Construction of a Wilms tumor risk model based on machine learning and identification of cuproptosis-related clusters by Jingru Huang, Yong Li, Xiaotan Pan, Jixiu Wei, Qiongqian Xu, Yin Zheng, Peng Chen, Jiabo Chen

“…Finally, the WT risk prediction model was constructed by four machine learning methods: random forest, support vector machine (SVM), generalized linear and extreme gradient strength model. …”
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Dunkl Linear Canonical Wavelet Transform: Concentration Operators and Applications to Scalogram and Localized Functions by Saifallah Ghobber, Hatem Mejjaoli

“…We show that a finite vector space spanned by the first eigenfunctions of such operators is of a maximal phase-space concentration and has the best phase-space concentrated scalogram inside the region of interest. …”
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Design and Implementation of Stock Market Prediction System for Used Cars in Nigeria by A. A. Ibrahim, A. A. Alabi, O. A. Ayilara-Adewale, F. R. Olokun-Olukotun

“…The model was designed by training and testing using pre-processed data. Python programming language was used in the implementation. …”
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MODELING OF WATER CIRCULATION IN THE ANTARCTIC SUBGLACIAL LAKE VOSTOK by G. V. Kazko, L. M. Savatyugin, I. N. Sokratova

“…Some results of modeling of the convective processes in the lake, obtained at the initial stage of circulation evolution using finite-difference grid with a spatial resolution of 8000 × 1500 ×30 mare shown.…”
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Traffic congestion prediction based on GPS trajectory data by Shuming Sun, Juan Chen, Jian Sun

“…Since speed sensors are not as widely used as GPS devices, the traffic congestion level is predicted based on processed GPS trajectory data in this article. Hidden Markov model is used to match GPS trajectory data to road network and the average speed of road sections can be estimated by adjacent GPS trajectory data. …”
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Comparison of Texture Features Used for Classification of Life Stages of Malaria Parasite by Vinayak K. Bairagi, Kshipra C. Charpe

“…Malaria is a vector borne disease widely occurring at equatorial region. …”
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Dimensional Analysis and Optimization of 3-DOF Parallel Bionic Mechanical Leg by Wang Xiaolei, Jin Zhenlin, Li Xiaodan, Liu Xiang

“…The dimension synthesis and optimization about the mechanical leg structure is completed. The position vector model of the mechanical legs is established. …”
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Topology Optimization Design of the Planar 3-RPR Fully Compliant Parallel Mechanism by Sha Sai, Zhang Rongxing, Zhou Lei, An Ziming

“…Based on the differential kinematics of parallel mechanism displacement vector differential mapping relation between input and output,through establishing a planar 3-RPR topology optimization model of fully compliant parallel mechanism（ SIMP interpolation model）,the solution is optimized by using the optimization criterion method（ OC） algorithm,and by using the Heaviside filtering technology,the checkerboard phenomenon is restrained and processed. …”
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Robust Fuzzy Logic Stabilization with Disturbance Elimination by Kumeresan A. Danapalasingam

“…In this paper, a mathematical derivation is carried out to prove that the controller is able to achieve asymptotic stability by processing state measurements. Robustness here refers to the ability of the controller to asymptotically steer the state vector towards the origin in the presence of model uncertainties and a disturbance input. …”
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Neutrino Emission from Cooper Pairs at Finite Temperatures by Lev B. Leinson

“…It is shown that taking into account the anomalous weak interactions in both the vector and axial channels is very important for a correct description of neutrino energy losses through the PBF processes. …”
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THE THE GREAT CASPIAN IN MODERN GEOPOLITICAL CONDITIONS by K. Al. Markelov

“…The space of the Greater Caspian Sea, as an explosive center of global and regional interests of multi-vector forces of international influence, is actively involved in these processes. …”
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Massive two-loop four-point Feynman integrals at high energies with AsyInt by Hantian Zhang

“…In the high-energy region, the Feynman integrals involving external and internal massive particles, such as the top quark, Higgs and vector bosons, can be asymptotically expanded and directly calculated in the small-mass limit. …”
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Timeless Approach to Quantum Jumps by Ignazio Licata, Leonardo Chiatti

