bluuebunny/crossref_metadata_2025_split huggingface dataset:
Fusion Image Style Transfer Network
Authors: Lai Shuren , You Fucheng , Gong Hechen , Zhao Yangze 
Published: September 2019

Abstract
Generating art automatically and quickly for machines is always a difficult task. The existing image style migration algorithms can realize the rapid generation of art images. However, these algorithms can only generate artistic images by migrating existing content maps, and can not modify the content of images artificially. This paper proposes an image style migration approach which can stylize artificially modified fusion image. Particularly, this strategy can correct the modification of the photographic images and enhance the style shifting details. Aiming at eliminating traces of modification, we adopt a autoencoder network to increase fusion image coordination. This network increases detail representation of fusion image. In order to enhance visual effects of style migration, we improve a neural style migration network to generate fusion image stylized graph. We show that this approach make the fused image more coordinated, resulting in a richer detail of the style image.
Vehicle detection in aerial image based on deep learning
Authors: Zhao Shuai , You Fucheng , Shang Lei , Han Chao , Wang Xuewei 
Published: September 2019

Abstract
At present, urban traffic congestion is becoming more and more serious. Traditional vehicle detection methods generally have problems of low precision and low recognition rate. In order to solve these problems, a vehicle detection method in aerial image based on deep learning is proposed. The method uses the YOLOv3 algorithm and optimizes the algorithm network, increase the number of rasters of the final predicted output, improves the detection ability of the network for dense groups, and verifies the effect by training a new model. The experimental results show that the new training model has a good effect on vehicle detection, which solves the problem of low detection and recognition rate of urban traffic vehicle detection, and makes good predictions and judgments on urban traffic congestion.
Cross-Modulated Amplitudes and Frequencies of Epileptic EEG
Authors: Cai Yujie , Dai Jiafei , Li Jin , Wang Jun , Hou Fengzhen 
Published: September 2019

Abstract
Epilepsy is a neural disorder with the hallmark of recurrent seizures. To characterize the epileptic brain electrical activities, we employed the cross modulation of instantaneous amplitudes and frequencies to separate synchronous and anti-synchronous modulation. Amplitude-amplitude, amplitude-frequency and frequency-frequency cross modulation were adopted to analyse the difference between EEG signal of epileptic patients and that of normal people. By comparing the observed patterns with two groups of EEG signals we demonstrate that the cross-modulation exponentials at the temporal region and the occipital region of right hemisphere are significant different.
Fuzzy Twin Support Vector Machine Based on Intra-class Hyperplane
Authors: Zhang Hanghang , Li Haipeng 
Published: September 2019

Abstract
Aiming at the sensitivity of twin support vector machines to noise and outliers, an improved fuzzy twin support vector machine is proposed. Aiming at the shortcomings of fuzzy membership based on the distance between a sample and its class center, this algorithm proposes a new fuzzy membership function that can effectively reflect sample uncertainty— based on intra-class hyperplane and sample affinity. When determining the membership function, the intra-class hyperplane replaces the class center, reducing the dependence on the sample set geometry and improving the model generalization ability. At the same time, considering the relation between each sample and the confusion degree of sample points, the sample affinity is applied to the design of membership function, so as to effectively distinguish the effective sample from noise and outliers and improve the classification accuracy. The experimental results show that compared with the twin support vector machine and the classic fuzzy support vector machine, the improved fuzzy twin support vector machine has better classification performance.
Research on the Application of Item-based Collaborative Filtering Algorithms in MOOC
Authors: Lu Qirong , Xia Jiwei 
Published: September 2019

Abstract
In the learning process, the recommendation system can recommend learning resources that are in line with the learning situation of the learning objects and help the learning objects to learn more easily and naturally. By analyzing the characteristics of item-based collaborative filtering algorithm, this paper applies it to the recommendation system of mooc learning resources to avoid the possible defects of this algorithm, such as low performance and offline processing in other scenarios, and gives full play to its good real-time performance and high recommendation efficiency. By analyzing the log files of imooc, this paper obtains the learned learning resources of the learning objects in imooc, takes the first 80% data of historical records, obtains the recommended list of learning resources through recommendation algorithm, and then compares the data of the last 20% of historical records. Finally, the algorithm is optimized according to the accuracy of the recommendation algorithm in the experiment and the actual learning scene.
A Novel Method for Reconstructing Dynamic Bayesian Network
Authors: Yu Ying , Huang Hao , Lu Jianye , Yang Zhen , Yang Wenwen 
Published: September 2019

Abstract
Upon data renewal, a Bayesian network might need reconstruction. In this paper, a novel method, which is based on a proposition, is proposed for such reconstruct work of a kind of symptom--disease Bayesian network scored by a K2 soring function. The proof of the proposition for the method is given firstly, and later the performance of the method is illustrated with numerical examples.
Artificial Intuition Reasoning System (AIRS) and Application in Criminal Investigations
Authors: Liu Shuxia , He Ping 
Published: September 2019

