bluuebunny/crossref_metadata_2025_split huggingface dataset:
Research on Chaotic Digital Image Encryption Algorithm
Authors: Jia Ye , Yu-fu Zheng , Zi-wei Yang 
Published: June 2019

Abstract
In view of the problems of pseudo-randomness, complexity, short period and limited precision of traditional digital image encryption technology, this paper improves the traditional chaotic digital image encryption technology. Firstly, a random sequence is generated from the chaotic map according to the definition, and then the design process is improved according to the encryption algorithm, and finally the simulation experiment is performed. The improved algorithm uses the Henon-mapped chaotic sequence to generate the shuffle control parameters, and replaces the gray value with the improved two-dimensional Logistic map sequence, shuffles the array using the Henon map, and changes the image pixels using the improved two-dimensional Logistic map. Grayscale values, these algorithms are highly secure against exhaustive attacks, statistical attacks, and plain-text attacks. Even if the attacker knows the algorithm, it does not know the parameters of the algorithm and cannot obtain image information. The improved encryption algorithm can increase the key space and improve the security performance of the encryption algorithm. The image viewing effect is also very good, and the time is greatly shortened, which can fully meet the real-time requirements.
Research on Alignment in the Construction of Parallel Corpus
Authors: Zong Zhaorong , Hong Changchun 
Published: June 2019

Abstract
Parallel corpora are of great value in the field of machine translation and cross-language information retrieval. Benefiting from the development of machine learning and deep learning, the technology of the construction of corpus evolves from vocabulary alignment, phrase alignment to chunk alignment. The high quality of automatic bilingual chunks alignment in corpus plays an important role in the performance improvement of machine translation systems, especially in computer-aided translation systems. In the study, the degree of adhesion and relaxation is used to measure the tightness and looseness of the inter-word connection when a chunk is identified, which can be expressed by a mathematical mode. The task of chunk alignment in the construction of a parallel corpus can be described as the three steps: input bilingual sentences, segment chunks, and semantic alignment. At present, most algorithms are based on statistical methods, and the output alignment results are machine-oriented.
Identification of Interference Sources in Spiral Galaxy Images Based on Convolutional Neural Network
Authors: Wu Shiqing , Hu Tao 
Published: June 2019

Abstract
In the spiral galaxy image, the luminosity of the precursor star due to its close proximity to the spiral galaxy reaches an approximate order of magnitude, which makes the precursor stars become an important interference source in the galaxy image and makes the computer difficult to distinguish them. Therefore, it is of great significance to remove the precursor stars from the galaxy image. In this paper, a modified convolution neural network (CNN) is used to classify spiral galaxies and stars in order to find pre-star interference. Convolutional neural network (CNN) is a popular image classification technology, which is included in depth learning. It solves the problem of a large amount of data and serious non-linearity on the basis of neural network. Based on CNN, this paper studies and improves the selection of network level, the optimization algorithm, batch normalization and so on. The two types of astronomical images of the target are trained and predicted, and the classification results are very good. At present, the error rate is around 3%.
Constructions of New Entanglement-Assisted Quantum Codes
Authors: Qian Jianfa , Zhang CLina 
Published: June 2019

Abstract
Entanglement-assisted quantum error-correcting codes are considered as a new research direction of quantum coding theory. In this work, based on cyclic codes, we present the constructions of new entanglement-assisted quantum error-correcting codes. Several new families of nonbinary entanglement-assisted quantum error-correcting codes with length n=2(q-1) can be efficiently constructed.
Theoretical and Empirical Study on Risk Measurement Method Statistics and Portfolio Model
Authors: Zhu Jiale 
Published: June 2019

