bluuebunny/crossref_metadata_2025 huggingface dataset:
Evaluation of a microinjection system for severe dry eye treatment
Authors: Meni-Babakidi Narcisse , Viramontes-Gamboa Gonzalo , Ibarra-Bracamontes Laura Alicia , Luna-Reyes Israel
Published: March 2021

This article presents the experimental results of a series of analysis and validation tests carried out on a microinjection system designed to deliver artifitial tears to patients suffering of severe dry eye. The microinjector has the following characteristics: high efficiency and precision, user friendly, portable (8.5 × 4.5 × 2.5 cm) and low manufacturing and assembling costs. The microinjector overcomes many of the shortcomings inherent to the manual method drip, it has a syringe reservoir to keep and deliver the artifitial tears. An electronically driven plunger pushes the solution into a capillary that transfer it to the patient’s eyes. The programmed time to deliver the tears fluid is set by the ptient through a “C” program in an Android based device. The real delivering time differs slightly from the programmed one due to frictional effects between the plunger and the syringe walls. The validation tests had the objective to quantify the time difference between the programmed and real delivering times, using as artifitial tears the Lagricel Ofteno brand, whis is the most used in Mexico. Two differentiable tests were done, in one test the plunger was lubricated with silicon oil (Ardes brand) for its compararation with the case where no lubricant is used. All test were done with an operating flow rate range of 0.13 - 60 µL/min). The results show that the microinjection system has the ability to offer high performance and precision with ± 0.191 and ± 0.137 % average error respectively for non-lubricated vs. lubricated tests.

The microinjection system can also be used for another compatible biomedical applications like chemotherapy, insulin administration, liquid drug delivery, among others adapting certain injection characteristics (flow rates and time).
Theoretical study of the open circuit voltage decay on Organic Photovoltaic (OPV) solar cells based on space radiation ionizing damage
Authors: Piña-López I , García-Ruiz K M , Barrueta-Flores C , Amador-Bedolla C
Published: March 2021

Organic photovoltaic (OPV) solar cells have progressed quite significantly as an affordable energy technology, with high-throughput roll-to-roll solution processing driving down costs to the point of competitiveness with current technologies. They potentially offer significant advantages over classical inorganic semiconductor cells; specifically, down costs, lightness, flexibility and controlled donor-acceptor film composition. Our specific interest is based on the applicability of organic photovoltaics cells for use in space based solar panels. The present work is a theoretical study of ionizing radiation effects in the organic photovoltaic structure P3HT: PCBM for total accumulated doses up to 1kGy (SiO2). We find that the open circuit voltage (Voc) varies with the accumulation of irradiation; however, other parameters such as relaxation time, short circuit current, and charge carrier density remain to first order constant. At the interface, the energetic mismatch of the molecular orbitals provides enough driving force to split the exciton in order to create free charge carriers (an electron (e-) and the corresponding hole (h+)). This is consistent with observations on preirradiation cases that depend directly on the Voc, due to carriers and quasi states; this leads to a linear recombination according to the Dose Damage Displacement (Dd) and Non-Ionizing Energy Loss (NIEL). Finally, we conclude that the organic photovoltaics will survive in a space environment up to 1 kGy (SiO2), contrary to popular belief that organics would be radiation “soft.”
Evaluation of heat transfer during the process of heating water in containers using a solar cooker box-type
Authors: Terres H , Chávez S , Lizardi A , Alvarez E
Published: March 2021

This work presents the experimental results and the evaluation of the heat transfer mechanisms by conduction, convection, and radiation that occur during the water heating process inside four containers with volumes of 250, 500, 750, and 1000 ml. using as for this process a box-type solar cooker. For the experimental measurements, a type k thermocouple arrangement was used, located in the water, the exterior surfaces of the containers, and the glass that forms part of the solar cooker cover. For the acquisition of the data perceived by the thermocouples, a Compact Field Point from National Instruments was implemented and for the measurement of global solar radiation, an Eppley 8-48 radiometer was used. The results obtained from the evaluation show that the most important heat transfer mechanism is by conduction located in the exterior glass of the solar cooker cover and the convection heat transfer in this same glass is the one with the lowest values. The evaluation of the results achieved contributes to the knowledge of the operation of solar cookers, which can contribute to the design and improvements of these solar energy devices.
LaAlO3:Pr3+ as photon radiotherapy dosimeter
Authors: Barrera-Angeles A A , Ugalde M A , Nolasco D , Gutiérrez-Márquez J G , Morales-Hernández A , Zarate-Medina J , Rivera-Montalvo T
Published: March 2021

