A supervised machine-learning analysis of doxorubicin-loaded electrospun nanofibers and their anticancer activity capabilities by Mohammadreza Rostami, Mohammadreza Rostami, Maliheh Gharibshahian, Maliheh Gharibshahian, Mehrnaz Mostafavi, Ali Sufali, Mahsa Golmohammadi, Mohammad Reza Barati, Reza Maleki, Nima Beheshtizadeh, Nima Beheshtizadeh

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A comparative analysis of deep learning models for assisting in the diagnosis of periapical lesions in periapical radiographs by Jian Liu, Chaoran Jin, Xiaolan Wang, Kexu Pan, Zhuoyang Li, Xinxuan Yi, Yu Shao, Xiaodong Sun, Xijiao Yu

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Research trends among new investigators at ISOQOL: a bibliometric analysis from 2019 to 2023 by Jae-Yung Kwon, Manraj N. Kaur, Ellen B. M. Elsman, Ava Mehdipour, Lori Suet Hang Lo, Ahmed M. Y. Osman, Sandrine Herbelet, Carrie-Anne Ng, Lotte van der Weijst, on behalf of the New Investigators Special Interest Group Members

“…A two-step screening process, guided by the Wilson and Cleary model of QoL, identified 561 unique documents for analysis. Descriptive metrics included publication trends, citations, journal impact factors, and geographic distribution, while network analysis explored co-authorship patterns. …”
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Performance Analysis of Optical Wireless Channel Based on Beamforming Techniques Using Advanced Modulation Schemes by Lwaa Faisal Abdulameer, Adil Fadhil Mushatet, Tania Tariq Salim

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Part of speech weighted multi-modal emotion analysis model with dynamic adjustment of semantic representation by HUA Qiang, CHEN Zhuo, ZHANG Feng, DONG Chunru

“…Comparative experimental results with the current advanced models such as tensor fusion network and low-rank multimodal fusion show that the average absolute errors of PW-DS model on public data sets CMU-MOSI and CMU-MOSEI are 0.607 and 0.510, respectively, and the binary classification accuracies are 89.02% and 86.93%, respectively, which is better than the models in the comparative experiments. …”
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Shifts in seasonal influenza patterns in Australia during and after COVID-19: A comprehensive analysis by Cynthia Lu, Ian G. Barr, Stephen Lambert, Kerrie Mengersen, Liping Wang, Weizhong Yang, Zhongjie Li, Sotiris Vardoulakis, Hilary Bambrick, Wenbiao Hu

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The lightning climatology of South Africa by Morné Gijben

“…In 2005, the South African Weather Service installed a state-of-the-art cloud-to-ground lightning detection network across the country. The data recorded by this network in 2006 was utilised in the development of an initial lightning climatology of South Africa. …”
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Artificial Intelligence in the Oil and Gas Industry: Applications, Challenges, and Future Directions by Marcelo dos Santos Póvoas, Jéssica Freire Moreira, Severino Virgínio Martins Neto, Carlos Antonio da Silva Carvalho, Bruno Santos Cezario, André Luís Azevedo Guedes, Gilson Brito Alves Lima

“…In the second step, the research focused on the OnePetro database, widely used by the oil industry, selecting articles with terms associated with production and drilling, such as “production system”, “hydrate formation”, “machine learning”, “real-time”, and “neural network”. The results highlight the transformative impact of AI on production operations, with key applications including optimizing operations through real-time data analysis, predictive maintenance to anticipate failures, advanced reservoir management through improved modeling, image and video analysis for continuous equipment monitoring, and enhanced safety through immediate risk detection. …”
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Safety of creatine supplementation: a scientometrics analysis on the impact of the ‘Creatine For Health’ initiative and introduction to CREAS by Diego A. Bonilla, Drew E. Gonzalez, Gustavo Humeres, Jisun Chun, Kelly Hines, Adriana Gil, Richard B. Kreider

“…The goal was to determine whether these perceptions aligned with the side effects reported in scientific literature or adverse effect monitoring systems. A big data text analysis was performed using the YouTube API v3 and the Twitter/X API v2, authorized under the X Academic Research program (Project name: “Creatine Safety” – APP ID: 21590870). …”
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Approach of detecting low-rate DoS attack based on combined features by Zhi-jun WU, Jing-an ZHANG, Meng YUE, Cai-feng ZHANG