Abstract
Intuition is a special function of human brain, and it is an urgent task to establish a reasoning system with intuitive characteristics in the field of artificial intelligence. The purpose of this paper is to establish a formal model of intuitive reasoning based on the analysis of the characteristics of intuitive reasoning in criminal investigation. At the same time, it provides an artificial intuition model for constructing inference machine of criminal investigation. First, a novel framework of intuitive reasoning system is established based on the principles of memory mapping and perceptual inversion. Secondly, according to the fuzzy perception of experience and knowledge, a formalized criterion which accords with humans intuitive reasoning is established, namely the intuitive characteristic index. Finally, the artificial intuition reasoning model is used to analyze a crime investigation case. The results show that the reliability of this artificial intuitive reasoning system is 85% in practical application, and this intuitive reasoning process is a learning system of experience and knowledge. If this intuitive reasoning system can simulate human brain’s intuitive reasoning after limited intuitive training and learning.
Research of Differential Privacy Protection on Social Network
Authors: Zhang Jian , Zhang Changlun , Chen Shihui , Wu Shupeng 
Published: September 2019

Abstract
Rapid development has been witnessed in social network. As a consequent, much more people are involved in getting it, sharing their own information to enlarge their social circle. In this paper, the security problem, which exists in privacy preserve in social network and process users’ private information via Differential Privacy Histogram Release is focused on. The method can process user’s privacy information on the premise of guaranteeing the availability of information, making the information released after publication different from the information before publication, thus making the user’s privacy information not leak. Shown by theoretical analysis and research results, safe release of private information can be guaranteed if processed by this method.
A Weak Centralized Consensus Mechanism with More Incentive Effects
Authors: Mu Yuxiang , Chen Wanghu , Liang Xiaoyan , Gao Yaqiong 
Published: September 2019

Abstract
In the blockchain system, the consensus mechanism not only helps the nodes maintain data consistency, but also has certain functions for token issuance and attack prevention. Aiming at the problems of low enthusiasm and weak centralization in Delegated Proof of Stake (DPoS), this paper proposes a weak centralization consensus mechanism with more incentive effect. We replace the voting link with opportunity verification mechanism, and make the voting link that affects the enthusiasm of nodes become the embodiment of their own rights and interests, so as to strive for the maximization of their own interests. And we also introduce the method of random guess to make the selection of representative nodes more random, so as to achieve the situation of weaker center. At last, combined with the existing problems, the paper analyses the feasible solution with this mechanism.
Neural Network Approach for Multiple-Class Classification
Authors: Wu Dengyi , Tu Chingsheng , Lee Shiejue , Wu Chihhung 
Published: September 2019

Abstract
Classification is a very important problem-solving technique. Given a set of attribute values about an object, a classifier determines which category the object belongs to. A classification task can be a binary or multiple classification; it can also be a single-label or multiple-label classification. Neural networks are an effective technique in the field of artificial intelligence. In this paper, we develop different schemes of neural networks for solving binary, multiple, single-label, and multiple-label classification problems. The ideas behind them are described in detail.
The Stage Model of Intelligent System Forensics
Authors: Zhao Ziyu , Wang Yongquan , Liao Genwei 
Published: September 2019

Abstract
With the rapid development of Internet, mobile communication is moving towards the 5G era, and the application of intelligent systems is in the ascendant. The corresponding intelligent system forensics has become one of the research highlights. By comparing the differences between intelligent system forensics and traditional electronic data forensics, this paper studies the specific content of intelligent system forensics, and proposes a stage model of forensics, which mainly included seven stages: formulation of forensics strategy, safe collection of media/equipment, equipment protection before laboratory forensics, preparation before laboratory forensics, development of laboratory forensics, reconstruction of the case process, and preservation of evidence. The model will be conductive to a more normalization process to improve the reliability, integrity and avoid misoperation of intelligent system forensics.
A integrated Navigation Filtering Method Based on Wavelet Neural Network
Authors: Tao Zhu , Gao Saisai , Huang Ying 
Published: September 2019

Abstract
Aiming at the problems of the difficulty to establish the model and the large data dimension for the traditional integrated navigation method, a method of using the wavelet neural network to directly predict the position and velocity error information is proposed. Get rid of the mathematical model establishment, void introducing new errors in the model establishment, and adopt multiple parallel networks to reduce the dimensionality of the data, which greatly reduces the amount of calculation. The Kalman filter is used as a reference for simulation experiment. The results show that the proposed method can effectively improve the accuracy and real-time performance of the integrated navigation system, and provides a new feasible path for combined navigation filtering.
Relaxation of Gene Network after Injection of Influenza Virus
Authors: Deng Shiguo , Ren Henggang , Yuan Qianshun , Yang Huijie 
Published: September 2019

