Double-component combined generalized weighted fractional Fourier transform based waveform design for massive MIMO by Xingjian LI, Zhiqun SONG, Yong LI, Lizhe LIU, Bin WANG, Chang WANG

“…In order to overcome the drawback of conventional diversity technologies that sacrificing valuable communication resources such as data rate or bandwidth in massive multiple input multiple output (MIMO) systems, a double-component combined generalized weighted fractional Fourier transform (DCGWFRFT) based waveform design method was proposed.The concept of computational diversity was introduced, and the diversity performance was improved via moderate computational resources without requiring channel state information at the transmitter.The principle of computational diversity of DCGWFRFT based waveform was firstly analyzed, and a DCGWFRFT based waveform design and transform process, which could be adopted combined with existing diversity methods, was then proposed according to the principle.Theoretical analysis proves that the proposed waveform design and transform process can perfectly recover the original transmitted signal in noise-free case, and the power of error of proposed waveform is distributed more evenly than that of untransformed waveform in noisy case.Simulation results show that the performance of DCGWFRFT based waveform has an advantage of at least 1.7 dB in bit signal-to-noise ratio compared with untransformed waveform when bit error rate is 10^-3.…”
Get full text

A Broyden Correction Image Reconstruction Algorithm for Electrical Capacitance Tomography System by CHEN Yu, XIA Zong-ji, LI Hong-bo, ZHOU Yu-jia

“…This algorithm meets the convergence condition and the error of image reconstruction is small. Simulation data and experimental results indicate that this algorithm can provide favorable stabilization and high quality images compared with SD, LBP, Landweber and CG and this new algorithm provides a feasible and effective way for ECT image reconstruction field.…”
Get full text

Exploring AI to automate EFL corrective written feedback in the first language by Rob Hirschel, Kayoko Horai

“…The classroom intervention on which this study is based had four main steps: a) individual or collective brainstorming and vocabulary search (5 minutes), b) subsequent free-writing activity in an online browser (10 minutes), c) reading the ChatGPT feedback in L1 Japanese (5 minutes), d) completing paper error logs to process feedback (5 minutes). Data was collected from students’ written submissions as well as the ChatGPT-generated feedback, students’ error logs, and surveys administered to students after each activity and at the end of the semester. …”
Get full text

INFLUENCE OF CAPITAL FLIGHT ON BUDGET IMPLEMENTATION IN NIGERIA by Kingsley Onyekachi ONYELE, Eberechi Bernadine NWOKOCHA

“…To achieve this broad objective, co-integration test and vector error correction were employed for the analysis using time series data spanning from 1986 to 2014. …”
Get full text

Strata pressure behavior law and regional-level intelligent early warning for high-intensity mining in extended working faces of medium-thick coal seams in Yuheng mining area by Feng CUI, Cheng ZONG, Xingping LAI, Tao XIE, Yunhu BAI, Yi ZHANG, Chong JIA, Hao WANG, Zhong LUO, Hao LIU

“…Finally, the engineering application performance test and prediction error analysis were carried out. The results show that the pressure distribution in the strike direction of the 11207 extended working face of Yuandatan Coal Mine presents an “M”-shaped feature of “double peaks-valley oscillation”. …”
Get full text

Short-Term Load Forecasting for Electrical Power Distribution Systems Using Enhanced Deep Neural Networks by Shewit Tsegaye, Sanjeevikumar Padmanaban, Lina Bertling Tjernberg, Kinde Anlay Fante

“…Thorough experimental analysis indicates that the root-mean-squared error (RMSE) achieved by the EPGA-enhanced LSTM for Jimma town power distribution system STLF is about 43.87. …”
Get full text

Soft-sensor modeling of silicon content in hot metal based on sparse robust LS-SVR and multi-objective optimization by GUO Dong-wei, ZHOU Ping

“…First, owing to the issue that the Lagrange multiplier of the standard least squares support vector machine (LS-SVR) is directly proportional to the error term and solves the lack of sparsity, the maximal independent set of sample data in the feature space mapping set was extracted to realize the sparse of the training sample set and reduce the computational complexity of modeling. …”
Get full text

Radiative heat and mass transfer significance through a permeable vertical plate with rotational effects: An artificial approach using the Levenberg–Marquardt algorithm by R. Kavitha, Kavikumar Jacob, Ahmad Haji Zadeh, Nagarajan Deivanayagampillai

