Multi-objective game for fighting against Distributed Reflection DoS attacks in software-defined network by Vianney Kengne Tchendji, Mthulisi Velempini, Priva Chassem Kamdem

“…In this paper, we leverage the advantages of software-defined networks (SDN) to propose a game-theoretic approach that predicts the defender’s best moves based on Nash strategies to mitigate this attack while avoiding botnet expansion. …”
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CENPF as a Potential Biomarker Associated with the Immune Microenvironment of Renal Cancer by Meilin Chen MS, Xiuxin Tang MS, YanPing Liang MD, Tangdang Ding MS, Meifang He PhD, Dong Wang PhD, Ruizhi Wang PhD

“…Prognostic analysis indicated that high follicular helper T-cell expression predicted poorer survival, while high plasma cell expression correlated with better outcomes. …”
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High-throughput discovery of perturbation-induced topological magnons by Mohammed J. Karaki, Ahmed E. Fahmy, Archibald J. Williams, Sara Haravifard, Joshua E. Goldberger, Yuan-Ming Lu

“…However, to make reliable and systematic predictions about the material realization of topological magnons has been a major challenge, due to the lack of neutron scattering data for most materials and the absence of reliable ab initio calculations for magnons. …”
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Machine learning based assessment of hoarseness severity: a multi-sensor approach centered on high-speed videoendoscopy by Tobias Schraut, Anne Schützenberger, Tomás Arias-Vergara, Melda Kunduk, Matthias Echternach, Stephan Dürr, Julia Werz, Michael Döllinger

“…Subjects were classified into two hoarseness groups based on auditory-perceptual ratings, with predicted scores serving as continuous hoarseness severity ratings. …”
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Spatial analysis of air pollutant exposure and its association with metabolic diseases using machine learning by Jingjing Liu, Chang Liu, Zhangdaihong Liu, Yibin Zhou, Xiaoguang Li, Yang Yang

“…By adjusting for demographic and lifestyle confounders, APs effectively predicted the risk of developing MDs (AUROC=0.890, 0.877, 0.710 for diabetes, dyslipidemia, and hypertension, respectively). …”
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Development of a deep learning model for automated detection of calcium pyrophosphate deposition in hand radiographs by Thomas Hügle, Elisabeth Rosoux, Guillaume Fahrni, Deborah Markham, Tobias Manigold, Fabio Becce

“…CPPD presence was then predicted using a convolutional neural network. We tested seven CPPD models, each with a different combination of sites out of TFCC, MCP-2 and MCP-3. …”
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Utilizing Multi-omics analysis to elucidate the role of mitochondrial gene defects in Gastric cancer progression. by Jie Chu, Hanying Song, Kemin Fu, Wei Xiao, Jiudong Jiang, Qixin Gan, Bo Deng

“…Additionally, both the ssGSEA algorithm and the CIBERSORT algorithm were utilized to evaluate changes and effects in immunological characteristics during gastric cancer pathogenesis.…”
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Foreign object detection for mining conveyor belts based on YOLOv5n-CND by SUN Aoran, ZHAO Peipei, YANG Di, ZHANG Junyi, YU Hongjian

“…Second, the normalized Gaussian Wasserstein distance (NWD) regression loss function was used to replace CIoU, improving the performance of multi-scale foreign object detection and accurately predicting the detection of adhering small objects. …”
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Toward precision oncology in LUAD: a prognostic model using single-cell sequencing and WGCNA based on a disulfidptosis relative gene signature by Panpan Li, Han Zhang, Limin Sun, Xiaojuan Wu

“…Gene expression in single cell RNA sequencing (scRNA-seq) data was assessed using the AUcell algorithm. In the TCGA [LUAD] dataset, disulfidptosis-related enrichment scores were calculated using ssGSEA, and core gene sets were identified through the Weighted Gene Co-expression Network Analysis (WGCNA) algorithm. …”
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GPR65 is a novel immune biomarker and regulates the immune microenvironment in lung adenocarcinoma by Hanxu Zhou, Zhi Chen, Shuang Gao, Chaoqun Lian, Junjie Hu, Jin Lu, Lei Zhang

“…Additionally, nomogram containing GPR65 and clinical features were constructed for predicting patient prognosis. Then, the correlation between GPR65 and immune cell infiltration was assessed by CIBERSORT, and the impact of hub gene on immunotherapy was determined using correlation analysis between GPR65 and immune checkpoint molecules. …”
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Land cover changes in grassland landscapes: combining enhanced Landsat data composition, LandTrendr, and machine learning classification in google earth engine with MLP-ANN scenari... by Cecilia Parracciani, Daniela Gigante, Onisimo Mutanga, Stefania Bonafoni, Marco Vizzari