The intention of radiotherapy is to control and cure tumor while avoiding late effects caused by radiation. High energy photon beam dose can be determined by different modalities. In this paper, dosimetric properties of praseodymium doped lanthanum aluminate exited by X-ray beams are reported. LaAlO3:Pr3+ powders samples were prepared using modified Pechinis’s method. The formations of the obtained samples were confirmed by an X-ray diffraction patterns. TL glow curve and dosimetric characteristics of LaAlO3:Pr3+ powder samples were investigated under X-ray irradiation effects. All TL measurements were made using an automated Harshaw TL reader 5500. TL glow curves were obtained using a constant heating rate 10 °C/s from room temperature up to 350°C in a nitrogen atmosphere. The dose response and minimum detectable dose (MDD) values of the samples were determined. Dosimetric characteristics of the samples were carefully analyzed. Experimental results of TL dosimetric characteristics of the powder samples appear to have potential application for high energy photon beam dose measurements.
Thermoluminescence properties of high-dose gamma-irradiated diamond films
Authors: Cruz-Zaragoza E , Marcazzó J , Pérez Ramírez E , Meléndrez R , Barboza-Flores M
Published: March 2021

Thermoluminescence (TL) properties of gamma-irradiated chemical vapor deposition (CVD) diamond films at high doses are presented. Samples of undoped and nitrogen-doped CVD diamonds were exposed to 60Co gamma sources and TL intensity as a function of the dose was analyzed. To evaluate the feasibility of using these materials as TL high-dose dosimeters, reproducibility of the TL signal, and the TL response as a function of absorbed dose from 100 Gy up to 10 kGy were studied. Furthermore, the fading of the TL glow curve was analyzed. Finally, to estimate the kinetics parameter values associated with the trap distribution in the CVD diamond, a computerized deconvolution was carried out by using the general order kinetics (GOK) model.
Gyro movement equations
Authors: Díaz P. , Cid A. , Granados J. , Velázquez A. JM , Velázquez J. A.
Published: March 2021

In this work the motion equations of a gyro with essential characteristics were constructed, where the rotor rotates to reason ψ around an axis mounted on a single universal joint, which can rotate freely around the vertical axis. The angle formed by the rotor shaft and the plane of the meridian is denoted with θ, latitude, the angle of the position on earth is denoted λ and with ωe the angular velocity of the Earth around its axis.

Based on the formulation of Lagrange, the motion equations governing this system were obtained, differential equations were also solved with the standardized Runge-Kutta method of order 4. Also, we present several phase spaces that show the temporal evolution of the system.
Research on Key Technologies of large capacity and long distance optical transmission systems
Authors: Zhou Quan
Published: March 2021

In recent years, with the rapid development of high-bandwidth applications and the rapid growth of Internet data services, the capacity of communication networks is growing rapidly. Optical fiber has become an ideal transmission medium for communication networks due to its advantages such as large bandwidth and low loss. Large-capacity and long-distance optical fiber communication networks have become the key research directions of optical communication systems. In this paper, the main technical means to achieve large-capacity and long-distance optical transmission are investigated. First, the application of orthogonal frequency division multiplexing (OFDM) technology in large-capacity transmission is briefly introduced, including its principle, main structure, advantages and disadvantages. Subsequently, wavelength division multiplexing (WDM) technology based on optical frequency comb is introduced. Finally, the methods to realize long-distance transmission are discussed, including Digital Backward Propagation (DBP), Phase-Conjugate Twin Wave (PCTW) and advanced modulation format.
Temperature control circuit design of high-precision laser diode based on type III compensation network
Authors: Tang Yu-long , He Yu-ling , Meng Yan-song , Wang Wei-wei , Zhang Rong-yan , Du Er-wang , Du Li-jun
Published: March 2021

Since the performance of laser diodes is sensitive to ambient temperature, thermoelectric cooler temperature control circuits based on standard PID temperature compensation networks are usually designed to achieve diode constant temperature control. The thermoelectric cooler time constant and thermistor thermal time constant introduced in the temperature control system will reduce the stability margin of the system. In view of this, this paper designed a high-precision laser diode temperature control circuit based on the type III compensation network, and established the transfer function model, optimized the compensation network parameter tuning method, made the phase margin of the temperature control system reach π/8, and the long-term temperature control accuracy was better than 3 mK in the ambient temperature range of 5 to 40 °C.
Block Fast FIR Algorithm and Circuit Design
Authors: Wang Di , Wu Tiebin , Guo Feng , Hao Ziyu , Li Hongliang
Published: March 2021

The performance of finite impulse response (FIR) filtering is an important index of the real-time processing ability of digital signal processing system. In this paper, various FIR filtering algorithms are analyzed, and based on fast fir algorithm (FFA), block FFA (BFFA) is proposed. A 128 order configurable FIR filter circuit with 16 order as a block is designed. The analysis of experimental data shows that the 16 bit integer FIR filter performance reaches 881.78Gop/s.
Identification circuit based on memristor
Authors: Gao Chang , Li Tong , Cao Xinzhou , Liu Na , Li Quan
Published: March 2021