Abstract
The fundamental purpose of securities investment is to obtain benefits. In order to diversify risks, many investors invest many kinds of securities simultaneously to achieve the maximum returns. Risk measurement methods and portfolio model have become the major issues faced with the financial sector. This paper analyses the calculating method and applicable condition of Markowitz risk remuneration model, Arrow-Pratt risk remuneration model and Jia & Dyer standard risk model. This paper gives the investment model optimized by mean entropy and portfolio model including transaction cost. Empirical analysis shows that the portfolio model is suitable for calculating the return and risk of portfolio. According to the model, investor’s different degree of risk avoidance will form different investment strategies.
Convolutional neural network for Iceberg Classifier
Authors: Shi Zhouan , Lu Xuheng , Hou Lunqing 
Published: June 2019

Abstract
Image classification has been a popular research field in computer version, and we employ convolutional neural network to solve a practical problem that is iceberg classifier. Iceberg classifier is critical import to keep the ship safe in the ocean, because the ships can program another routine after they detect the iceberg. When radar detects an object, it cannot separate it from ship or any other solid object. The radar images contain the shape, size and brightness features. There are several ways to solve the iceberg classification problem: (1) Hough transform [1] (2) convolution neural network [2]. Convolutional neural network can obtain image features that are invisible for human beings. Convolution neural network has achieved expected performance in many image classification problems. Our experiment shows that convolution neural network can classify the iceberg from any other object and we get accuracy 96% and F1 score 96%. Support vector machine [3] achieves accuracy 79% and F1 score 78%.
Research on Microservice Anomaly Detection Technology Based on Conditional Random Field
Authors: Cao Wei , Cao Zhiying , Zhang Xiuguo 
Published: June 2019

Abstract
Recently, the existing microservice anomaly detection methods which mainly monitor the system metrics and analyze the system logs have low efficiency and consume much time. This paper proposes a microservice anomaly detection method based on Conditional Random Field(CRF). The method takes the collected system parameters such as CPU utilization, memory utilization, bandwidth occupancy as the characteristic values of the observation sequence, and labels the abnormal types of the sequences corresponding to the feature values, and then creates the microservice fault matrix. Operators can quickly retrieve the specific anomaly information of the microservice error according to the microservice fault matrix. Compared with the traditional Hidden Markov Model-based detection method, this method can find the abnormal sequence corresponding to the observation sequence in the global scope. The experimental results show that the method proposed by this paper can accurately find the faults in the microservice system, and the accuracy and recall rate are relatively high.
Research on Service Dependency Mining Technology Based on Tag Extension and Bipartite Graph
Authors: Zhang Liangjun , Zhang Xiuguo , Cao Zhiying 
Published: June 2019

Abstract
Due to the rapid development of service portfolio model on network, service computing has become a hot topic in recent years. It is important for both service management and service recommendation to clarify the dependencies between services. Tag, as a widely used network information resource in the current service field, can intuitively reflect the function, purpose and other attributes of the service, and it has become a common resource in the field of service discovery and combination. Tag sparsity, however, will reduce the accuracy of service relationship analysis. Therefore, this paper proposes a service dependency mining method based on tag extension and bipartite graph. By extending the existing tags and abstracting the combination of service and the relationship between the extension tags into a bipartite graph, dependency propagation mechanism in bipartite graph is applied to improve the comprehensiveness and accuracy of the service dependency mining. The programmable Web APIs and Mashups are used to show the validity of the service dependency mining method.
Research on Combination Forecast Model of Aerospace Relay’s Storage Life
Authors: Wang Ying , Liang Kai , Liu Qi , Zhang Ting , Li Shou , Gou Yao , Li Bao Hua , Liu Jin Ran 
Published: June 2019

Abstract
With the rapid development of China space industry, relay is widely used in aerospace control system, thus it has a higher request for the relay reliability. The space relay is stored for a long time and may have a storage life of 15-20 years or much longer. In order to ensure that the relay always keeps in the activated state, it has very practical significance to predict the storage life of relay. Firstly, a single prediction model of space relay storage life is established, such as gray system theory prediction model and neural network prediction model. Then the prediction results are analyzed and the model error evaluation is carried out. According to the results of comparison, the advantages and disadvantages are obtained and improved. Finally, the storage life combination model of space relay is established, and Matlab software is used for the simulation and prediction of gray neural network to improve the accuracy of the prediction model
High Resolution Measurement with Asynchronous Optical Sampling
Authors: Jiang Jiaxin , Abuduweili Abulikemu 
Published: June 2019

