VERIFICATION OF A TRAIN ON RAILWAY TRACK SIMULATION AND OPTIMIZATION SYSTEM by Adam MAŃKA, Piotr KISIELEWSKI, Jarosław KONIECZNY, Krzysztof LABISZ, Janusz ĆWIEK

“…The main achievement is the development of an algorithm that simulates the passage of a train over 500 km, the duration of which did not exceed two minutes. …”
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Cystinosis symposium: a rare disease model for comprehensive care by Ashley M. Gefen, Frederick J. Kaskel, Frederick J. Kaskel, Joshua J. Zaritsky

“…This conference was one of the first to address the glaring deficiencies in the care of children and adults with cystinosis by focusing on themes that are mutually applicable to multidisciplinary healthcare providers, educators, and families. The ultimate goal was to disseminate new information and awareness to all engaged in the cystinosis community and provide an algorithm to navigate more effectively the promising future toward a cure.…”
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Image Target Detection and Recognition Method Using Deep Learning by Hongyan Sun

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Forced Response Vibration Analysis of the Turbine Blade with Coupling between the Normal and Tangential Direction by Aram Mahmoodi, Hamid Ahmadian

“…To validate the algorithm of the solution, numerical results of previous references in the turbine-blade field are regenerated. …”
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SYNTHESIS OF THE TECHNICAL CONTROL SYSTEMS WITH VARIABLE STRUCTURE by I. V. Prokopyev

“…The recommendation of modification of Demark trends algorithm by means of the sliding Yazvinsky's window and a method of self-organization for increase of accuracy of creation of a predictive model of damage is made. …”
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Target Detection and Image Enhancement for Underwater Environment: Research on Improving YOLOv7 by Yang Luo, Wen Feng

“…Meanwhile, the image enhancement algorithm designed in this paper plays an important role in improving the quality of the input data, which effectively enhances the performance of the target detection model in the complex underwater environment. …”
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Cooperative spectrum sensing scheme based on crowd trust and decision-making mechanism by Xiao-mao WANG, Chuan-he HUANG, Yi-long LV, Bin WANG, Xi-ying FAN, Hao ZHOU

“…A distributed consensus-based scheme by simulating the crowd trust and decision-making mechanism was proposed.This scheme firstly predicts the dynamic trust value among sensing users by the previous cooperative process,and then generates the user's relative trust value,and makes the data interaction among the users by using the combination of relative trust value and decision-making mechanism.All users' state can reach a consensus as the credible and iterative data interaction.All users get the final results by the determinant algorithm.This new spectrum sensing scheme utilizes the imbalance of each users' sensing ability in the real environment.Each secondary user can maintain cooperation with others only through the local information exchange with the neighbors.It is quite different from traditional spectrum sensing scheme,such as OR-rule,1-out-of-N rule and ordinary iterative method.Three SSDF attacks were analysed,on the basis of the corresponding anti-attack policy was proposed.Theoretical analysis and simulation results show that the new scheme is better than the existing cooperative spectrum sensing algorithm in accuracy and security.New scheme not only can improve the accuracy of spectrum sensing but also has the strong anti-attack capability.…”
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Electricity Theft Detection in a Smart Grid Using Hybrid Deep Learning-Based Data Analysis Technique by Camille Franklin Mbey, Jacques Bikai, Felix Ghislain Yem Souhe, Vinny Junior Foba Kakeu, Alexandre Teplaira Boum

“…Therefore, we proposed a hybrid artificial intelligence (AI) technique considering sudden changes of consumption in order to accurately predict fraudulent consumers in the smart network. …”
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Making sense of transformer success by Nicola Angius, Pietro Perconti, Alessio Plebe, Alessandro Acciai

“…In particular, available experimental studies turned to test the theory of mind, discourse entity tracking, and property induction in NLMs are examined under the light of the functional analysis in the philosophy of cognitive science; the so-called copying algorithm and the induction head phenomenon of a Transformer are shown to provide a mechanist explanation of in-context learning; finally, current pioneering attempts to use NLMs to predict brain activation patterns when processing language are here shown to involve what we call a co-simulation, in which a NLM and the brain are used to simulate and understand each other.…”
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Elastoplastic Constitutive Model for Energy Dissipation and Crack Evolution in Rocks by Lei Cheng, Zhi Yu, Xinxi Liu

