bluuebunny/crossref_metadata_2025 huggingface dataset:
Mixed Convection in Lid-Driven “T” Shallow Cavity Heated From Bottom and Filled by Two Immiscible Fluids of Air and Al2O3-Water Nanofluid
Authors: koulali Aimad , Meziani Bachir , Sadaoui Djamel , Adnani Massinissa , Sahi Adel
Published: December 2020

This work present numerical simulation results of mixed convection in lid-driven “T” shallow cavity, filled by two immiscible fluids layers of air and Al2O3-water nanofluid. Mixed convection condition is created by the upper wall movement and temperature difference between the alveolus bottom and upper wall. Hydrodynamic and thermal characteristics of the flow have been predicted by solving the Navier- Stokes and energy equation using finite volume method. Coupling between two fluids layers are achieved using continuity of temperature and velocity at the interface air-nanofluid. Nano-particle volume fraction effect and geometrical shape of alveolus sidewalls (plane shape, concave shape and convex shape) have been chosen as discussed parameters. Analysis of obtained results shows that the heat transfer rate decreased with increasing volume fraction of solid inside the nanofluid layer. In addition, geometrical shape of alveolus sidewalls has a poor effect on flow structure and isotherms distribution in the physical domain.
The percentage effect of slag on the behavior of a high performance concrete
Authors: Rihia Chaher , Hebhoub Houria
Published: December 2020

The purpose of this study is to determine the feasibility of the partial replacement of cement with recycled fines in a high performance concrete whose purpose is to minimize the use of Portland cement and reduce the environmental impact of this waste. In the context of which, we used the fines of the granulated slag from El Hadjar-Annaba as a partial replacement of cement with substitution rates of 10, 15, 20%, and to study the behaviour in the fresh state (density and workability) and the mechanical performances (compressive and flexural tensile strength) and dimensional variation in the cured state, and then compared the results found with control samples of 0% substitution rate. Subsequent to which, it can be concluded that the introduction of recycled fines reduces the density and workability and improves the concrete's mechanical performance.
Sexual Practices During Adolescence
Authors: Arruda Emanoela Priscila Toledo , Brito Luiz Gustavo Oliveira , Prandini Tatiana Rocha , Lerri Maria Rita , Reis Rosana Maria dos , Barcelos Thays Marina Roncato , Lara Lúcia Alves Silva
Published: December 2020

Adolescence is characterized by significant biological and psychological changes. During this time, the increased production of androgens leads to increased sexual behavior, and this may contribute to early initiation of sexual activity. The objectives of the present cross-sectional study of adolescents enrolled in state schools in the city of Ribeirão Preto, state of São Paulo, Brazil, were to determine the average age at the first sexual intercourse (sexarche), the average number of sexual partners, and the frequency of contraceptive and condom use. Information on the age at sexarche, number of sexual partners, use of different contraceptive methods, and use of condoms were obtained using a semistructured questionnaire. Quantitative variables are expressed as means and standard deviations (SDs), and qualitative variables as absolute and relative frequencies. The chi-squared test was used for comparisons of qualitative variables, and the Student t-test for comparisons of continuous variables. All statistical analyses were performed using SAS (version 9.4, North Carolina State University, USA). We evaluated 202 students who answered the questionnaire, 69 males (36.36%) and 133 females (63.64%). The age at sexarche for men ranged from 7 to 18 years old, and for women from 7 to 17 years old. Forty-eight girls (36.01%) and 21 boys (30.43%) were in the first year of high school, 66.94% of adolescents reported sexual intercourse, and 56.25% used a condom during the first sexual intercourse. A total of 36.72% of students said they had safe sex most of the time, and 83.59% said that the first sexual intercourse happened because they “had a crush on” the other person.
Cytotoxic Activity of Antineoplastic Agents on Fertility: A Systematic Review
Authors: Moura Gabriel Acácio de , Monteiro Paula Bruno
Published: December 2020

Objective To analyze the long-term effects of antineoplastic treatments on patient fertility.

Selection of Studies The studies were selected through the New PubMed, Scielo and Lilacs databases along with references used for the creation of the present work. For the selection of studies, articles published between the periods from January 1, 2015 to April 6, 2020 in the English, Portuguese and Spanish languages were used. As inclusion criteria: cohort studies and studies conducted in vitro. As exclusion criteria: review articles, reported cases, studies that do not address thematic reproduction, studies that do not address the cancer theme, articles that used animals, articles that address the preservation of fertility and articles in duplicate in the bases.

Data Collection The collected data included: age of the patient at the beginning of treatment, type of neoplasm, type of antineoplastic treatment, chemotherapy used, radiotherapy dosage, radiotherapy site, effect of antineoplastic agents on fertility and number of patients in the study.

Data Synthesis Thirty studies were evaluated, antineoplastic chemotherapy agents and radiotherapy modulate serum hormone levels, reduces germ cell quantities and correlated with an increase in sterility rates. The effects mentioned occur in patients in the prepubertal and postpubertal age.