Abstract
Asynchronous optical sampling is an emerging new measuring technique that exploits the frequency resolution, frequency accuracy of frequency combs for ultrahighresolution, high-sensitivity broadband spectroscopy and time-offset measurement. This review describes principles and applications of Asynchronous optical sampling and summarizes the current state of the art. As laser technology progresses, Asynchronous optical sampling will continue to mature and could surpass conventional frequency and time measurement technology for a wide range of laboratory and field applications.
Design of Portable Reflectivity Test Probe
Authors: Ping Wei , Lewu Deng , Lei Zhang , Peng Cui 
Published: June 2019

Abstract
This paper introduced the design of a portable probe which can measure the reflectivity of the surface radar stealth coating. By using swallowing pulse in the design of variable frequency division phase-locked frequency synthesis technology to microwave circuit, automatic control circuit and the H horn probe integration, solve the rigid connection deformations of RF cable and adapter vulnerability caused by the phase and impact the measuring accuracy of standing wave change. With the special design of the new probe, it has the characteristics of high stability, good repeatability, small effect of environmental temperature, excellent reliability and automation.
Research and Design of Block Cipher Special Instruction Set
Authors: Chang Zhongxiang , Dai Zheng , Song Wei , Zhu Hang , Chen Mengfei 
Published: June 2019

Abstract
The existing instructions are used to implement the block cipher algorithm with low efficient. So this paper classifies the operations in the cryptographic algorithm, and analyses the characteristics of bit width, combination and parallel mode in the cipher algorithm of different operations. Further develop the parallelism of S-box and shift instructions, improve the hybrid computing ability of arithmetic operation instructions, research and design new types of instructions for data position transformation, such as extract shift, shift insertion, data grouping and data mixing. At the last, this paper implements the cipher algorithm with the new instruction, such as DES, IDEA, BEST and other block cipher algorithms. The number of instructions is 14% ∼ 35% of Haswell processor, and 40% to 68% of the COBRA cipher processor.
Design of Software and Hardware of Analog Display Board Based on RS485 Communication
Authors: Pengchong Zhang , Xianzhou Feng 
Published: June 2019

Abstract
As an important human-machine interaction component in the ship damage control system, the analog display board has a large number of indicator lights arranged on the board. But meanwhile, the indicator lights are in different working states and need to be controlled by multiple driving circuit boards. Thus, the application of RS485 bus communication can effectively solve the problem of communication between the controller side and multiple driving circuit boards. And the multiplexing of output ports on each driving circuit board will be regarded as a pragmatic approach to solve the numerous indicator lights that are in different working states on the board.
Research on Technical Architecture and Application of Big Data Cloud Platform for Electric Power Measurement
Authors: Huaiying Shang , Yan Liu , Angang Zheng , Songfeng Qin , Yong Wang , Wulei Zhang 
Published: June 2019

Abstract
This paper studies the technical architecture and composition of the cloud computing platform. The data types and data source related to the big data of the power energy measurement are discussed. The design of the large data application service scene of the power energy measurement is discussed in combination with the technical targets and business objectives. Finally, the development of cloud platform and its application in business field are prospected.
TeaBOT Order Packaging Machine Design
Authors: Zhang Qiao Ling , Ai Ting 
Published: June 2019

Abstract
A Circuit design for meeting the rules of Tea Dispensing Machine, To achieve create data objects are what actually push the data objects to the database. Weight Sensor Load Cell and Motor Controller for The Raspberry Pi communicates both with the local hardware and with the database in order to dispense and complete orders as they come in.
Spectrum Allocation Based on Simultaneous Wireless Information and Power Transfer in Cognitive Radio Networks
Authors: Shi Qiuju , Li Jianbin 
Published: June 2019