“…LDoS (low-rate denial of service) attack is a kind of RoQ (reduction of quality) attack which has the characteristics of low average rate and strong concealment.These characteristics pose great threats to the security of cloud computing platform and big data center.Based on network traffic analysis,three intrinsic characteristics of LDoS attack flow were extracted to be a set of input to BP neural network,which is a classifier for LDoS attack detection.Hence,an approach of detecting LDoS attacks was proposed based on novel combined feature value.The proposed approach can speedily and accurately model the LDoS attack flows by the efficient self-organizing learning process of BP neural network,in which a proper decision-making indicator is set to detect LDoS attack in accuracy at the end of output.The proposed detection approach was tested in NS2 platform and verified in test-bed network environment by using the Linux TCP-kernel source code,which is a widely accepted LDoS attack generation tool.The detection probability derived from hypothesis testing is 96.68%.Compared with available researches,analysis results show that the performance of combined features detection is better than that of single feature,and has high computational efficiency.…”
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Hyperspectral identification of travertine state in Huanglong by the PSO-BPNN method by Menghui Xu, Weihong Wang, Jialun Cai, Qunwei Dai, Jing Fan, Sicheng Li

“…The Siamese network method was employed to generate data labels, and the spectral features of the travertine formations were extracted by combining the sensitive bands with pre-processed and reduced data. …”
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Novel logic mining incorporating log linear approach by Siti Zulaikha Mohd Jamaludin, Nurul Atiqah Romli, Mohd Shareduwan Mohd Kasihmuddin, Aslina Baharum, Mohd. Asyraf Mansor, Muhammad Fadhil Marsani

“…In this paper, we proposed a novel logic mining by introducing log-linear analysis to select the best attributes which formulate the logical rule that will be embedded into the energy-based ANN named Discrete Hopfield Neural Network (DHNN). …”
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Racial Disparities in Clinical Outcomes of Takotsubo Cardiomyopathy: An Analysis of the National Inpatient Sample 2006 to 2018 by Chi N. Duong, Quoc V. P. Bui, Thomas Duong, Dai Q. Phan, Jan Mazur, Eugene Chung, Vien T. Truong

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Energy Consumption Analysis of Iot-Manet Based Systems with Anova Assessment for Tackling Covid-19 by Ashu Gautam, Rashima Mahajan, Sherin Zafar

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An equity-based spatial analytics framework for evaluating pharmacy accessibility using geographical information systems by Sara Al-Naabi, Noura Al Nasiri, Talal Al-Awadhi, Meshal Abdullah, Ammar Abulibdeh

“…The methodology involves spatial distribution analysis using Average Nearest Neighbor (ANN), Moran's I for spatial autocorrelation, Kernel Density Analysis (KDA), Thiessen polygons for catchment areas, and Network analysis for determining service areas and accessibility by walking and driving distances. …”
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Towards ROXAS AI: automatic multi-species ring boundaries segmentation as regression in anatomical images by Marc Katzenmaier, Marc Katzenmaier, Vivien Sainte Fare Garnot, Jan Dirk Wegner, Georg von Arx, Georg von Arx

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Landslide Susceptibility Assessment in Ya’an Based on Coupling of GWR and TabNet by Jiatian Li, Ruirui Wang, Wei Shi, Le Yang, Jiahao Wei, Fei Liu, Kaiwei Xiong

“…The performance of TabNet is compared against Random Forest, Light Gradient Boosting Machine, deep neural networks, and Residual Networks. The experimental results indicate that (1) the GWR-based sampling strategy substantially improves model performance across all tested models; (2) TabNet trained using the GWR-based negative samples achieves superior performance over all other evaluated models, with an average AUC of 0.9828, exhibiting both high accuracy and interpretability; and (3) elevation, land cover, and annual Normalized Difference Vegetation Index are identified as dominant predictors through TabNet’s feature importance analysis. …”
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Machine learning algorithms to predict stroke in China based on causal inference of time series analysis by Qizhi Zheng, Ayang Zhao, Xinzhu Wang, Yanhong Bai, Zikun Wang, Xiuying Wang, Xianzhang Zeng, Guanghui Dong

“…Data analysis was performed from June 1 to December 1, 2024. …”
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A new CNN deep learning model for computer-intelligent color matching by He Zhibin, Tan Yanmei, Li Sa

“…To solve the above problems, this study optimized the convolutional neural network (CNN) algorithm using the genetic algorithm (GA), extracted data through the GA, and then processed the information using the CNN algorithm. …”
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Face Detection Using Hybrid SNN-ANN to Process Neuromorphic Event Stream by Waseem Shariff, Paul Kielty, Joe Lemley, Peter Corcoran

“…To overcome these limitations, this paper explores the benefits of neuromorphic event cameras, which capture asynchronous pixel-level changes, offering lower data processing demands and reduced latency. The paper proposes a hybrid architecture combining Spiking Neural Networks (SNNs) and Artificial Neural Networks (ANNs). …”
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