Conclusion Antineoplastic treatments have cytotoxic effects on the germ cells leading to hormonal modulation, and pubertal status does not interfere with the cytotoxic action of therapies.
Spectrum of F8 Genotype and Genetic Impact on Inhibitor Development in Patients with Hemophilia A from Multicenter Cohort Studies (J-HIS) in Japan
Authors: Shinozawa Keiko , Yada Koji , Kojima Tetsuhito , Nogami Keiji , Taki Masashi , Fukutake Katsuyuki , Yoshioka Akira , Shirahata Akira , Shima Midori ,   study group on JAPAN HEMOPHILIA INHIBITOR STUDY (J-HIS)
Published: December 2020

Some genetic and treatment-related factors are risk factors for inhibitor development in patients with hemophilia A (PwHA). However, the genotype distribution of the factor VIII gene (F8) and genetic impact on inhibitor development in Japanese PwHA remain unknown. In 2007, the Japan Hemophilia Inhibitor Study 2 (J-HIS2) was organized to establish a nationwide registry system for hemophiliacs and to elucidate risk factors for inhibitor development, designed for prospective investigation following a retrospective study (J-HIS1) which had already finished. Patients, newly diagnosed after January 2007, were enrolled in J-HIS2 and followed up for inhibitor development and clinical environments since 2008 onward. In the present study, F8 genotypes of PwHA were investigated in the patients recruited from the J-HIS2 cohort as well as those with inhibitor from the J-HIS1 cohort. F8 variants identified in 59 PwHA with inhibitor in J-HIS1 were: 20 intron-22 inversions, 5 intron-1 inversions, 9 large deletions, 4 nonsense, 8 missense, 11 small in/del, and 2 splice-site variants. F8 variants identified in 267 (67 with inhibitor) PwHA in J-HIS2 were: 76(28) intron–22 inversions, 3(2) intron–1 inversion, 1(0) duplication, 8(5) large deletions, 21(7) nonsense, 109(7) missense, 40(11) small in/del, and 9(7) splice-site variants. Forty variants were novel. The cumulative inhibitor incidence rate in the severe group with null changes was 42.4% (95% confidence interval [CI]: 33.7–50.8), higher than that with nonnull changes (15.6% [95%CI: 6.8–27.8]), in J-HIS2. Relative risk for inhibitor development of null changes was 2.89. The spectrum of F8 genotype and genetic impact on inhibitor development in Japanese PwHA were consistent with the previous reports.
Fractional order analysis of modified stretch–twist–fold flow with synchronization control
Authors: Fiaz Muhammad , Aqeel Muhammad
Published: December 2020

Nonlinear behavior and fractional order chaoticity with synchronization control of modified stretch–twist–fold (MSTF) flow are studied in this article. Analytical determination of the chaotification threshold is of great interest in engineering and control analysis. Generally speaking, a necessary condition of an ordinary differential system for the existence of chaos is that its spatial dimension equals at least three. However, for the fractional equation, it is not the case. It is studied that the fractional order MSTF flow exhibits rich dynamical properties and can be chaotic with the effective dimension ∑ less than 2. The chaotic behavior is conjectured on the basis of numerical simulation using the Adams–Bashforth–Moulton method. Synchronization of the fractional MSTF flow at different fractional orders is examined by an active control method. The proposed control has certain significance in terms of reducing the time and complexity for strategy implementation.
High-temperature annealing of AlN films grown on 4H–SiC
Authors: Brunner F. , Cancellara L. , Hagedorn S. , Albrecht M. , Weyers M.
Published: December 2020

The effect of high-temperature annealing (HTA) at 1700 °C on AlN films grown on 4H–SiC substrates by metalorganic vapor phase epitaxy has been studied. It is shown that the structural quality of the AlN layers improves significantly after HTA similar to what has been demonstrated for AlN grown on sapphire. Dislocation densities reduce by one order of magnitude resulting in 8 × 108 cm−2 for a-type and 1 × 108 cm−2 for c-type dislocations. The high-temperature treatment removes pits from the surface by dissolving nanotubes and dislocations in the material. XRD measurements prove that the residual strain in AlN/4H–SiC is further relaxed after annealing. AlN films grown at higher temperature resulting in a lower as-grown defect density show only a marginal reduction in dislocation density after annealing. Secondary ion mass spectrometry investigation of impurity concentrations reveals an increase of Si after HTA probably due to in-diffusion from the SiC substrate. However, C concentration reduces considerably with HTA that points to an efficient carbon removal process (i.e., CO formation).
Inertial particle separation in helical channels: A calibrated numerical analysis
Authors: Palumbo Joshua , Navi Maryam , Tsai Scott S. H. , Spelt Jan K. , Papini Marcello
Published: December 2020