Abstract
This paper proposes an incentive simultaneous wireless information and power transfer (SWIPT) scheme for cognitive radio networks, wherein the secondary user (SU) provides wireless power transfer for the primary user (PU) in the exchange for partial bandwidth of the latter. To enable the proposed scheme, both the secondary transmitter (ST) and the primary receiver (PR) are equipped with multiple antennas. Specifically, SU helps to charge PU via adjusting its beamforming vector and PR harvests energy with a subset of its antennas; as a reward, PU allocates part of its bandwidth to SU. Our goal is to jointly optimize the beamforming vector of SU, the bandwidth allocation and covariance matrix of PU, such that the transmission rate of SU is maximized and meanwhile PU’s requirements in transmission rate and energy are satisfied. This optimization problem is non-convex. To handle this non-convex problem, we decompose it into two independent subproblems. One is to optimize the covariance matrix, the other is to optimize the beamforming vector of SU as well as the bandwidth allocation of PU, which is divided into a two-layer optimization problem. In the inner subproblem, we obtain the optimal beamforming vector for any given fixed bandwidth allocation, while in the outer subproblem we propose a gradient based algorithm and obtain the optimum bandwidth allocation. Numerical results are given to show the achievable system performance with varying parameters and also the convergence of the proposed algorithm.
Research on 4G And 5G Authentication Signaling
Authors: Song Lei , Xu Zhan , Tian Zhigang , Chen Jinhui , Zhi Ruxin 
Published: June 2019

Abstract
In recent years, the development and standardization of 5G networks have received extensive attention. 3GPP officially confirmed that Service-Based Architecture (SBA) is the unified infrastructure of the 5G core network (5GC). The Service-Based Interface (SBI) is an important part of the SBA for interaction between network function services within the 5GC. The fifth generation mobile network will support a range of use cases and requirements that are completely different from traditional 4G networks, such as providing a high level of authentication mechanisms. This paper is organized as follows: First, we compare the difference between 4G authentication and 5G authentication in three aspects including the 4G architecture, authentication process, and communication protocol stack, then implement the simulation environment, and finally evaluate the performance by comparing the delay.
Temporal Convolutional Networks for Anomaly Detection in Time Series
Authors: He Yangdong , Zhao Jiabao 
Published: June 2019

Abstract
Convolutional Networks have been demonstrated to be particularly useful for extracting high level feature in structural data. Temporal convolutional network (TCN) is a framework which employs casual convolutions and dilations so that it is adaptive for sequential data with its temporality and large receptive fields. In this paper, we apply TCN for anomaly detection in time series. We train the TCN on normal sequences and use it to predict trend in a number of time steps. Prediction errors are fitted by a multivariate Gaussian distribution and used to calculate the anomaly scores of points. In addition, a multi-scale feature mixture method is raised to promote performance. The validity of this method is confirmed on three real-world datasets.
Research on the Performance Assessment of Teaching Cloud Platform Based on Fuzzy Comprehensive Evaluation
Authors: Yang Yi , Song Yan 
Published: June 2019

Abstract
Teaching cloud platform is a complex system in which enterprises, teachers, experts, and students participate together. The quality of teaching platform based on cloud computing is directly related to the normal development and effect of teaching work. According to the principle of comprehensive evaluation of an information system, the performance evaluation index system model of teaching cloud platform is first constructed. Then evaluation research with fuzzy comprehensive evaluation method is conducted on the system. Finally, experimental verification on an example is completed.
Research on Multi-wavelength Fiber Laser Based on Nonlinear Effect
Authors: Lv Xiao-Guang , Liao Tong-Qing , Yi Yan 
Published: June 2019

