The Impact of Road Functions on Road Congestions Based on POI Clustering: An Empirical Analysis in Xi’an, China by Hui Zhu, Kaiqi Zhang, Changjun Wang, Lujin Jia, Siyu Song

“…Moreover, the POIs with flexible traffic flows increase road congestion, while the POIs with predicted traffic flows have no statistically significant correlation with road congestion. …”
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The Face and number plate recognition for car anti-theft by Quoc Bao Truong, Tan-Loc Tran, Thanh Tan-Kiet Nguyen, Huu Cuong Nguyen

“…The system automatically predicts whether the driver is valid with the registration number plate. …”
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A Novel Hybrid Model for Short-Term Forecasting in PV Power Generation by Yuan-Kang Wu, Chao-Rong Chen, Hasimah Abdul Rahman

“…Moreover, five types of forecasting modules were developed and utilized to predict the one-hour-ahead PV output. They include the ARIMA, SVM, ANN, ANFIS, and the combination models using GA algorithm. …”
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The Fault-Tolerant Control Strategy for the Steering System Failure of Four-Wheel Independent By-Wire Steering Electric Vehicles by Qianlong Han, Chengye Liu, Jingbo Zhao, Haimei Liu

“…The front wheel controller predicts the necessary steering angle in accordance with a linear model and addresses the requirements of the front wheels and additional torque. …”
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Cost-Effective, Time-Efficient Passenger Rail System for the Eastern United States by James Mathias, Dal Hyung Kim

“…The results of the program predicted a passenger starting at the farthest point of the system boards the train at 16:02 on average and arrives at a different point of the system at 07:57 on average the following day, assuming the train travels an average speed of 70 mph. …”
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Correlation analysis of m6A-modified regulators with immune microenvironment infiltrating cells in lung adenocarcinoma. by Wei Ye, Tianpeng Huang

“…The m6A score was constructed using the principal component analysis algorithm to quantify the m6A modification mode of a single tumor.…”
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Vegetation Classification and Survey: five years and looking ahead by Idoia Biurrun, Jürgen Dengler, Wolfgang Willner

“…For articles that performed a plot-based classification, we provide information on classification approach, plot size, importance value, taxonomic coverage, number of plots, and classification algorithm. We also analyze the bibliometric performance of VCS across the five years and predict a CiteScore of 3.6 and a Journal Impact Factor of 2.7 for 2024 (to be published in 2025). …”
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Machining effects and multi-objective optimization in Inconel 718 turning with unitary and hybrid nanofluids under MQL by Paresh Kulkarni, Satish Chinchanikar

“…The cutting parameters were optimized by combining the Technique for Order of Preference by Similarity to the Ideal Solution (TOPSIS) and genetic algorithm. The study reveals an average error of less than 10% between experimental and predicted responses from the proposed optimization model. …”
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Detecting Fraudulent Transaction in Banking Sector Using Rule-Based Model and Machine Learning by Cut Dinda Rizki Amirillah

“…The precision data of 99% indicates that the model’s predictions of anomalies are indeed anomalies, while a recall value of 1.0 shows that the model successfully identified all anomalies in the dataset. …”
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Mathematical Modeling of High-Energy Shaker Mill Process with Lumped Parameter Approach for One-Dimensional Oscillatory Ball Motion with Collisional Heat Generation by Kwon Joong Son

“…Incorporating these thermal interactions allows the model to provide a more comprehensive depiction of the energy dynamics within the system, leading to more precise predictions of temperature changes. Utilizing a lumped parameter method, the study simplifies complex airflow dynamics and non-uniform temperature distributions in the milling system, enabling efficient numerical analysis. …”
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Development of a High‐Latitude Convection Model by Application of Machine Learning to SuperDARN Observations by W. A. Bristow, C. A. Topliff, M. B. Cohen

“…Further it is found that the mean‐squared difference between predictions of the model and observed values of the velocity are substantially lower than the same quantity calculated for an existing climatology that was not formed with ML techniques.…”
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Development of several machine learning based models for determination of small molecule pharmaceutical solubility in binary solvents at different temperatures by Mohammed Alqarni, Ali Alqarni

