Spectrophotometric Determination of Bismuth(III) with Arsenazo(III) Reagent in Water samples and Veterinary Preparation by Baghdad Science Journal

“…The limit of detection (LOD) and the limit of quantification (LOQ) are 0.0633 and 0.0847 ?…”
Get full text

Two New Approaches (RAMS-RATMI) in Multi-Criteria Decision-Making Tactics by Reda M. S. Abdulaal, Omer A. Bafail

“…When a decision must be made, a tool called multi-criteria decision-making (MCDM) is used to assess and select alternatives among numerous criteria. For a wide variety of complex problems, MCDM methods have demonstrated usefulness in finding the optimal solutions. …”
Get full text

Robust Classification of UWB NLOS/LOS Using Combined FCE and XGBoost Algorithms by Shoude Wang, Nur Syazreen Ahmad

“…The method begins with feature selection using the Pearson Correlation Coefficient to filter less correlated features of the UWB Channel Impulse Response (CIR) data, followed by outlier handling. …”
Get full text

Comparative Analysis of ARIMA, Prophet, and Glmnet for Long Term Evolution (LTE) Base Station Traffic Forecasting by Tutun Juhana, Hajiar Yuliana, . Hendrawan, . Iskandar, Yasuo Musashi

“…The findings reveal that Glmnet consistently outperforms ARIMA and Prophet across all categories of traffic forecasting on the selected performance metrics. Its ability to handle complex data structures, manage multicollinearity, and deliver robust and accurate predictions makes it the preferred choice for forecasting cellular network traffic in the telecommunications domain.   …”
Get full text

Prediction of Enthalpy of Mixing of Binary Alloys Based on Machine Learning and CALPHAD Assessments by Shuangying Huang, Guangyu Wang, Zhanmin Cao

“…The model performance was further optimized through Recursive Feature Elimination (RFE) and Maximal Information Coefficient (MIC) feature selection methods. Shapley Additive Explanations reveals that the primary factors affecting the mixing enthalpy, such as atomic radius and electronegativity, align with the key parameters of the Miedema model, thereby confirming the physical interpretability of our data-driven approach. …”
Get full text

Comparing the Efficiency of Sediment Rating Curve and ANN Models in Estimating River Bed-load by Jamal Mosaffaie, Amin Saleh pourjam, Mahmudreza Tabatabaei

“… Evaluation and selection of the most appropriate methods for bed-load estimation is necessary because of the sampling difficulties and inaccurate estimations of the empirical equations. …”
Get full text

XPolypNet: A U-Net-Based Model for Semantic Segmentation of Gastrointestinal Polyps With Explainable AI by Arjun Kumar Bose Arnob, Muhammad Mostafa Monowar, Md. Abdul Hamid, M. F. Mridha

“…To address the challenges of varying polyp sizes, indistinct boundaries, and complex textures, the model used a combined loss function (Binary Cross-Entropy and Dice Loss). …”
Get full text

UGS-M3F: unified gated swin transformer with multi-feature fully fusion for retinal blood vessel segmentation by Ibtissam Bakkouri, Siham Bakkouri

“…However, accurately segmenting blood vessels in fundus images is challenging due to factors such as significant variability in vessel scale and appearance, occlusions, complex backgrounds, variations in image quality, and the intricate branching patterns of retinal vessels. …”
Get full text

Information Merging for Improving Automatic Classification of Electrical Impedance Mammography Images by Jazmin Alvarado-Godinez, Hayde Peregrina-Barreto, Delia Irazú Hernández-Farías, Blanca Murillo-Ortiz

“…Breast cancer remains one of the leading causes of mortality among women worldwide, highlighting the critical need for early and accurate detection methods. Traditional mammography, although widely used, has limitations, including radiation exposure and challenges in detecting early-stage lesions. …”
Get full text

Electrochemical Determination of Caffeine Content in Ethiopian Coffee Samples Using Lignin Modified Glassy Carbon Electrode by Meareg Amare, Senait Aklog

“…In agreement with reported works, caffeine contents (w/w%) of 0.164 in Wonbera coffee; 0.134 in Wolega coffee; 0.097 in Finoteselam coffee; and 0.089 in Zegie coffee were detected confirming the applicability of the developed method for determination of caffeine in a complex matrix environment. …”
Get full text

A novel wind speed prediction model based on neural networks, wavelet transformation, mutual information, and coot optimization algorithm by Faezeh Amirteimoury, Farshid Keynia, Elaheh Amirteimoury, Gholamreza Memarzadeh, Hanieh Shabanian

“…To tackle this issue, this paper proposes a new wind speed prediction model that combines four techniques: Discrete Wavelet Transform, which smooths the wind speed signal; Mutual Information, which selects the most informative part of the wind speed time series; Coot Optimization Algorithm for optimal feature selection; and Bidirectional Long Short-Term Memory for capturing complex patterns. …”
Get full text

Simultaneous analysis of all SNPs in genome-wide and re-sequencing association studies. by Clive J Hoggart, John C Whittaker, Maria De Iorio, David J Balding

