Shoreline evolution in adjacent to a coastal structure in Hiep Thanh commune, Duyen Hai district, Tra Vinh province by Van Duy Dinh, Thanh Tran, Dat Pham, Do Nhut An Lieu, Van Ty Tran

“…However, this solution exacerbates the issue since the fundamental processes of coastal erosion remain inadequately explored and understood. …”
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Shoreline evolution in adjacent to a coastal structure in Hiep Thanh commune, Duyen Hai district, Tra Vinh province by Van Duy Dinh, Thanh Tran, Dat Pham, Do Nhut An Lieu, Van Ty Tran

“…However, this solution exacerbates the issue since the fundamental processes of coastal erosion remain inadequately explored and understood. …”
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Crafting an effective questionnaire: An essential prerequisite of engaging surveys by Hunny Sharma, Manisha Ruikar

“…By understanding the art of engaging surveys, researchers can optimize their data collection processes and enhance the reliability and validity of their findings.…”
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A Vine-Copula Method for Outlier Identification in Photovoltaic Arrays by Haitao Li, Weiqiong Song, Le Zhao, Shuai Guo, Wei Song, Li Huang

“…After refining the current data, a similar approach is taken to address voltage irregularities. …”
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YOLOv8 and point cloud fusion for enhanced road pothole detection and quantification by Junkui Zhong, Deyi Kong, Yuliang Wei, Bin Pan

“…The experiments were conducted over a 4.7-kilometer road section, demonstrating that on well-maintained road surfaces, the proposed method improves detection accuracy by $$6.5\%$$ compared to the standalone use of YOLOv8, achieving a precision of $$95.8\%$$ , a recall of $$93.3\%$$ , and an F1 score of $$94.53\%$$ . The model processes a single image in 0.23 seconds. Furthermore, the error rates for perimeter, surface area, and depth detection are limited to within $$4\%$$ , $$5\%$$ , and $$4\%$$ , respectively.…”
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Decoding public sentiment topics in google map reviews on urban infrastructure development of belt and road initiative by Yue Xiong, Jiayong Liang, Chenghe Guan

“…Moreover, higher urban growth rates at country level correlate with more positive sentiments and a greater focus on development. …”
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One-way Video Transmission Technology for Urban Rail Transit Based on EndpointDevices by ZHANG Lidong, XU Ziheng, WANG Kun

“…[Result & Conclusion] Compared with conventional UDP (user datagram protocol) transmission methods, the proposed one-way video transmission scheme demonstrates more stable data transfer rates and lower latency, meeting the real-time transmission requirements of urban rail transit services. …”
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Reducing Defense Vulnerabilities in Federated Learning: A Neuron-Centric Approach by Eda Sena Erdol, Hakan Erdol, Beste Ustubioglu, Guzin Ulutas, Iraklis Symeonidis

“…Despite its advantages, this distributed structure is vulnerable to attacks as end users keep their data and training process private. Current defense mechanisms often fail when facing different attack types or high percentages of malicious participants. …”
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Linking Satellite and Ground Observations of NO₂ in Spanish Cities: Influence of Meteorology and O₃ by Carlos Morillas, Sergio Álvarez, José C. M. Pires, Adrián Jesús García, Sara Martínez

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Health information system in primary health care units of the Central Zone, Tigray, Northern Ethiopia by Letekirstos Gebreegziabher Gebretsadik, Abate Bekele Belachew, Gebregziabher Berihu Gebrekidan, Alemayohu Bayray, Akberet Lemlem, Lewtnesh Berihun Dangew, Haftom Temesgen Abebe

“…The average lot quality assurance sampling accuracy rates are below the acceptable level, indicating issues in the data documentation and validation processes. …”
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Development experience of information system for ranking of academic and pedagogical staff by A. A. Chernousov, E. V. Vavilova

“…Implementation of rating system in Plekhanov Russian University of Economics proved the flexibility of the proposed approach, reduction of labor costs for data processing, full transparency of calculations, and, as a consequence, reduction of questions from the rated academic and pedagogical staff. …”
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Design of an improved graph-based model for real-time anomaly detection in healthcare using hybrid CNN-LSTM and federated learning by G Muni Nagamani, Chanumolu Kiran Kumar

“…Real-time monitoring and anomaly detection are essential in healthcare to ensure safe conditions for patients and maintain the integrity of medical data samples. The majority of existing systems, despite improvements in healthcare technologies, cannot capture the spatial and temporal patterns of multimodal data simultaneously, process high Volume data in real-time, and ensure the privacy of patients' identity effectively. …”
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Discrete wavelet integrated convolutional residual network for bearing fault diagnosis under noise and variable operating conditions by Yunfeng Ni, Shuang Li, Ping Guo

