Increase the effectiveness of radar detection systems by adapting to the spatial orientation of the object of observation by S. N. Yarmolik, M. V. Svinarskiy, A. S. Khramenkov, E. V. Zaiko

“…An important aspect of creation of effective recognition systems is the adaptation of radiolocation portraits to the corners of the spatial orientation of the observed object. …”
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A Broad Range Triboelectric Stiffness Sensor for Variable Inclusions Recognition by Ziyi Zhao, Zhentan Quan, Huaze Tang, Qinghao Xu, Hongfa Zhao, Zihan Wang, Ziwu Song, Shoujie Li, Ishara Dharmasena, Changsheng Wu, Wenbo Ding

“…The proposed sensor system can identify the multi-layer stiffness structure of objects, enabling effective recognition of variable inclusions in soft objects with an accuracy of 99.7%.…”
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Reframing Recognition in Organizations by Matthew Sowcik, Hannah Carter, Valerie McKee

“…Although research has pointed to the numerous benifits associated with recognition programs, many organizations still struggle to create and deliver effective recognition programs. Many of these programs fail due to the lack of structure enabling employees to recognize each other, difficulty selecting individuals to recognize, lack of clarity concerning program objectives, and company cultures that do not support recognition. …”
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Reframing Recognition in Organizations by Matthew Sowcik, Hannah Carter, Valerie McKee

“…Although research has pointed to the numerous benifits associated with recognition programs, many organizations still struggle to create and deliver effective recognition programs. Many of these programs fail due to the lack of structure enabling employees to recognize each other, difficulty selecting individuals to recognize, lack of clarity concerning program objectives, and company cultures that do not support recognition. …”
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Recognition of Process Disturbances for an SPC/EPC Stochastic System Using Support Vector Machine and Artificial Neural Network Approaches by Yuehjen E. Shao

“…However, because EPC compensates for the effects of underlying disturbances, the disturbance patterns are embedded and hard to be recognized. Effective recognition of disturbance patterns is a very important issue for process improvement since disturbance patterns would be associated with certain assignable causes which affect the process. …”
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A Smart Textile-Based Tactile Sensing System for Multi-Channel Sign Language Recognition by Keran Chen, Longnan Li, Qinyao Peng, Mengyuan He, Liyun Ma, Xinxin Li, Zhenyu Lu

“…Experimental results show effective recognition of complex gestures, highlighting the system’s potential for broader applications in human-computer interaction.…”
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Research on Degradation State Recognition of Planetary Gear Based on Multiscale Information Dimension of SSD and CNN by Xihui Chen, Liping Peng, Gang Cheng, Chengming Luo

“…Finally, CNN is used to achieve the effective recognition of the degradation state of planetary gear. …”
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Bayesian-optimized stacking ensemble with multimodal feature selection for tobacco leaf maturity classification by Yunpeng Lu, Yang Wu, Lu Zhang, Jinguo Huang, Guangwei Sun, Jing Liu

“…However, the subtle changes in color, shape, and texture of tobacco leaf images at various maturity levels are one of the main challenges for effective recognition. In this study, we preprocess tobacco leaf images and extract features including color, shape, and texture, collectively forming a multimodal feature set. …”
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Aircraft Skin Damage Visual Testing System Using Lightweight Devices with YOLO: An Automated Real-Time Material Evaluation System by Kuo-Chien Liao, Jirayu Lau, Muhamad Hidayat

“…The experimental results confirmed the effective recognition of defects with the mean average precision (mAP@0.5) at 0.853 for YOLOv9c for all classes. …”
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Analysis and training of a traffic sign recognition neural network model by A. U. Mentsiev, T. G. Aigumov, E. M. Abdulmukminova

“…The purpose of the research is to develop and train a neural network model based on convolutional neural networks for effective recognition of road signs in images.Method. Deep learning methods were used, namely convolutional neural networks, which allow you to automatically extract image characteristics and train on a large data set. …”
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Construction and value of a vestibular function calibration test recognition model based on dual-stream ViT and ConvNeXt architecture by Xu LUO, Peixia WU, Weiming HAO, Yinhong QU, Han CHEN

“…ObjectiveTo improve the efficiency and accuracy of videonystagmography calibration test results while enabling effective recognition of saccadic undershoot waveform by developing a dual-stream architecture-based deep learning model. …”
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Mechanisms for implementing the principles of social dialogue in the activities of the International Labour Organization by Yu. D. Dreval

