Designing a Dynamic Model for Evaluating Construction Investment Projects A System Dynamics Approach by Majid Moatamedi, Mohammad Hossein Darvish Motevlli

“…The basic analytical method in this research is simulation using system dynamics methodology. …”
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Feasibility, Advantages, and Limitations of Machine Learning for Identifying Spilled Oil in Offshore Conditions by Seong-Il Kang, Cheol Huh, Choong-Ki Kim, Meang-Ik Cho, Hyuek-Jin Choi

“…Traditional chemical methods in oil fingerprinting have limitations in terms of both time and cost. …”
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Maintenance of the Results of Stage II Lower Limb Lymphedema Treatment after Normalization of Leg Size by Jose Maria Pereira de Godoy, Henrique Jose Pereira de Godoy, Renata Lopes Pinto, Fernando Nestor Facio, Maria de Fatima Guerreiro Godoy

“…The aim of this study was to identify strategies to transfer responsibility of the maintenance of the results of lymphedema treatment to the patient. Methods. Maintenance of the reduction of edema was evaluated in a prospective clinical trial in patients with Stage II leg lymphedema. …”
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Immunological aspects of the lethal HIV / COVID-19 coinfected cohort by A. I. Mazus, E. V. Tsyganova, A. S. Zhilenkova, N. V. Glukhoedova, M. D. Geyne, Yu. A. Anikina, Yu. G. Parkhomenko, N. V. Mozgaleva, P. A. Vedyapin, O. A. Tishkevich

“…Statistical data processing was provided by SPSS 17 version (allowable error E = 5 %).   Results and discussion. The study demonstrated CD4+ and CD8+ reduction in HIV-infected with COVID-19. …”
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The Automatable Activity–Based Approach to Complexity Unit Scoring as a task-specific model approach to monetizing outcomes of pathology artificial intelligence solutions by Stavros Pantelakos, Martha Nifora, Georgios Agrogiannis

“…Previous studies have attempted to extrapolate cost containment in conjunction with the implementation of digital pathology solutions mostly on the basis of operational cost savings or diagnostic error reduction. However, no study has attempted to link a wider spectrum of potential diagnostic tasks performed by artificial intelligence algorithms to financial figures. …”
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Energy efficient design and implementation of approximate adder for image processing applications by Naik Jatothu Brahmaiah, Kumar Kanagala Sateesh, Krishnaiah Kondragunta Rama, Koteswararao Seelam

“…Approximate computing is a new technique that promises to speed up computations while preserving a level of precision suitable for error-tolerant systems such as neural networks and graphics. …”
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Design and testing of a RealSense-based variable spraying control system for field kale by Yahui Luo, Wen Li, Pin Jiang, Kaiwen Tang, Zhiluo Liang, Yixin Shi

“…Precision PWM variable spray technology and target detection, identification, and localization technology are key to solving the pesticide waste associated with traditional constant application methods and to improving pesticide utilization for achieving precise application. …”
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The effect of Wrestling+ warm-up program on balance and proprioception of adolescent wrestlers by Saleh Esmailnezhad, Hasan Daneshmandi, Nader Samami, Bahman Mirzaei

“…Additionally, there was a significant reduction in proprioception errors during knee movements (p < 0.001). …”
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Context-Aware Multimodal Fusion with Sensor-Augmented Cross-Modal Learning: The BLAF Architecture for Robust Chinese Homophone Disambiguation in Dynamic Environments by Yu Sun, Yihang Qin, Wenhao Chen, Xuan Li, Chunlian Li

“…Furthermore, the sensor-augmented module significantly improves robustness under noise (speech SNR to 18.6 dB at 75 dB noise, 12.7% reduction in word error rates). By bridging gaps among tonal phonetics, contextual semantics, and computational efficiency, BLAF establishes a scalable paradigm for robust Chinese homophone disambiguation in industrial NLP applications. …”
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Cost Effectiveness Analysis of Eribulin Mesylate as a Treatment for Metastatic Breast Cancer in Spain: Management in the Later Line of Therapy by Gabriel Tremblay, Unnati Majethia, Ilias Kontoudis, Jesús De Rosendo

“…This difference may fall within the margin of error for the model and could potentially be addressed by a minor reduction in the eribulin price.…”
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An ensemble-driven machine learning framework for enhanced water quality classification by Preet Singh, Taniya Hasija, Salil Bharany, Hafiza Nazra Tun Naeem, B. Chinna Rao, Seada Hussen, Ateeq Ur Rehman

