The good, the better and the challenging: Insights into predicting high-growth firms using machine learning by Sermet Pekin, Aykut Şengül

“…This study aims to classify high-growth firms using several machine learning algorithms, including K-Nearest Neighbors, Logistic Regression with L1 (Lasso) and L2 (Ridge) Regularization, XGBoost, Gradient Descent, Naive Bayes and Random Forest. …”
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Multisegment Mapping Network for Massive MIMO Detection by Yongzhi Yu, Jianming Wang, Limin Guo

“…Because of the large number of massive MIMO antennas, the computational complexity of detection has increased significantly, which poses a significant challenge to traditional detection algorithms. However, the use of deep learning for massive MIMO detection can achieve a high degree of computational parallelism, and deep learning constitutes an important technical approach for solving the signal detection problem. …”
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PULSim: User-Based Adaptable Simulation Tool for Railway Planning and Operations by Yong Cui, Ullrich Martin, Jiajian Liang

“…Users and researchers gain the ability to rapidly develop their own algorithms, supported by the tailored simulation process in a flexible manner. …”
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Role of Customs Legislation and Practice of Its Implementation in the Protection of Fauna of Ukraine by I. O Panov

“…The author has emphasized the need to develop automated algorithms for the exchange of information on the movement of wild animals across the border between the relevant government agencies in order to further control the legality of the origin of animals and bring to justice those who illegally released wild animals. …”
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Drone Landing and Reinforcement Learning: State-of-Art, Challenges and Opportunities by Jose Amendola, Linga Reddy Cenkeramaddi, Ajit Jha

“…It also revisits Reinforcement Learning Algorithms, the main frameworks and simulators adopted for specific landing operations. …”
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Predictive Analytics in Finance Using the Arima Model. Application for Bucharest Stock Exchange Financial Companies Closing Prices by Spulbar Cristi, Ene Cezar Cătălin

“…Moreover, the selected model is part of the time series analysis under prediction algorithms, the purpose of the research being to predict the prices of the selected shares. …”
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Deep learning–based resource allocation for secure transmission in a non-orthogonal multiple access network by Miao Zhang, Yao Zhang, Qian Cen, Shixun Wu

“…Machine learning techniques, especially deep learning algorithms have been widely utilized to deal with different kinds of research problems in wireless communications. …”
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Integrating Satellite Data and In-situ Observations for Trophic State Assessment of Renuka Lake, Himachal Pradesh, India by Sujit Kumar Jally, Rakesh Kumar and Sibabrata Das

“…The present study focuses on estimating the Trophic State Index (TSI) of Renuka Lake, the smallest Ramsar site in India, utilizing in-situ observed Secchi disk transparency (SDT) and satellite data. Site-specific algorithms were developed by establishing the relationship between the spectral band ratio of Landsat 8 OLI and LISS-III with that of in-situ measured SDT data. …”
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Investigating Pre-service Chemistry Teachers’ Problem Solving Strategies: Towards Developing a Framework in Teaching Stoichiometry by Allen A. Espinosa, Rebecca C. Nueva España, Arlyne C. Marasigan

“…The study found out that the most prominent strategy among pre-service chemistry teachers is the mole method, which is algorithmic by nature. Very few of them used the proportionality method and none made use of the logical method. …”
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Stock price prediction using the Sand Cat Swarm Optimization and an improved deep Long Short Term Memory network by Burak Gülmez

“…The research evaluates multiple algorithms including ANN, LSTM variants, Auto-ARIMA, Gradient Boosted Trees, DeepAR, N-BEATS, N-HITS, and the proposed LSTM-SCSO using DAX index data from 2018 to 2023. …”
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Identification of hub genes and pathogenesis in Kawasaki disease based on bioinformatics analysis by Min Cao, Zhenhu Zhang, Qian Liu, Yuda Zhang

