bluuebunny/crossref_metadata_2025_split huggingface dataset:
Finding new physics, phenomenological, experimental and astrophysical predictions
Authors: Das C R , Huitu K , Kurmanaliyev Zh , Mauyey B , Kärkkäinen T 
Published: December 2020

Abstract
The crucial phenomenological and experimental predictions for new physics are outlined, where the number of problems of the Standard Model (neutrino masses and oscillations, dark matter, baryon asymmetry of the Universe, strong CP-problem) could find their solutions. The analogies between the cosmological neutrino mass scale from the early universe data and laboratory probes are discussed, as well as the search for new physics and phenomena.
Asymmetric kink solutions of hyperbolically deformed model
Authors: Gani V A , Moradi Marjaneh A 
Published: December 2020

Abstract
We study some properties of kink solutions of the model with non-polynomial potential obtained by deforming the well-known φ
6 field model. We consider the excitation spectrum of the kink. We also discuss the properties of the ‘kink+antikink’ system as a whole that are not inherent to a solitary kink or antikink.
The dual properties of two-color QCD with baryon, chiral and isospin densities
Authors: Khunjua T G , Klimenko K G , Zhokhov R N 
Published: December 2020

Abstract
The phase structure of dense quark matter in the two color case has been investigated with nonzero baryon μB
, isospin μI
and chiral isospin μ

I5 chemical potentials. It has been demonstrated that due to the duality properties the phase diagram is extremely symmetric and the whole phase diagram in the case of two colors can be obtained just by dualities from the phase structure of three color case. This shows that the dualities are rather useful tool.
In-medium J/ψ mass shift by the D meson loop effect
Authors: Chhabra R , Tsushima K 
Published: December 2020

Abstract
The mass shift of the J/^ state in-medium in symmetric nuclear matter with zero and finite temperature and cold strange matter was investigated by an effective Lagrangian plus QCD sum-rule approach. The in-medium mass of the J/ψ state is evaluated through the intermediate pseudoscalar D-meson loop for the J/ψ self-energy. The effect of medium is incorporated through the in-medium mass of D meson calculated using chiral SU(3) model plus QCD sum-rule approach. The self energy loop integral is regularized using the phenomenological form factor of the dipole form. We compare our results with some of the results in the literature. The present results should be helpful to better understand the expected data from heavy ion collision experiments, such as CBM and PANDA.
Production of K(892)*0 mesons in 3He+Au collisions at

sNN=200GeV
Authors: Berdnikov A Ya , Berdnikov Ya A , Borisov V S , Kotov D O , Mitrankov Iu M 
Published: December 2020

Abstract
Collisions of small systems such as p/d/3He+Au are important for the investigation of quark-gluon plasma (QGP) in relativistic heavy ion collisions. These experiments distinguish the effects of the initial state of cold nuclear and the final state of hot matter. The research of light hadron production is one of the leading directions in the effects of the cold and hot nuclear matter studies. Due to a short lifetime and strange quark content, the K
*0-meson is sensitive to the properties of the hot dense matter and strangeness production from an early partonic phase (i.e. QGP). This report presents invariant transverse momentum spectra and nuclear modification factors (RHeAu
) of K
*0-meson as a function of pT
measured in 3He+Au collisions at

s

N
N

=
200

GeV

by the PHENIX experiment. In results, the nuclear modification factors for K
*0-meson in d+Au and 3He+Au collisions are in a good agreement. Values of RHeAu
for K
*0, φ, and π
0 mesons are equal within uncertainties in all centrality bins in the whole pT
range. In conclusion, the obtained results might indicate that CNM effects are not responsible for the differences of K
*0 and φ to π
0 suppression level seen in heavy ion collisions.
Pion femtoscopy in p+Au and Au+Au collisions at

sNN=200GeV

using transport approach
Authors: Kuzina E , Khyzhniak E , Ermakov N , Nigmatkulov G , Alpatov E 
Published: December 2020