“…Traditional methods for diagnosing bearing faults under noisy conditions often rely on complex data preprocessing and struggle to maintain accuracy in high-noise environments. …”
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Diagnosis of winter precipitation types using the spectral bin model (version 1DSBM-19M): comparison of five methods using ICE-POP 2018 field experiment data by W. Bang, J. T. Carlin, K. Kim, A. V. Ryzhkov, A. V. Ryzhkov, G. Liu, G. Lee

“…We compare the performance of the SBM and four other diagnostic methods that use the following variables: (1) atmospheric thickness, (2) wet-bulb temperature, (3) temperature and relative humidity, and (4) wet-bulb temperature and low-level lapse rate. Three reference WPTs (snow (SN), rain (RA), and RASN) are obtained from particle size velocity (PARSIVEL) disdrometer data using a newly proposed decision tree algorithm. …”
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The Role of Insulin Within the Socio-Psycho-Biological Framework in Type 2 Diabetes—A Perspective from Psychoneuroimmunology by Anne Wevers, Silvia San Roman-Mata, Santiago Navarro-Ledesma, Leo Pruimboom

“…This study proposes a theory that expands insulin’s role beyond traditional metabolic functions, incorporating it into the Mitochondrial Information Processing System (MIPS) and exploring it from an evolutionary medicine perspective to explore its function in processing psychological and social factors into biological responses. …”
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Statistical Analysis Method for Optimal Prameters of Telemetry Communication by XIE Jun, WU Sailong, HAO Hang, ZHANG Songwei, WU Ruiqing, SUN Xiangyang

“…In addition, the proposed method completes a parameter optimization time of merely 0.08 seconds when processing 350 000 logging data points, demonstrating significant superiority over the existing optimization method based on machine learning and genetic algorithm. …”
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Machine Learning-Enabled Prediction and Optimization of Sulfur Recovery Units: A Step towards Industry 4.0 Integration by Imran Khan, Husnain Saghir, Muhammad Ahsan

“…An industrial sulfur recovery unit was simulated in Aspen HYSYS and validated using real-world industrial data. The simulation incorporated artificial uncertainties (±5%) in key process parameters, including acid gas flow rate, acid gas temperature, air flow rate, air temperature, and Claus reactor inlet temperature. …”
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Use of patient-centred outcome measures alongside the personal wheelchair budget process in NHS England: A mixed methods approach to exploring the staff and service user experience... by Lorna Tuersley, Naa Amua Quaye, Kalpa Pisavadia, Rhiannon Tudor Edwards, Nathan Bray

“…Three-quarters of users or their carers rated the use of the tools in the assessment process as 'helpful' or 'very helpful'. …”
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Analysis of the health status of patients with type 1 and type 2 diabetes mellitus living in urban and rural areas of the Saratov region (according to the data of the federal regis... by A. D. Ponomarev, G. Yu. Sazanova, M. A. Kunitsyna, L. M. Terina, A. A. Vojteshak

“…Mathematical, statistical and analytical research methods were used. Statistical data processing was carried out using the Microsoft Excel 2019 program. …”
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Abnormal traffic detection method based on LSTM and improved residual neural network optimization by Wengang MA, Yadong ZHANG, Jin GUO

“…Problems such as a difficulty in feature selection and poor generalization ability were prone to occur when traditional method was exploited to detect abnormal network traffic.Therefore, an abnormal traffic detection method based on the long short term memory network (LSTM) and improved residual neural network optimization was proposed.Firstly, the features and attributes of network traffic were analyzed, and the variability of the feature values was reduced by preprocessing of network traffic.Then, a three-layer stacked LSTM network was designed to extract network traffic features of different depths.Moreover, the problem of weak adaptability of feature extraction was solved.Finally, an improved residual neural network with skipping connecting line was designed to optimize the LSTM.The defects of deep neural network such as overfitting and gradient vanishing were optimized.The accuracy of abnormal traffic detection was improved.Experimental results show that the proposed method has higher training accuracy and better visibility of data processing.The classification accuracy rates under two classifications and multiple classifications are 92.3% and 89.3%.It has the lowest false positive rate when the parameters such as precision rate and recall rate are optimal.Moreover, it has strong robustness when the sample is destroyed.Furthermore, better generalization ability can be achieved.…”
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