Hongbing Ma

“…Experimental results show that our method consistently outperforms several state-of-the-art image fusion techniques, including both traditional algorithms and deep learning-based approaches, in terms of visual quality and objective performance metrics (<inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><msub><mi>Q</mi><mrow><mi>A</mi><mi>B</mi><mo>/</mo><mi>F</mi></mrow></msub></mrow></semantics></math></inline-formula>, <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><msub><mi>Q</mi><mrow><mi>C</mi><mi>B</mi></mrow></msub></mrow></semantics></math></inline-formula>, <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><msub><mi>Q</mi><mi>E</mi></msub></mrow></semantics></math></inline-formula>, <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><msub><mi>Q</mi><mrow><mi>F</mi><mi>M</mi><mi>I</mi></mrow></msub></mrow></semantics></math></inline-formula>, <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><msub><mi>Q</mi><mrow><mi>M</mi><mi>I</mi></mrow></msub></mrow></semantics></math></inline-formula>, <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><msub><mi>Q</mi><mrow><mi>M</mi><mi>S</mi><mi>E</mi></mrow></msub></mrow></semantics></math></inline-formula>, <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><msub><mi>Q</mi><mrow><mi>N</mi><mi>C</mi><mi>I</mi><mi>E</mi></mrow></msub></mrow></semantics></math></inline-formula>, <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><msub><mi>Q</mi><mrow><mi>N</mi><mi>M</mi><mi>I</mi></mrow></msub></mrow></semantics></math></inline-formula>, <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><msub><mi>Q</mi><mi>P</mi></msub></mrow></semantics></math></inline-formula>, and <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><msub><mi>Q</mi><mrow><mi>P</mi><mi>S</mi><mi>N</mi><mi>R</mi></mrow></msub></mrow></semantics></math></inline-formula>). …”
Get full text

Development and validation of an explainable machine learning model for predicting postoperative pulmonary complications after lung cancer surgery: a machine learning studyResearch... by Shaolin Chen, Ting Deng, Qing Yang, Jin Li, Juanyan Shen, Xu Luo, Juan Tang, Xulian Zhang, Jordan Tovera Salvador, Junliang Ma

“…Feature selection involved univariate analysis, collinearity analysis, nine ML algorithms, and expert consensus. Twelve independent ML models and 26 stacking ensemble models were developed. …”
Get full text

Effects of Exchange, Anisotropic, and External Field Couplings on a Nanoscale Spin-2 and Spin-3/2 System: A Thermomagnetic Analysis by Julio Cesar Madera, Elisabeth Restrepo-Parra, Nicolás De La Espriella

“…To determine the thermomagnetic behaviors of the nanoparticle, numerical simulations using Monte Carlo techniques and thermal bath class algorithms are performed. The results exhibit the effects of exchange couplings (<inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><msub><mi>J</mi><mn>1</mn></msub><mo>,</mo><msubsup><mi>J</mi><mn>2</mn><mo>′</mo></msubsup></mrow></semantics></math></inline-formula>), magnetocrystalline anisotropies (<inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><msubsup><mi>D</mi><mrow><mn>3</mn><mo>/</mo><mn>2</mn></mrow><mo>′</mo></msubsup><mo>,</mo><msubsup><mi>D</mi><mn>2</mn><mo>′</mo></msubsup></mrow></semantics></math></inline-formula>), and external magnetic fields (<inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><msup><mi>h</mi><mo>′</mo></msup></semantics></math></inline-formula>) on the finite-temperature phase diagrams of magnetization (<inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><msub><mi>M</mi><mi>T</mi></msub></semantics></math></inline-formula>), magnetic susceptibility (<inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><msub><mi>χ</mi><mi>T</mi></msub></semantics></math></inline-formula>), and thermal energy (<inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><msub><mi>k</mi><mi>B</mi></msub><msup><mi>T</mi><mo>′</mo></msup></mrow></semantics></math></inline-formula>). …”
Get full text

Interplay between tumor mutation burden and the tumor microenvironment predicts the prognosis of pan-cancer anti-PD-1/PD-L1 therapy by Wuyuan Liao, Wuyuan Liao, Wuyuan Liao, Xinwei Zhou, Xinwei Zhou, Hansen Lin, Hansen Lin, Zihao Feng, Zihao Feng, Xinyan Chen, Yuhang Chen, Yuhang Chen, Minyu Chen, Minyu Chen, Mingjie Lin, Mingjie Lin, Gaosheng Yao, Gaosheng Yao, Jinwei Chen, Jinwei Chen, Haoqian Feng, Haoqian Feng, Yinghan Wang, Yinghan Wang, Zhiping Tan, Zhiping Tan, Youyan Tan, Jun Lu, Jun Lu, Pengju Li, Pengju Li, Jinhuan Wei, Jinhuan Wei, Li Luo, Li Luo, Liangmin Fu, Liangmin Fu, Liangmin Fu