Inertial microfluidics has been used in recent years to separate particles by size, with most efforts focusing on spiral channels with rectangular cross sections. Typically, particles of different sizes have been separated by ensuring that they occupy different equilibrium positions near the inner wall. Trapezoidal cross sections have been shown to improve separation efficiency by entraining one size of particles in Dean vortices near the outer wall and inertially focusing larger particles near the inner wall. Recently, this principle was applied to a helical channel to develop a small-footprint microfluidic device for size-based particle separation and sorting. Despite the promise of these helical devices, the effects of channel geometry and other process parameters on separation efficiency remain unexplored. In this paper, a simplified numerical model was used to estimate the effect of various geometric parameters such as channel pitch, diameter, taper angle, depth, and width on the propensity for particle separation. This study can be used to aid in the design of microfluidic devices for optimal size-based inertial particle separation.
Methyl-torsion-facilitated internal energy delocalization following electronic excitation in m-fluorotoluene: Can meta and para substitution be directly compared?
Authors: Davies Alexander R. , Kemp David J. , Wright Timothy G.
Published: December 2020

Coupling between vibrations, and between vibrations and torsions—a generalization of intramolecular vibrational redistribution (IVR)—provides routes to internal energy delocalization, which can stabilize molecules following photoexcitation. Following earlier work on p-fluorotoluene (pFT), this study focuses on m-fluorotoluene (mFT) as probed via the S1 ↔ S0 electronic transitions and the D0+ ← S1 ionization, using two-dimensional laser-induced fluorescence and zero-electron-kinetic energy spectroscopy, respectively. Wavenumbers are reported for a number of vibrations in the S0, S1, and D0+ states and found to compare well to those calculated. In addition, features are seen in the mFT spectra, not commented on in previous studies, which can be assigned to transitions involving vibration–torsion (“vibtor”) levels. Comparisons to the previous work on both m-difluorobenzene and mFT are also made, and some earlier assignments are revised. At lower wavenumbers, well-defined interactions between vibrational and vibtor levels are deduced—termed “restricted IVR,” while at higher wavenumbers, such interactions evolve into more-complicated interactions, moving toward the “statistical IVR” regime. It is then concluded that a comparison between mFT and pFT is less straightforward than implied in earlier studies.
Fruiting body form, not nutritional mode, is the major driver of diversification in mushroom-forming fungi
Authors: Sánchez-García Marisol , Ryberg Martin , Khan Faheema Kalsoom , Varga Torda , Nagy László G. , Hibbett David S.
Published: December 2020

Significance

The Agaricomycetes is a conspicuous and successful group of Fungi, containing ∼36,000 described species. The group presents striking diversity in fruiting bodies, including those with a pileus (cap) and stipe (stalk), puffballs, coral fungi, crust-like forms, etc. Agaricomycetes also comprise ecologically diverse species, including decayers, mycorrhizal symbionts, and pathogens. We assembled a “megaphylogeny” with 8,400 species that represent ∼23% of the known diversity of Agaricomycetes and used it to investigate the relative impact of fruiting body forms and nutritional modes on diversification rates. Across all Agaricomycetes, a pileate-stipitate fruiting body is associated with increased diversification compared to other forms. No such relationship was found for nutritional modes, including mycorrhizal symbiosis. We conclude that morphological innovation has driven diversification in Agaricomycetes.
Does political settlements analysis capture the unsettling politics of oil in Africa?
Authors: Oppong Nelson
Published: December 2020

Analysis of political settlements has emerged from the shadows of new institutionalism and moved to the epicentre of political economy analysis across Africa. This debate takes on the framework by scrutinising its applicability to the politics of oil through the combined lens of critical political economy and contentious politics. It argues that contrary to the postulations of strategic elite bargains by political settlement researchers, Africa's oil landscape is marked by pluralistic politics and contestations at multiple scales.
Enhancement of luminescence and thermal stability in Sr2.92-xTmxSiO5:Eu2+ for white LEDs
Authors: Peng Lingling , Qinping Qiang , Cao Shixiu , Chen Wenbo , Han Tao
Published: December 2020

Sr2.92-xTmxSiO5:Eu2+ (x = 0–0.09) orange emitting phosphors for white LED were prepared by solid-state method. The crystal structure and morphology of Sr2.92-xTmxSiO5 were determined by XRD and SEM. The phosphor showed strong absorption spectra and can be excited by near-ultraviolet (NUV) light in the range of 200−550 nm which matched well with the NUV light-emitting diode (LED) chips. The emission spectra showed asymmetric band around 585 nm under NUV and assigned to the 4f65d-4f7 transition of Eu2+ occupied Sr2+ sites in the host lattice. It is observed that 5d electron state of Eu2+ which easily influenced by the crystal field was not changed after Tm3+ co-doping in the host. Enhanced emission intensity, improved thermostability and fluorencence decay time have been made via crystal chemical unequivalence substitution of Tm3+ in Sr2+ site. The energy transfer took place between the Tm3+ and Eu2+ activator, the underlying mechanisms of enhanced luminescence and decay fluorescence properties by energy transfer were analyzed.
Instability of single-walled carbon nanotubes conveying Jeffrey fluid*
Authors: Jia Bei-Nan , Jian Yong-Jun
Published: December 2020