“…Materials and Methods: Gene Expression Omnibus (GEO) datasets GSE68004 and GSE73461 were downloaded, and the differentially expressed genes (DGEs) were taken, along with DEGs enrichment analysis and protein interaction network. Finally, five algorithms in CytoHubba plug-in were applied to obtain hub genes. …”
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Compressive Strength Evaluation of Fiber-Reinforced High-Strength Self-Compacting Concrete with Artificial Intelligence by Tu T. Nguyen, Hoa Pham Duy, Tung Pham Thanh, Hoang Hiep Vu

“…Various AI models were developed with different training algorithms and a number of nodes in the hidden layer to obtain the optimal model for the FRHSSCC data. …”
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Intellectual measurement and evaluation of the results of customs authorities’ activities by G. I. Goremykina, Yu. E. Gupanova

“…The study is based on a cognitive approach that allows describing the intellectual environment of customs authorities and models of evaluation and management based on fuzzy logic algorithms. The implementation of the technology for presenting experts’ knowledge in the subject area is carried out on the basis of constructing a prescriptive logical production model that allows formalizing expert knowledge in the form of implicative statements involving fuzzy formulations in antecedents and consequents, and using a generalized modus ponens as a logical conclusion. …”
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Improving stroke risk prediction by integrating XGBoost, optimized principal component analysis, and explainable artificial intelligence by Lesia Mochurad, Viktoriia Babii, Yuliia Boliubash, Yulianna Mochurad

“…To improve stroke risk prediction models in terms of efficiency and interpretability, we propose to integrate modern machine learning algorithms and data dimensionality reduction methods, in particular XGBoost and optimized principal component analysis (PCA), which provide data structuring and increase processing speed, especially for large datasets. …”
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Are Selective Serotonin Reuptake Inhibitors a Secondary Cause of Low Bone Density? by Kim Chau, Stephanie A. Atkinson, Valerie H. Taylor

“…Additional longitudinal studies and further research on possible mechanisms surrounding the association between SSRI use on bone metabolism need to be conducted. Treatment algorithms need to recognize this association to ensure that vulnerable populations are screened.…”
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Distortion Optimized Packet Scheduling and Prioritization of Multiple Video Streams over 802.11e Networks by Ilias Politis, Michail Tsagkaropoulos, Thomas Pliakas, Tasos Dagiuklas

“…Two intelligent scheduling algorithms are proposed: the “even-loss distribution,” where each video sender is experiencing the same loss and the “greedy-loss distribution” packet scheduling, where selected packets are dropped over all streams, ensuring that the most significant video stream in terms of picture context and quality characteristics will experience minimum losses. …”
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Identifying Safeguards Disabled by Epstein-Barr Virus Infections in Genomes From Patients With Breast Cancer: Chromosomal Bioinformatics Analysis by Bernard Friedenson

“…MethodsPublicly available genome data from approximately 2100 breast cancers and 25 ovarian cancers were compared to cancers with proven associations to EBV, including 70 nasopharyngeal cancers, 90 Burkitt lymphomas, 88 diffuse large B-cell lymphomas, and 34 gastric cancers. Calculation algorithms to make these comparisons were developed. …”
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Optimization of Toolpath Planning and CNC Machine Performance in Time-Efficient Machining by Arbnor Pajaziti, Orlat Tafilaj, Afrim Gjelaj, Besart Berisha

“…We propose a method that integrates advanced algorithms to identify and eliminate redundant movements, optimize the toolpaths, and improve the machining strategies. …”
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Climatology of Total Cloudiness in the Arctic: An Intercomparison of Observations and Reanalyses by Alexander Chernokulsky, Igor I. Mokhov

“…The main reason for the discrepancies among observations is the difference in the cloud-detection algorithms, especially when clouds are detected over the ice/snow surface (during the whole year) or over the regions with the presence of strong low-tropospheric temperature inversions (mostly in winter). …”
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Analysis of Acoustic Signals of Footsteps from the Piezoelectric Sensor by Bilge Çiğdem Çiftçi, Gamze Kaya, Mustafa Kurt

“…The source of the acoustic signal can be determined by matching it with the existing database using machine learning algorithms like face recognition systems for future goals.…”
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