“…Subsequently, a three-dimensional finite difference scheme for the theoretical model is derived to implement a numerical algorithm. Finally, using argillaceous siltstone as an example, the validity of the theoretical model and its algorithmic implementation is verified through experimental testing, result analysis, model construction, secondary development, and numerical simulation. …”
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Statistical Analysis of the Model Parameters of the Epidemic Situation by Yu. B. Grishunina, N. A. Kontarov, G. V. Arkharova, N. V. Yuminova

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Study on multi-parameter optimization of seismic isolation bearings for continuous girder bridges considering interactions among key parameters by Zhaolan Wei, Bowen Yang, Qixuan You, Konstantinos Daniel Tsavdaridis, Shaomin Jia

“…First, using a conventional particle swarm optimization (PSO) algorithm, the individual and combined effects of each parameter on key response indicators are identified. …”
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Used economy market insight: Sailboat industry pricing mechanism and regional effects. by Zhanni Huang, Hansheng Hu, Di Wu

“…Therefore, this article uses the random forest model and XGBoost algorithm to identify core price indicators, and uses an innovative rolling NAR dynamic neural network model to simulate and predict second-hand sailboat price data. …”
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A Classification Method Related to Respiratory Disorder Events Based on Acoustical Analysis of Snoring by Can WANG, Jianxin PENG, Xiaowen ZHANG

“…A classification method is presented based on respiratory disorder events to predict the apnea-hypopnea index (AHI) of OSAHS patients. …”
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D2D cooperative caching strategy based on graph collaborative filtering model by Ningjiang CHEN, Linming LIAN, Pingjie OU, Xuemei YUAN

“…A D2D cooperative caching strategy based on graph collaborative filtering model was proposed for the problem of difficulty in obtaining sufficient data to predict user preferences in device-to-device (D2D) caching due to the limited signal coverage of base stations.Firstly, a graph collaborative filtering model was constructed, which captured the higher-order connectivity information in the user-content interaction graph through a multilayer graph convolutional neural network, and a multilayer perceptron was used to learn the nonlinear relationship between users and content to predict user preferences.Secondly, in order to minimize the average access delay, considering user preference and cache delay benefit, the cache content placement problem was modeled as a Markov decision process model, and a cooperative cache algorithm based on deep reinforcement learning was designed to solve it.Simulation experiments show that the proposed caching strategy achieves optimal performance compared with existing caching strategies for different content types, user densities, and D2D communication distance parameters.…”
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Ambulance Siren Detection using Artificial Intelligence in Urban Scenarios by Muhammad Usaid, Muhammad Asif, Tabarka Rajab, Munaf Rashid, Syeda Iqra Hassan

“…With this validated algorithm, researchers can develop a real-time hardware-based model to detect emergency vehicles and make them arrive at the hospital as soon as possible. …”
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Artificial intelligence in drug development: reshaping the therapeutic landscape by Sarfaraz K. Niazi, Zamara Mariam

“…Over the past 30 years, machine learning, deep learning, and neural networks have revolutionized drug design, target identification, and clinical trial predictions. AI has boosted pharmaceutical R&D (research and development) by identifying new therapeutic targets, improving chemical designs, and predicting complicated protein structures. …”
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A mode of action protein based approach that characterizes the relationships among most major diseases by Hongyi Zhou, Brice Edelman, Jeffrey Skolnick

“…Abstract Disease classification is important for understanding disease commonalities on both the phenotypical and molecular levels. Based on predicted disease mode of action (MOA) proteins, our algorithm PICMOA (Pan-disease Classification in Mode of Action Protein Space) classifies 3526 diseases across 20 clinically classified classifications (ICD10-CM major classifications). …”
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USE OF MODERN INFORMATION TECHNOLOGIES TO ENSURE THE COMPETITIVENESS OF REGIONS IN THE CONTEXT OF DECENTRALIZATION OF POWER by Lev Kloba, Solomiya Kloba

“…The main advantages of automation of the educational process in Amalgamated hromada schools are investigated. …”
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A deep machine learning model development for the biomarkers of the anatomical and functional anti-VEGF therapy outcome detection on retinal OCT images by B.E. Malyugin, S.N. Sakhnov, L.E. Axenova, K.D. Axenov, E.V. Kozina, V.V. Vronskaya, V.V. Myasnikova

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