Exploring the Impact of Streets’ Syntactic Properties on the Urban Functions and Land Use: Insights from Spatial Network Analysis by Aya Furat Alobaydi, Dhirgham Alobaydi, Sally Fakhri Abdullah

“…High choice values also correlate with commercial activity (ρ=0.160, p<0.01), so spatial accessibility plays a big role in shaping urban functions and land use. There is a lot to learn from this in other historical urban situations to compare and apply urban design principles based on syntactic properties. …”
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Aggregation-Based Ensemble Classifier Versus Neural Networks Models for Recognizing Phishing Attacks by Wojciech Galka, Jan G. Bazan, Urszula Bentkowska, Kamil Szwed, Marcin Mrukowicz, Pawel Drygas, Lech Zareba, Marcin Szpyrka, Piotr Suszalski, Sebastian Obara

“…Unlike other phishing datasets, this data provides dates which is important for the incremental learning approach. The proposed approach of ensemble learning models, based on aggregation functions, is compared to the well-known neural network models which may be treated as state of the art models in recognizing phishing attacks. …”
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Autonomous Intelligent VNF Profiling for Future Intelligent Network Orchestration by Nasim Ferdosian, Shadi Moazzeni, Pratchaya Jaisudthi, Yifei Ren, Himanshu Agrawal, Dimitra Simeonidou, Reza Nejabati

“…In this article, we propose a profile-based data-driven analysis framework to extract and analyze the characteristics and behavior of virtualized network functions (VNFs) in virtualized networks from the resource and performance perspective. …”
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Indicated factors of physical development, physical readiness, functional condition and efficiency of female students in the process of adaptation to training by M.S. Avdeeva, O.V. Tulyakova

“…Purpose: to determine indicated factors of physical development, physical readiness, functional condition and efficiency of female students in the process of adaptation to learning. …”
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Functional Monitoring of Patients With Knee Osteoarthritis Based on Multidimensional Wearable Plantar Pressure Features: Cross-Sectional Study by Junan Xie, Shilin Li, Zhen Song, Lin Shu, Qing Zeng, Guozhi Huang, Yihuan Lin

“…The multidimensional gait features extracted from the data and physical characteristics were used to establish the KOA functional feature database for the plantar pressure measurement system. 40mFPWT and TUGT regression prediction models were trained using a series of mature machine learning algorithms. …”
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Construction of Integrated Platform for Eco-Sustainable Tourism and Marketing in Southeast Asia Based on Machine Learning by Yi-Tui Chen, Yi-Min Li, Tzu-Wen Tseng

“…The experimental results of this study showed that the difference between different loss functions of the improved transfer algorithm based on machine learning is not significant, which indicated that the method proposed in this study is robust to the choice of a loss function. …”
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HIV- and AIDS-associated neurocognitive functioning in Zambia &amp;ndash; a perspective based on differences between the genders by Kabuba N, Menon JA, Franklin Jr DR, Heaton RK, Hestad KA

“…The norms corrected for effects of age, education, and gender in the general population, and the test battery measures domains of attention/working memory (learning and delayed recall), executive function, verbal fluency, processing speed, verbal and visual episodic memory, and fine motor skills. …”
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Ideational Meaning of Material Process in EFL Students’ Problem-Solving Text: A Frame of Systemic Functional Linguistics by Veronika Listi Ferdini Damopolii, Eva Tuckyta Sari Sujatna, Dadang Suganda, Rosaria Mita Amalia

“…The pedagogical contribution of this study is to apply SFL as a model and use descriptive language to examine how linguistic choices reflect social contexts and their functions in students' lives in advancing their learning. …”
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Effect and Mechanism of Yisui Fuyongtang (YSFYT) Decoction on Cognitive Function and Synaptic Plasticity in Rats with Vascular Cognitive Impairment by Tingliang Gong, Zhaoliang Luo, Li Huang, Caixian Xiao, Junlu Yi, Junfeng Yan, Qian Chen, Weihong Li, Wenqiang Tao

“…Clinical medications have found that Yisui Fuyongtang (YSFYT) Decoction is effective in improving neurological signs and learning-memory functions in patients who develop white matter lesions and whole brain atrophy. …”
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Using Deep Learning (CNN, RNN, LSTM, GRU) methods for the prediction of Protein Secondary Structure by Ezgi Çakmak, İhsan Hakan Selvi