“…This study shows that advanced machine learning models, particularly BNN and NODE, can predict pharmaceutical solubility and improve crystallization process design and optimization.…”
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An AI framework for counterattack detection and decision-making evaluation in football by Jiangyan Yang, Huanmin Ge, Yixiong Cui

“…Subsequently, a comprehensive approach integrating Transformer and Graph Neural Networks was employed to model and predict match event decisions based on prior match events and tracking data. …”
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Transductive zero-shot learning via knowledge graph and graph convolutional networks by Qiong Li, Xin Sun, Junyu Dong

“…During testing, a clustering strategy, the Double Filter Module with Hungarian algorithm, is applied to the unseen samples, and then, the learned classifiers are used to predict their categories. …”
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FRESH: Fusion-Based 3D Apple Recognition via Estimating Stem Direction Heading by Geonhwa Son, Seunghyeon Lee, Yukyung Choi

“…Secondly, we designed a 3D detection algorithm that not only recognizes the dimensions and location of apples, as existing methods do, but also predicts their 3-axis rotation. …”
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Shoe configuration effects on equine forelimb gait kinetics at a walk by Rita Aoun, Zaneta Ogunmola, Anaïs Musso, Takashi Taguchi, Catherine Takawira, Mandi J. Lopez

“…A random forest classifier algorithm was used to predict shoeing condition from kinetic outcome measures. …”
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In vitro machine learning-based CAR T immunological synapse quality measurements correlate with patient clinical outcomes. by Alireza Naghizadeh, Wei-Chung Tsao, Jong Hyun Cho, Hongye Xu, Mohab Mohamed, Dali Li, Wei Xiong, Dimitri Metaxas, Carlos A Ramos, Dongfang Liu

“…To improve their efficacy and expand their applicability to solid tumors, scientists optimize different CARs with different modifications. However, predicting and ranking the efficacy of different "off-the-shelf" immune products (e.g., CAR or Bispecific T-cell Engager [BiTE]) and selection of clinical responders are challenging in clinical practice. …”
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Integrative analysis of epigenetic subtypes in acute myeloid Leukemia: A multi-center study combining machine learning for prognostic and therapeutic insights. by Jincan Li, Shengyue Wang

“…Drug sensitivity was predicted using the pRRophetic algorithm with GDSC database reference.…”
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Modeling the determinants of attrition in a two-stage epilepsy prevalence survey in Nairobi using machine learning by Daniel M. Mwanga, Isaac C. Kipchirchir, George O. Muhua, Charles R. Newton, Damazo T. Kadengye, Abankwah Junior, Albert Akpalu, Arjune Sen, Bruno Mmbando, Charles R. Newton, Cynthia Sottie, Dan Bhwana, Daniel Mtai Mwanga, Damazo T. Kadengye, Daniel Nana Yaw, David McDaid, Dorcas Muli, Emmanuel Darkwa, Frederick Murunga Wekesah, Gershim Asiki, Gergana Manolova, Guillaume Pages, Helen Cross, Henrika Kimambo, Isolide S. Massawe, Josemir W. Sander, Mary Bitta, Mercy Atieno, Neerja Chowdhary, Patrick Adjei, Peter O. Otieno, Ryan Wagner, Richard Walker, Sabina Asiamah, Samuel Iddi, Simone Grassi, Sloan Mahone, Sonia Vallentin, Stella Waruingi, Symon Kariuki, Tarun Dua, Thomas Kwasa, Timothy Denison, Tony Godi, Vivian Mushi, William Matuja

“…These findings will inform development of a web-based algorithm to predict attrition risk and aid in targeted follow-up efforts in similar studies.…”
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Load Balancing and Alternative Path Selection in Self-Organized Networks: A Data Plane Approach by Gergely Sarkozi, Peter Voros

“…This paper presents a novel load balancing algorithm tailored for deeply programmable networks, offering a decentralized approach to optimizing packet forwarding and load distribution. …”
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