DEStech Transactions on Computer Science and Engineering
Research on Apple Image Segmentation in Natural Environment Based on Deep Learning
To accurately identify apples from the complex background in the natural environment and help the apple harvesting robot harvest apples accurately, an improved apple image segmentation algorithm based on Deeplabv3 framework is proposed, which is named as AppleDNet. Using the famed Deeplabv3 algorithm, combined with Atrous convolution, Depthwise separable convolution and transfer learning, not only can achieve more accurate segmentation results but also improve segmentation speed. In addition, the traditional image filtering algorithm is adopted to obtain a smoother segmentation image and effectively eliminate the image stitching trace. The experimental results demonstrate that the performance of the proposed method is superior to the original Deeplabv3 and other popular mainstream image segmentation algorithms, with an overall accuracy of 97.90%, which has certain significance and advantages in practice.
Optimized Apriori Algorithm Description and Application in Vehicle Fault Phenomenon Correlation Analysis
This paper proposes an optimized Apriori data correlation analysis algorithm and describes it, and evaluates the results of the model in the correlation analysis of vehicle fault phenomena. The algorithm reduces the load of I/O interface and improves the computational efficiency by optimizing the number of frequent itemset and pruning In the data mining process. The algorithm is applied to the correlation analysis of common faults in vehicle engine system. The optimized traversal method enables it to quickly find frequent patterns, correlations and causal structures among fault data sets, and detect potential correlations among faults, which achieves better application effect.
Signal Adaptive Control of Isolated Intersection Based on Type-Two Fuzzy Control
In this paper, the signal control problem of isolated intersection during peak period is studied based on the type-two fuzzy control method to reduce the vehicle delay of isolated intersection. Firstly, the traffic flow model and evaluation index model of isolated intersection are established, and the factors of saturation flow rate and lane length are fully considered. In order to relieve the traffic pressure effectively, a type-two fuzzy controller is proposed for the signal control method, which solves the coordination and dynamic uncertainty problems in the traffic of isolated intersection. By using adaptive genetic algorithm to optimize the parameters of membership function in the type-two fuzzy controller, the parameters of the type-two fuzzy controller can be adjusted in real time according to the change of traffic flow, so that the controller can achieve adaptive control effect of traffic signals. At last, the simulation results show that the type-two fuzzy controller designed in this chapter has a better control effect in the peak period of traffic flow and reduces the vehicle delay of isolated intersection.
Research on Seismic Signal Classification Based on Time-Frequency Map and Deep Learning
Time frequency analysis is an effective method of processing non-stable signals, and this paper attempts to introduce the combination of time-frequency graph and deep learning neural network to study the classification of seismic signals. The short-term Fourier transformation, wavelet transformation and S transformation were used to obtain the timefrequency graph in seismic signal processing, and the good performance of image feature extraction ability was used by deep learning neural network, and Resnet50 was used to classify the results. The combination of timefrequency graph and deep learning neural network can effectively classify seismic signals, and from the classification accuracy, the combination of S transformation and Resnet50 network reached 89.82%, which is more superior.
A Practical Q/V Band Smart Gateway Diversity Scheme for Very High Throughput Satellite Systems
The use of Q/V band feeder links and Ka band user links is a feasible solution to support the next iteration of High Throughput Satellite. The gateway transmit diversity technique is a way to compensate the rain attenuation of Q/V band feeder links. This paper analyzes a practical combination scheme that combinates N-active (K=2) with N+1 diversity method in detail from the working principle, gateway handover status transfer process, evaluation of system availability and implementation complexity. Compared with the existing N+P scheme, the proposed scheme can provide higher system availability and more stable user experience under the condition of properly increasing the complexity of payload design. Compared with N-active scheme that has been reported, it is much easier to implement in engineering and more cost-effective. As a result, the combination scheme is an optimized solution based on a tradeoff between performance improvement and complexity of the payload.
This paper proposes the TransE-CBA (TransE Based On Improved Bernoulli And Adam) model, an improved TransE model. We used an improved Bernoulli distribution sampling method to improve the accuracy of negative samples, and used the Adam algorithm to update the gradient to improve the performance of the algorithm. Experiment result shows that, on the FB13 and WN18 datasets, the TransE-CBA model has a lower average ranking score (MeanRank) than TransE as a whole, and the proportion of the top ten triples (HITS@10) Higher, better sorting effect.
Cardiology Prediction Based on Machine Learning
Heart disease is an important disease that endangers human health, with a high mortality rate. Machine learning assisted diagnosis of medical data is a hot topic, and it has made great contributions in predicting patient outcomes and reducing mortality. Therefore, based on the heart disease index data, this paper uses Decision tree model, Clustering model, and Naive Bayes model to predict whether or not having heart disease. The results show that the Naive Bayes algorithm has better prediction accuracy and can assist doctors in diagnosis and treatment.
