Graph convolution network for fraud detection in bitcoin transactions by Ahmad Asiri, K. Somasundaram

“…GCN is of special interest in our case. Different evaluation parameters such as accuracy, ROC and F1 score are analyzed for different models. …”
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View-invariant object representation in anterior and posterior inferotemporal cortex: A machine learning approach by Jun-ya Okamura, Daisuke Fukano, Keisuke Murakami, Gang Wang

“…A classifier was trained by support vector machine (SVM) to create a hyperplane that separated one object from the other three objects at the same viewing angles, and then tested by response vectors to the object images at different viewing angles. In area TE, dynamics of the performance evaluated by d’ showed viewing angle tolerance of 30–90° to the objects with prior experience in learning association of different views. …”
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A Secure Asymmetric Optical Image Encryption Based on Phase Truncation and Singular Value Decomposition in Linear Canonical Transform Domain by Anshula Sangwan, Hukum Singh

“…A new asymmetric optical double image encryption algorithm is proposed, which combines phase truncation and singular value decomposition. …”
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An Extensive Study Using the Beetle Swarm Method to Optimize Single and Multiple Objectives of Various Optimal Power Flow Problems by K. Sriram, S. P. Mangaiyarkarasi, S. Sakthivel, L. Jebaraj

“…This article deals with the use of beetle swarm optimization algorithm (BSOA), for optimal power flow (OPF) solution, in an effective approach. …”
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Classification of Hybrid and Peking Duck DOD Varieties Based on Feather Images Using CNN by Khoironi, I Wayan Rangga Pinastawa

“…In this study, a deep learning approach with the Convolutional Neural Network (CNN) algorithm was applied to classify DOD varieties based on feather images. …”
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Division of images into areas of local extrema with a monotonic change in pixel brightness by A. T. Nguyen, V. Yu. Tsviatkou

“…The developed algorithm differs from the known segmentation algorithms by using a set of brightness thresholds (by the number of regions), varying by one in each cycle, starting from the values of local extrema, taking into account the increase or decrease in brightness to select adjacent pixels that are attached to the regions formed from these local extrema. …”
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Research on heat transfer characteristics of crude oil storage tank heated by jet in combination with mechanical stirring by Hang Dong, Xiaowan Liang, Xiaonian Xiong, Mingyu Lei, Jian Zhao

“…However, the internal heat transfer characteristics during heating and the effects of different agitators are unclear. This paper simulated the heating process of single jet and three agitators under different stirring speeds, considering crude oil rheology and wax crystal latent heat, using the SIMPLE algorithm. …”
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Advanced Machine Learning and Deep Learning Approaches for Estimating the Remaining Life of EV Batteries—A Review by Daniel H. de la Iglesia, Carlos Chinchilla Corbacho, Jorge Zakour Dib, Vidal Alonso-Secades, Alfonso J. López Rivero

“…To address these, we propose a comprehensive set of evaluation metrics and emphasize the need for larger and more diverse datasets. …”
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Optimization of clustering parameters for single-cell RNA analysis using intrinsic goodness metrics by Nicolina Sciaraffa, Antonino Gagliano, Luigi Augugliaro, Claudia Coronnello, Claudia Coronnello

“…Despite the advancements and numerous adaptations of clustering algorithms, the correct clustering of cells remains a challenging endeavor that is dependent on the data in question and on the parameters selected for the clustering process. …”
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Comparative Assessment of Data Quality Dimensions in Scientific Multimedia Indexing Process by Hamid Hassani, Azadeh Mohebi, Mohammad Javad Ershadi

“…Also, using the correlation matrix, the intensity and direction of the relationship and correlation between the different dimensions of data quality have been evaluated. …”
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Numerical Simulation of Wind-Induced Vibration Response Characteristics of High-Rise Buildings with Podiums by Guangbiao Jiang, Zeyan Chen, Hongxi Qin, Linlei Dong, Ao Tang