Abstract
A multi-wavelength erbium-doped fiber laser (MWEDFL) is introduced, which uses highly erbium-doped fiber (EDF) as the gain medium and uses the nonlinear effect of the single mode fiber to suppress the mode competition. In order to obtain higher side mode suppression ratio and flatness, a nonlinear fiber loop mirror is added to the structure. The results show that a stable multi-wavelength laser with 16 lasing wavelengths and a side mode suppression ratio (SMSR) higher than 30dB is obtained.
The simulation of Active Disturbance Rejection Control for the temperature control in space environment
Authors: Ning Juan , Shao Jing-yi , Zhou Ying , Wang Zi-juan 
Published: June 2019

Abstract
In order to improve the temperature control effect of nonlinear, large time-delay and inertia space environment simulation equipment, and to solve the contradiction between heating rapidity and overshoot, this paper introduces the Active Disturbance Rejection Control algorithm into space environment simulation temperature control. Based on the platform model, Active Disturbance Rejection Control controller was designed, and the cascade control model of the heat sink gas-nitrogen temperature space environment simulation equipment was established. The cascade control system was simulated on the MATLAB software platform, and the specimen was raised from 0 °C to 100 °C. The step response rise time was about 4000 s. The specimen rise temperature rate is about 1.5°C/min, and the temperature control process is smooth and there is no overshoot. The simulation shows that the Active Disturbance Rejection Control can effectively improve the space environment simulation temperature control effect.
Integrated VCSOA and PIN with high sensitivity
Authors: Dong Zhixing , Li Xun , Wang Heng , Zuo Chengliang 
Published: June 2019

Abstract
An integrated vertical cavity semiconductor optical amplifier (VCSOA) and PIN photodetector was proposed in attempting to raise the sensitivity in high speed fiber-optic communication systems. Two slightly different structures have been studied under this configuration. For the cascade and the resonance structure, our simulation results showed that their sensitivity could reach -33dBm and -36dBm at a bit rate of 10Gb/s, respectively. We also managed to fabricate the cascade structure and demonstrated a 7dBm improvement on sensitivity as compared to the conventional PIN photodetector.
Inverse Designed Ultra-compact Broadband High-order Mode Filter
Authors: You Guoqing , Gao Dingshan 
Published: June 2019

Abstract
Utilizing the inverse design method of nonlinear direct-binary-search (DBS) optimization algorithm, we designed an ultra-compact broadband high-order mode filter on silicon-on-insulator wafer. The incident TE0 mode is prohibited to pass through the high-order mode filter while the TE1 mode can pass with low insertion loss. The footprint of this mode filter is only 1.56 μm × 2.4 μm. Numerical simulation shows that the insertion loss of this mode filter is lower than 0.26 dB and the extinction ratio is lower than 24.5 dB in the wavelength range from 1500 nm to 1600 nm. The insertion loss at the centre wavelength of 1550 nm is only 0.18 dB.
Three-dimensional Acoustic Target Surface Reconstruction Method Based on Marching Cubes
Authors: Liu Jingyang , Zeng Xiangrui , Xue Huanhuan 
Published: June 2019

Abstract
Marching Cubes is an isosurface reconstruction algorithm based on volume data. In order to solve the problems of low resolution, rough surface, insufficient texture and stereo sense in the process of three-dimensional acoustic target’s visualization, a method based on Marching Cubes is used to reconstruct the surface of three-dimensional acoustic target in this paper. By constructing the minimal cube in acoustic data field, determining the connection mode, vertex coordinates and normal vectors of triangle elements in the cube where the target contour lies, we establish the target’s three-dimensional surface model, and the reconstruction of three-dimensional acoustic target is realized. The performance and validity of the method are validated by the sea trial data from three-dimensional imaging sonar, and the performance of the method is tested by multi-resolution data, and a three-dimensional surface model of buried target is constructed based on the sea trial data. The results show that the surface reconstruction technology of three-dimensional acoustic target based on marching cubes algorithm has the advantages of simple structure and less computation, and the time-consuming of the algorithm is proportional to the number of sampling points. In the process of three-dimensional acoustic image visualization, surface reconstruction technology can effectively improve the stereo sense and recognition of buried targets.