Use of Neuro-Net Modeling for Forecasting Key Finance Figures at Trade Enterprises by A. R. Baghirzade

Get full text

Research on the Classification of Sun-Dried Wild Ginseng Based on an Improved ResNeXt50 Model by Dongming Li, Zhenkun Zhao, Yingying Yin, Chunxi Zhao

Get full text

Using the ASTER GDEM v.2 global digital elevation model to identify areas of possible activation of karst processes in the Arkhangelsk region (Russia) by E.V. Polyakova, Y.G. Kutinov, A.L. Mineev, Z.B. Chistova, T.Ya. Belenovich

“…The possibility of applying the method of detecting drainless depressions, which is used in hydrological correction of the digital elevation model, to identify areas of probable activation of the karst processes in the territory of the Arkhangelsk region was considered. …”
Get full text

Enhancing Security of Proof-of-Learning Against Spoofing Attacks Using Feature-Based Model Watermarking by Ozgur Ural, Kenji Yoshigoe

“…The rapid advancement of machine learning (ML) technologies necessitates robust security frameworks to protect the integrity of ML model training processes. Proof-of-Learning (PoL) is a critical method for verifying the computational effort in training ML models, while model watermarking is a strategy for asserting model ownership. …”
Get full text

Sensitivity Analysis of the WRF Model to Simulate Precipitation in the Metropolitan Area of the Valley of Mexico for the Period June-September 2019 by Indalecio Mendoza Uribe, Víctor Kevin Contreras Tereza, Pamela Iskra Mejía Estrada, Olivia Rodríguez López

“…The results of the model were compared with the observation records, considering five thresholds of rainfall. …”
Get full text

Development and optimization of a neural network model using genetic algorithm to predict the performance of a packed bed reactor treating sulphate-rich wastewater by Manoj Kumar, Rohil Saraf, Shishir Kumar Behera, Raja Das, Mansi Aliveli, Arindam Sinharoy, Eldon R. Rene, Ravi Krishnaiah, Kannan Pakshirajan

Get full text

Synergizing Software Engineering and AI: A Sustainable Intelligent Model for Automating Higher Education Quality Assurance Auditing by Ibrahim Ahmed Al-Baltah

“…The software architecture of the proposed model consists of three layers that systematically interact with each other to achieve the model goal. …”
Get full text

An efficient supervised framework for music mood recognition using autoencoder‐based optimised support vector regression model by Gaurav Agarwal, Hari Om

Get full text

Research on fault diagnosis of amorphous alloy transformers by using vibration signals and a PSO-optimized full-process WPT-SVM model by Daosheng Liu, Wentao Yang, Longsheng Liu, Zhe Zhao

“…The PSO algorithm is used to optimize the number of WPT decomposition layers, wavelet basis functions, SVM kernel parameters g and penalty parameters c to enhance the accuracy of feature extraction and classification. …”
Get full text

A simplified downlink interference model for low- altitude three-dimensional networking scenarios by ZHOU Jiao, LI Xin, CAO Lei, CHEN Weiyan, FAN Wen, ZHANG Xin, QIN Jie, XU Lefei

“…This model could obtain the performance of low-altitude coverage using only the angle of tilt and the relative position information between users and base stations, thereby simplifying the process of performance and interference analysis in low-altitude scenarios.…”
Get full text

EFFICIENCY AND ACCURACY OF CONVOLUTIONAL AND FOURIER TRANSFORM LAYERS IN NEURAL NETWORKS FOR MEDICAL IMAGE CLASSIFICATION by Fauzi Nafi'udin, Hasih Pratiwi, Etik Zukhronah

“…In addition, the model with the Fourier transform layer also shows faster execution time per epoch, which indicates efficiency in data processing. …”
Get full text

Impact of process parameters and material selection on the mechanical performance of FDM 3D-Printed components by Md Mahbub Morshed Haque, Suchinto Roy Dhrubo, Al-Fida Zubayer Pranto, Akash Ahmed, Md Miraj Arefin, Md Arifuzzaman, Md Shariful Islam

“…Fused Deposition Modelling (FDM) is a widely adopted additive manufacturing technique that constructs objects by sequentially depositing layers of thermoplastic filament. …”
Get full text

Simulation of Soil Freeze-thaw Process and Water Balance in Shrubland Meadow in Shallow Mountain Area of Qilian Mountains by Tiaoxue LU, Linshan YANG, Jingru WANG, Xingyi ZOU, Wanghan HE