Abstract
The relaxation of gene network after injection of influenza virus is investigated from the perspective of diffusion process. The key idea is to separate each snapshot network into communities, and the identification number of the community in which every node occurs is used to represent the state of the node in this snapshot. From a series of snapshots of network one can construct the trajectories for all the nodes, which form an ensemble. The relaxation is then described by the division and fusion of the communities. It is found that the gene networks for healthy individuals evolves regularly, while that for the individuals affected by influenza virus in a chaotic way.
An Improved Infrared Image Contrast Enhancement Method
Authors: Wang Yuanbin , Zhang Jian 
Published: September 2019

Abstract
Aiming at the characteristics of infrared image, such as concentrated gray level distribution, low contrast and poor resolution, the paper proposes an improved infrared image enhancement algorithm. Firstly, the original image is filtered by adaptive median filtering method, then platform histogram equalization and gamma transformation are performed on the filtered image to improve the overall contrast of the image. At the same time, the filtered image is performed by Laplacian sharpening to get the edge information of the image. Finally, we obtained an enhanced infrared image by weighted combination of gamma transformation and Laplacian sharpening. Experiment shows that target contrast and average brightness are enhanced by the proposed algorithm, furthermore, the overall information is preserved and the edge information of the image is obtained, which improves the visual effect.
Research on Die Casting Process of Magnesium Alloy Motorcycle Wheel Based on New Engineering Construction
Authors: Zhang Zhanling , Zhang Yanqin , Zhang Hui , Pan Aiqiong , Liu Jun 
Published: September 2019

Abstract
Magnesium alloy forming technology is a hot spot in the world. This paper introduces the application of AM60B magnesium alloy and die casting technology in the forming of motorcycle wheel casting, and the test and analysis of die casting process, Finally, qualified magnesium alloy wheel castings are produced. the selection of die casting process parameters was 680 ∼ 700°C, the casting temperature of 240 ∼ 280°C, and the pressure ratio between 180 ∼ 200MPa and the holding time was 20 ∼ 25s. Under the condition of optimum technological parameters, obtained by casting the mechanical properties testing results: σb=218∼227MPa, HBS=66∼71, δ5=9.8 ∼10.7% and ak = 17.5 * 104∼18.7 * 104j / m2. The practice has proved that the die casting technology is a suitable process for magnesium alloy wheels, and it has reference value for the mass production of large area magnesium alloy casting.
Data Acquisition and Analysis of Photocell Characteristics and Its Application in Switch Circuit Control
Authors: Wang Lingbo 
Published: September 2019

Abstract
Photocells which produce a voltage and supply an electric current when illuminated have been widely used. The basic characteristics of the photocell were tested and analysed through experiments by an optical control experimental platform, such as short circuit current, open circuit voltage, illumination characteristic, volt ampere characteristic, load characteristic, and spectral characteristic. The experimental results are in agreement with the theoretical analysis. The light control switch circuit was realized by using photocell. In this way, the principles and operation of photocell can be well comprehended.
A Comparison of Two Methods for Determining the Genome Size of Taimen
Authors: Yang Guiqiang , Zhang Liying , Wang Zhanquan , Li Wentong , Yuan Ding 
Published: September 2019

Abstract
To compare the two methods for determining the genome size of Taimenes (Hucho taimen). The present study determined genome size (or C- values) of 30 individuals of Taimenes by the method of PI (propidium iodide) and DAPI (4’,6-diamidino-2-phenylindole), through the flow cytometry, using chicken erythrocyte DNA content as a standard. The result showed that (1) With the method of PI and DAPI through the flow cytometry, DNA content in blood erythrocyte was 5.65±0.25 pg•2C-1 and 5.04±0.12 pg•2C-1(Fig. 1 and Fig. 2), and genome size (Gb) were 2.70 ± 0.12 Gb and 2.41 ± 0.06 Gb. By Independent-Samples T Test, the genome size (Gb) of blood erythrocyte determined by PI was significantly greater than that determined by DAPI(Table 1). (2)Several of the main support salmonids were clustered by furthest neighbor of any two C-values with the measure of euclidean distance. From the Fig. 3, we found that taimen and fine scale (Brachymystax lenok)first clustered into the same subgroup 1, brook trout (Salvelinus fontinalis) and Atlantic salmon (Salmo salar) clustered into the same sub-group 2, rainbow trout (Oncorhynchus mykiss) and pelyad (Coregonus peled) clustered into the same sub-group 3, Subgroup 1 and subgroup 2 firstly clustered into the same team, then come together with subgroup 3. The result indicates that (1) PI method can more accurately reflect the distribution of DNA content in blood erythrocyte of taimen, and more accurate prediction genome size of taimen.(2)Cluster analysis of C-values of several salmons may be related to their respective origin distribution and the filter feeding characteristics of Pelyad.
Safety Valuation of Military Aviation Control System Based on Cloud Model
Authors: Ye Zelong , Wen Xiangxi , Wu Minggong , Li Jiawei , Qiu Shidai 
Published: September 2019