“…The forecasting method along with the selection of spatial drivers to predict land cover change, demonstrated high efficiency compared to other studies. …”
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OntoCommerce: Incorporating Ontology and Sequential Pattern Mining for Personalized E-Commerce Recommendations by Ghulam Mustafa, Naveed Ahmad Jhamat, Zeeshan Arshad, Nadia Yousaf, Md. Nazmul Abdal, Mohammed Maray, Dokhyl Alqahtani, Mohamad Amir Merhabi, Muhammad Abdul Aziz, Touseef Ahmad

“…This ontology is then utilized to calculate customer preference similarities and generate predictions for the intended customer. The SPM algorithm is applied to the results of collaborative filtering to generate personalized recommendations for the customer. …”
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A robust method to simultaneously place sensors and calibrate parameters for urban drainage pipe system models using Bayesian decision theory by Yuan Huang, Junyi Xiong, Jiangjiang Zhang, Feifei Zheng, Yiran Ji, Hoshin Gupta

“…Comparisons with two empirical approaches, where sensors are evenly deployed or installed in flood hotspots, show that the proposed method provides more accurate water level and flood predictions with less uncertainties across various scenarios. …”
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Specificity and Selectivity of Raman Spectroscopy for the Detection of Dose‐Dependent Heavy Metal Toxicities by Isaac D. Juárez, Nicholas Shepard, Cole Sebok, Sudip Biswas, Endang Septiningsih, Dmitry Kurouski

“…We also performed ICP‐MS of harvested rice tissue, allowing us to build Raman‐based calibration curves for predicting the HM concentration within rice. Lastly, we built a machine‐learning algorithm that could interpret the Raman spectra to diagnose the specific type of HM toxicity with an average of 84.5% accuracy after only 1 week of HM stress. …”
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Building a composition-microstructure-performance model for C–V–Cr–Mo wear-resistant steel via the thermodynamic calculations and machine learning synergy by Shuaiwu Tong, Shuaijun Zhang, Chong Chen, Tao Jiang, Peng Li, Shizhong Wei

“…By using phase content and experimental parameters as input features, the Gradient Boosted Tree model and Support Vector Regression model demonstrated strong applicability in predicting frictional performance and wear, respectively. …”
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Assessing the Soldier Survivability Tradespace Using a Single IMU by Matthew P. Mavor, Victor C. H. Chan, Kristina M. Gruevski, Linda L. M. Bossi, Thomas Karakolis, Ryan B. Graham

“…Further, we used these predictions to calculate meaningful tradespace metrics, which had an excellent agreement with calculations using the true labels. …”
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Modeling Canopy Height of Forest–Savanna Mosaics in Togo Using ICESat-2 and GEDI Spaceborne LiDAR and Multisource Satellite Data by Arifou Kombate, Guy Armel Fotso Kamga, Kalifa Goïta

“…We tested four methods: Random Forest (RF), Support Vector Machine (SVM), Extreme Gradient Boosting (XGBoost) and Deep Neural Network (DNN). The RF algorithm obtained the best predictions using 98% relative height (RH98). …”
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Strategic Implementation of Super-Agents in Heterogeneous Multi-Agent Training for Advanced Military Simulation Adaptability by Huseyin Oktay Altun, Huseyin Furkan Ceran, Korkut Kutay Metin, Tolga Erol, Emre Fisne

“…While independent learning agents excel in predictable environments with fast training capabilities, HMAT stands out in dynamic scenarios for its adaptability and superior performance. …”
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Preventing Overturning of Mobile Cranes Using an Electrical Resistivity Measurement System by Hongseok Jang, Yeonho Lee, Hongseok Lee, Youngtaek Cha, Sungjoon Choi, Jongkyu Park

“…The ERMS, mounted on a mobile crane, continuously monitors the ground conditions in real time and predicts the likelihood of ground subsidence to prevent accidents. …”
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Computational modelling and optimization of porous plates for mandibular fracture fixation accounting for bone healing by Ali Mehboob, Imad Barsoum, Hassan Mehboob, Abdelhak Ouldyerou, Rashid K. Abu Al-Rub

“…The healing process was predicted using a mechano-regulation algorithm. Conventional plate showed excessive interfragmentary strain (IFS) of approximately 1.4 and 0.6 in the 0.5 mm and 2.0 mm fracture gaps, respectively, which resulted in delayed healing. 2 MPP bone plates exhibited improved biomechanical performance with less stress in the bone plates and improved micromovement at the fracture site, promoting early bone union. …”
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