“…Therefore, predicting the protein secondary structure becomes important for studying its structure and function. Many emerging methods, including machine learning, as well as deep learning, have been used to predict the secondary structure of proteins and comprise a crucial part of Structural Bioinformatics. …”
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Development of educational function of university libraries in the border regions of Russia and China (on the example of the Khabarovsk territory and Heilongjiang province) by Olga A. Simonenko, Ekaterina P. Krivtsova

“…We are talking about the impossibility of isolated development and the presence of a high interest in finding partners abroad. The educational function of the university library includes education, information literacy, self-education and individual learning, as well as communication between subjects of the educational process.…”
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High-density lipoprotein cholesterol subfraction HDL2 is associated with improved endothelial function in systemic lupus erythematosus by Tze Ping Loh, Lieng Hsi Ling, Anselm Mak, Lingli Gong, Nien Yee Kow, Chun En Yau, Sen Hee Tay, Ainsley Ryan Yan Bin Lee, Cheryl Kai Ting Chua, Wan Ling Cheng, Avery Joy Li Chia, Shi Yin Wong, Bernett Teck Kwong Lee

“…Flow-mediated dilatation (FMD) is an established non-invasive assessment of vascular endothelial function. Lipoprotein subfractions may be better predictors of FMD than conventional cholesterol measurements. …”
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Value-difference learning based mMTC devices access algorithm in multi-cell network by Xin LI, Jun SUN

“…In the massive machine type communication scenario of 5G, the access congestion problem of massive machine type communication devices (mMTCD) in multi-cell network is very important.A double deep Q network with value-difference based exploration (VDBE-DDQN) algorithm was proposed.The algorithm focused on the solution that could reduce the collision when a number of mMTCDs accessed to eNB in multi-cell network.The state transition process of the deep reinforcement learning algorithm was modeled as Markov decision process.Furthermore, the algorithm used a double deep Q network to fit the target state-action value function, and it employed an exploration strategy based on value-difference to adapt the change of the environment, which could take advantage of both current conditions and expected future needs.Moreover, each mMTCD updated the probability of exploration according to the difference between the current value function and the next value function estimated by the network, rather than using the same standard to select the best base eNB for the mMTCD.Simulation results show that the proposed algorithm can effectively improve the access success rate of the system.…”
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Towards a New Generation of Impulse‐Response Functions for Integrated Earth System Understanding and Climate Change Attribution by Alexander J. Winkler, Carlos A. Sierra

“…Abstract Impulse‐response functions (IRFs) are mathematical functions that represent the response of the coupled carbon‐climate system to different trajectories of fossil‐fuel emissions and land‐use. …”
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Improving the interoperability of a Function-as-a-Service platform using an orchestration framework with a cloud-agnostic approach by Zameer Ahmed Adhoni, Dayananda Lal Narayan

“…Function-as-a-Service (FaaS) applications suffer from cold-start latency owing to their high execution time and memory usage. …”
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MENet: A Mitscherlich function based ensemble of CNN models to classify lung cancer using CT scans. by Surya Majumder, Nandita Gautam, Abhishek Basu, Arup Sau, Zong Woo Geem, Ram Sarkar

“…In this paper, we propose an ensemble model, called the Mitscherlich function-based Ensemble Network (MENet), which combines the prediction probabilities obtained from three deep learning models, namely Xception, InceptionResNetV2, and MobileNetV2, to improve the accuracy of a lung cancer prediction model. …”
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Predicting the Compressive Strength of High-Performance Concrete utilizing Radial Basis Function Model integrating with Metaheuristic Algorithms by LiWei Hu

“…One of these neural networks is the radial basis function (RBF), with one input layer, one or more hidden layers, and one output layer. …”
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Information Educational Environment of Higher Educational Institution in Training of Professionally-Oriented Foreign Language: Essence, Content, Functions by E. Y. Kamysheva

“…Attention is paid to the description of the fundamental principles of information-educational environment functioning: structuredness, hierarchy, openness, adaptability, variability, integration, interactivity. …”
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Formation and creative manifestation of functional ensembles of intellectual agents based on live information in various spheres of life activity by Evgeny Bryndin

“…Functional ensembles of harmoniously interacting intellectual agents with living information can virtually model creativity for various spheres of life activity. …”
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A Novel Hybrid Radial Basis Function Method for Predicting the Fresh and Hardened Properties of Self-Compacting Concrete by Zhangabay Nurlan

“…Results demonstrate powerful potential in the learning section as well as approximation in the testing phase. …”
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