We report instability of the single-walled carbon nanotubes (SWCNT) filled with non-Newtonian Jeffrey fluid. Our objective is to get the influences of relaxation time and retardation time of the Jeffrey fluid on the vibration frequency and the decaying rate of the amplitude of carbon nanotubes. An elastic Euler–Bernoulli beam model is used to describe vibrations and structural instability of the carbon nanotubes. A new vibration equation of an SWCNT conveying Jeffrey fluid is first derived by employing Euler–Bernoulli beam equation and Cauchy momentum equation taking constitutive relation of Jeffrey fluid into account. The complex vibrating frequencies of the SWCNT are computed by solving a cubic eigenvalue problem based upon differential quadrature method (DQM). It is interesting to find from computational results that retardation time has significant influences on the vibration frequency and the decaying rate of the amplitude. Especially, the vibration frequency decreases and critical velocity increases with the retardation time. That is to say, longer retardation time makes the SWCNT more stable.
Negative photoconductivity in low-dimensional materials*
Authors: Cui Boyao , Xing Yanhui , Han Jun , Lv Weiming , Lv Wenxing , Lei Ting , Zhang Yao , Ma Haixin , Zeng Zhongming , Zhang Baoshun
Published: December 2020

In recent years, low-dimensional materials have received extensive attention in the field of electronics and optoelectronics. Among them, photoelectric devices based on photoconductive effect in low-dimensional materials have a broad development space. In contrast to positive photoconductivity, negative photoconductivity (NPC) refers to a phenomenon that the conductivity decreases under illumination. It has novel application prospects in the field of optoelectronics, memory, and gas detection, etc. In this paper, we review reports about the NPC effect in low-dimensional materials and systematically summarize the mechanisms to form the NPC effect in existing low-dimensional materials.
A scanning distortion correction method based on X – Y galvanometer Lidar system*
Authors: Qi Bao-Ling , Wang Chun-Hui , Guo Dong-Bing , Zhang Bin
Published: December 2020

Aiming at the problem of scanning distortion in X–Y galvanometer light detecting and ranging (Lidar) scanning system, we propose a method of image scanning distortion correction with controllable driving voltage compensation. Firstly, the geometrical optics vectors model is established to explain the principle of pincushion distortion in the galvanometer scanning system, and the simulation result of scanning trajectory is consistent with experiments. The linear relationship between the driving voltage and the scanning angle of the galvanometer is verified. Secondly, the relationship between the deflection angle of the galvanometer and the scanning trajectory and the driving voltage is deduced respectively, and an image scanning correction algorithm with controllable driving voltage compensation is obtained. The simulation experiment results of the proposed method show that the root-mean-square error (RMSE) and the corresponding curve between the scan value and the actual value at different distances, have a good correction effect for the pincushion distortion. Finally, the X–Y galvanometer scanning Lidar system is established to obtain undistorted two-dimensional scanned image and it can be applied to the three-dimensional Lidar scanning system in the actual experiments, which further demonstrates the feasibility and practicability of our method.
Analysis of Bc
→ τντ
at CEPC *
Authors: Zheng Taifan , Xu Ji , Cao Lu , Yu Dan , Wang Wei , Prell Soeren , Cheung Yeuk-Kwan E. , Ruan Manqi
Published: December 2020

Precise determination of the

branching ratio provides an advantageous opportunity for understanding the electroweak structure of the Standard Model, measuring the CKM matrix element

, and probing new physics models. In this paper, we discuss the potential of measuring the process

with

decaying leptonically at the proposed Circular Electron Positron Collider (CEPC). We conclude that during the Z pole operation, the channel signal can achieve five-

significance with

Z decays, and the signal strength accuracies for

can reach around 1% level at the nominal CEPC Z pole statistics of one trillion Z decays, assuming the total

yield is

. Our theoretical analysis indicates the accuracy could provide a strong constraint on the general effective Hamiltonian for the

transition. If the total

yield can be determined to

(1%) level of accuracy in the future, these results also imply

could be measured up to

(1%) level of accuracy.
Intelligent detection system of asset security vulnerability hidden danger under multiple and heterogeneous Web network
Authors: Li Yonggang , Li Jie
Published: December 2020

—Traditional network security vulnerability detection system is affected by detection tools, and the detection accuracy of complex network vulnerability is low. Therefore, this paper designs an intelligent detection system of asset security vulnerabilities under the multi heterogeneous web network. By crawling the asset security data in web network by crawler, the crawling data is integrated by using the characteristics of multi heterogeneous network. According to different types of security vulnerabilities, vulnerability detection is carried out to realize the intelligent detection of network asset security vulnerabilities. In order to verify the detection effect of system security vulnerabilities, comparative experiments are designed. The results show that the average false alarm rate of the designed system is only 12.3%, which is nearly 40% lower than that of the traditional system, which effectively improves the vulnerability detection accuracy.
Construction of a neural network model for performance prediction in shot put athletes
Authors: Tuo Xinling , Li Tao
Published: December 2020

