FEATURES OF THE DEVELOPMENT OF HEALTH AND SOCIAL SECURITY OF SOVIET PRISONERS IN INSTITUTIONS OF CONFINEMENT IN 1956-1991 by Dmitry Yushchenko

“…In this regard, the author summarizes the conclusion that features, as well as problems, medical and consumer services of convicts are caused by a set of factors arising both from the relationship of the administration (employees) of correctional institutions and special contingent (including those violating the regime of serving the sentence), and in connection with the policy pursued by the state, aimed at the use of virtually free labor of convicts. …”
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Features of human papillomavirus infection frequency in different regions of the Russian Federation (literature review) by E. V. Belyaeva, O. A. Tokarskaya, T. A. Bairova

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Dropout Prediction Model for College Students in MOOCs Based on Weighted Multi-feature and SVM by Zhang Yujiao, Ang Ling Weay, Shi Shaomin, Sellappan Palaniappan

“…Predicting dropout rates is the first step to address this problem, and MOOCs have a large amount of behavioral data that can be used for such predictions. …”
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Instance Segmentation Algorithm of Urban Street Scene Based on Data Augmentation and Feature Enhancement by LI Chengyan, CHE Zixuan, ZHENG Qisen

“…Compared with the traditional method, the processed image is closer to the real source data distribution. Aiming at the problem of small target segmentation in urban street scenes, the idea of feature weighting and feature fusion is introduced. …”
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UAV Small Target Detection Model Based on Dual Branches and Adaptive Feature Fusion by Guogang Wang, Mingxing Gao, Yunpeng Liu

“…In order to solve the problem of small and dense targets in drone aerial images, a small target detection model based on dual branches and adaptive feature fusion is proposed. …”
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Explainable one-class feature extraction by adaptive resonance for anomaly detection in quality assurance. by Hootan Kamran, Dionne Aleman, Chris McIntosh, Tom Purdie

“…This iterative process tends to eliminate unacceptable plans, creating a significant class imbalance problem for machine learning efforts aimed at automating the classification of RT plans as either acceptable or not. …”
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Short-Term Photovoltaic Power Combined Prediction Based on Feature Screening and Weight Optimization by Liqing Geng, Yadong Yang, Genghuang Yang, Yongfeng Zheng, Xiaocong Liu

“…Aiming at the problem of low prediction accuracy caused by the intermittent and fluctuating characteristics of photovoltaic power, a short-term photovoltaic power combined prediction method based on feature screening and weight optimization is proposed. …”
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Adaptive Scattering Feature Awareness and Fusion for Limited Training Data SAR Target Recognition by Chenxi Zhao, Daochang Wang, Xianghui Zhang, Yuli Sun, Siqian Zhang, Gangyao Kuang

“…Therefore, how to perceive and integrate ESFs emerges as an essential issue. To address this problem, the adaptive scattering feature awareness and fusion network is proposed to obtain the more holistic target description. …”
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An improved Red-billed blue magpie feature selection algorithm for medical data processing. by Chenyi Zhu, Zhiyi Wang, Yinan Peng, Wenjun Xiao

“…To adapt to the feature selection problem, we convert the continuous optimization algorithm to binary form via transfer function, which further enhances the applicability of the algorithm. …”
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Using Image Feature Extraction to Identification of Ancient Ceramics Based on Partial Differential Equation by Chuanbao Niu, Mingzhu Zhang

“…This idea was used to turn the problem of division into a problem of difference. …”
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Enhancing Facial Feature Detection: Hybrid Active Shape and Active Appearance Model (HASAAM) by Musab Iqtait, Jafar Ababneh, Mohammad Rasmi, Amer Abu-Jassar, Suhaila Abuowaida

“…The aim of the HASAAM integrated fitting model is to find new solutions for the feature identification issue by combining the strengths of the Active Shape Model (ASM) and Active Appearance Model (AAM) to provide unique findings on the feature detection problem. …”
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An Interior Point Method for L1/2-SVM and Application to Feature Selection in Classification by Lan Yao, Xiongji Zhang, Dong-Hui Li, Feng Zeng, Haowen Chen