“…The ANN accurately predicts flow dynamics and heat transfer using numerical simulation data. Model accuracy is validated through mean squared error graphs, regression analysis, and error histograms, demonstrating reliable fluid dynamics predictions under varying conditions.…”
Get full text

Machine Learning Impact on Modern Business Intelligence by Raziyeh Moghaddas, Farinaz Tanhaei, Maryam Al Moqbali, Solmaz Safari

“…Finally, we assessed the performance of each model using standard evaluation metrics, i.e., Mean Absolute Error (MAE), Mean Squared Error (MSE), and the R-squared (R²) score. …”
Get full text

Availability predictions of solar power plants using multiple regression and neural networks: an analytical study by Ashish Kumar, Kanak Saini, Ashish Kumar, Dinesh Kumar Saini

“…The impact of failure and repair rates on the availability of the PV power plant investigated. Experimental data used to calculate the Mean Absolute Error (MAE) and Root Mean Square Error (RMSE) of both predictive techniques. …”
Get full text

Forecasting the daily energy load schedule of working days using meteofactors for the central power system of Mongolia by A. G. Rusina, O. Tuvshin, P. V. Matrenin

“…According to the method of statistical analysis, daily load curves were constructed with an absolute percentage error of 2.68%. …”
Get full text

Integrating deep learning in stride-to-stride muscle activity estimation of young and old adults with wearable inertial measurement units by Min Khant, Darwin Gouwanda, Alpha A. Gopalai, Chee Choong Foong

“…These findings indicate that the proposed technique can efficiently extract relevant gait data and estimate the muscle activity, potentially simplifying gait analysis and making it more affordable and accessible to a wider range of users.…”
Get full text

Multimodal Fusion Anomaly Detection Model for Agricultural Wireless Sensors by Zhenggui Zhou

“…The existence of anomalous data leads to the deterioration of the agricultural data quality, which hinders the efficient development of agricultural data analysis. …”
Get full text

Research on deconvolution methods for thermal network of power devices by DENG Erping, YANG Ying, WANG Yanhao, CHANG Guiqin, HUANG Yongzhang, DING Lijian

“…In this paper, by studying the core aspect of deconvolution in the structure function method, the theoretical analysis of three deconvolution calculation methods was carried out from three aspects: calculation method input, calculation method core, and error analysis; data analysis was carried out from six aspects: number of iterations, calculation time, sampling frequency, accuracy of calculation methods, selection of calculation methods and practical application. …”
Get full text

Multiple Imputation Based on Conditional Quantile Estimation by Matteo Bottai, Huiling Zhen

“…Multiple imputation is a simulation-based approach for the analysis of data with missing observations. It is widely utilized in many set- tings and preeminent among general approaches when the analytical method does not involve a likelihood function or this is too complex. …”
Get full text

Automatic Recognition of Motor Skills in Triathlon: A Novel Tool for Measuring Movement Cadence and Cycling Tasks by Stuart M. Chesher, Carlo Martinotti, Dale W. Chapman, Simon M. Rosalie, Paula C. Charlton, Kevin J. Netto

“…Following an initial analysis, a further six triathletes were recruited to collect additional cycling data to train the machine learning model to more effectively recognise cycling task changes. …”
Get full text

Development and validation of a novel AI-derived index for predicting COPD medical costs in clinical practice by Guan-Heng Liu, Chin-Ling Li, Chih-Yuan Yang, Shih-Feng Liu

“…Methods: A retrospective analysis of 396 COPD patients was conducted, utilizing clinical, demographic, and comorbidity data. …”
Get full text

Smoking Behavioral Intentions of Nursing Students in Kendari by Deni

“…The type of research used is qualitative with a case study design. The analysis takes the form of domain analysis using Focus Group Discussion data collection techniques for eight nursing students in Kendari. …”
Get full text

Generalized Class of Finite Population Variance in the Presence of Random Nonresponse Using Simulation Approach by Sapna Javed, Saadia Masood, Ali Shokri

“…In this article, we estimate the finite population variance in random nonresponse using simple random sampling, which may be helpful for data analysis in applied and environmental sciences. …”
Get full text

Smart forecasting: Enhancing virtual power plant performance with analytical frameworks by Maja Celeska Krstevska, Petar Krstevski, Mare Srbinovska, Vesna Andova, Aleksandra Krkoleva Mateska

“…Cyril and Methodius University in Skopje (UKIM) facilities, (ii) solar radiation data for Skopje city region, and (iii) historical PV power generation data. …”
Get full text