Abstract
Correlation femtoscopy provides information about the space-time structure and evolution of the fireball created in ultra-relativistic nucleus-nucleus collisions. The dependence of the femtoscopic radii on transverse pair momentum and charged particle multiplicity of an event reflects the mechanism of collective behavior. In this work, the femtoscopic radii of identical charged pions were calculated in the UrQMD model for Au+Au and p+Au collisions at

s

N
N

=
200

GeV

and compared to each other at the same multiplicities. The physics implications of this comparison will be discussed.
On generalized Melvin solutions for Lie algebras of rank 4
Authors: Bolokhov S V , Ivashchuk V D 
Published: December 2020

Abstract
We consider generalized Melvin-like solutions associated with Lie algebras of rank 4 (namely, A
4, B
4, C
4, D
4, and the exceptional algebra F
4 ) corresponding to certain internal symmetries of the solutions. The system under consideration is a static cylindrically-symmetric gravitational configuration in D dimensions in presence of four Abelian 2-forms and four scalar fields. The solution is governed by four moduli functions Hs
(z) ( s = 1,…,4) of squared radial coordinate z = ρ
2 obeying four differential equations of the Toda chain type. These functions turn out to be polynomials of powers (n
1, n
2, n
3, n
4) = (4, 6, 6, 4), (8, 14, 18, 10), (7, 12, 15, 16), (6, 10, 6, 6), (22, 42, 30, 16) for Lie algebras A
4, B
4, C
4, D
4, F
4, respectively. The asymptotic behaviour for the polynomials at large distances is governed by some integer-valued 4 × 4 matrix v connected in a certain way with the inverse Cartan matrix of the Lie algebra and (in A
4 case) the matrix representing a generator of the ℤ2-group of symmetry of the Dynkin diagram. The symmetry properties and duality identities for polynomials are obtained. We also presented 2-form flux integrals over 2-dimensional discs.
On the Cosmological Origin of Astroparticles: New Concepts, Phenomena and Processes in galactic SMBH
Authors: Avetissian A K 
Published: December 2020

Abstract
The previous theoretical studies concerning the Russian programs OLIMPIA and “Synthesis of heavy elements” are developing based on original cosmological phenomenon of “gravitons’ entanglement”, revealed in scope of Non-Inflationary Cosmology theory, created by author. The broad review of this theoretical concept together with prediction of “initial cosmic quasiparticles” – mixture of correlated carriers of the fundamental physical fields in their vacuum states – were able to initiate another phenomenon, so called “large-scale entanglement of the prototypes of astroparticles”. These phenomena could generate within earliest Universe and be continued even during the formation of galaxies, when the trapped inside the SMBH initial Bose-condensate could become a large-scale coherent state through the induced gravitational collapse, turning further into an effective model of a galactic source of high energies. Such a model is able to verify the theoretical mechanism of the galactic jet.
Evolution of the cluster of primordial black holes within the Fokker-Planck approach
Authors: Stasenko V D , Kirillov A A 
Published: December 2020

Abstract
The calculation results of the evolution of the cluster of primordial black holes based on the Fokker-Planck equation with neglecting of the gas accretion onto black holes are presented. In addition, we consider how a massive black hole located within the cluster center affects on its evolution. Despite it creates an additional potential in the central region of the cluster and might capture surrounding black holes, a negligible growth rate of a central black hole was shown for 1 Gyr. Furthermore, we find a significant (approximately tenfold) expansion of the cluster.
Multi-messenger cosmology of new physics
Authors: Khlopov M Yu 
Published: December 2020

Abstract
The observational evidence for the inflationary cosmology with baryosynthesis and dark matter/energy can be viewed as the messenger for new physics, which governed the Universe origin, evolution and structure. To specify the physics beyond the Standard model (BSM), underlying the modern cosmological paradigm additional model dependent messengers are proposed, involving multi-component and composite dark matter, meta-stable particles, primordial black holes and antimatter domains in baryon asymmetrical Universe.
Primordial Black Holes Around Us Now, Long Before, and Far away
Authors: Dolgov A D 
Published: December 2020

