Mapping individual tree crowns to extract morphological attributes in urban areas using unmanned aerial vehicle-based LiDAR and RGB data by Geonung Park, Bonggeun Song, Kyunghun Park

“…This approach also improved the effectiveness of the DL model, Mask R-CNN, by resolving challenges in label generation. …”
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Enhancing education quality with hybrid clustering and evolutionary neural networks in a multi phase framework by Saleem Malik, Chandrakanta Mahanty, Jnanaranjan Mohanty, Krunal Vaghela, T. Narmadha, R. Sivaranjani, Javed Khan Bhutto, Saiful Islam, Anwar Khan, Amanuel Zewdie

“…The algorithm improves prediction power through progressive convergence. …”
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A Method of Locating and Measuring Train Wheel Tread Defects Based on YOLOv3-tiny by JIN Kairong, WANG Junping, CHEN Shenglan

“…In order to solve the key problems that the detection frame is too large and too small, traditional image algorithms such as Fourier transform, band-stop filter, and threshold segmentation are used to construct a defect size measurement model, contours of roughly located defects are extracted and detection frame size is optimized, and finally location and size of defect are accurately calculated. …”
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Research on Book Recommendation Integrating Book Category Features and User Attribute Information by Yan Chen, Eric Blancaflor, Mideth Abisado

“…Aiming at the problem of poor recommendation effect caused by data sparsity in traditional collaborative filtering algorithm in book recommendation, this study proposes a personalized recommendation model (BCF-UAI) that combines book category features and user attribute information, aiming to improve the accuracy and generalization ability of the recommendation system. …”
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Research on intelligent energy management strategies for connected range-extended electric vehicles based on multi-source information by Xuewen Zhai, Hanwu Liu, Wencai Sun, Zihang Su

“…The Euclidean distance between consecutive traffic scenario matrices is used as a basis for similarity to optimize speed and predict future vehicle speeds. Moreover, a multi-objective intelligent EMS based on deep reinforcement learning (DRL) is employed, utilizing the Deep Deterministic Policy Gradient (DDPG) algorithm to comprehensively consider vehicle dynamics, energy consumption economy, and the degradation of batteries. …”
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Reconstruction for Scanning LiDAR with Array GM-APD on Mobile Platform by Di Liu, Jianfeng Sun, Wei Lu, Sining Li, Xin Zhou

“…This method avoids the need for field-of-view registration, improves data utilization, and reduces the complexity of the algorithm while eliminating the effect of LiDAR motion. …”
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Hunting Stability Enhancement of a Train Bogie Employing Inerter-Based Suspension Mechanism by Yong Wang, Chenyang Hong, Haodong Meng

“…The structural parameter analysis of inerter-based suspension mechanism is conducted, and the structural parameters are optimized using the nondominated sorting whale optimization algorithm (NSWOA). …”
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Protein docking by the underestimation of free energy funnels in the space of encounter complexes. by Yang Shen, Ioannis Ch Paschalidis, Pirooz Vakili, Sandor Vajda

“…This algorithm explores the free energy surface spanned by encounter complexes that correspond to local free energy minima and shows similarity to the model of macromolecular association that proceeds through a series of collisions. …”
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Uncertainty quantification with graph neural networks for efficient molecular design by Lung-Yi Chen, Yi-Pei Li

“…Using benchmarks from the Tartarus and GuacaMol platforms, our results show that UQ integration via probabilistic improvement optimization (PIO) enhances optimization success in most cases, supporting more reliable exploration of chemically diverse regions. …”
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An interpretable integrated machine learning framework for genomic selection by Jinbu Wang, Jia Zhang, Wenjie Hao, Wencheng Zong, Mang Liang, Fuping Zhao, Longchao Zhang, Lixian Wang, Huijiang Gao, Ligang Wang

“…Moreover, we introduced the NuSVR model, which achieved the highest accuracy among nine compared algorithms. …”
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On the academic ideology of “Sorting the gangue is sorting the images” by Hongwei MA, Ye ZHANG, Peng WANG, Xiangang CAO, Zhen NIE, Xiaorong WEI, Wenjian ZHOU, Mingzhen ZHANG