“…Additionally, we employed algorithms such as CIBERSORT and ESTIMATE to assess the correlation between the risk score and TME components. …”
Get full text

Integrating Gut Microbiome and Metabolomics with Magnetic Resonance Enterography to Advance Bowel Damage Prediction in Crohn&amp;rsquo;s Disease by Huang L, Meng J, Lin S, Peng Z, Zhang R, Shen X, Zheng W, Zheng Q, Wu L, Wang X, Wang Y, Mao R, Sun C, Li X, Feng ST

“…Seven machine learning algorithms, each paired with seven distinct combinations of multi-omics features, were evaluated using nested 5-fold cross-validation to construct an optimal prediction model. …”
Get full text

Flow Characteristics by Blood Speckle Imaging in Non-Stenotic Congenital Aortic Root Disease Surrounding Valve-Preserving Operations by Shihao Liu, Justin T. Tretter, Lama Dakik, Hani K. Najm, Debkalpa Goswami, Jennifer K. Ryan, Elias Sundström

“…BSI, utilizing block-matching algorithms, enabled detailed visualization and quantification of flow parameters from the echocardiographic data. …”
Get full text

Radiative closure assessment of retrieved cloud and aerosol properties for the EarthCARE mission: the ACMB-DF product by H. W. Barker, J. N. S. Cole, N. Villefranque, Z. Qu, A. Velázquez Blázquez, C. Domenech, S. L. Mason, R. J. Hogan

“…Note that this study, like the ACMB-DF process with real EarthCARE observations, does not comment explicitly on performance of retrieval algorithms.</p>…”
Get full text

Predicting Olympic Medal Performance for 2028: Machine Learning Models and the Impact of Host and Coaching Effects by Zhenkai Zhang, Tengfei Ma, Yunpeng Yao, Ningjia Xu, Yujie Gao, Wanwan Xia

“…The proposed models, through an innovative integration of clustering, dimensionality reduction, and predictive algorithms, provide reliable forecasts and data-driven insights for optimizing national sports strategies. …”
Get full text

Effect of tool angle in nanocutting of single crystal GaN using diamond cutter by Yongqiang WANG, Hao XIA, Zhihang HU, Shuaiyang ZHANG, Shaohui YIN

“…Post-simulation analysis utilizes sophisticated algorithms to dissect the deformation mechanisms: employed to identify, characterize, and quantify the evolution of dislocations, including their types (e.g., perfect dislocations, partial dislocations), Burgers vectors, and densities within the workpiece. …”
Get full text

Supply chain management and optimization in transportation logistics by Saoussen Krichen

“…Depending on the<ul><li><em>Approximate methods </em>as heuristics and meta-heuristics, are techniques that solve problems in a reasonable runtime and memory consumption, compared to exact algorithms. But, it no guarantees the optimality of the generated solution. …”
Get full text

Evaluation of Knowledge Management Maturity Level in Iranian Audiovisual Archives Based on the APQC Model by Sepideh Ciruskabiri, Atefeh Sharif, Saeed Rezaei Sharifabadi, Mohammad Hassanzadeh

“…Moreover, investment in modernizing technological infrastructures and integrating innovative tools—such as artificial intelligence and machine learning algorithms—can markedly enhance the processes of data collection, storage, and retrieval. …”
Get full text

Use of ICT to Confront COVID-19 by Yousry Saber El Gamal

“…. , AI techniques, particularly machine learning algorithms, can also be used to correlate the patient’s data parameters with a specific drug’s usage. …”
Get full text

PREFACE by Oleh Strelko, Oleh Pylypchuk, Yuliia Berdnychenko

“…The article traces how modern methods – such as spectroscopy, hyperspectral imaging, chromatography, and machine learning algorithms – enable accurate determination of stain age, opening new frontiers for forensic science. …”
Get full text

Enhancing Sustainable Manufacturing in Industry 4.0: A Zero-Defect Approach Leveraging Effective Dynamic Quality Factors by Rouhollah Khakpour, Ahmad Ebrahimi, Seyed Mohammad Seyed Hosseini

“…Moreover, the gathered data from defect detection can be used in two ways: to prevent defect occurrence in the future (detect-prevent) and to design algorithms for predicting when a defect may occur in the future, hence, to prevent defects before they arise (predict-prevent). …”
Get full text

Improving health-promoting workplaces through interdisciplinary approaches. The example of WISEWORK-C, a cluster of five work and health projects within Horizon-Europe by Deborah De Moortel, Michelle C Turner, Ella Arensman, Alex Binh Vinh Duc Nguyen, Víctor Gonzalez

“…These shifts are giving rise to new forms of work (eg, hybrid work, gig economy jobs) and reshaping management and work organization practices (eg, through algorithmic decision-making or digital monitoring of worker performance). …”
Get full text