“…The soft voting ensemble model, therefore, shows a relative improvement of 1.46% in accuracy over the best-performing base learner and a 27.8% reduction in its error rate. It is, therefore, confirmed that ensemble learning soft voting improves the reliability of water quality classification as well as accuracy, thus providing a strong platform for future environmental monitoring systems.…”
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The impact of study size on meta-analyses: examination of underpowered studies in Cochrane reviews. by Rebecca M Turner, Sheila M Bird, Julian P T Higgins

“…We examine the distribution of power available in studies within meta-analyses published in Cochrane reviews, and investigate the impact of underpowered studies on meta-analysis results.<h4>Methods and findings</h4>For 14,886 meta-analyses of binary outcomes from 1,991 Cochrane reviews, we calculated power per study within each meta-analysis. …”
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Simulation Study on the Accuracy of Modified Distributed Beamforming in Phased Array Weather Radars for Various Precipitation Events by Steffy Benny, Swaroop Sahoo, S. Athira, V. Chandrasekar

“…The modified DB technique radar variables have been found to have error less than 5 dBZ for reflectivity, 1 dB for differential reflectivity and 0.08 for correlation coefficient. …”
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Optimization and predictive performance of fly ash-based sustainable concrete using integrated multitask deep learning framework with interpretable machine learning techniques by Bhupesh P. Nandurkar, Jayant M. Raut, Pawan K. Hinge, Boskey V. Bahoria, Tejas R. Patil, Sachin Upadhye, Vikrant S. Vairagade, Sagar D. Shelare

“…Abstract Concrete strength prediction is of great relevance for construction safety and quality assurance; however, these methods often trade-off their accuracy or interpretability, especially when it comes to the use of supplementary cementitious materials like fly ash in process. …”
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Human-machine interaction in mechanical systems through sensor enabled wearable augmented reality interfaces by K. Balamurugan, G. Sudhakar, Kavin Francis Xavier, N. Bharathiraja, Gaganpreet Kaur

“…The proposed setup demonstrated an enhanced industrial performance in a simulated environment through error reduction by 22.3 % along with a 31.1 % increase in task speed and a 27.8 % improvement in situational awareness recorded through NASA-TLX cognitive load evaluations. …”
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Microstate Dynamics in Working Memory: Exploring Spatial Information Coding of Stimulus and Behavioral Performance by Hamideh Norouzi, Mohammad Reza Daliri

“…Saccade error was used as a behavioral index of WM performance. …”
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Machine Learning Techniques for Predicting Typhoon‐Induced Storm Surge Using a Hybrid Wind Field by Changyu Su, Bishnupriya Sahoo, Miaohua Mao, Meng Xia

“…ML is trained to overcome the residual error of the FVCOM, effectively reducing the inherent uncertainty of traditional methods. …”
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Enhanced Spatiotemporal Landslide Displacement Prediction Using Dynamic Graph-Optimized GNSS Monitoring by Jiangfeng Li, Jiahao Qin, Kaimin Kang, Mingzhi Liang, Kunpeng Liu, Xiaohua Ding

“…The DCRNN-proposed model achieved the highest accuracy among eight competing models, recording a Root Mean Square Error (RMSE) of 2.773 mm in the Vertical direction, a 39.1% reduction compared to its baseline. …”
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Effects of aerobic training on brachial artery flow-mediated dilation in healthy adults: a meta-analysis of inter-individual response differences in randomized controlled trials by Armin H. Paravlic, Kristina Drole

“…The standard deviation of change scores in the intervention and control groups suggests that most of the variation in the observed change from pre-to-post intervention is due to other factors (e.g., measurement error, biological variability etc.) unrelated to the intervention itself. …”
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GMTP: Enhanced Travel Time Prediction with Graph Attention Network and BERT Integration by Ting Liu, Yuan Liu

“…Additionally, two self-supervised tasks are designed for improved model accuracy and robustness. (3) Results: The fine-tuned model had comparatively optimal performance metrics with significant reductions in Mean Absolute Error (MAE), Mean Absolute Percentage Error (MAPE), and Root Mean Squared Error (RMSE). (4) Conclusions: Ultimately, the integration of this model into travel time prediction, based on two large-scale real-world trajectory datasets, demonstrates enhanced performance and computational efficiency.…”
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