Aiming at the characteristics of the memristor with memory function in the circuit, the establishment of the memristor model and the simulation of the recognition circuit based on the memristor were carried out through the PSPICE simulation software. The NiO memristor was successfully fabricated on Si substrate by magnetron sputtering method, and the typical V-I hysteresis characteristic curve was obtained. Connecting the NiO memristor to the identification hardware circuit, the physical test results show that it is the same as the simulation diagram of the recognition circuit based on the memristor, which further confirms that the identification circuit based on the memristor has the learning function.
Distributed diffusion fusion cooperative spectrum sensing based on reinforcement learning
Authors: Jiang Lijun , Zhang Xiaoge
Published: March 2021

The openness and complexity of wireless channels make collaborative spectrum sensing vulnerable to malicious users[1]. Therefore, it is very important to identify the attributes of malicious users before collaborative spectrum awareness networks make data fusion decisions. In this paper, a method combining reinforcement learning and cognitive user credit model is proposed, in which the maximum and minimum eigenvalues of signals are used as the initial information for exchange, and the whole sensing network tends to diffuse and fuse nodes with high credit. Finally, the convergence value of the whole network is compared with the decision threshold to complete collaborative spectrum sensing. By combining with consensus fusion network and traditional collaborative sensing algorithm, the proposed method can effectively improve the convergence speed of fusion network and shorten the sensing time on the premise of effectively identifying malicious users[2], so as to improve the spectrum sensing performance and make the collaborative sensing network more adaptive and stable.
Research on telemetry data compression technology based on inter frame differential adaptive run length encoding
Authors: Fenglei Shi
Published: March 2021

Aiming at the problem of massive historical telemetry data storage in flight test, a lossless compression method based on adaptive interval run length encoding is proposed. Aiming at the problem of low compression efficiency of traditional run length encoding algorithm for word data, by studying the storage characteristics of telemetry data, this algorithm automatically identifies the frame format of telemetry data, and carries out longitudinal run length adaptive interval encoding for inter frame differential data to improve the compression efficiency. The test results show that the compression ratio of the improved algorithm is improved by 58.1% and 1.5% compared with the traditional run length encoding algorithm and the inter frame differential lateral run length encoding algorithm.
Influence of Retinal Degeneration Stages on RGC Threshold under epiretinal electrical stimulation: A Modeling Study
Authors: Zheng Shiwei , Zhou Wenqi , Song Xiaoyu , Li Liming
Published: March 2021

Retinal prosthesis is an effective treatment to restore partial functional vision for degeneration diseases such as retinitis pigmentosa (RP). The persistent degeneration of the retina can influence the effect of retina prosthesis. However, how the different stages of retinal degeneration influence the retinal ganglion cell (RGC) responses to external electric stimulation remains unclear. In our present study, we established the multilayer retinal model of normal mouse and retinal degeneration (rd1) mouse in different degeneration stages (early, middle and late stage). Meanwhile, the morphology-realistic RGC models with membrane dynamics in different degeneration stages were also established. The effects of retinal structure, ganglion cell morphology and Na+ conductance on RGC threshold in response to electrical stimulation were explored. The simulation results showed that the RGC threshold of early degeneration stage was basically the same as that of the normal retina. While the thresholds of middle and late degeneration stages were both higher than that of the early stage, and the late stage showed a higher RGC threshold than the middle stage. This study would provide theoretical support for personalizing design of visual prostheses to treat different degeneration stages of RP patients.
Mapping Algorithm of Multi - code combination spread spectrum technology for Short Packet Transmission
Authors: Lu Yikun , Dou Gaoqi , Zhang Wenjuan
Published: March 2021

Multi-code combined spread spectrum (MCSS) is based on M-ary spread spectrum to improve information payload by combining multiple spread spectrum sequences, which solved the contradictions between spread spectrum gain and transmission efficiency under limited channel bandwidth conditions. This paper focuses on two mapping algorithms of multi-code combination spread spectrum and their decoding algorithms for MCSS, which transmits the information by combining multiple spreading sequences. The R-combined mapping algorithm is provided to keep the sequence orthogonal and the design complexity increases with the increase of the number of correlators at the receiver while the SVC algorithm is adopted and MMP algorithm is used to realize multi-code combination spread spectrum with increasing sequences. The BER performance of the two algorithms is compared through simulation analysis
Application of 5G+VR technology in training and teaching of integrated wiring technology
Authors: Zheng Liping
Published: March 2021

The successful research and development, promotion and application of 5G technology in the new era will have a huge impact on the various industries in society. The development of computer and network technology plays an important role in promoting the practical training. VR technology is one of the important products of information and network technology. It takes multimedia technology as the core and presents knowledge to students more vividly in an audio-visual way, which can help students better understand. The paper analyzes the application of 5G+VR technology in the training and teaching of integrated wiring technology in detail, and aims to provide help for better application of 5G+VR technology.
Data-driven based optimization for high-speed dry cutting gear hobbing processing parameters
Authors: Wu Dayuan , Yan Ping , Pei Jie , Zhou Hui , Yi Runzhong , Guo You
Published: March 2021