“…A non-zero coefficient estimate was interpreted as corresponding to a significant SNP. …”
Get full text

Lung Cancer Management: Revolutionizing Patient Outcomes Through Machine Learning and Artificial Intelligence by Taghi Riahi, Bahareh Shateri‐Amiri, Amirhossein Hajialiasgary Najafabadi, Sina Garazhian, Hanieh Radkhah, Diar Zooravar, Sahar Mansouri, Roya Aghazadeh, Mohammadreza Bordbar, Shirin Raiszadeh

Get full text

Potential Skill Map of Predictors Applied to the Seasonal Forecast of Summer Rainfall in China by Liu Boqi, Zhu Congwen

“…Anomalous summer rainfall in China is affected by many factors, whose complex interaction restricts the predictability of Chinese summer rainfall (CSR). …”
Get full text

Historical information based iterative soft Kalman time-varying channel estimation method by Lu CHENG, Lihua YANG, Zenghao WANG, Jie ZHANG, Yan LIANG

“…For high-speed mobile MIMO-OFDM systems,a historical information based iterative soft-Kalman filter time-varying channel estimation method was proposed.Considering that the channels experienced by different trains in the high-speed railway environment have strong correlation,the channel information of the historical train was firstly used to obtain the optimal basis function,which can be employed to model the channel.By the optimal basis function,the computational complexity was reduced and the channel estimation accuracy was improved for the proposed method.Secondly,the soft-Kalman filter and data detection were jointed to estimate the base coefficient in each iteration.To reduce the effect of data detection error propagation on the channel estimation,the soft data detection scheme was employed and the soft detection error was treated as noise in each iteration.In addition,the soft-Kalman filter used in the proposed method does not involve the AR model tracking factor,thereby avoiding the computational complexity introduced by the estimated tracking factor.The simulation results show that the proposed method has better estimation performance,and is more suitable for time-varying channel acquisition of actual high-speed mobile scenarios.…”
Get full text

Historical information based iterative soft Kalman time-varying channel estimation method by Lu CHENG, Lihua YANG, Zenghao WANG, Jie ZHANG, Yan LIANG

“…For high-speed mobile MIMO-OFDM systems,a historical information based iterative soft-Kalman filter time-varying channel estimation method was proposed.Considering that the channels experienced by different trains in the high-speed railway environment have strong correlation,the channel information of the historical train was firstly used to obtain the optimal basis function,which can be employed to model the channel.By the optimal basis function,the computational complexity was reduced and the channel estimation accuracy was improved for the proposed method.Secondly,the soft-Kalman filter and data detection were jointed to estimate the base coefficient in each iteration.To reduce the effect of data detection error propagation on the channel estimation,the soft data detection scheme was employed and the soft detection error was treated as noise in each iteration.In addition,the soft-Kalman filter used in the proposed method does not involve the AR model tracking factor,thereby avoiding the computational complexity introduced by the estimated tracking factor.The simulation results show that the proposed method has better estimation performance,and is more suitable for time-varying channel acquisition of actual high-speed mobile scenarios.…”
Get full text

Research on Aircraft Control System Fault Risk Assessment Based on Composite Framework by Tongyu Shi, Yi Gao, Long Xu, Yantao Wang

“…Taking into account the severity, the detection, and the risk damping coefficient, the calculation result of IRPN is 158.00. …”
Get full text

Differences of Intrasession Reproducibility of Circumpapillary Total Retinal Thickness and Circumpapillary Retinal Nerve Fiber Layer Thickness Measurements Made with the RS-3000 Op... by Yoshiyuki Kita, Gábor Hollό, Ritsuko Kita, Daisuke Horie, Makoto Inoue, Akito Hirakata

“…Intraclass correlation (ICC), coefficient of variation (CV) and reproducibility coefficient (RC) were calculated for each parameter.…”
Get full text

Nitrous oxide prediction through machine learning and field-based experimentation: A novel strategy for data-driven insights by Muhammad Hassan, Khabat Khosravi, Travis J. Esau, Gurjit S. Randhawa, Aitazaz A. Farooque, Seyyed Ebrahim Hashemi Garmdareh, Yulin Hu, Nauman Yaqoob, Asad T. Jappa

“…Applying machine learning to predict complex environmental phenomena like greenhouse gas emissions (GHG) is gaining significant attention. …”
Get full text

Research on formant estimation algorithm for high order optimal LPC root value screening by Hua LONG, Shumeng SU

“…Objectives: The existing linear prediction (LP) formant estimation algorithms are difficult to locate formant precisely because of the pseudo root interference and interaction between poles.Because of the low order fitting formant of LP prediction,the accuracy of formant extraction is fundamentally limited.It is difficult to remove false roots and spectrum aliasing caused by pole interaction in the formant extraction of high-order LP.In order to solve the problem of large error of LP formant detection,a formant estimation algorithm based on high-order LP coefficient root value screening was proposed. …”
Get full text