“…It is emphasised that the right to freedom of association and effective recognition of the right to collective bargaining play a dual role (both as a fundamental human right in the field of labour and as an important component of social and political processes). …”
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Emotion Recognition from Speech in a Subject-Independent Approach by Andrzej Majkowski, Marcin Kołodziej

“…The research findings indicated that the effective recognition of a broad spectrum of emotions in a subject-independent approach is limited. …”
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Impact of the Radar Image Resolution of Military Objects on the Accuracy of their Classification by a Deep Convolutional Neural Network by I. F. Kupryashkin

“…It is shown that the use of pretrained MobileNetV1 and Xception networks does not lead to an improvement in the classification accuracy compared to a simple VGG-type network.Conclusion. Effective recognition of military objects at a resolution worse than one meter is practically impossible. …”
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Sound quality impacts dogs’ ability to recognize and respond to playback words by Fumi Higaki, Tamás Faragó, Ákos Pogány, Ádám Miklósi, Claudia Fugazza

“…Our findings show that the level of sound degradation significantly affects dogs’ recognition of recorded speech and suggest that current commercially available AIC devices are not recommended for testing effective recognition of the recorded words.…”
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A New Efficient Hybrid Technique for Human Action Recognition Using 2D Conv-RBM and LSTM with Optimized Frame Selection by Majid Joudaki, Mehdi Imani, Hamid R. Arabnia

“…These features are subsequently processed by the LSTM to capture temporal dependencies across frames, enabling effective recognition of both short- and long-term action patterns. …”
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Efficient Recognition of the Propagated Orbital Angular Momentum Modes in Turbulences With the Convolutional Neural Network by Zikun Wang, Maxime Irene Dedo, Kai Guo, Keya Zhou, Fei Shen, Yongxuan Sun, Shutian Liu, Zhongyi Guo

“…Generally, atmospheric turbulence can distort the helical phase fronts of OAM beams, which presents a critical challenge to the effective recognition of OAM modes. Recently, convolutional neural network (CNN), as a model of deep learning, has been widely applied to machine vision. …”
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Multi-Feature Fusion for Enhanced Feature Representation in Automatic Modulation Recognition by Jiuxiao Cao, Rui Zhu, Lingfeng Wu, Jun Wang, Guohao Shi, Peng Chu, Kang Zhao

“…Testing with real-world signals collected under realistic channel conditions using USRP devices further confirms the model’s superior performance, achieving an effective recognition rate of 99.27% when the two USRP devices are in close proximity. …”
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Analysis of possible markers of effective antitumor cellular immune response before starting therapy with immune check-point inhibitors by A. M. Malkova, R. V. Orlova, N. V. Zhukova, A. R. Gubal, V. V. Sharoiko

“…The aim of the study. to analyse possible markers of an effective antitumor cellular immune response.Material and methods. using the keywords «checkpoint inhibitors, immunotherapy, t-lymphocytes, exhausted t-lymphocytes, anti-tumor immune response», review and original articles (n=34) published from 2005 to 2020 in the Pubmed, Web Of Science, Elsevier databases were selected.Results. the study revealed possible markers reflecting a high activity of an adaptive immune response based on effective recognition of tumor antigens through MHC molecules, a sufficient number of T-lymphocytes and a predominance of T-cytotoxic cells, as well as a low level of expression of inhibitory receptors and small molecules. the presence of single nucleotide polymorphisms in the HLA-I and HLA-II genes encoding MHC-I and MHC-II proteins, respectively, a high level of lymphocytes, among which the most important is the predominance of CD8+ t cells and a low level of T-regulatory cells (T-reg), as well as the presence of single nucleotide polymorphisms in the genes encoding FcγR receptors of T-lymphocytes showed their predictive significance. the diagnostic significance of determining the expression of inhibitory receptors for T-lymphocytes (TIM3, LAG3, TIGIT), especially in combination with the determination of PD-1 expression, was also revealed.Conclusion. the results obtained may be relevant for applying new methods for the assessment of the functional activity of the T-cell immune response before starting therapy with checkpoint inhibitors, as well as for the development of new diagnostic panels, which may be of interest to employees of clinical diagnostic laboratories and research centers.…”
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IRF2BP2 binds to a conserved RxSVI motif of protein partners and regulates megakaryocytic differentiation by Guanchao Wang, Tiantian Lu, Lei Zhang, Jianping Ding

“…The motif-containing peptides tend to form a short loop along with a short β-strand, which facilitates effective recognition and tight binding by the RING domain. …”
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