“…This paper studies feature selection for support vector machine (SVM). …”
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Research of Fault Feature Extraction and Diagnosis of Planetary Gear Train based on SPS and CNN by Pan Zheng, Jianhua Zhou, Sujie Gao, Ben Chen, Xiangxiong Liu, Shijing Wu

“…In order to solve the problem that the complex structure and operating conditions of planetary gear box lead to the difficulty of signal fault feature extraction， the frequency spectrum feature of gearbox vibration signal with faults is preliminarily deduced by analyzing the vibration mechanism of planetary gear train. …”
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Research and implementation of dynamic path tracking method for badminton based on multi-feature fusion by Jiajia He, Jianqiang He

“…Abstract Aiming at the problem that it is difficult to capture the trajectory of the more specialised movements in badminton, which leads to the blurring of the tracking path, a dynamic path tracking method for badminton based on multi-feature fusion is proposed. …”
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Rolling Bearing with Isometric Feature Mapping and Fuzzy C means Fault Identification Method by WANG Ya-ping, LI Shi-song, GE Jiang-hua, XU Di, LI Yun-fei

“…In the fault identification of rolling bearing, the traditional ISOMAP algorithm is met with the problem of large deviation of geodesic distance and aliasing in fault identification. …”
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Computing feature matrices using PCA-SVD hybrid method on small-scale systems by Le Tien Hung, Vu Minh Trong, Phan Viet Thanh, Nguyen Le Van

“…The task of performing feature extraction from input matrices is a well-known problem in biometric recognition. …”
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User-Independent Activity Recognition via Three-Stage GA-Based Feature Selection by Theresia Ratih Dewi Saputri, Adil Mehmood Khan, Seok-Won Lee

“…Therefore, it is unwise to recognize different activities using the same features. This work presents a solution to this problem. …”
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Block-chain abnormal transaction detection method based on adaptive multi-feature fusion by Huijuan ZHU, Jinfu CHEN, Zhiyuan LI, Shangnan YIN

“…Aiming at the problem that the performance of intelligent detection models was limited by the representation ability of original data (features), a residual network structure ResNet-32 was designed to automatically mine the intricate association relationship between original features, so as to actively learn the high-level abstract features with rich semantic information.Low-level features were more transaction content descriptive, although their distinguishing ability was weaker than that of the high-level features.How to integrate them together to obtain complementary advantages was the key to improve the detection performance.Therefore, multi feature fusion methods were proposed to bridge the gap between the two kinds of features.Moreover, these fusion methods can automatically remove the noise and redundant information from the integrated features and further absorb the cross information, to acquire the most distinctive features.Finally, block-chain abnormal transaction detection model (BATDet) was proposed based on the above presented methods, and its effectiveness in the abnormal transaction detection is verified.…”
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Service clustering method based on description context feature words and improved GSDMM model by Qiang HU, Jiaji SHEN, Guanghui JING, Junwei DU

“…To address the problem that current service clustering methods usually faced low quality of service representation vectors, a service clustering method based on description context feature words and improved GSDMM model was proposed.Firstly, a feature word extraction method based on context weight was constructed.The words that fit well with the context of service description were extracted as the set of feature words for each service.Then, an improved GSDMM model with topic distribution probability correction factor was established to generate service representation vectors and achieve distribution probability correction for non-critical topic items.Finally, K-means++ algorithm was employed to cluster Web services based on these service representation vectors.Experiments were conducted on real Web services in Web site of Programmable Web.Experiment results show that the quality of service representation vectors generated by the proposed method is higher than of other topic models.Further, the performance of our clustering method is significantly better than other service clustering methods.…”
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A Localization Method for UAV Aerial Images Based on Semantic Topological Feature Matching by Jing He, Qian Wu

“…In order to address the problem of Unmanned Aerial Vehicles (UAVs) being difficult to locate in environments without Global Navigation Satellite System (GNSS) signals or with weak signals, this paper proposes a localization method for UAV aerial images based on semantic topological feature matching. …”
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