Correct/Incorrect Analysis of Responses When Estimating the Cognitive Function of Spontaneous Language in the Elderly by Toshiharu Igarashi, Katsuya Iijima, Kunio Nitta, Yu Chen

“…” Furthermore, differences in question content had a substantial impact on the participants’ responses; for instance, questions related to ADL (activities of daily living) elicited more “socially acceptable responses,” whereas questions regarding orientation often resulted in “memory errors” or “lack of understanding.” These findings suggest that routine interaction with AI agents can potentially enable the early detection of cognitive decline in older adults, facilitating timely and appropriate interventions. …”
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An enhanced deep learning approach for speaker diarization using TitaNet, MarbelNet and time delay network by Muzamil Ahmed, Riad Alharbey, Ali Daud, Hikmat Ullah Khan, Javeria Nawal, Ghazia Arshad

“…We evaluate the proposed approach on two standard datasets of VoxConverse and VoxCeleb, comparing clustering-based methods with the proposed Neuro-TM Diarizer using three metrics: Diarization Error Rate (DER), false alarm rate, and missed detection rate. …”
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Quantitative Method for Ultrasonic Testing of Lead Seal Defects in High Voltage Cable Accessories by Zheng Hai, Cai Qiushen, Zheng Jishi, Zhen Zhiming, Zou Wei, Chen Jianping

“…By focusing on the longitudinal wave fan scan images of these defects and integrating threshold segmentation with corrosion algorithms, the method provides real-time information on defect characteristics, including cross-sectional area and height. The findings reveal significant improvements over the traditional −6dB method: a 5% reduction in distance error, a 10% enhancement in defect size accuracy, and an overall accuracy rate exceeding 85%. …”
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Exploring Grammatical Structure: A Corpus Analysis on the Use of “To Be” in Vocational Students’ WhatsApp Group Conversations using AntConc by Muhammad Arba’in, Itsna Millatul Himmayati, Dwi Hastuti, Desi Nosita, Triyoko Triyoko

“…The analysis involves employing a descriptive method from corpus linguistic research to understand sentence variations and detect common errors related to the usage of “to be”. …”
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Improving wind and power predictions via four-dimensional data assimilation in the WRF model: case study of storms in February 2022 at Belgian offshore wind farms by T. Ivanova, T. Ivanova, S. Porchetta, S. Porchetta, S. Buckingham, G. Glabeke, G. Glabeke, J. van Beeck, W. Munters

“…We focus on improving model output during storms impacting the Belgian–Dutch wind farm cluster located in the Southern Bight of the North Sea via the four-dimensional data assimilation (nudging) technique in the Weather Research and Forecasting (WRF) model. Our findings indicate that assimilating wind observations significantly reduces the relative root-mean-square error for wind speed at a wind farm located 47 km downwind from the offshore lidar platform. …”
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Development of RelaxQuest: A Serious EEG-Controlled Game Designed to Promote Relaxation and Self-Regulation with a Potential Focus on ADHD Intervention by Alan F. Pérez Vidal, José-Antonio Cervantes, Jesse Y. Rumbo-Morales, Felipe D. J. Sorcia-Vázquez, Gerardo Ortiz-Torres, Christian A. Castro Moncada, Ignacio de la Torre Arias

“…These include omission errors, commission errors, response times, standard deviations of response times, and other relevant variables. …”
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Limb Body Wall Complex: First Trimester Ultrasonographic Diagnosis of a Case with Exencephaly and Megacystis by Mert Turğal, Aslıhan Yazıcıoğlu, Özgür Özyüncü, M. Sinan Beksaç

“…Despite the anomaly arises from an error occuring during the embryonic folding, the exact pathophysiological mechanisms are poorly understood. …”
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Development and Study of Demodulators for Frequency Hopping Spread Spectrum Signals by D. I. Kaplun, V. V. Gulvanskiy, I. I. Kanatov, D. M. Klionskiy, A. B. Khachaturyan, D. N. Butusov, V. F. Lapizkiy, V. I. Bobrovskiy

“…This signal is stable to jamming (until the third side finds out the number sequence), which makes it possible to use it for special purposes (however, the signal still needs additional encryption).Demodulation includes signal detection, synchronization, message type determination (modulation speed and modulation type), decoding, determination of autostarting and autostop combinations (for message identification), composition of the received message. …”
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An Investigation of Interpolation Techniques to Generate 2D Intensity Image From LIDAR Data by Imran Ashraf, Soojung Hur, Yongwan Park

“…Light detection and ranging (LIDAR) has become a part and parcel of ongoing research in autonomous vehicles. …”
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Sensor-Based Gait Analysis: A Comparative Study of Ultrasonic and Laser Sensors for Gait Monitoring in Rollator-Assisted Walking by Ivan Omeko, Stefan Twieg, Martin Obert

