Intelligent Hybrid Control Strategy for Trajectory Tracking of Robot Manipulators by Yi Zuo, Yaonan Wang, Lihong Huang, Chunsheng Li

“…We address the problem of robust tracking control using a PD-plus-feedforward controller and an intelligent adaptive robust compensator for a rigid robotic manipulator with uncertain dynamics and external disturbances. …”
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Urgent Measures at a Prehospital Stage in Battle Trauma by T. V. Smelaya, V. Ye. Nikitayev

“…Specialized medical teams are formed to solve this problem.…”
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Facial Emotion Images Recognition Based On Binarized Genetic Algorithm-Random Forest by Murad Ibrahim Husin Alzawali, Yusliza Yusoff, Razana Alwee, Zuriahati Mohd Yunos, Mohamad Shukor Talib, Haswadi Hassan, Fahad Taha AL-Dhief, Musatafa Abbas Abbood Albadr, Majid Razaq Mohamed Alsemawi, Sharifah Zarith Rahmah Syed Ahmad

“…Moreover, the most common problem that must be resolved in face emotion recognition systems is the feature extraction methods, which is comparable to traditional manual feature extraction methods. …”
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Indicators for the Compression and Stretching Characteristics of the HTF-Coordinate of WRF by Hailiang Zhang, Huoqing Li, Shuiyong Fan

“…The HTF-coordinate is a feature that has been imported into the Weather Research and Forecasting (WRF) model version 4, and it is important to understand how it can be used efficiently. …”
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Chinese Named Entity Recognition Method Based on Bidirectional LSTMCNNCRF by LIU Yu-peng, LI Dong-dong

“…Traditional algorithms of named entity recognition rely on a large number of artificial features and external knowledge To solve this problem, we propose a novel neural network structure which combines the bidirectional LSTM(Long ShortTerm Memory), CNN(Convolution Neural Network) and CRF(Conditional Random Field) This algorithm can also automatically get both characterlevel and wordlevel representations It is a truly endtoend system, requiring no feature engineering and data processing Thus, it can be easily applied to various fields of named entity recognition task Finally, the experimental results show that the F1 measure of the algorithm in the medical and news field is 9097% and 9219%, respectively …”
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Automated Reconstruction of Parametric BIM for Bridge Based on Terrestrial Laser Scanning Data by Guocheng Qin, Yin Zhou, Kaixin Hu, Daguang Han, Chunli Ying

“…However, these solutions still encounter problems, such as the inability to obtain the actual geometric features of a bridge quickly and accurately. …”
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The impact of chronic herpes virus infection on the bone system in children by M. A. Telesh, N. Yu. Krutikova, V. V. Sokolovskaya

“…Herpes virus infections currently are urgent problem in infectology, pediatrics and therapy. The feature of these diseases is the possibility of direct and indirect effects of the virus on various organs and systems: immune, nervous, endocrine, bone, in children in particular. …”
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Atlantic Multidecadal Variability in a model with an improved North Atlantic Current by Annika Drews, Richard J. Greatbatch

“…We also argue that changing ocean heat transport is an essential feature of our results.…”
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FAULT DIAGNOSIS OF SCRAPER CONVEYOR REDUCER BASED ON IMPROVED FIREFLY ALGORITHM TO OPTIMIZE NEURAL NETWORK by MAO Jun, GUO Hao, CHEN HongYue

“…The second application feature data sample for fault diagnosis model based on neural network training. …”
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Multi-factor person entity relation extraction model based on distant supervision by Yangchen HUANG, Yan JIA, Liang GAN, Jing XU, Jiuming HUANG, Zhonghe HE

“…Aiming at the problem that the basic assumption of distant supervision was too strong and easy to produce noise data,a model of the person entity relation extraction which could automatically filter the training data generated by distant supervision was proposed.For training data generation,the data produced by distant supervision would be filtered by multiple instance learning and the method of TF-IDF-based relation keyword detecting,which tried to make the training data has the manual annotation quality.Furthermore,the model combined lexical and syntactic features to extract the effective relation feature vector from two angles of words and semantics for classifier.The experiment results on large scale real-world datasets show that the proposed model outperforms other relation extraction methods which based on distant supervision.…”
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Fuzzy Volterra Integral Equations with Piecewise Continuous Kernels: Theory and Numerical Solution by S. Noeiaghdam, D.N. Sidorov, A.I. Dreglya

“…This research focuses on addressing both linear and nonlinear fuzzy Volterra integral equations that feature piecewise continuous kernels. The problem is tackled using the method of successive approximations. …”
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Efficient DDoS attack detection and prevention scheme based on SDN in cloud environment by Heng HE, Yan HU, Lianghan ZHENG, Zhengyuan XUE