Distance Classifier Ensemble Based on Intra-Class and Inter-Class Scatter
Distance classifier ensemble method based on Intra-class and Inter-class Scatter is proposed in this paper. By Bootstrap technology, the training samples are sampled repeatedly to generate several subsample set, define Intra-class and Inter-class Scatter matrix with subsample set, train subsample set with scatter matrix, generate individual classifier. In the classifier ensemble, the results are integrated with the relative majority voting method. Experiment is tested on UCI standard database, the experimental results show that the proposed ensemble method based on Intra-class and Inter-class Scatter for distance classifier is effective, and it is superior to other methods in classification performance.
Multi-Objective Evolutionary Algorithm for Path Optimization of Urban Express Vehicles
In view of the actual situation of delivering express delivery in the city. Put forward five objectives: the number of vehicles, total distance, maximum working time, early delivery time, delayed delivery time. Also designed three-stage multi-objective genetic algorithm. A large number of solutions were randomly generated in the first stage of the algorithm, and the approximate Pareto front was quickly found from the solution set with the extreme solution and elite strategy, while the local optimization algorithm is used to optimize the extreme solution. The second stage is divided into multi-objective problems according to the importance of the target, and the path of the unified distribution station is optimized by local optimization algorithm to obtain the relative optimal solution. The third stage corrects the obtained solution with mixed neighborhood, which makes the final solution meet the requirements of express delivery, and solves the occasional local optimal solution problem. Experiments show that this algorithm is superior to the two commonly used algorithms in multi-objective express delivery scenarios.
Design of Wideband Communication Waveform for Swarm UAV Warfare
In order to improve the battlefield survivability and information reliability of swarm UAV (unmanned aerial vehicle) data link network, the signal waveform was redesigned in signal time domain and frequency, combining with symbol interleave and LDPC encoding. The physical layer design of the terminal machine was optimized, the collision probability of the signal was reduced, and the transmission time delay of time-sensitive information was reduced.
Synthesis of Cross-Coupled Resonator Filters Using Optimization Techniques
SolvOpt was a method to solve the local extremum of nonlinear objective function. A single local optimization method based on SolvOpt that synthesizes coupling matrix for cross-coupled microwave filters was presented. In order to solve the global minimum value of cost function, the setting rule of SolvOpt initial value was given, SolvOpt method simplified the process of synthesizing coupling matrix and provides fast convergence and good accuracy to find the final solution, compared hybrid optimization methods. Last, application examples illustrate the excellent performance and the validity of this method.
The system uses STM32 as the main control SCM, esp8266 as WiFi module, WiFi receives and processes the control signal from mobile phone, transmits the signal through the serial port communication of SCM, so as to realize the mobile phone control motor drive, and LCD module displays the current status of the car. L293N is used as the motor driving module, and Bluetooth is used to send instructions to control the movement track of the car. The system used the modular design, through making and debugging the system, it runs well. The system can be better applied in the wireless communication control, and has a good reference for the unmanned driving and wireless short distance control.
Research on the Design of Virtual Experiment Platform of Product Appearance Structure Based on Emotion Measurement
This paper mainly studied the influence of the design of virtual experiment platform on the users' emotional state and learning achievements, and explored the relationship between the three. The routine methods of emotion elicitation and measurement were studied. The emotion of users was elicited by different interaction design and visual design, and the emotion state of users was measured by SAM. Through the experiment, we got the conclusion that the design change will affect the emotion, and the emotion valence and the learning achievement are positively related, and provide the theoretical basis for the subsequent platform design.
Evaluation of Product Texture Learning Platform Based On Fuzzy Evaluation
In order to better design the product texture learning platform, this paper designs the user experience evaluation scheme and process of the product texture learning platform based on the fuzzy comprehensive evaluation method and user experience measurement. User experience evaluation is divided into three dimensions: performance measurement, visual style measurement and cognitive measurement. Quantitative data of user experience is obtained through task experiment and questionnaire. Based on the fuzzy comprehensive evaluation method, the fuzzy comprehensive evaluation factors are constructed, the evaluation index system of the first and second level indexes is calculated, the interface evaluation value of the product texture learning platform is obtained, and the interface design scheme with the highest evaluation value is selected.
Artificial Fish Swarm Algorithm Based on Tabu Search
In this paper, through the analysis of artificial fish swarm algorithm, the algorithm is effectively improved. Tabu search is added into the artificial fish swarm algorithm, and Tabu search table is set, so that the artificial fish swarm algorithm can effectively avoid falling into the local optimization when searching for the optimal solution, which speeds up the later convergence speed and improves the performance of the algorithm. The simulation results show that compared with Tabu search algorithm and artificial fish swarm algorithm, the improved artificial fish swarm algorithm has obvious improvement in convergence speed, calculation accuracy and jumping out of local optimal ability.