Abstract
Recent astronomical data on black holes observations are reviewed. The arguments in favor that the observed black holes are predominantly primordial (PBH) are presented. The mass spectrum of PBH is best fit to the log-normal one. A model of PBH formation with log-normal spectrum is briefly described.
Capabilities of the Maple computer algebra system in the study of set theory and combinatorics
Authors: Olenev A A , Kirichek K A , Potekhina E V , Pelikh O V 
Published: December 2020

Abstract
The basic branch of both discrete and continuous mathematics is Set theory, the study of which is a difficult task. Designed and developed in the Maple computer algebra system, the Maplets package–the set theory application–enables to provide assistance both in teaching (by demonstrating the performance of operations on sets, testing knowledge and skills in using operations), and in studying set theory and solving the simplest combinatorial tasks (can be used as a simulator for students). By using interactive worksheets and animated images in Maple, students are given the opportunity for numerous experiments that will contribute to the development of their math education as well as computational skills. The application will form a sustainable need for the use of computer systems by students in the study of various branches of mathematics.
Research on Dynamic Identity Authentication Mechanism Based on Digital Signature
Authors: Zhan Weishu , Ye XinXin 
Published: December 2020

Abstract
With the economic development of globalization, the widespread Internet and the continuous establishment of national informatization, information security has become the focus of the national security guarantee system. Identity authentication is the first line of defense of the network communication system and the network security portal. Cryptography is the core content of the information security system and is widely used in various applications such as network security and data security. As the cornerstone of network security, since passwords are easy to be stolen or lost, it is not safe to authenticate identity with static passwords alone. Therefore, dynamic identity authentication came into being. It effectively resists the main security threats and attacks faced by static password authentication, solves the main drawbacks of static password authentication technology, and effectively prevents replay attacks. In addition, dynamic identity authentication solves the problem of static passwords being stolen in the database or stolen during transmission, thereby preventing illegal users from intruding and accessing the system. This article first studies the principle of digital signature technology and the design idea of dynamic identity authentication, and combines the advantages of both to propose a new dynamic identity authentication system based on digital signature technology.
Research on data access security agent technology in cloud computing security
Authors: Ou Xian 
Published: December 2020

Abstract
Cloud computing is a new application model, with multi-tenant, flexible, fast and easy to scale features, it can significantly reduce operating costs and improve operational efficiency. Cloud computing has received extensive attention from the business community and academia. With the continuous development of cloud computing technology, security and privacy issues have become the biggest obstacles to cloud computing applications. This paper first introduces the main problems faced by access control in the cloud environment, then researches and analyzes the cloud access security agent technology in terms of functional role and key technologies, and predicts the future challenges of the cloud access security agent technology based on the analysis of existing technologies.
Research on Cloud Storage Platform Technology Based on Hadoop
Authors: Hu Hairong , Fang Lulu , Yang Chaohong , Zhang Yang 
Published: December 2020

Abstract
In order to solve the problem of high cost of traditional data calculation and storage, and difficulty in writing parallel programs, this article summarizes the core technology of Hadoop, and uses Hadoop distributed processing technology and virtualization technology to design and build a cloud computing storage platform. The experiment proves that, compared with the traditional single-machine computing method and the physical machine cluster computing method, the platform has higher performance, and the resource utilization rate has also been improved.
Test Input Selection for Deep Neural Networks
Authors: Wang Zhiyu , Xu Sihan , Cai Xiangrui , Ji Hua 
Published: December 2020