This paper is to investigate the role of artificial neural network models in the prediction of sports performance and to establish artificial neural network models to evaluate the correlation between athletes’ special performance and special physical quality. The results show that the artificial neural network model overcomes the shortcomings of multiple regression models and gray models that require a pre-determined mathematical model, and more accurately reflects the functional relationship between the training indexes of the special quality of shot put athletes and the special athletic performance, and more accurately predicts the special performance of shot put athletes. It further showed that the special physical quality of shot put athletes is an important basis for their special athletic ability. With the physical quality index as the independent variable and the special performance as the dependent variable, the prediction model of the athletes’ special performance can be established, which can accurately diagnose and evaluate the development level of the athletes’ physical quality, and clarify the key points and objectives of the training content, so as to improve the scientific level of the training of shot put.
Development of Intelligent School P.E.in the Era of AI
Authors: Mei First author: Yang , Liuqing Second Author: Ouyang
Published: December 2020

In this paper, through the analysis of the future development of school physical education (P.E.) in the era of AI, new theories and research ideas are provided. The idea of intelligent education advocates the idea of lifelong education and happy learning, and the corresponding idea of P.E. should also be the idea of lifelong sports, happy sports and intelligent sports. In the era of AI, the application of modern P.E. is different from the traditional P.E. The teachers’ explanation and demonstration can effectively improve the students’ interest in learning and improve the teaching effect. The teachers become more effective in guiding the students’ learning, improving the ability of the P.E. teachers to update their knowledge and use P.E. technology, improve the quality of P.E. and P.E. evaluation system.
Federated Diabetes Mellitus Analysis via Homomorphic Encryption
Authors: Xie Yun , Li Peng , Zhu Xiang , Wu Qiuling
Published: December 2020

Diabetes is one of the most extensive chronic diseases in the world. Most patients suffer from the disease and its complications for a long time due to the lack of accurate and standardized treatment at early stage. Therefore, by analyzing diabetes data and establishing relevant predictive models, it is very meaningful to give reasonable health advice to high-risk groups. The establishment of an accurate prediction model requires a large number of data sources as support, and multiple medical institutions participate in data contribution and collaborative learning. Federated learning provides a secure general architecture for distributed collaborative learning. However, in the process of federated learning, the data of participants is still subject to the risk of security attacks or indirect information leakage. For example, when a participant uploads the local model parameters to an honest but curious cloud server, the cloud server can obtain relevant information from the participant. In order to solve this problem, this paper proposes a federated forest algorithm based on homomorphic encryption to strengthen the protection of the data privacy of the participants while ensuring that the accuracy of data analysis does not decrease. Analysis proves that our algorithm has good performance in privacy protection and prediction accuracy.
The Effectiveness of Autonomous Listening Study and Pedagogical Implications In the Module of Artificial Intelligence
Authors: Hu Jiahao , Hu Xujie
Published: December 2020

The artificial intelligence (abbreviated as AI) technology promotes the change in listening studying. An AI robot named as King of Listening Study is applied. To assess its effectiveness, an interview was made with the learners. The AI-aided study was more effective in promoting learners’ confidence. The inclusion of AI functions arouses students’ motivation to improve listening skill. Some points needs discussing. Listening can be integrated with speaking. Visual support is necessary. The investigation also indicates some pedagogical implications.
Application of Machine Learning and Real-time Feedback System to Predict Arriving Time
Authors: Guo Kaiwen
Published: December 2020

Real-time location feedback provides customers with direct information about the location of the package, which also provides one of the factors needed to predict the arrival time. This is not a simple math problem once we have the real-time location data because using math equations could not account for different situations that might occur to packages, which would again provides a inaccurate delivery time. By using machine learning, based on the data collected earlier and the information about the location from the use of real-time location feedback system, computers would be able to predict a delivery time with different factors involved, including weather and the possibility of the accident happened on the way. Using those different skills and factors, customers would be able to get an arrival time that is more precise than before and able to do decisions based on that. The main idea of this article is to predict the delivery time with the combination of the real-time location feedback system and machine learning.
Construction of entanglement-assisted quantum MDS codes
Authors: Guo Guanmin , Li Ruihu , Zheng Youliang , Zhang Mao
Published: December 2020

Entanglement-assisted quantum error correction codes (EAQEECs) can improve the reliability of transmission, which make use of pre-existing entanglement between two parties. In this paper, we construct two classes of entanglement-assisted quantum maximum distance separable (EAQMDS) codes via generalized Reed-Solomon (GRS) codes. Consequently, the results show that some of these EAQMDS codes have much larger minimum distance than ones available in the literature. Meanwhile, many of these EAQMDS codes are new in the sense that the parameters of these codes are not covered by the previously known ones. (Abstract)
Multi-View Deep Clustering based on AutoEncoder
Authors: Dong Shihao , Xu Huiying , Zhu Xinzhong , Guo XiFeng , Liu Xinwang , Wang Xia
Published: December 2020

In recent years, with the development of deep learning, replacing traditional clustering methods with subspaces extracted by deep neural networks will help better clustering performance. However, due to the instability of unsupervised learning, the features extracted each time are different even if the same data is processed. In order to improve the stability and performance of clustering, we propose a novel unsupervised deep embedding clustering multi-view method, which treats multiple different subspaces as different views through some data expansion methods for the same data. Specifically, our method uses a variety of different deep autoencoders to learn the latent representation of the original data and constrain them to learn different features. Our experimental evaluations on several natural image datasets show that this method has a significant improvement compared to existing methods.
Demand analysis and framework function design of cyber range construction in Colleges and Universities
Authors: Yuehong Zhang
Published: December 2020