Abstract
At present, the flight training, army operation increase constantly, the army ATC faces rigorous challenges. The safety evaluation on ATC can enhance the control effect and guarantee fly safety. In this paper, an evaluation index system is established based on ‘human factor, machine factor, environment factor and management factor’. On the basis of AHP and cloud model, the safety evaluation model is built. To validate the model, an experiment is operated, the result is accord with the real situation, which proves the scientifically and feasibility of this model.
The simulation of three crossroad traffic queueing systems using petri nets and colored petri nets program
Authors: Wicaksono A , Rudhito M A 
Published: September 2019

Abstract
This research aims to develop a simulation of traffic flow at the crossroads, that’s Monjali, Kentungan and Gejayan crossroads in Yogyakarta with and without underpass. The simulation using petri nets and colored petri nets programs. We assume that each crossroad has the same density, and we look that the traffic flow just went one way. The results of the study show that the queuing system for three traffic intersections can be modeled using petri nets. Furthermore, a queue simulation can be carried out with the help of a colored petri nets program. Simulation results indicate a buildup at certain junctions without underpasses and with underpasses
Driver Parking Behaviour: An Observational and Experimental Intervention Study
Authors: Najihah Mad Rosni Nurul , Fadzil Jobli Ahmad , Neging Maureen 
Published: September 2019

Abstract
Illegal parking has become a major problem in Malaysia especially in urban area due to the increased traffic volumes and limited parking space. When the parking facilities are limited, driver factor thus has a significant effect on the formation of traffic congestion. Extensive work has been conducted to address this issue, however most studies did not incorporate the impact of driver behaviour at limited parking condition whereas it is understood that “cruising for parking” at limited parking facilities has a very strong influence on the road traffic jams. Thus, objectives of this study are to analyse drivers’ personality traits which focus on consideration and selfishness traits; and to investigate drivers’ personality traits and their impact on driver parking behaviour in Kuching, Sarawak. Analyzation of driver parking behaviour was based on observational study of driver, vehicle, and situational variables. Experimental intervention then conducted to different age groups of drivers. They were asked to respond to questions that related to the driver parking behaviour characteristic. Analyses of the data reported in this study revealed that most of the drivers are considerate enough but they become a selfish person when confront with difficult situation at the parking space and their action sometimes are susceptible to illegal parking. The findings significantly beneficial to the traffic engineer, policy maker and researcher in enhancing parking control and management system.
Potential Use of Locally Available Filter Media in a UAFB Reactor Coupled with Natural Treatment in Soybean Industry Wastewater Treatment
Authors: Nayono Satoto E. , Purwantoro Didik 
Published: September 2019

Abstract
Many food industries in developing countries cannot afford proper wastewater treatment and directly discharge their wastewater into surface water bodies causing several problems such as aesthetical, health and environmental problems. A new approach for low-cost wastewater treatment which is reliable, allows nutrients and energy recovery should be promoted. One of the alternative wastewater treatment technologies is anaerobic wastewater treatment which offers a number of advantages such as low energy requirement, low production of sludge and the possibility of energy recovery. As one of the disadvantages of using anaerobic method is that the effluent usually does not meet the authority’s regulation to be discharged directly into water bodies, to further treat the effluent in order to meet the standard, the up flow anaerobic fixed-bed reactor will be coupled with a ‘natural treatment’. This paper presents preliminary results of a research which has the main goal to examine the of several locally available materials as packing media in UAFB reactor and the appropriate vegetations for constructed wetland and/or macrophyte pond. Additionally, potential energy recovery from soybean wastewater is also calculated.
Influence of groundnut shell ash on the properties of cement pastes
Authors: Usman Jamilu , Yahaya Nasiru , Mohammed Mazizah E 
Published: September 2019

Abstract
This paper presents the effect of groundnut shell ash (GHA) on the properties of cement paste. Cement pastes containing GHA as cement replacement in different proportions up to 50% by weight were prepared. At fresh state, the consistency and setting times of the pastes were checked, while at hardened state, soundness and compressive strength of the pastes were determined. In addition, the microstructure of the hardened paste was investigated using the Fourier Transformed Infrared (FTIR) technique. The results show that GHA increased water demand and delayed setting times, but improved soundness of cement paste. Moreover, compressive strength enhancement of hardened cement paste due pozzolanic reaction as evidenced by the microstructure analysis (FTIR) was observed with up to 10% GHA replacing cement. Thus, GHA is a good potential material for cement replacement in cement paste.