The formulation of gear hobbing processing parameters relies on extensive professional knowledge and artificial experience, and inappropriate processing parameters will lead to low machining precision and high manufacturing costs. In order to obtain suitable processing parameters in high speed dry hobbing gear process, Gradient boosting regression (GBR) and Generalized Regression Neural Network (GRNN) are adopted to establish a process parameter optimization model targeting gear machining accuracy and machining energy consumption. And then a method based on Differential Evolution (DE) algorithm, parameter adaptive multi-object differential evolution (AMDE), for hobbing processing parameter optimization is proposed. Machining experiment verification shows that the established gear hobbing accuracy prediction model and energy consumption estimation model have high prediction accuracy, and AMDE has strong optimization capabilities and robustness.
Measurement of Small Defect Testing Accuracy in Additive Manufacturing Alloy Using Industrial CT Method
Authors: Guo Zhimin , Ni Peijun , Dai Yuelai , Zhang Weiguo , Huang Kuidong
Published: March 2021

This article is based on the application of industrial CT testing in additive manufacturing parts. Based on the existing industrial X-ray CT inspection equipment, it aims to solve the problem of identifying small defects under the uncertainty of test results. Under the premise of removing artifacts, this paper studies the measurement methods of small defects, and analyzes the uncertainty of the test results by designing a comparison test block. This paper combines theoretical analysis and experimental research, and compares the test results with the half-width method to study the accuracy of the test method. In order to improve the accuracy of industrial CT quantitative non-destructive detection of small defects, this paper closely studies the engineering application and combines the practical application of industrial CT to solve the basic problems of key research work.
Research review about the progress of transient electronics in sensor and electronic skin
Authors: Jiang Min , Gan Hua , Xiao Jinxing , Zhu Zhiyuan
Published: March 2021

Transient electronics, a new type of electronic device, is made of degradable materials. After a programmed set period of operations, transient electronics can be partially or completely degraded when they are subjected to certain stimulus. Transient electronics can work normally without extreme conditions, and can degrade immediately after stable operation. It could supplement the limitation of traditional electronics, and could be of great interest for applications in electronic skin and sensors.
A Review of Research Topics of Safety Management Systems
Authors: Guo Chenggong , Jiang Feng , Chen Tao , Li Ying
Published: March 2021

Safety management systems(SMSs) is a systematic safety management method, which is widely used and researched all over the world. This article reviews the current literature of safety management systems, summarizes and analyzes eight important research topics at the theoretical level, practical level, and standard level, including analysis of the connotation and extension, effectiveness analysis, integration of a safety management system and other systems, steps and content of construction, evaluation, comparison and selection of standards. Furthermore, based on the above analysis results and the current status of the application of safety management systems in China, two recommendations on important research directions are proposed. The research indicates that in order to improve the application effect of safety management systems in Chinese enterprises, we should concentrate on the basic theoretical research. Three questions need to be answered urgently at this stage: “What is a safety management system (SMS)?”, “Why does it fail?” and “How to improve?”.
Study on the Construction of Safety Management System of Chinese Electric Power Enterprises Based on Systematic Thinking
Authors: Chenggong Guo , Feng Jiang , Ying Li , Yun Luo
Published: March 2021

In order to clarify the construction process and content of Safety Management System (SMS) and deepen the systematic construction of safety management of power enterprises in China, the paper analyses the current problems of SMS construction of domestic electric power enterprises. A construction method of SMS for China’s electric enterprises is proposed based on systematic thinking and system modelling method. Taking State Grid Corporation of China (SGCC) as an example, the construction model of SMS is designed based on the Hall three dimensions structure model. According to China’s national regulations and power industry safety management requirements, as well as practical experience of SGCC, ten core elements of the system were screened. The SMS operation cycle of Leadership-Responsibility-Plan-Do-Check-Act (LRPDCA) was designed based on the concept of Plan-Do-Check-Act (PDCA) and the characteristics of China’s power safety management. The results have some guidance significance to continually promote safety management capacity of electric power enterprise in the new era.
Web application vulnerability detection method based on machine learning
Authors: Hu Lilan , Chang Jie , Chen Ze , Hou Botao
Published: March 2021

In order to solve the security problems caused by network vulnerabilities, a web application vulnerability detection method based on machine learning is proposed to effectively prevent cross site scripting attacks of web applications and reduce the occurrence of network security incidents. Through the in-depth study of the existing security vulnerability detection technology, combined with the development process of machine learning security vulnerability detection technology, the requirements of security vulnerability detection model are analyzed in detail, and a cross site scripting security vulnerability detection model for web application is designed and implemented. Based on the existing network vulnerability detection technology and tools, the verification code identification function is added, which solves the problem that the data can be submitted to the server only by inputting the verification code. According to the server filtering rules, the network code bypassing the server filtering is constructed. Experimental results show that the model has a low rate of missed detection and false alarm, and the improved model is more efficient.
Challenges and Corresponding Solutions of Generative Adversarial Networks (GANs): A Survey Study
Authors: Chen Haiyang
Published: March 2021