This paper designs the network topology design, node simulation and environment construction, and drives the cyber range in three dimensions according to the teaching and scientific research needs of colleges and Universities: the module based on the classroom, the safety challenge of self-defining schedule, and the dynamic practice based on the team, so as to meet the needs of teaching and scientific research in the construction of cyber range in Colleges and universities.
A method of accelerating CNN computation on DSP
Authors: Li Bin , Luo Ying-guang , Guo-bin Fu Luo , Peng Ye , Hu Jia
Published: December 2020

Because convolution network contains a lot of multiplication and addition operations, there is still room for optimization after it is implemented on the hardware platform. This paper mainly studies the method of accelerating the deep learning algorithm on DSP, proposes to improve the convolution layer calculation by using Winograd algorithm, and implements it on GPDSP. The final results show that it can increase the parallelism of data calculation and significantly reduce the computing time.
Profit Optimization for Multiuser Video Transmission over Mobile Networks
Authors: Xu Jingce , Mai Yazong , Li Jie
Published: December 2020

With the increasing demand for high quality mobile video, how to receive higher quality video through mobile network with lower payment is a becoming an emerging problem. Existing approaches for Dynamic Adaptive Streaming over HTTP (DASH) face tremendous challenges when applying to video streaming in devices with different resolutions. In this paper, we propose a comprehensive profit optimization model with consideration of the cost of Content Provider, traffic payment, QoE factors and the relationship between device resolution and video quality. For ensuring the optimal profit of Content Provider and End Users at same time, we formulate both of their profit as a hybrid-objective optimization model. By solving the model, the optimum bitrates and the resulting profit can be obtained through our proposed algorithm. The simulation results demonstrate that the proposed method increases the average profit of End Users in 10%-15% compared with existing approaches.
Fault diagnosis Based on An Improved Statistics Principal Analysis Similarity Factor
Authors: Yin Hongxu , Wu Yuguang , Mu Zhijun , Geng Hongbin , Li Xiaobo
Published: December 2020

To settle the issue of conventional principal component analysis similarity factor cannot take advantage of higher-order statistics information of process variables, we presented an improved statistics principal analysis similarity factor (SPASF) to identify fault patterns in our work. In the improved SPASF approach, process data is first converted from original space into a new statistics space by the means of statistics pattern analysis (SPA) technology, and principal component analysis (PCA) is then employed to extract principal components in statistics space. At last, the pattern of snapshot dataset is recognized by measuring the similarity of principal components derived from statistics snapshot dataset and statistics historical fault dataset. The effectiveness of suggested SPASF based approach is verified through a case study on continuous stirring tank reactor (CSTR) by the means of recognizing fault patterns of snapshot datasets.
Recommendation algorithm based on user attributes and tag preferences
Authors: Zhang Min , Yan Xiaoling , Peng Hongwei
Published: December 2020

Aiming at the problem of sparse data and low recommendation accuracy of recommendation systems in a big data environment, a UT-CF algorithm that combines user attributes and tag preferences is proposed. The algorithm extracts and selects user attribute information, calculates the user attribute similarity matrix according to the user attribute characteristics; obtains the user’s tag score according to each score of the user item score matrix, obtains the user tag preference matrix, and calculates the difference between user tags Similarity, to get the user’s similar neighbors; In order to reduce the search space of similar users, the K-means clustering algorithm based on the principle of maximum distance is introduced. Make the top k recommendations based on the recommendations of the target user’s nearest neighbors. Through the experiment of MovieLens 100K data set, the algorithm improves the accuracy of recommendation.
Constructions of ternary LRCs with optimal distance
Authors: Zheng Youliang , Li Ruihu , Lv Jingjie , Zhang Mao
Published: December 2020

As a new class of erasure codes, locally repairable codes (LRCs) can provide data repair capability for distributed storage system. In this paper, we firstly propose an effective construction method to obtain optimal LRCs based on ternary optimal codes. Then, three classes of optimal LRCs are constructed by ternary cyclic codes and constant cyclic codes. All codes we gained have the optimal distance and reach the Cadambe-Mazumdar (C-M) bound.
CenterNet-Triplets application: surveillance camera illegal management detection
Authors: Zhu Xiangxiang , Yang Li , Zhang Dongping , Chen Ping
Published: December 2020