“…The HC-SR04 demonstrated relatively low measurement error, with Root Mean Square Error (RMSE) values ranging from 0.64 cm to 0.89 cm but required a 5V power supply and additional voltage conversion components, complicating integration to single board computers (SBC). …”
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An eco-friendly chemometrics assisted UV spectrophotometric method for simultaneous determination of sofosbuvir, simeprevir and ledipasvir in pharmaceuticals by Adil Alshehri, Ali Alqahtani, Abdulrhman Alsayari, Ahmed A. Almrasy

“…SRACLS models demonstrated superior analytical performance with lower detection limits (0.5171, 0.5175, 0.2950 μg/mL), higher precision (relative bias corrected mean square error of prediction, RBCMSEP: 0.1481–0.2509%), and better predictive capability (relative root mean square error of prediction, RRMSEP: 1.0285%, 1.2668%, 1.8933%) compared to CRACLS models (RRMSEP: 3.0655%, 1.9264%, 2.7201%). …”
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Chemometric and computational modeling of polysaccharide coated drugs for colonic drug delivery by Ahmad Khaleel AlOmari, Khaled Almansour

“…Assessment metrics, such as the coefficient of determination (R²), root mean square error (RMSE), and mean absolute error (MAE), emphasize the MLP model’s exceptional performance. …”
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RESEARCH ON DEEP NEURAL NETWORK LEARNING BASED ON IMPROVED BP ALGORITHM by HUANG Pei

“…Deep learning can make the computing model that contains a number of processing layers to learn the data that contains many levels of abstract representation.This kind of learning way in the most advanced speech recognition,visual object recognition,object detection and many other areas,such as biology,genetics and medicine brought significant improvement.Deep learning can find the complex structure of large data,and the convolution neural network as one of the important models of the depth study in the processing of voice,image,video and text,and other aspects of a new breakthrough.It is the use of BP algorithm to guide the machine how to get the error before the layer to adjust the parameters of this layer,so that these parameters are more conducive to the calculation of the model.In view of the shortcomings of traditional BP algorithm,a fast BP algorithm is proposed,which has the disadvantages of slow convergence speed and often falls into local minimum points.The improved convolutional neural network is used to validate the data set MNIST,English character recognition and medical image.The simulation results show the effectiveness of the proposed algorithm.…”
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A literature survey of shapelet quality measures for time series classification by Teng Li, Xiaodong Guo, Cun Ji

“…With the rapid development of the Internet of Things, time series classification (TSC) has gained significant attention from researchers due to its applications in various real-world fields, including electroencephalogram/electrocardiogram classification, emotion recognition, and error message detection. To improve classification performance, numerous TSC methods have been proposed in recent years. …”
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Sub-ppb H₂S Sensing with Screen-Printed Porous ZnO/SnO₂ Nanocomposite by Mehdi Akbari-Saatlu, Masoumeh Heidari, Claes Mattsson, Renyun Zhang, Göran Thungström

“…The relative concentration error was carefully calculated based on analytical sensitivity, confirming the sensor’s precision in measuring gas concentrations. …”
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Advanced Hybrid Brain Tumor Segmentation in MRI: Elephant Herding Optimization Combined with Entropy-Guided Fuzzy Clustering by Baiju Karun, Arunprasath Thiyagarajan, Pallikonda Rajasekaran Murugan, Natarajan Jeyaprakash, Kottaimalai Ramaraj, Rakhee Makreri

“…By managing image noise and reducing computational demands, the EHO-EnFCM approach not only captures intricate tumor structures but also facilitates efficient image processing, making it suitable for real-time clinical applications. Overall, the findings reveal the potential of this hybrid approach to advance MRI-based tumor detection, offering a promising tool that enhances both accuracy and computational efficiency for medical imaging and diagnosis.…”
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Sensitive and selective electrochemical biosensor based on Manganese(II) complex for simultaneous determination of adenine and guanine from clinical samples and DNA extract samples by Melaku Metto, Alemu Tesfaye, Minaleshewa Atlabachew, Abayneh Munshea, Atakilt Abebe

“…The interference recovery results showcased an error rate of less than 6 %, highlighting the method's superior lower detection limit and broader dynamic range compared to existing techniques. …”
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Predictors for estimating subcortical EEG responses to continuous speech. by Joshua P Kulasingham, Florine L Bachmann, Kasper Eskelund, Martin Enqvist, Hamish Innes-Brown, Emina Alickovic

“…Recently, subcortical responses to more ecologically relevant continuous speech were detected using linear encoding models. These methods estimate the temporal response function (TRF), which is a regression model that minimises the error between the measured neural signal and a predictor derived from the stimulus. …”
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The role of artificial intelligence in breast cancer screening as a supportive tool for radiologists by Agata Król, Katarzyna Kwaterska, Karol Kutyłowski, Paweł Łuckiewicz

“…Difficulties, possible errors and people’s opinion were also highlighted. …”
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Optimization Algorithm of Neural Network Structure Based on Adaptive Genetic Algorithm by XILiang, WANGRui dong

“…The experiment show that the algorithm for traditional neural network algorithm for function fitting better test; on breast_cancer dataset, the accuracy is 97 57% and the detect errors is 2 07%,better than the classical machine learning algorithms…”
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