Enhancing LiDAR Mapping with YOLO-Based Potential Dynamic Object Removal in Autonomous Driving by Seonghark Jeong, Heeseok Shin, Myeong-Jun Kim, Dongwan Kang, Seangwock Lee, Sangki Oh

“…The system achieved RMSE (Root Mean Square Error) reductions compared to conventional methods, with RMSE values decreasing from 0.9870 to 0.9724 in open areas and from 1.3874 to 1.1217 in urban areas. …”
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Association of Osteopontin (OPN) Level in Diabetic Nephropathy Patients as an Early Diagnostic Marker by Anwar Shahzad, Khalil Ur Rahman, Yasir Hamayun, Henna Khalid, Mariam Riaz

“… OBJECTIVES The study aimed to find an association between OPN levels and diabetic nephropathy as a serum marker in DM patients for early detection. …”
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IoT-Enhanced Smart Parking Management With IncepDenseMobileNet for Improved Classification by Xiaoxia Zheng, Wenxi Feng, Ning Wang, Huhemandula

“…” Statistical testing validated the robustness of the technique, while sensitivity analysis identified optimal hyperparameter combinations. The findings indicate significant improvement in parking management via accurate prediction of occupancy trends, identification of peak demand, and detection of payment and violation issues. …”
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Development of automatic insect-tracking robot system for measuring local activity changes in free walking by Ryoko Sekiwa, Tatsuya Ibuki, Shunsuke Shigaki

“…The robot tracks the insect with an error margin of less than 5 mm, recording the EAG responses associated with the olfactory reception during this process. …”
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Farmers’ knowledge and perception of finger millet blast disease and its control practices in western Kenya by Wilton Mbinda, Agnes Kavoo, Fredah Maina, Margaret Odeph, Cecilia Mweu, Naomi Nzilani, Mathew Ngugi

“…Descriptive analysis was done by calculating means, percentages, frequencies, and standard errors. Comparative statistics, chi-square and t-tests, were used to evaluate differences existing among the farm characteristics and socio-demographics and the knowledge and perceptions of blast disease and its management practices. …”
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SEISMIC PICTURE OF A FAULT ZONE. WHAT CAN BE GAINED FROM THE ANALYSIS OF FINE PATTERNS OF SPATIAL DISTRIBUTION OF WEAK EARTHQUAKE CENTERS? by Gevorg G. Kocharyan, Svetlana B. Kishkina, Aleksey A. Ostapchuk

“…Based on the data from a very dense network of digital seismic stations installed in this region and with application of modern data processing methods, differential coordinates of microearthquakes can be determined with errors of about first dozens of meters.It is thus possible to precisely detect boundaries of the areas wherein active deformation processes occur and to reveal spatial patterns of seismic event localization.In our analyses, data from the most comprehensive seismic catalog were used. …”
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Advancement in public health through machine learning: a narrative review of opportunities and ethical considerations by Sumit Singh Dhanda, Deepak Panwar, Chia-Chen Lin, Tarun Kumar Sharma, Deependra Rastogi, Shantanu Bindewari, Anand Singh, Yung-Hui Li, Neha Agarwal, Saurabh Agarwal

“…Mental health prediction systems based on NLP and wearable data delivered up to 91% accuracy in stress and depression detection, while hospital resource forecasting models using deep learning minimized errors in predicting emergency admissions. …”
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Evaluation of climate indices related to water resources in Iran over the past 3 decades by Fatemeh Chaparinia, Mostafa Hadei, Kamyar Yaghmaeian, Mahdi Hadi, Kazem Naddafi

“…The GSOD data undergo extensive automated quality control processes to eliminate random errors and ensure data reliability. Long-term trends were analyzed using linear regression, and spatial patterns were identified using K-means and hierarchical clustering methods. …”
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Efficient Wheat Disease Identification Using Hybrid Swin-SHARP Vision Model by Waqar Khalid, Yazeed Alkharijah, Syed Muhammad Usman, Shehzad Khalid

“…The proposed model outperformed state-of-the-art existing models, including CNN-CGLCM-HSV-SVM, GhostNet V2, ResNet 50, MobileNet V2–VGG-16, CNN-CGL CM-HSV-SVM, and Swin Transformer by 4.8%, 1.76%, 1.2%, 13.6%, 4.8%, and 1.4% respectively, on the YELLOW-RUST-19 dataset. These findings concluded that the SVH model is a strong approach to accurately detect yellow rust disease and can be used in real time, particularly in resource-constrained agricultural settings.…”
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BoostPolyGlot: A Structured IR Generation-Based Fuzz Testing Framework for GCC Compiler Frontend by Hui Liu, Hanbin Guo, Peng Liu, Tongding Hou