Abstract
With the rapid development of deep learning technologies, the quality and security of deep learning systems have aroused great concern recently. Much research has been done in testing deep learning systems. Nevertheless, the oracle problem still remains since the input space of DNN-based software is usually very large and manually labeling is boring and cost-effective. Inspired by structural testing for traditional software, in this paper, we propose an algorithm to mitigate the oracle problem by selecting test inputs worth labeling. Specifically, we propose a test subset selection algorithm that can automatically select a test suite with high coverage but a small size when the labeling budget is limited. Compared with DeepXplore, the proposed algorithm can generate smaller test suites with higher coverage.
Optimal valid path prediction method for inter-domain networks considering commercial relationships*
Authors: Zhang Jingye , Zhang Jun , Xiong Xinli , Wang Yongjie 
Published: December 2020

Abstract
In the security research of large-scale inter-domain networks, it is often necessary to consider network state changes under the condition of failure or attack. In this case, the connection between ASes often switches between disconnection and recovery frequently, requiring frequent prediction of the AS-level path. Previous AS-level path prediction methods generally require detailed network information data and are complicated to calculate, which is difficult to meet the needs of such large-scale dynamic computation. In this paper, an optimal valid path prediction method for inter-domain networks considering commercial relations is proposed. This method predicts the optimal valid path according to the commercial relationships between ASes, which requires less network information data and low computational complexity. Through experiments, it is found that compared with the shortest path method commonly used in the security simulation of large-scale inter-domain networks, the prediction results are closer to the actual path of the network and can better reflect the actual path situation of the inter-domain network with lower computational complexity.
Clustering Preserving Projections for High-Dimensional Data
Authors: Cai Weiling , Zhou Honghan , Xu Le 
Published: December 2020

Abstract
In this paper, a novel clustering preserving projection method is presented to retain the cluster (or group) structures hidden in the original data. This method involves two steps: (1) the famous clustering method Fuzzy c-means is utilized to discover the cluster distribution in data; (2) such distribution is preserved by finding a linear embedding that minimizes the intra-cluster compactness in low-dimensional space. The feasibility and effectiveness of the proposed method are demonstrated on UCI dataset and USPS digital handwritten dataset.
Text classification based on graph convolutional network with attention
Authors: Tong Genmei , Zhu Min 
Published: December 2020

Abstract
The paper proposes a text classification method based on the graph convolutional network, the traditional text classification problem can be transformed into the node classification problem in the graph, and then proposes a attention structure to increase the weight of certain words and phrases. This paper verifies that the above structure has a positive effect on text classification accuracy. In particular, the structure can handle irregular data, such as citation network. We obtain very competitive results on 5 commonly used text classification datasets and achieve state-of-the-art results on 4 datasets, which include one dataset of citation network. Experiments show that combination of both structures can significantly reduce the classification error.
Digital Signal Modulation Classification using Data Conversion Method based on Convolutional Neural Network
Authors: Yang Yong , Chen Menghan , Wang Yizhu , Ma Piming 
Published: December 2020

Abstract
Automated modulation classification (AMC) plays a very important part in cognitive electronic warfare. Deep learning (DL) is a new machine learning (ML) method, which has been successfully implemented in many application fields. This paper proposes a new data conversion algorithm in order to gain a better classification accuracy of target signal modulation. Then a Convolutional Neural Network (CNN) architecture is developed, and its performance is proved to be better than the traditional data conversion method. In addition, the impacts of representation on classification performance are also analysed. Experimental results demonstrate the significant performance advantage of the proposed data conversion method using DL-based approach for modulation classification.
Achieving Manufacturing Excellence through the Integration of Process Planning Change and Data-driven Simulation
Authors: Wang Xiaogang , Liu Yiqun , He Yang , Li Nie , Mu Hua , Bai Yuewei 
Published: December 2020

Abstract
In this paper, a data-driven simulation framework with the integration of process planning change is proposed. It solves the problems of insufficient throughput and unbalanced resource utilization caused by the extremely unbalanced working time, improper resources allocation. Integration with Flexsim using a 3D graphical user interface is designed to meet the needs of complex data management. Experiments were tested, and the results show that the proposed approach combines the real-time rescheduling and quickly changing.
Towards quality analysis of MES through CMM data interoperation
Authors: Wei Shuangyu , Bai Yuewei , Xu Lai 
Published: December 2020