Generative Adversarial Networks (GANs) are an innovative class of deep learning generative model that has been popular among academics recently. GANs are able to learn distributions on complex high-dimensional data which made it efficient in images and audio processing. Nevertheless, in the training of GANs, some major challenges exist namely mode collapse, non-convergence, and instability. In recent years, in order to overcome these challenges, researchers have proposed many variants of GANs by redesigning network architecture, changing the form of objective functions, and altering optimization algorithms. In this research, we conducted a comprehensive investigation on the progress of GANs design and optimization solutions. Finally, according to the classification method, we provided a problem-solving structure to solve conquer the GANs training challenges.
An Auto-segmentation and Measurement of Visceral Adipose Tissue On Ultrasound Image
Authors: Yi Shifan , Liu Paul , Liu Dong c. , Yin Hao
Published: March 2021

In order to effectively segment the visceral adipose tissue and help the doctors to rapidly diagnose the potential risks of metabolic syndrome, here we developed a deep learning-based method which is based on the U-net architecture for segmenting and measuring the visceral adipose tissue(VAT). And even no matter which orientation that the operator takes, the model can segment the visceral fat area and then use the appropriate outputs to compute the max thickness of VAT. One hundred and fourteen healthy volunteers were enrolled in this study. Ultrasound(US) was performed, and then the visceral adipose tissue was segmented and measured by the model that we use. We regard the distance behind the linea alba in the xiphoid process as the thickest visceral adipose tissue(VAT max). The dice score and accuracy are 3.46%, 96.44% respectively. In addition, compared with the manually outlined segmentation, the pearson correlation coefficient and the mean relative error (MRE) are R=0.9231 (P<0.001) and 10.12% in the measurement of the VAT max between original and output images. The auto-segmentation and measurement of visceral adipose tissue on ultrasound method demonstrate the accuracy of deep learning in segmentation and measurement of visceral adipose tissue.
Citation Recommendation based on Citation links Explanation
Authors: Zhang Yanping , Lin Dongyang , Chen Xi , Qian Fulan
Published: March 2021

With the rapid increase of scientific papers, it is difficult for researchers to obtain appropriate references. Due to the black-box property of neural network, the existing content-based citation recommendation methods are mainly embedding text into a low-dimensional space, and citation links are not interpretable (e.g., paper A cites paper B because of topic X). To solve this problem, we propose a Weighted Citation Network with Citation Links Explanation (WCN-CLE) algorithm. Because citation links mainly depends on the content, we need to explore textual reasons for citation links. Firstly, we extract word fragments through citation network information for each citation link as its explanation. Secondly, we construct a weighted HIN network with two kinds of vertex (paper and author). The weight of each edge is calculated by its word fragments. Then the query document is linked to the HIN network through author information and word fragments similarity with candidate papers. Finally, each vertex’s feature representation is obtained by network representation learning method, and recommend papers through vector similarity. Experimental results on two real-world datasets show that WCN-CLE has better performance due to its integration of structural information and semantic information.
An Adaptive End-to-end Codec based on Multi-source Fusion for UAV Equipped with 5G NSA Network
Authors: Su Yu , Cheng Qianqian , Wang Shuijie , Qiu Yuhe
Published: March 2021

This paper proposed an adaptive end-to-end codec based on multi-source fusion. Our codec adjusts the coding scheme according to the channel condition adaptively, selects deep recursion when the channel is good to obtain sufficient and effective information, and shallow recursion to ensure the transmission of key frames when the channel condition is poor. Besides, communication information is also imported into the codec through parallel branches to avoid confusion caused by multiple sources. We test on the DJI M210 UAV equipped with 5G network to verify the usability of the adaptive end-to-end codec both quantitatively and qualitatively. Under the same target detection level, our codec provides higher compression rate, and adjusts the compression rate to adapt to different conditions.
Application of weighted sample entropy in detection of abnormal signal
Authors: Zhang Hong , Lv Shengze , He Shasha
Published: March 2021

An improved sample entropy (SE) algorithm named weighted sample entropy(WSE) is proposed in this paper to optimize the problems existing in SE based on weighting. The principle of WSE algorithm is given, and the performance of it for dynamical change detection is analyzed using synthetic signal. The results show that WSE can accurately capture amplitude information and amplify the detection results of dynamical changes compared with SE and PE in the case of high complexity, but it requires a higher computation cost than the others. From all the analyses in this paper, we find that WSE has a better performance for dynamical change detection compared with the other three algorithms in abnormal amplitude.
Analysis of Object Detection Performance Based on Faster R-CNN
Authors: Li Wenze
Published: March 2021