There are two types of illegal business in city management: out-of-store management and illegal mobile management, we simply refer to as outmanagement and flowmagement. The main way to deal with illegal buessiness is manual management. However, this requires a lot of costs, and it is impossible for city management personnel to conduct 24hour inspections. In order to improve management efficiency and save labor costs, this article uses city surveillance cameras, combined with deep learning object detection methods, to conduct real-time detection of illegal operations. Aiming at the situation where the amount of surveillance video data is small, a data enhancement method is proposed to improve the detection effect. CenterNet-Triplets is a object detection algorithm without anchor boxes. Its backbone network is Hourglass Network. The AP of CenterNet-Triplets on MS-COCO dataset is 47.0%, and it has a good detection speed. Experimental results show that CenterNet-Triplets is suitable as a method for detecting illegal operations in city management.
Research on Cloud Architecture of Enterprise Distributed Business Information System Based on SOA
Authors: Hu Hai-rong , Fang Lu-lu , Yang Chao-hong , Zhang Yang
Published: December 2020

The current SOA-based Enterprise Distributed Business Information System has poor scalability and low utilization, in order to solve this problem, this article analyzes the possibility of integration between Cloud Computing and SOA after telling the similarities between the two. We proposed a SOA-based Cloud architecture model, and applied it to Enterprise Distributed Information Systems, and proposed SOA-based Enterprise Distributed Business Information System Cloud Architecture Conceptual Model and Operating Model. This scheme can well solve the problems of the current system, and can greatly improve the quality and efficiency of system development, and has guiding significance for the development direction of enterprise information systems.
A multi-objective routing optimization model for ship intelligent navigation
Authors: Gao Zhupeng , Li Yuankui , Cui Jinlong
Published: December 2020

In order to solve the problem of ship route planning in the autonomous navigation and decision-making of ships, based on the electronic chart display and information system (ECDIS), the meteorological conditions of ocean-going ships were analyzed and the grid method was used to establish an environmental model. The voyage time, fuel consumption and navigation safety were taken as optimization goals, and a multi-objective ship route optimization model was established, then the non-dominated sorting genetic algorithm with elite strategy (NSGA-II) was applied in the optimization route searching to realize the solution of the optimal ship route.
Research on Digital Mapping Method Based on Complex Terrain
Authors: Zhu Pengpeng , Cui Hengle , Zhang Zipan , Li Jian , Ding Xiaopeng
Published: December 2020

Based on UAV low-altitude remote sensing technology and tilt photography technology, combined with highway projects, the UAV operating process, quality inspection and accuracy, and positioning accuracy in the mountainous complex terrain conditions are analyzed, and operating experience is summarized for subsequent navigation. The production provides guidance. At the same time, it also provides a reference for the exploration of digital mapping methods, and lays a theoretical foundation for the research of mapping methods. The combination of mapping methods in complex terrain with high technology is highly innovative.
Application of machine learning on the modelling of diffusion Magnetic Resonance Imaging signal
Authors: Ye Chen , Xu Daoyun , Wang Lihui , Zhu Yuemin
Published: December 2020

The modelling of diffusion Magnetic Resonance Imaging (dMRI) signals is very important for medical clinical application. However, the traditional method is to use a fixed mathematical model to make assumptions about the diffusion-weighted (DW) signals of all regions of human organ, which is unreasonable. In this paper, Convolutional Neural Network (CNN), a machine learning based method is used for learning the different characteristics of the signals, and finally intelligently give multi-model predictions for different regions of human livers. The performance of the proposed method is verified on both simulation and real liver data. The results show that the multi-model predicted by CNN method has high performance in distinguishing normal liver from diseased liver, and has great clinical application prospects
Protein function module of deep learning and PPI network prediction
Authors: TaoLu  , Huo Sicong
Published: December 2020

The outbreak of new coronavirus in 2020, the development of bioinformatics technology has become a new hot spot, in which the prediction of protein function module has become a research hotspot. The existing algorithms for predicting protein functional modules have the disadvantages of low accuracy and few functional modules. In this paper, an algorithm for deep learning and PPI network prediction of protein functional modules is proposed. Firstly, three important attributes of PPI network (node location, PPI network structure and core node) are integrated. Then the improved density algorithm is used for clustering analysis, and then the improved isometric mapping dimension reduction algorithm is used for principal component analysis. Finally, MLP is used for training The protein function module was obtained. The accuracy, F value, dimensionality reduction rate and the number of protein functional modules were compared among the other three PPI network based algorithms acc-fmd, MCL and mcode. The experimental results show that IIMP algorithm is better than other algorithms in accuracy, F value, dimension reduction rate and number of recognition modules.
Transient analysis of the fault process of double Y-type three-phase asynchronous motor during open phase operation
Authors: Hailing LU , Chaohui ZHAO , Hebiao SHEN , Licong DUAN
Published: December 2020

In order to reduce the loss caused by the failure of large motors, it is of great significance to accurately detect and predict the state of the motor during operation. Based on the theory of motor asymmetry, combined with the influence of temperature on the winding resistance in the actual operation of the motor, with the help of ANSYS finite element analysis software, a simulation model of a large three-phase asynchronous motor with double Y windings is established. This article uses the Maxwell circuit editor module to build an external circuit. First, verify the abnormal characteristics of the three-phase current when the phase is missing through simulation, and then analyze the influence of the resistance asymmetry on the motor operating characteristics. The simulation results show that the abnormality of the three-phase current caused by the winding asymmetry is regularly and cyclically amplified, that is, in the actual motor operation, the first phase of the abnormal winding can be determined by real-time observation of the three-phase current. In this way, we can avoid the burning of the motor.
IoT based cloud monitoring system for high-voltage power distribution room in the electric substation
Authors: Wu Shuifeng , Mao Wenqi , Li Gang , Gan Shengliang , Liu Yun , Yan Ying
Published: December 2020

