Improving the quality of payment fraud detection by using a combined approach of transaction analysis by Світлана Гавриленко, Олексій Абдуллін

“…F1-score ranges from 96 to 100% for different subclasses. The feature importance within each subclass is evaluated by the gradient boosting algorithm. …”
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MODELING OF WORK DEVICES WITH RPA TEST COMPLEX OMICRON CMC 356 by Pavel Vivchar, Dmitri Oleynikov, Victoria Lyhmanova, Svyatoslav Strakhov, Sergey Jastrebov, Anna Diachenko, Elena Zakharova

“…On the basis of the actual characteristics of the head sections offeeders for the city of Mineralnye Vody was developed simulation algorithm of the terminal Sirius-2-L, check the operation of the device protection in the event of damage at different points in the investigated area of the distribution network. …”
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Complex Neutrosophic Approach for Uncertainty Management in Employment Competence for Higher Vocational College Students by Shuo Du, Lijuan Zhao

“…We introduce a real-world case study to optimize the evaluation of different vocational employment configurations based on ten competing criteria. …”
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Assessment of binary prediction of fraudulent advertisements in ATS candidate tracking cloud systems by V. V. Ligi-Goryaev, G. A. Mankaeva, T. B. Goldvarg, S. S. Muchkaeva, V. V. Dzhakhnaev

“…Some features that could be useful in detecting fraudulent job ads include job location, job description, job requirements, job responsibilities, company information, and recruiter data. Subsequently, different machine learning algorithms can be trained on prepared datasets using standard methods such as cross-validation to assess their performance. …”
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A Survey of Dense Object Detection Methods Based on Deep Learning by Yang Zhou, Hui Li

“…We discuss the similarities and differences, as well as the advantages and disadvantages, of dense object detection algorithms based on five different approaches: NMS, LOSS, re-scoring, transform and YOLO. …”
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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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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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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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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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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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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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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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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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