The related regions with convolutional neural networks (R-CNN) models have been widely used in the field of object detection. Faster R-CNN significantly improves the overall performance by adding RPN, especially in terms of detection speed. However, the application of different pre-training models will result in a great difference in the performance of Faster R-CNN. This paper analyzed the performance of Faster R-CNN models based on different pre-training models and conducted a comprehensive evaluation of the performance of Faster R-CNN. The experimental results showed the accuracy and detection speed of R-CNN, fast R-CNN and faster R-CNN based on three different data sets. They can objectively and comprehensively evaluate the performance of R-CNN, fast R-CNN, and faster R-CNN.
Localization and Navigation Analysis of Mobile Robot Based on SLAM
Authors: An Juan , Mou Hairong , Lu Rui , Li Youbing
Published: March 2021

In recent years, many advanced computer technologies have appeared on the market, for example, artificial intelligence. With the maturity of artificial intelligence technology, the transformation of intelligent robots are also more perfect. The difficulty that we have always wanted to break through is to install positioning navigation on mobile robots. Through continuous efforts, the navigation and positioning technology on the robot can now be used proficiently in a known environment, but we need further research when using it in an unknown environment. In the navigation and positioning technology, it introduced simultaneous positioning and map construction algorithms (SLAM, simultaneous localization and mapping). The algorithm can learn about the surrounding environment information through the sensors carried by the robot. If this algorithm can be skillfully applied to navigation and positioning technology, I believe it will be helpful for the application of positioning and navigation technology in unknown environments.
A method for defining rule elements based on civil aircraft interface development process
Authors: Zhang Jiejing , Zhang Xinyu , Zhang Xinai , Guo Dake , Li Haomin
Published: March 2021

In the process of civil aircraft design and development, interface definition is a very important and complex process element. In this paper, a rule element definition method based on civil aircraft interface development process is proposed, and the rule element definition to support the interface development process is given. Rule elements provide useful input on structure and content for civil aircraft interface definition activities, especially for low-level interface definition activities. All levels of an interface definition can be related to rule elements, but lower-level interface definitions have the greatest amount of data, and most of the definitions are done in lower-level interfaces. For the design activities of the stakeholders in the low-level interface development process, these rule elements are equivalent to the formulation of multi-dimensiona and unified standards and requirements, so that the stakeholders of interface definition (main manufacturer and suppliers at all levels) can carry out coordinated interface development activities under such standards and requirements.
Airborne Software Data Coupling and Control Coupling Analysis
Authors: Hua Hui , Zhang Xinai , Zhao Yi , You Ran
Published: March 2021

As a part of software structural coverage, the data coupling and control coupling analysis help to evaluate the implementation of requirements and the code quality to some extent. This paper researches the data and control coupling definitions, analysis methods and the differences of requirements between DO-178B and DO-178C, thus providing reference for airborne software verification.
Research on the Feasibility and Distribution Mode of Urban Logistics Distribution by Rail Transit
Authors: Yue Shuai , Wang Yabin , Zhao Mei , Liu Yuehe
Published: March 2021

In modern economic and social development, rail transit is the lifeblood of new urbanization and high-quality development in urbanized areas. As a core element of economic development, logistics plays an increasingly obvious role in promoting economic transformation and high-quality development. Under the normalization of epidemic prevention and control, expand the comprehensive logistics distribution system and focus on the deep integration of urban rail transit in densely populated cities. It is very necessary to promote the extension of the supply chain and improve the quality and efficiency of urban logistics distribution.
Design of the stringer end of the composite centre wing lower panel in the plug-in butt joint form
Authors: Yuan Xinhao , Li Qiming , Gong Dezhi
Published: March 2021

The outer wing and the central wing of the aircraft are butted at the wing root through rib 1. The load transfer in the connection zone of the wing root is complex. In the plug-in butt form, additional bending moment will be generated, which is the most prone to damage. Based on the analysis of the force transmission in the butt joint area of the wing root, combined with the test data, this paper proves that the main failure mode of the composite central wing lower panel is the delamination failure of the stringer web at the end, and suggestions for optimal design are proposed.
A Review on Mechanical Properties of Inorganic–Matrix EBR System
Authors: Yao Jitao , Ma Pengfei
Published: March 2021

With a large number of important and commemorative historical buildings in the maintenance and reinforcement of the increasingly stringent requirements, the role of inorganic–matrix EBR reinforcement system in the existing masonry structures reinforcement is also increasingly concerned. In this paper, the mechanical properties of textile, mortar and composite materials are compared and analyzed, and the influence of different parameters on the test results is discussed. The results exhibit that the strength range of each material is obvious. For textiles, the tensile strength ranges from 1120 MPa to 5800 MPa, and the elastic modulus ranges from 55.6 GPa to 276.6 GPa. For mortar, the compressive strength is from 12.3 MPa to 80 MPa, and the elastic modulus is from 6 GPa to 39 GPa. In addition, the cracking process of composite specimens can be divided into three stages: un-cracked, crack development and cracked. All kinds of test results can not be compared with the same standard and conditions, due to the significant differences in specimen designs and loading methods, which provides the research direction for the next stage of test and theoretical analysis.
Airborne Software Change Control Process and Strategies of Civil Aircraft
Authors: Zhao Chen , Chu Yi
Published: March 2021

