Efficiency Analysis of Turkish Container Ports: SFA or DEA? by İsmail Yenilmez

“…Purpose: The study compares the efficiency of Turkish container ports using Stochastic Frontier Analysis and Data Envelopment Analysis. It aims to provide comparative insights for enhancing ports' operational performance. …”
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Nonlinear mixed models and related approaches in infectious disease modeling: A systematic and critical review by Olaiya Mathilde Adéoti, Schadrac Agbla, Aliou Diop, Romain Glèlè Kakaï

“…When conducting an in-depth analysis of microinfection dynamics, one must account for the substantial heterogeneity across countries. …”
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Bregman divergences for physically informed discrepancy measures for learning and computation in thermomechanics by Andrieux, Stéphane

“…This study is motivated by the need of “discrepancy measures” between physically constrained fields that are used both in traditional algorithms, analysis methods and data driven modelling or applications as well.We give also a characterization of symmetrical Bregman divergences through their generating functions which can only be quadratic forms. …”
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Assessing the factors militating against the effective implementation of electronic health records (EHR) in Nigeria by Abisola Esther BABATOPE, Idowu Peter ADEWUMI, Damola Olanipekun AJISAFE, Kayode Olayiwola ADEPOJU, Adetola Rachael BABATOPE

“…Purposive sampling was adopted to select the study participants, and a structured questionnaire was used for data collection. Statistical Product and Service Solutions (SPSS) version 27 was used for data analysis, R and Microsoft Excel were used for data visualization. …”
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Safety huddle in healthcare settings: a concept analysis by Ibrahim Ghoul, Abdullah Abdullah, Fateh Awwad, Latefa Ali Dardas

“…This study clarifies the concept of “safety huddle” through a rigorous concept analysis. Methods Rodgers and Knafl’s evolutionary concept analysis methodology was applied. …”
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An integrated approach to image quality: comparative analysis of bilinear and nearest neighbor interpolation by Wusat Ullah, Seher Ilyas, Hamza Naveed, Saalam Ali

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Evaluating GRU Algorithm and Double Moving Average for Predicting USDT Prices: A Case Study 2017-2024 by Rahmat Rizky, Munirul ula, Zara Yunizar

“…This study evaluates the effectiveness of Gated Recurrent Units (GRU) and Double Moving Average (DMA) in predicting USDT (Tether Coin) prices using historical data from 2017 to 2024, sourced from Investing.com. …”
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Biomarker and clinical data–based predictor tool (MAUXI) for ultrafiltration failure and cardiovascular outcome in peritoneal dialysis patients: a retrospective and longitudinal st... by Eva María Arriero-País, María Auxiliadora Bajo-Rubio, Roberto Arrojo-García, Pilar Sandoval, Guadalupe Tirma González-Mateo, Patricia Albar-Vizcaíno, Gloria del Peso-Gilsanz, Marta Ossorio-González, Pedro Majano, Manuel López-Cabrera, Gloria del Peso-Gilsanz

“…PD outcomes were analysed in four categories (endurance, exit from PD, cause of PD end, technical failure) by using MMT biomarkers in effluents and clinical databases.Results MMT biomarkers and clinical data can predict PD with a mean absolute error of 16.99 months by using an Extra Tree (ET) regressor. …”
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Explainable Pre-Trained Language Models for Sentiment Analysis in Low-Resourced Languages by Koena Ronny Mabokela, Mpho Primus, Turgay Celik

“…Sentiment analysis is a crucial tool for measuring public opinion and understanding human communication across digital social media platforms. …”
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Transfer learning‑based attenuation correction in 99mTc-TRODAT-1 SPECT for Parkinson’s disease using realistic simulation and clinical data by Wenbo Huang, Han Jiang, Yu Du, Haiyan Wang, Hao Sun, Guang-Uei Hung, Greta S. P. Mok