“…In order to evaluate the influence of different parameters on the wind-induced vibration response of high-rise buildings with podiums, a total of 11 comparative conditions were set, including the presence or absence of podiums, podium height, podium area, and podium layout conditions. …”
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Robustness Study of Non-Dimensional Star Pattern Recognition for a Typical Star Tracker by Jafar Roshanian, Shabnam Yazdani, Masoud Ebrahimi

“…In order to evaluate the effect of angle differences on algorithm performance, overall disposition of bright point centers is modeled. …”
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SDGTrack: A Multi-Target Tracking Method for Pigs in Multiple Farming Scenarios by Tao Liu, Dengfei Jie, Junwei Zhuang, Dehui Zhang, Jincheng He

“…In pig farming, multi-object tracking (MOT) algorithms are effective tools for identifying individual pigs and monitoring their health, which enhances management efficiency and intelligence. …”
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Applicability Analysis of Log Calculation Method for Organic Matter Maturity of Changning Shale Gas Reservoir in Southern Sichuan Basin by QIU Dingguo, YAN Jianping, GUO Wei, LIAO Maojie, QIU Xiaoxue, HUANG Yi

“…The shale formation of Wufeng formation and Longmaxi formation in southern Sichuan are affected by sedimentation and uplift caused by multi-stage tectonic movement, which makes the degree of thermal evolution in different regions very different. The maturity of organic matter is an important parameter to evaluate the degree of thermal evolution of shale gas reservoirs. …”
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SAFIRE STRENGTH OPTIMIZATION: EFFECT ON TISSUE CONTRAST AND PATHOLOGICAL ASSESSMENT OF BRAIN MSCT WITH NON-HEMORRHAGE STROKE (SNH) by I Putu Eka Juliantara, Angel Lingkan Martoyo, Made Sayang Pratista

“…Background: Sinogram Affirmed Iterative Reconstruction (SAFIRE) is an Iterative Reconstruction algorithm that combines IR techniques that utilize raw data and image data iterations as parameters that underlie noise regularization in images in the reconstruction process to improve image quality. …”
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Advancements in Parkinson’s Disease Diagnosis: A Comprehensive Survey on Biomarker Integration and Machine Learning by Ruchira Pratihar, Ravi Sankar

“…This comprehensive review explores the advancements in machine learning algorithms in the diagnosis of Parkinson’s disease (PD) utilizing different biomarkers. …”
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State information-driven surrogate-assisted differential evolution for computationally expensive constrained optimization problems by Zihua Zhu, Zan Yang, Zhiyong Liu, Liming Chen, Xiwen Cai

“…Secondly, different ensemble mutation and environmental selection operations are tailored specially for subpopulations where both an inner evolution-driven parent expansion and update rate-based surrogate switch strategies are designed to regulate the search ability of the algorithm. …”
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Ultimate Compression: Joint Method of Quantization and Tensor Decomposition for Compact Models on the Edge by Mohammed Alnemari, Nader Bagherzadeh

“…The process includes training floating-point models, applying tensor decomposition algorithms, binarizing the decomposed layers, and fine tuning the resulting models. …”
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Application of deconvolutional networks for feature interpretability in epilepsy detection by Sihao Shao, Yu Zhou, Ruiheng Wu, Aiping Yang, Qiang Li

“…Even automated detection algorithms are already available to assist clinicians in reviewing EEG data, many algorithms used for seizure detection in epilepsy fail to account for the contributions of different channels. …”
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Methodolo- gical Aspects of Semantic Relationship Extraction for Automatic Thesaurus Generation by N. S. Lagutina, K. V. Lagutina, E. I. Mamedov, I. V. Paramonov

“…These algorithms are based on different relation extraction techniques: lexico-syntactic patterns, morpho-syntactic rules, measurement of term information quantity, general-purpose thesaurus WordNet, and Levenstein distance. …”
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