“…Coal gangue sorting is the most basic, effective, and important technical measure to improve coal quality. …”
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GeoTemporal clustering for aquifer delineation: a big data approach to synchronizing and analyzing variable-length groundwater time series by Khalid ElHaj, Dalal Alshamsi

“…This technique is adaptive and can be improved through ongoing monitoring. The algorithm components are modular and upgradable thus future studies should optimize and test their generalizability using additional datasets.…”
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Rock Fracture Monitoring Based on High-Precision Microseismic Event Location Using 3D Multiscale Waveform Inversion by Yi Wang, Xueyi Shang, Kang Peng, Rui Gao

“…Based on this initial location, the multiscale waveform inversion strategy (from coarse to fine grids) and the L-BFGS iteration optimization algorithm were separately jointly selected to improve wavefield modeling speed efficiency and iterative convergence rate. …”
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Exploring Monte Carlo Negotiation Search with Nontrivial Agreements by Elijah Alden Malaby, John Licato

“…We demonstrate significant improvement of our algorithm over random agreement sampling, although further work is required to more consistently produce optimal agreements.…”
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Adaptive SDN switch migration mechanism based on coalitional game by Lan YAO, Julong LAN

“…The problem of poor control plane performance causes in software-defined Networking due to the unreasonable mapping relationship between controllers and switches.To address this issue,an adaptive switch migration mechanism based on coalitional game was proposed.First,comprehensively considering the controller resource utilization,control overhead,and flow establishment time,the switch migration problem was modeled as a combination optimization problem.Then,a game theory was introduced to design a distributed algorithm,where each controller ran control logic independently and implemented coalitional game between controllers to achieve an adaptive switch migration mechanism that adapted to traffic characteristics.The simulation results show that the proposed mechanism can better adapt to the flow characteristics,reduce the control traffic overhead by about 19% and the average flow settling time by 30%,and improve the controller resource utilization.…”
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Unraveling C-to-U RNA editing events from direct RNA sequencing by Adriano Fonzino, Caterina Manzari, Paola Spadavecchia, Uday Munagala, Serena Torrini, Silvestro Conticello, Graziano Pesole, Ernesto Picardi

“…Using in vitro synthesized and human ONT reads, our model optimizes the signal-to-noise ratio improving the detection of C-to-U editing sites with high accuracy, over 90% in all samples tested. …”
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Predicting Employee Turnover Using Machine Learning Techniques by Adil Benabou, Fatima Touhami, My Abdelouahed Sabri

“…This study aims to identify the most effective machine learning model for predicting employee attrition, thereby providing organizations with a reliable tool to anticipate turnover and implement proactive retention strategies.Objective: This study aims to address the challenge of employee attrition by applying machine learning techniques to provide predictive insights that can improve retention strategies.Methods: Nine machine learning algorithms are applied to a dataset of 1,470 employee records. …”
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Low power IoT device communication through hybrid AES-RSA encryption in MRA mode by Qiang Chang, Tianqi Ma, Wenzhong Yang

“…This modification optimizes computational efficiency and strengthens security.Furthermore, we investigate the feasibility of integrating the RSA and AES algorithms and propose a novel RSA-AES hybrid algorithm MRA. …”
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Detecting Simulated Nosocomial Disease Outbreaks with Sequential Monte Carlo Methods by Dr Conor Rosato

“…Conclusion: By detecting nosocomial disease outbreaks early, healthcare facilities can implement timely interventions to mitigate the spread of infections, protect vulnerable patients and optimize resource allocation. Our methodology offers a valuable tool for improving infection control practices and enhancing patient safety in healthcare settings.…”
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Energy-based segmentation methods for images with non-Gaussian noise by Jiatao Zhong, Shiyin Du, Canruo Shen, Yiting Chen, Min Gao, Medha Naidu, Xiaoping Shi, Yuejiao Fu

“…We apply the Kullback–Leibler (KL) divergence to demonstrate the feasibility of our method for non-Gaussian noisy images. Notably, the algorithm automatically determines whether the model is solvable using a Gaussian approach and, if not, effortlessly switches to a non-Gaussian alternative. …”
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