“…For addressing the problem of two typical types of distributed denial of service (DDoS) attacks in cloud environment,a DDoS attack detection and prevention scheme called SDCC based on software defined network (SDN) architecture was proposed.SDCC used a combination of bandwidth detection and data flow detection,utilized confidence-based filtering (CBF) method to calculate the CBF score of packets,judged the packet of CBF score below the threshold as an attacking packet,added its attribute information to the attack flow feature library,and sent the flow table to intercept it through SDN controller.Simulation results show that SDCC can detect and prevent different types of DDoS attacks effectively,and it has high detection efficiency,reduces the controller’s computation overhead,and achieves a low false positive rate.…”
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Application of Optimization Parameters VMD and MED in Fault Diagnosis of Train Gearbox Rolling Bearings by Changqing LI, Jianhui LIN, Yongxu HU

“…Aiming at the problem of feature extraction of train gearbox rolling bearing’s incipient fault in the case of strong noise, a method of fault diagnosis based on minimum entropy deconvolution (MED) and parameter optimized variational mode decomposition (VMD) was proposed. …”
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Video description method based on multidimensional and multimodal information by Enjie DING, Zhongyu LIU, Yafeng LIU, Wanli YU

“…In order to solve the problem of complex information representation in automatic video description tasks,a multi-dimensional and multi-modal visual feature extraction and fusion method was proposed.Firstly,multi-dimensional features such as static and dynamic attributes of the video sequence were extracted by transfer learning,and the image description algorithm was also used to extract the semantic information of the key frames in the video.By doing this,the video features extraction was carried out.Then,multi-layer long and short memory networks were used to fuse multi-dimensional and multi-modal information,and finally generated a language description of the video content.Compared with the existing methods,experimental simulations results show that the proposed method achieves better results in the video automatic description task.…”
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THE USE OF PARABOLIC SPLINEES IN CAD OF LINEAR STRUCTURES by V. I. Struchenkov

“…The unknown extremal is a parabolic spline, that is, a plane curve, the elements of which are parabolas of the second order conjugated by line segments. The principal feature of the problem is that the number of spline elements is unknown. …”
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Multiscale transformers and multi-attention mechanism networks for pathological nuclei segmentation by Yongzhao Du, Xin Chen, Yuqing Fu

“…To solve the problem that the high density of cell nuclei and the complexity of the background make it difficult to extract features, a dense attention module is embedded in the encoder, which improves the learning of the target cell information to minimize target information loss; Additionally, to solve the problem of poor segmentation accuracy due to the blurred cell boundaries, the Multi-scale Transformer Attention module is embedded between encoder and decoder, improving the transfer of the boundary feature information and makes the segmented cell boundaries more accurate. …”
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Global Exponential Stability of Both Continuous-Time and Discrete-Time Switched Positive Time-Varying Delay Systems with Interval Uncertainties and All Unstable Subsystems by Thanasak Mouktonglang, Suriyon Yimnet

“…A distinctive feature of this research is that all subsystems are considered to be unstable. …”
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Stakeholder cooperation in implementation of the sustainable development concept: Montenegrin tourist destinations by Ljiljana Pjerotic

“…Tourism destination planning is a complex process, due to the existence of a wide variety of stakeholders with a wide range of opinions, multiple problem visions and different interests. Despite the complexity of the planning process one feature acknowledged for successful destination management planning is high level of stakeholder cooperation. …”
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استخدام تمرينات باستخدام صناديق القفز بارتفاعات مختلفه في تطوير بعض القدرات البدنيه والحركيه وانجاز 100م حواجز للطالبات... by انتصار مزهر صدام

“…And should the individual Ttoiralkablaat to perform each event to the development capabilities physical and kinetic force it and the speed, flexibility and agility using different elevations boxes and back training methods considered researcher studying this problem through the use of this type of training and study aimed at identifying the impact of exercise using funds different elevations in the development of some physical and motor abilities of the research sample and chose researcher way intentional students from the fourth stage totaling 20 students opted for testing the capabilities of physical and motor after the agreed upon by experts (jump broadband and consistency, and test partridge for the maximum duration of 10 the distance and achievement 100 meter hurdles and the researcher concluded that the proposed exercise worked to develop explosive power and feature maximum speed, speed and researcher recommends certainly attention trained muscle strength along with other physical attributes …”
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Fault detection and diagnosis method for heterogeneous wireless network based on GAN by Xiaorong ZHU, Peipei ZHANG

“…Aiming at the problem that in the process of network fault detection and diagnosis,how to train the precise fault diagnosis and detection model based on small data volume,a fault diagnosis and detection algorithm based on generative adversarial networks (GAN) for heterogeneous wireless networks was proposed.Firstly,the common network fault sources in heterogeneous wireless network environment was analyzed,and a large number of reliable data sets was obtained based on a small amount of network fault samples through GAN algorithm.Then,the extreme gradient boosting (XGBoost) algorithm was used to select the optimal feature combination of input parameters in the fault detection stage and completed fault diagnosis and detection based on these data.Simulation results show that the algorithm can achieve more accurate and efficient fault detection and diagnosis for heterogeneous wireless networks,with an accuracy of 98.18%.…”
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