“…When existing fuzz testing methods are applied to compiler testing, although they can detect common errors like lexical and syntax errors, there are issues such as insufficient pertinence in constructing the input corpus, limited support for structured Intermediate Representation (IR) node manipulation, and limited perfection of the mutation strategy. …”
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The Mediating Effect of Accounting Information Quality on the Relationship Between Workforce Education Level and Investment Efficiency by Ayat Naji Mahdi Al-Obaidi, Pari Chalaki, Mehdi Heidari

“…This enhancement involves reducing reporting errors, detecting and addressing irregularities, and increasing transparency in financial reporting. …”
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Passive surveillance of bat-borne viruses in Hungary by Miss Anna Szabó, Dr. Zsófia Lanszki, Dr. Gábor Kemenesi, Dr. Endre Sós, Miss Ágnes Nagy, Dr. Éva Szűts, Dr. Tamás Görföl

“…Complete genomes were de novo assembled and manually error corrected. Results: More than 200 bats were received in the frame of our program between 2018 and 2023. …”
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Evaluating key predictors of breast cancer through survival: a comparison of AFT frailty models with LASSO, ridge, and elastic net regularization by Senyefia Bosson-Amedenu, Emmanuel Ayitey, Francis Ayiah-Mensah, Luyton Asare

“…Model performance was evaluated using Akaike Information Criterion (AIC), Bayesian Information Criterion (BIC), Mean Absolute Error (MAE), and Mean Squared Error (MSE) metrics across three sample sizes (25%, 50%, and 75%). …”
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Brief Communication: Maternal Plasma Autoantibodies Screening in Fetal Down Syndrome by Karol Charkiewicz, Monika Zbucka-Kretowska, Joanna Goscik, Slawomir Wolczynski, Adam Lemancewicz, Piotr Laudanski

“…The predictive value of the classifier (specificity and sensitivity) is 100%, classification errors, 0%, cross-validation errors, 0%. Conclusion. …”
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Intra‐ and inter‐session reliability and repeatability of 1H magnetic resonance spectroscopy for determining total creatine concentrations in multiple brain regions by Jedd Pratt, James McStravick, Aneurin J. Kennerley, Craig Sale

“…We provide new minimum detectable change data for tCr concentrations, a detailed discussion of the inherent error sources in repeated 1H MRS, including the substantial effect of the analysis package on tCr quantification, and suggestions for how these should be managed to improve the interpretability and clinical value of future research. …”
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Advancing Perimeter Security: Integrating DAS and CNN for Object Classification in Fiber Vicinity by Adrian Tomasov, Pavel Zaviska, Petr Dejdar, Ondrej Klicnik, Francesco da Ros, Tomas Horvath, Petr Munster

“…The system successfully differentiates events such as vehicle movement, fence manipulation, and construction work, while anomaly detection capabilities further enhance security by identifying irregular activities with minimal error. …”
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Deep Learning Models and Fusion Classification Technique for Accurate Diagnosis of Retinopathy of Prematurity in Preterm Newborn by Nazar Salih, Mohamed Ksantini, Nebras Hussein, Donia Ben Halima, ali Abdul Razzaq, Sohaib Ahmed

“…This shows that the proposed method helps identify ROP in premature infants. The study's findings imply the proposed method has the potential to significantly enhance the precision and speed with which ROP is diagnosed, which in turn could lead to earlier detection and treatment of the illness and a decreased likelihood of childhood blindness. …”
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Comment on Krüger, L. Decreasing Trends of Chinstrap Penguin Breeding Colonies in a Region of Major and Ongoing Rapid Environmental Changes Suggest Population Level Vulnerability.... by W. Chris Oosthuizen, Murray Christian, Mzabalazo Ngwenya

“…Chinstrap penguin population trends are an important research topic, but we caution that Krüger (2023)’s statistical analyses (intended to form the foundation for drawing valid, evidence-based inferences from sparse data) contain fundamental errors that invalidate that paper’s findings. We discuss oversights in several key steps (data processing, exploratory data analysis, model fitting, model evaluation, and prediction) of that paper’s analysis to help others detect and avoid some of the pitfalls associated with estimating population trends via mixed models. …”
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Integrating experimental and theoretical investigations of porous graphite materials with scanning electron microscope image processing by Muhammad Punhal Sahto, Wang Wei, Muhammad Fawad Jamil, Awais Mehmood, Mariyam Sattar, Asif Raza, Mujib Ur Rahman, Mumtaz A. Qaisrani

“…A dual-path X-ray imaging detection system was used for experimental validation. …”
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Cybersecurity in Connected and Autonomous Vehicles: A Systematic Review of Automotive Security by Rafael Abreu, Frederico Branco, Manuel J. Cabral S. Reis, Carlos Serodio

“…Providing awareness and training is also essential to mitigate human error. These findings are a foundation for designing more resilient and secure Connected and Autonomous Vehicles systems.…”
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