“…All datasets used for DL-based methods were split to 7/8 for training and 1/8 for validation, and a 1-/2-/5-fold cross-validation were applied to test all 100 clinical datasets, depending on the numbers of clinical data used in the training model. Results With 8 available clinical datasets, TLAC-MC achieved the best result in Normalized Mean Squared Error (NMSE) and Structural Similarity Index Measure (SSIM) (TLAC-MC; NMSE = 0.0143 ± 0.0082/SSIM = 0.9355 ± 0.0203), followed by DLAC-AUG, DLAC-MIX, TLAC-ANA, DLAC-CLI, DLAC-MC, ChangAC and NAC. …”
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Different Estimation Methods Using Ranked Set Sampling for the Ramos–Louzada Distribution by Diaa S. Metwally, Amal S. Hassan, Mohammed Elgarhy, Ehab M. Almetwally, Abdoulie Faal, Ahmed M. Gemeay

“…By evaluating the estimated quality for SRS and RSS based on the partial and total ranking metrics, we conclude that the maximum likelihood and maximum product spacing approaches seem very useful for both sampling processes. Analysis shows that estimates of RSS datasets have lower mean squared errors compared with SRS estimates. …”
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A Bayesian Approach to Step-Stress Partially Accelerated Life Testing for a Novel Lifetime Distribution by Mervat K. Abd Elaal, Hebatalla H. Mohammad, Zakiah I. Kalantan, Abeer A. EL-Helbawy, Gannat R. AL-Dayian, Sara M. Behairy, Reda M. Refaey

“…To overcome this, step-stress partially accelerated life testing is employed to reduce testing time while preserving data quality. This paper develops a Bayesian model based on Type II censored data, assuming that item lifetimes follow the Topp–Leone inverted Kumaraswamy distribution, a flexible alternative to classical lifetime models due to its ability to capture various hazard rate shapes and to model bounded and skewed lifetime data more effectively than traditional models observed in real-world reliability data. …”
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Quadripartitioned Neutrosophic Soft Pre - Open And Pre - Closed Sets by S. Ramesh Kumar, Dr. A. Stanis Arul Mary

“…The proposed method not only minimizes bias but also provides more accurate population median estimates with reduced estimation error, making it a more reliable tool in the context of uncertain or incomplete data, where traditional estimators might fall short. …”
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Analysis of Financial Performance in Dairy Enterprises; The Case Study of Konya, Turkey by Cennet Oğuz, Aysun Yener

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From Polar Day to Polar Night: A Comprehensive Sun and Star Photometer Study of Trends in Arctic Aerosol Properties in Ny-Ålesund, Svalbard by Sandra Graßl, Christoph Ritter, Jonas Wilsch, Richard Herrmann, Lionel Doppler, Roberto Román

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Inter-player Variability Within the Same Positional Status in High-level Men's Volleyball by João Bernardo Martins, José Afonso, Ademilson Mendes, Letícia Santos, Isabel Mesquita

“…Researchers should be cautious of aggregating data from players of different positional status, and even from players within the same positional status …”
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3D IntelliGenes: AI/ML application using multi-omics data for biomarker discovery and disease prediction with multi-dimensional visualization by Rishabh Narayanan, Elizabeth Peker, William DeGroat, Dinesh Mendhe, Saman Zeeshan, Zeeshan Ahmed

“…Methods In this study, we focused on addressing such challenges by developing an innovative solution to better visualize results produced by AI/ML approaches on integrated clinical and multi-omics data for novel biomarker discovery and predictive analysis. …”
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Children with Additional Support Needs Risk Missing Out on Effective Vision Screening: Audit and Survey Considering Attendance Rates and Parent Reported Barriers to Service Access,... by Cirta Tooth, Julius Rogowski

“…This study evaluates attendance rates and barriers to attendance for children requiring follow-up in an urban hospital eye service after their initial screening visit. Methods and Analysis: Retrospective data on attendance, visual acuity, refractive errors, and presence of additional support needs (ASN) were collected from the National Database for preschool screening and the hospital electronic record system. …”
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Estimation and Assessment of Partial Shading Patterns in Large PV Farms Using ANN Algorithm by Efendi S Wirateruna, Mochamad Ashari, Dedet Candra Riawan

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A Comprehensive Method for Anomaly Detection in Complex Dynamic IoT Systems by Andrii Liashenko, Larysa Globa

“…Modern dynamic systems, such as transportation networks and IoT infrastructures, generate massive volumes of interrelated temporal data represented as temporal graphs. Conventional methods – like clustering, statistical thresholds, and classical time series analysis – often fail to account for the spatial-temporal dependencies inherent in these systems, leading to high false positive rates or missed complex anomalies. …”
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