On Characteristics of Symbolic Execution in the Problem of Assessing the Quality of Obfuscating Transformations by Petr D. Borisov, Yury V. Kosolapov

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THE PROBLEMS OF THE TRAINING SYSTEM OF SCIENTIFIC AND TEACHING STAFF IN POSTGRADUATE SCHOOL by S. Rukavishnikov

“…The article considers the main problems of the efficiency of the system of the preparation of scientific and scientific-teaching staff in contemporary conditions of the reformation of system of higher and postgraduate education in the Russian Federation. …”
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New pilgrims. Towards the problem of studying spiritual tourism in the Urals by Gleb V. Zhoga

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THE PROBLEMS OF ASSESSING THE EFFECTIVENESS OF THE INDIVIDUAL-ACCRUAL MODEL OF PENSION INSURANCE by A. K. Solov’ev

“…The main methodological feature and originality of this study is a multi-factor analysis, using methods of comparative analysis and actuarial forecasting of the whole set of conditions for the formation and implementation by insured persons of their pension rights in the individual-accrual model (both external to the pension system and internal as well), not carried out in other studies on this problem.Results.The article presents the results of economicstudies of the national practice of formation and implementation of pension rights of workers in the framework of the individual-accrual pension insurance program. …”
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A Road Extraction Algorithm for the Guided Fusion of Spatial and Channel Features from Multi-Spectral Images by Lin Gao, Yongqi Zhang, Aolin Jiao, Lincong Zhang

“…In the road extraction task, for the problem of low utilization of spectral features in high-resolution remote sensing images, we propose a Multi-spectral image-guided fusion of Spatial and Channel Features for road extraction algorithm (SC-FMNet). …”
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WSCDNet: A Window Structural Similarity Guided Deep Feature Recalibration Method for Remote Sensing Image Change Detection by Siming Fu, Sijun Dong, Xiaoliang Meng

“…This enables the model to better capture temporal information during feature extraction. Furthermore, we use a dense ladder-shaped fusion method, making full use of the multilevel feature maps in the feature pyramid. …”
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MP-NER: Morpho-Phonological Integration Embedding for Chinese Named Entity Recognition by Pu Li, Guopeng Cheng, Guojun Deng, Shuanghong Qu, Min Huang, Guoxiang Li

“…Ablation experiments further validate the effectiveness of the introduced radicals and phonetic features. The experimental results demonstrate that this model effectively captures the semantic information of Chinese characters, addresses the problem of Chinese character heterophony, and improves entity recognition performance. …”
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Boosting Degradation Representation Learning for Blind Image Super-Resolution by YUAN Jiang, MA Ji, ZHOU Dengwen

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A Greedy Constructive Heuristic for Solving the Team Orienteering Problem with Variable Time Windows by Bibiana Granda, Begoña Vitoriano

“…These nodes can also impose time-window constraints, which can be variable if they are defined by a spread process, which behavior can be modified. The problem including all these features is the Team Orienteering Problem with Variable Time Windows (TOPVTW). …”
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State Instruments of Protectionism in Russian Industrial Policy: Theory and Practice by A. A. Rashchikov

“…The article examines the specifics and features of protectionism in Russian modern management. …”
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Phenomenology of abuse and neglect of children with developmental disabilities by Buha Nataša, Milanović-Dobrota Biljana, Stanimirov Ksenija, Mijatović Luka

“…Research findings indicate that the risk of maltreatment increases with the severity of behavioural problems, deficits in social skills and the presence of pronounced communication difficulties. …”
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The development features of entrepreneurship in the Khatlon and Sughd regions of the Republic of Tajikistan by Kh. I. Aminov

“…The article analyzes the state and reveals development features of entrepreneurship in two major regions of Tajikistan – Khatlon and Sughd. …”
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Angle Modulated Artificial Bee Colony Algorithms for Feature Selection by Gürcan Yavuz, Doğan Aydin

“…In this paper, to overcome this problem, angle modulation technique is used to reduce feature subset selection problem to four-dimensional continuous optimization problem instead of presenting the problem as a high-dimensional bit vector. …”
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MEMBRANOUS FLOWS IN GAS-LIQUID COLLECTORS-REGENERATORS OF SOLAR ABSORPTIVE SYSTEMS FEATURES by Doroshenko А.V., Kirillov V.H.

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Lane Detection Based on Connection of Various Feature Extraction Methods by Mingfa Li, Yuanyuan Li, Min Jiang

“…Lane detection is a challenging problem. It has attracted the attention of the computer vision community for several decades. …”
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Research on Spectrum Feature Identification of Indoor Multimodal Communication Signal by Yunfei Chen, Yang Liu, Xintao Fan

“…In order to solve the problem of large signal acquisition error caused by radio wave multipath effect in indoor environment, firstly, the signal source carried on the motion platform is collected for spectrum signal, and the signal processed by wavelet threshold denoising algorithms extracted and stored for spectrum feature extraction. …”
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A robust cyclic-feature detection against noise uncertainty by Qiang CHEN, Ming JIN, Jingwen TONG

“…However, noise uncertainty will degrade its performance severely. Aiming at this problem, a cyclic-feature detection method resisting to noise uncertainty was proposed. …”
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Method of anti-confusion texture feature descriptor for malware images by Yashu LIU, Zhihai WANG, Hanbing YAN, Yueran HOU, Yukun LAI

“…It is a new method that uses image processing and machine learning algorithms to classify malware samples in malware visualization field.The texture feature description method has great influence on the result.To solve this problem,a new method was presented that joints global feature of GIST with local features of LBP or dense SIFT in order to construct combinative descriptors of malware gray-scale images.Using those descriptors,the malware classification performance was greatly improved in contrast to traditional method,especially for those samples have higher similarity in the different families,or those have lower similarity in the same family.A lot of experiments show that new method is much more effective and general than traditional method.On the confusing dataset,the accuracy rate of classification has been greatly improved.…”
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Internet traffic classification using SVM with flexible feature space by Yaguan QIAN, Xiaohui GUAN, Bensheng YUN, Qiong LOU, Pengfei MA

“…SVM is a typical machine learning algorithm with prefect generalization capacity,which is suitable for the internet traffic classification.At present,there are two approaches,One-Against-All and One-Against-One,proposed for extending SVM to multi-class problem like traffic classification.However,these approaches are both based on a unique feature space.In fact,the separating capacity of a special traffic feature is not similar to different applications.Hence,flexible feature space for extending SVM was proposed,which constructs independent feature space with optimal discriminability for each binary-SVM and trains them under their own feature space.Finally,these trained binary-SVM were ensemble by One-Against-All and One-Against-One approaches.The experiments show that the proposed approach can efficiently improve the precision and callback of the traffic classifier and easily obtain more reasonable optimal separating hyper-plane.…”
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Internet traffic classification using SVM with flexible feature space by Yaguan QIAN, Xiaohui GUAN, Bensheng YUN, Qiong LOU, Pengfei MA

“…SVM is a typical machine learning algorithm with prefect generalization capacity,which is suitable for the internet traffic classification.At present,there are two approaches,One-Against-All and One-Against-One,proposed for extending SVM to multi-class problem like traffic classification.However,these approaches are both based on a unique feature space.In fact,the separating capacity of a special traffic feature is not similar to different applications.Hence,flexible feature space for extending SVM was proposed,which constructs independent feature space with optimal discriminability for each binary-SVM and trains them under their own feature space.Finally,these trained binary-SVM were ensemble by One-Against-All and One-Against-One approaches.The experiments show that the proposed approach can efficiently improve the precision and callback of the traffic classifier and easily obtain more reasonable optimal separating hyper-plane.…”
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