Under the background of developing smart grids and ubiquitous electric Internet of Things (UEIoT) in China, an IoT based cloud monitoring system for high-voltage power distribution room in the electric substation has been proposed in this paper as a typical pioneer project. This system includs perception layer, network layer, application layer. The Key technologies, which contribute to realize real-time automatic control, intelligent regulation, online analysis and decision-making, are illustrated in detail. The proposed IoT based cloud monitoring system has been conducted in several areas of Hunan province and the field application illustrates the benefits of this system in the aspects of reducing manual operation, raising efficiency and preventing accidents.
Research on Simulation and Planning of Combustion Chamber in Gas Turbine
Authors: Liu Zeyuan , Lv Rongxin , Zuo Jiankai , Chen Jiatong , Yin Xiangquan , Zhao Xinyu
Published: December 2020

A gas turbine is an internal combustion power machine that drives the impeller to rotate at a high speed with a continuous flow of gas as the working medium, and converts the energy of the fuel into useful work. Nowadays, all developed countries attach great importance to the development of gas turbines, and the combustion chamber of the gas turbine is an important part of it. If the combustion chamber is properly optimized, the combustion efficiency will be greatly improved. The change of the number of blades of the gas turbine will have a great influence on the combustion effect inside the combustion chamber. In this paper, the gas turbine blade values are modified to study its influence on the combustion chamber flow field characteristics and methane mixing characteristics. Finally, when other conditions are constant, the larger the value of the blade, the more conducive to the formation of the return zone of the combustion chamber and the mixing of gas, and the better the combustion effect in the combustion chamber. This study also provides a reference for the design of gas turbine combustor.
X-band RCS Reduction of Airborne Antenna Array Using Loaded PIN Diodes
Authors: Wu Zijian , Wang Fei , Zhou Jianjiang
Published: December 2020

The paper applies PIN diodes to airborne microstrip antenna array to achieve radar cross section (RCS) reduction while the array is not at work, thus enhance the stealth performance of the aircraft. PIN diode can be regarded as a variable resistance or capacitance when it is forward-biased or reverse-biased, respectively. The equivalent resistance value of PIN diode in the forward-biased state is optimized and the radiation performance of the antenna array is not seriously affected. Simulation results show that the method can dramatically reduce the antenna RCS by disturbing the electric field distribution of current incident wave. The experiment results depict that maximum RCS reduction of aircraft model is more than 25dB, thus validates the proposed method.
Research on the Influence of Electromagnetic Radiation in the Automobile on the SAR Value of Human Body
Authors: Wang Jian , Mu Sikai , Hai Zhenyang
Published: December 2020

At present, the research on Evaluating Systematic Electromagnetic performance of automobile has gradually become a heated topic. With the deepening of research, personal safety in electromagnetic environment has been paid increasingly more attention. In terms of the complexity of the electromagnetic environment in the automobile, the automobile pole antenna, the wiring harness, the DC-DC converter, and the electromagnetic field distribution is simulated by the three-dimensional electromagnetic simulation software EMC studio, then the electric field intensity and the XZ plane current distribution at different seat positions can be obtained, and the SAR value absorption of human body at different seat positions and different human body sizes in the automobile is also calculated. The simulation results show that the electromagnetic radiation in the automobile will not do harm to the human body, which provides reference for the later research of human electromagnetic safety in electric automobile.
Instance segmentation model CP-Condinst
Authors: Yuan Jianye , ding Xinwang , Sun Lele
Published: December 2020

With the rapid development of deep learning image recognition technology, people have higher and higher requirements on the accuracy and speed of segmentation recognition. So instance segmentation becomes more and more important. The accuracy and speed of segmentation recognition are increasingly demanded. Recently, Shen Chunhua et al. proposed a very quantized instance segmentation model CondInst. In the paper, which used CSPResNet instead of ResNet, and added a Prediction module method to the head to improve model accuracy. Finally, on the MS COCO2017 data set, the simulation results show that CondInst’s AP, AP50, AP75, APS, APM and APL were increased by 0.2%, 0.4%, 0.3%, 0.1% and 0.4% respectively in the 50 layer residual model of our model, compared with CondInst’s AP, AP50, AP75, APS, APM and APL.The experimental results show that the method has certain practical value.
Mechanism synthesis for knee rehabilitation of patients with different heights taking the ankle as reference point
Authors: Araque J , Peña C A , Moreno G
Published: December 2020

This article analyzes different trajectories that different patients take when performing knee rehabilitation movements, which are flexion-extension movements in the supine position, analyzing the trajectory taking the patient’s ankle as a reference point, aiming to design a mechanism that can offer a solution to the following more than one trajectory issue, which will allow it to be used for more than one movement, in more than one patient.