Abstract
The implementation of MBD/MBE (Model-based Design and Engineering) in the product design and manufacturing can effectively support multi-step data interoperation among “Design-Manufacture-Measurement.” Due to the limited data interoperation functions provided by the current CMM software (Coordinate Measurement Machine), most studies of MBD/MBE focused on designing the upstream. In contrast, the downstream (the underlying measurement data utilization) research is less. MES has an essential function in managing the manufacturing quality that analyses the condition and its development trend by collecting the manufacturing process quality data. Insufficient use of the underlying measurement data will lead to limited MES functions, especially for the capability of decision-making in intelligent manufacturing systems. The paper presents a measurement data interoperation method based on the interoperation layer method to support the quality analysis in MES (Manufacturing Execution System), discusses the relevant critical logic and data processing flow of the layer. It is verified that it can provide more comprehensive measurement data for quality management in the workshop.
Research on Space Launch Information Integration
Authors: Feng Wu , Ailiang Zhang , Xiuluo Liu , Jia Wang , Ying Liu , Jianjun Qi , Min Wang 
Published: December 2020

Abstract
The key directions for the automation, intelligence and integrated development of space launch have been very clear. Within the scope of C3I systems, professional automation system, ground handling system, research is conducted on the overall technical architecture of the space launch information integration, including: (1) Research on technical specifications system to promote the systematization and consistency for technical specifications at each level of access, transmission, processing and application; (2) Research on system functional architecture, highlighting the unified terminal access, unified transmission carrying, unified basic application and unified information interaction; (3) In view of the future development direction of space launch informatization, research will be carried out on relevant information guarantee technologies for remote command operation, automatic detection and diagnosis, wireless object connection and unattended launch tower.
House Price Prediction with An Improved Stack Approach
Authors: Zhang Hang , Wang Kehan , Li Mengchu , He Xinchen , Zhang Ruibo 
Published: December 2020

AbstractAs a typical framework in ensemble learning, Stacking creates a multi-layer learner by integrating the learning results of different individual learners. Despite a general improvement in accuracy, multiple layers in stacking results in high computation cost. In addition, some individual learners do not perform better than others in single-model prediction task. To solve the above drawbacks of traditional stacking, this paper proposes an improved Stacking algorithm based on the concept of “weighted attribute”. For each individual learner, a corresponding weight will be calculated based on its prediction performance on training data. Weights will then be used as evaluation criteria for model performance. Models with larger weights will be selected as attributes for meta-learner. When improved Stacking algorithm is applied on the same dataset, experiment results indicate a slight improvement in prediction accuracy and a relatively large reduction in computation cost. This demonstrates practical application value of the improvement.
Research on multi-feature fusion text classification model based on self-attention mechanism
Authors: Luo Xiaoxia , Wang XuanHao 
Published: December 2020

Abstract
For complex long texts, critical semantic information will be weakened and non-critical features will be forgotten. This paper proposes a multi-feature fusion text classification model based on autoattention mechanism. The preprocessed text data is represented by character-level vectors through the Bert model. First of all, self attention mechanism (Self-Attention) is used to learn the dependence of text words to capture the internal structural information of the text, Secondly, according to Deep superposition convolutional neural network (DSCNN) and Bi-directional Gated Recurrent Unit (BiGRU) based on soft attention mechanism (Soft-Attention), the semantic features of text data are extracted separately, and two different feature extraction results are combined. Finally, the Softmax layer is used to classify the deep-extracted features, and the accuracy of the classification model is improved by adding a uniform distribution item to the cross-entropy loss function. The text is verified in the medical consultation data set, and the results show that the F1 value of the text classification of the model is as high as 88.91%, Text semantic understanding is better than mainstream models.