“… According to the usual quantum description, the time evolution of the quantum state is continuous and deterministic except when a discontinuous and indeterministic collapse of state vector occurs. The collapse has been a central topic since the origin of the theory, although there are remarkable theoretical proposals to understand its nature, such as the Ghirardi–Rimini–Weber. …”
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Deep learning approach to bacterial colony classification. by Bartosz Zieliński, Anna Plichta, Krzysztof Misztal, Przemysław Spurek, Monika Brzychczy-Włoch, Dorota Ochońska

“…It can be achieved using computer-aided methods, which make the recognition processes more automatic and thus significantly reduce the time necessary for the classification. …”
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Аlgorithm of fast computation of local image histograms on video card1 by Ph. S. Trotski, B. A. Zalesky

“…Now local histograms are used for solution of some tasks of image processing and recognition, but their application is restricted due to the long computational time. …”
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Multi-dimensional secure query scheme for fog-enhanced IIoT by Yousheng ZHOU, Chang TAN, Fei TANG

“…In view of the fact that most of the existing range query schemes for fog-enhanced IoT cannot achieve both multi-dimensional query and privacy protection,a privacy-preserving multi-dimensional secure query scheme for fog-enhanced IIoT was proposed.Firstly,the multiple ranges to be queried were mapped into a certain query matrix.Then,auxiliary vectors were constructed to decompose the query matrix,and then the auxiliary vector was processed by BGN homomorphic encryption to form a query trapdoor.Finally,with the homomorphic computation utilized by an IoT device terminal,the query trapdoor could be matched to its sensor data.Spatial complexity could be effectively reduced with the used specific auxiliary vectors.The confidentiality of sensor data could be ensured and the privacy of user’s query mode could be protected by the homomorphic encryption property.Experiments results show that the computational and communication costs are relatively low.…”
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New method of text representation model based on neural network by Shui-fei ZENG, Xiao-yan ZHANG, Xiao-feng DU, Tian-bo LU

“…Method of text representation model was proposed to extract word-embedding from text feature.Firstly,the word-embedding of the dual word-embedding list based on dictionary index and the corresponding part of speech index was created.Then,feature vectors was obtained further from these extracted word-embeddings by using Bi-LSTM recurrent neural network.Finally,the sentence vectors were processed by mean-pooling layer and text categorization was classified by softmax layer.The training effects and extraction performance of the combination model of Bi-LSTM and double word-embedding neural network were verified.The experimental results show that this model not only performs well in dealing with the high-quality text feature vector and the expression sequence,but also significantly outperforms other three kinds of neural networks,which includes LSTM,LSTM+context window and Bi-LSTM.…”
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Artificial Bee Colony Algorithm Based on the Division Between Exploration and Exploitation and Its Application in Esophageal Cancer Prediction by WANG Yingcong, YAN Jun, SUN Junwei, WANG Yanfeng

“…However, the basic ABC algorithm prioritizes exploration during the search process and performs poorly in exploitation, leading to slow convergence speed and low solution accuracy. …”
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A survey on the state-of-the-art machine learning models in the context of NLP by Wahab Khan, Ali Daud, Jamal A. Nasir, Tehmina Amjad

“… Machine learning and Statistical techniques are powerful analysis tools yet to be incorporated in the new multidisciplinaryfield diversely termed as natural language processing (NLP) or computational linguistic. The linguistic knowledge may be ambiguous or contains ambiguity; therefore, various NLP tasks are carried out in order to resolve the ambiguity in speech and language processing.The current prevailing techniques for addressing various NLP tasks as a supervised learning are hidden Markov models (HMM), conditional random field (CRF), maximum entropy models (MaxEnt), support vector machines (SVM), Nave Bays, and deep learning (DL).The goal of this survey paper is to highlight ambiguity in speech and language processing, to provide brief overview of basic categories of linguistic knowledge, to discuss different existing machine learning models and their classification into different categories and finally to provide a comprehensive review of different state of the art machine learning models with the goal that new researchers look into these techniques and depending on these, develops advance techniques. …”
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Sufficient conditions for convergence of positive solutions to linearized two-dimensional sediment transport problem by Alexander I. Sukhinov, Valentina V. Sidoryakina, Andrey A. Sukhinov

“…The sediment transportation is one of the major processes that define the magnitude and back surface changing rate for water bodies. …”
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