In the modern civil aircraft, the number and complexity of airborne software are increasing rapidly. The software may change at any stage of the development process and the change process should be under control. This article analyzes the basic unit of software change control and the configuration identification used for airborne software, then introduces a process and strategies of software change control for civil aircraft.
Science Popularization-oriented Art Design of Interactive Installation based on the Protection of Endangered Marine Life-the Blue Whale
Authors: Liu Jiahe
Published: March 2021

In today’s world, marine pollution is becoming more and more serious, and the protection of marine ecosystems and endangered marine organisms has become an important international issue. In 2012, the blue whale was officially listed on the IUCN Red List of Threatened Species. As the top predator in the ocean, blue whales are seeing a drastically decreasing population, which will break the ecological balance of the region. The interlocked food chain in the ocean means it would eventually lead to the forming of an “ocean desert”. Therefore, it is urgent to start the popularization of science to protect the endangered marine organisms for the public. Based on human-computer interaction and sound visualization, the author designs an interactive installation with the theme of “The Last Whale Sound”, aiming to increase the public’s attention to endangered marine organisms, to arouse people’s self-reflection and environmental awareness, and to make the public consciously participate in protecting marine ecosystems.
Combining AI with Corporate Governance to Enhance Operational Efficiency of Universities
Authors: Lin Chien-Cheng , Huang Ya-Yuan , Zhang Jia-Qi , Chang Shih-Feng
Published: March 2021

Since the 21st century, more and more attention has been paid to the education of college students in our country, and the curriculum reform has been actively carried out. It is necessary to cultivate students’ core quality and improve their ability to adapt to society and self-learning. Under the new situation, universities should constantly reform, update their teaching concepts, adopt the latest teaching equipment and ideas, readjust their teaching methods and plans, and provide reference for the future. According to relevant research, the administrative system of universities affects the cultivation of students’ quality and ability to a certain extent. This paper combines AI and corporate governance to explore the influence of the administrative mechanism on the operation of universities under the new situation, and puts forward some solutions and suggestions.
Learning-based Buffer Starvation Modeling for Packets Prefetching Strategies of Video Streaming Services
Authors: Su Yu , Wang Shuijie , Cheng Qianqian , Qiu Yuhe
Published: March 2021

Improving the quality of experience (QoE) of video streaming is a significant task in the wireless network scenario. Buffer starvation in the transmission process will cause playback freeze, and a certain number of packets must be prefetched before the service restarts. Taking into account the shortcomings of buffer in video streaming services, this paper proposes a deep learning-based starvation probability calculation model and a reinforcement learning-based packet prefetching model. The deep learning approach extracts the correlation between different timing inputs through the recurrent neural network module to return an explicit result and the precise distribution of the number of buffer starvation. The reinforcement learning approach leverages a better trade-off between start-up/rebuffering delay and buffer starvation by adjusting the packet prefetching strategy, so that the long-term objective quality of experience (QoE) of the video stream is optimized. Our framework can be applied to actual scenarios including finite video streaming and long video streaming transmission.
Implementation and Optimization of Data Prefetching Algorithm Based on LLVM Compilation System
Authors: Chai Yunda , Chen Mengyao , Li Jianan , Han Lin
Published: March 2021

In order to reduce the problem of mismatch between high-performance processors and DRAM speeds, current processors have added a cache structure, but the low cache hit rate also seriously affects the actual performance of the program. Data prefetching technology can alleviate the problems of memory access latency and low hit rate caused by the speed difference between high-performance processors and DRAM. Based on the LLVM open source compiler, this article first implements the data prefetch module on the Shenwei platform. This paper improves the prefetch distance algorithm, proposes a new prefetch scheduling algorithm, introduces a cost model to evaluate the prefetch revenue, and accurately determines the insertion timing of the prefetch instruction to improve the cache hit rate. SPEC2006 performance test results show that after optimization, Shenwei 1621 processor single-core can achieve a maximum performance improvement of 50%, and an average performance improvement of 11%.
A review of action recognition based on Convolutional Neural Network
Authors: Jiaxin Yang , Fang Wang , Jieru Yang
Published: March 2021

At present, the development of video action recognition is very rapid in many fields, such as video understanding, intelligent monitoring, and human-computer interaction. However, there are some challenges in the development of action recognition, and researchers have tried to put forward some explorations. Convolutional neural network (CNN) is applied to action recognition, which improves the performance of action recognition. It is divided into 3 methods in this paper. In addition, C3D, Two-stream and I3D, three classic CNN algorithms, are reproduced. And their recognition rates are 72%, 78.0% and 97.6% respectively on the UCF101 dataset.
The Study of Graph Convolutional Network for Activity Recognition
Authors: Zhu Yanrui , Ren Yuxin
Published: March 2021