“…Soil water-heat dynamics are pivotal in influencing regional hydrological processes.Understanding the dynamics of soil thermal and moisture changes during freezing and thawing processes is essential for assessing water balance in high-altitude regions.This study utilizes meteorological and soil water-heat observational data from a typical shallow mountainous catchment in the Qilian Mountains to simulate the water-heat dynamics of subalpine shrub meadow soil using the SHAW model， analyzing the changes in water balance during the soil freezing and thawing process.The results indicate that the SHAW model effectively simulates the temporal and vertical variations in soil temperature and moisture in subalpine shrub meadow soils.The findings demonstrates that the Nash-Sutcliffe Efficiency （NSE） for simulated soil temperature at various depths exceeded 0.88， with ae correlation coefficient （R） greater than 0.97and a Root Mean Square Error （RMSE） less than 1.89 ℃.For soil moisture， the correlation coefficient （R） was greater than 0.94， NSE was greater than 0.88.and the RMSE was less than 0.05 m³·m⁻³.Overall， the simulation of soil temperature is more accurate than that of soil moisture， especially in deeper soil layers.The soil freezing and thawing periods， delineated by temperature profiles， revealed a distinct unidirectional freezing and thawing characteristic of the subalpine shrub meadow soil， with the longest duration in the complete freezing period and the shortest in the freezing period.The trends in temperature and moisture across the soil profile exhibit a "U" shape， indicating higher soil temperatures and moisture during the thawing period compared to the freezing period， with significant fluctuations in surface soil moisture and relative stability at deeper layers.The water balance characteristics are significantly varied across different soil freezing and thawing periods.During the freezing period， the precipitation input is 4.28 mm， with the main expenditure of water is deep percolation at 9.06 mm.In the complete freezing period， the precipitation input is 28.69 mm， with the main expenditure of water is surface runoff at 17.90 mm.During the thawing period and the complete thawing period， the precipitation input is 106.29 mm and 207.31 mm respectively， with the major water output through evapotranspiration， where plant transpiration accounted for 78.11% and 71.54% respectively.The soil moisture shows a negative balance during the freezing and complete thawing periods， indicating a net loss of moisture.Conversely， the soil moisture exhibits a positive balance during the complete freezing and thawing periods， signifying a net increase in moisture.This study may provide empirical data and theoretical support for the formation and transformation of water resources in the Qilian Mountain region.…”
Get full text

Developing a business model focused on the planning sustainability of forest sector enterprises by Ihor Soloviy, Orest Kiyko, Vasyl Lavnyy, Igor Bukhanevych, Oksana Pelyukh, Mykhailo Ilkiv, Taras Chelepis, Dmytro Savka, Andriy Lutsenco

“…The aim of the study is to analyze and develop prototypes of a sustainable business model for Ukrainian forest enterprises using a specific wood processing enterprise as an example. …”
Get full text

High‐Resolution Simulation of Dense Fog in Tianjin City: Effect of Horizontal Resolutions From Mesoscale to Large Eddy Scale by Meng Tian, Shun Li, Wei Wei, Jianbo Yang, Bingui Wu, Suhong Ma, Yang Guo, Qing Liu, Haohao Nie

“…The results reveal: With increasing resolution, the model becomes more sensitive to fluctuations of meteorological variables within the fog layer, resulting in a more pronounced diurnal variation and a tendency for the fog to dissipate more readily. …”
Get full text

MATHEMATICAL MODELING OF HEATING RATE PRODUCT AT HIGH HEAT TREATMENT by M. M. Akhmedova, M. E. Akhmedov, A. F. Demirova, V. V. Pinyaskin

“…Methods of computing and mathematical modeling are all widely used in the study of various heat exchange processes that provide the ability to study the dynamics of the processes, as well as to conduct a reasonable search for the optimal technological parameters of heat treatment.This work is devoted to the identification of correlations among the factors that have the greatest effect on the rate of heating of the product at hightemperature heat sterilization in a stream of hot air, which are chosen as the temperature difference (between the most and least warming up points) and speed cans during heat sterilization.As a result of the experimental data warming of the central and peripheral layers compote of apples in a 3 liter pot at high-temperature heat treatment in a stream of hot air obtained by the regression equation in the form of a seconddegree polynomial, taking into account the effects of pair interaction of these parameters.…”
Get full text

Improving brain tumor classification: An approach integrating pre-trained CNN models and machine learning algorithms by Mohamed R. Shoaib, Jun Zhao, Heba M. Emara, Ahmed S. Mubarak, Osama A. Omer, Fathi E. Abd El-Samie, Hamada Esmaiel

Get full text

PaleAle 6.0: Prediction of Protein Relative Solvent Accessibility by Leveraging Pre-Trained Language Models (PLMs) by Wafa Alanazi, Di Meng, Gianluca Pollastri

“…Inspired by the remarkable success of NLP techniques, this study leverages pre-trained language models (PLMs) to enhance RSA prediction. We present a deep neural network architecture based on a combination of bidirectional recurrent neural networks and convolutional layers that can analyze long-range interactions within protein sequences and predict protein RSA using ESM-2 encoding. …”
Get full text

A Dual-Layered Pythagorean Neutrosophic and Partial Locality Framework for Emotionally Adaptive Furniture Product Design Based on Elderly User Perception by Mingyan Yang

“…In this paper, we propose a novel dual-layered framework that models elderly perception using Pythagorean Neutrosophic Sets (PNS) and Partial Locality Theory. …”
Get full text

Context‐Sensitive Conscious Interpretation and Layer‐5 Pyramidal Neurons in Multistable Perception by Talis Bachmann

“…Methods A cortical multicompartment layer‐5 pyramidal neuron‐based generic processing model is presented in order to conceptualize a possible mechanistic solution for the explanatory cul‐de‐sac. …”
Get full text