GCN is an excellent single-modal machine learning model for processing non-Euclidean data, such as skeleton data. Conventional GCN only uses single-modal data as its input. When we have multiple modal data, the application of GCN will be limited. To utilize multi-modal data advantages, we propose a method to combine GCN and LSTM to extract skeleton feature and acceleration feature, respectively. To test our method, we did a lot of experiments on Cooking Activity Dataset.
LCSSA optimization for vectorization recognition rate improvement
Authors: Chen Mengyao , Chai Yunda , shang Jiandong
Published: March 2021

LLVM converts the loop to LCSSA during the loop transformation process. The loop of LCSSA has better locality and can facilitate other optimizations of the loop, but at this stage LLVM does not support some special LCSSA loops in the automatic vectorization process, in the case of external use of non-array and non-inductive variable instructions in the loop, automatic vectorization cannot be performed, which makes the compiler lose some optimization opportunities for automatic vectorization. In response to this problem in LLVM, this paper proposes an algorithm to reconstruct PHI nodes. By adding new basic blocks, reconstructing the value of PHI nodes to eliminate the influence of external use in the loop on automatic vectorization, so that the loop can be automatically vectorized. Improve LLVM’s automatic vectorization capabilities. Through the test on the TSVC test set, the vectorized recognition rate has increased by 23%.
The Framework Design of the Construction of a Comprehensive Information Management Service Platform at the Township
Authors: Yu Zhang , Pei Qiao , Xitao Huang , Liyuan Xiao
Published: March 2021

This article makes full use of geographic information and other industry thematic data, builds a township-level database and informational integrated management service platform, develops mobile APP and multiple characteristic applications, and deeply promotes the guarantee service of geographic information at the township level (sub-district office) and below, helping rural revitalization, building beautiful villages, deepening the promotion and application, and forming a township information service system that integrates government decision-making, department management, and public application, in order to promote grassroots information management, improve grassroots human settlements, scientific planning and construction, strengthen ecological and environmental protection services to provide useful references.
To explore the mechanism of action of Irpex lacteus treatment of hyperuricemia from the perspective of network pharmacology
Authors: Hongshi Bu , Xiaohuan Li , Junze Liu , Wang Renguang , Wang Shumin
Published: March 2021

Objective: To explore the active ingredients and mechanism of Irpex lacteus against HUA (hyperuricemia) by using network pharmacology and molecular docking technology. Methods: Through literature search and collection, drug-like screening, target prediction, construct a target library of chemical components related to Irpex lacteus; search and construct HUA disease target library through disease database. The PPI network of the crossover gene between the components of Irpex lacteus and HUA was constructed using STRING and Cytoscape; the GO function enrichment analysis of the crossover genes and the enrichment analysis of the KEGG signaling pathway were realized through the Metascape database; the purpose of the “target-signal pathway” network was to analyze its specific mechanism of action; molecular docking to verify the binding ability of the main active ingredients and key targets. Results: 56 active ingredients were screened, the core target of PPI network mitogen-activated protein kinase 3(MAPK3), mitogen-activated protein kinase ’(Mitogen-activated protein kinase 1, MAPK1), etc.; involved 1387 GO biological processes, 48 cell components, and 113 molecular functions; signaling pathway involved AGE-RAGE signaling pathway in diabetes complications, PI3K-Akt signaling pathway, IL-17 signaling pathway, etc; molecular docking results show that the core component tremutins A/C/E had good docking activity with each target. Conclusion: The related products of Irpex lacteus can treat HUA through multiple components, multiple targets, and multiple pathways, which could provide reference for further research and development.
A Slow-Motion Detecting Algorithm using High Order Statistic Approach
Authors: Fuqing Yuan , Lu Jinmei
Published: March 2021

Motion detection is vital for consumer electronics and the Internet of things (IOT). For a scenario where the motion is slow and gentle, the resolution of the motion sensor is critical for the detection, while the algorithm development is another critical issue to differentiate the motion signal from noise measurement. This paper investigates the feasibility of using higher order statistics kurtosis as a motion indicator. Statistical hypothesis test has been developed to assess the motion presence. Several experiments are conducted to test the feasibility and performance of the approach. The results show the approach is feasible, but with some limitations.
Application of Collaborative Representation in Audio Signal Recognition
Authors: Huang Qun.Feng. , Li Xiao.Jiang.
Published: March 2021

Feature extraction and classifier design are the main problems of acoustic signal recognition algorithms. In this paper, we extract the mel-frequency cepstral coefficients of the acoustic features of vehicles in complex scenes. Collaborative representation is introduced for the design of a classification scheme (Collaborative Representative Classification, CRC), which synthetically considers the relationship among samples. Experiments show that the proposed algorithm produces good performance in vehicle recognition for the case of a complex data set. Compared with other classification algorithms, the method improves the precision of recognition.