The Design and Implementation of Handicraft Trading Platform Based on Intelligent Mobile Terminal
At present, the marketing channel of handicrafts is single, and there is no professional platform related to handicrafts, so a handicrafts trading platform based on intelligent mobile terminal is designed and developed. The platform consists of the client and server. Users log on to the platform through the smart mobile client, after which they can publish works, buy works, post comments in works, find works by category, or follow the authors they like. The server users MySQL to store data and information. The users on the trading platform can be both sellers and buyers, who gather for their hobbies and specialties. Through this platform, users can learn and communicate with each other to improve their skills, so it plays a supporting role in the inheritance and development of craft skills.
On the Cybernetics of Artificial Personality: Correlating with Human Traits
George and Mary (G&M) is a US patented cybernetics application of two talking heads which uses a repertoire of sentences to generate artificial conversation with no linguistic analysis or parsing. The underlying design assumption of G&M is age dependence: The artificial personality follows Age Trend Classification (ATC) model with four complex dimensions. The idea of adult age dependence contrasts with main currents in academic psychology, which assume a substantially constant personality in adulthood. The Big 5 personality traits are widely used as a psychological personality model, part of their popularity is the free availability of evaluation questionnaires. This work is a correlation study between four ATC and five Big 5 traits, taking into account age dependence, so that correlation is represented graphically as profiles rather than single values of correlation coefficients. The practical consequences of validated artificial personality include customized man-machine interaction to the age and personality of the users and targeted internet marketing.
Design and Application of Intelligent Epidemic Prevention Monitoring System Based on Behavior Track
The novel coronavirus pneumonia is highly infectious and has a long incubation period. In order to solve novel coronavirus infection in enterprises, institutions and communities, such as detection and monitoring of early and latent period of pneumonia, contact personnel search and other issues, an intelligent epidemic prevention monitoring system has been developed based on the technologies of no body temperature detection, personnel positioning trajectory analysis, epidemic information filling, data analysis and intelligent alarm. The system has functions of filling in body temperature reports, reworking information, daily attendance cards, epidemic analysis reports, suspicious personnel contact and tracking, etc. it helps to report and isolate patients for treatment timely, and provides powerful data support for comprehensive monitoring of regional epidemic situation, effectively protecting people's health.
Active and Passive Combined Identification Approaches for Industrial Control Devices
Obtaining a complete device inventory is important for securing industrial control systems. For that reason, we developed an industrial control device identification method based on the combination of active and passive approaches. The main tasks of identification method consist of device level identification and specific device information acquisition. Device level identification algorithm, particularly with IPlayer data pre-processing, helps to obtain device types in a passive way, distinguishing between PLCs and non-PLC devices in a short time. After that, we use the active method to further obtain the details of different types of devices. Experimental results verify the effectiveness of this method.
Research on the Reform Path of Engineering Education Curriculum System in Local Universities Under the New Engineering Background
The traditional curriculum setting mode is still the bottleneck restricting the reform of engineering education in local universities. The curriculum setting framework of the "discipline" system occupies a dominant position, resulting in the inability to connect the training objective, curriculum objective and curriculum system. Under the new engineering background, the reform of engineering education in local universities is promoted. Curriculum system reform is the basis of action plan, According to the principle of order, completeness, appropriateness and testability, handling the relationship between the theoretical courses and practical courses, branch courses and comprehensive courses, compulsory courses and elective courses, explicit courses and implicit courses, innovation education courses and entrepreneurship education courses, that is conducive to promoting the transformation and development of local undergraduate universities.
We found that the Multi-data-type Interval Decision Diagrams (MIDD) approach proposed by Ngo et al. has some flaws: the way in which the critical mark of an attribute is represented does not retain the critical information, definition of the internal node is not entirely correct, and there are bugs in the corresponding algorithms. The first flaw could lead to potential missing attribute attacks, the second one wastes resources, and the last one makes the decision diagrams inconsistent. Two solutions were proposed to fix the first flaw. The first solution is to expand the scope of representation of internal nodes from only normal attributes of subject, object, operations, and environmental conditions to other required elements so that the critical attribute marks, obligations and/or advices, etc. are also represented by nodes. The second solution is to bind the critical mark of an attribute to its value. For the second flaw, corresponding definition was revised. For the third problem, a debug suggestion was made. The corresponding decision diagrams showed that the proposed schemes can overcome these problems of the MIDD approach.
An Improved Ant System Algorithm for the Ship Lock Arrangement Problem
With the fast development of the inland waterway transport and the increasing of quantity ships, it is obviously exposed the deficiency of inland river ship locks navigation capacity. In order to improve the ship lock navigation capability, to ensure convenient, safe, stable and orderly navigation through the ship locks, this paper established the improved ant system algorithm for the ship lock arrangement, and implemented corresponding algorithm through further design. The calculation results show that the improved ant system algorithm is effective in application of the ship lock arrangement.
Performance Evaluation of Aerospace Service Network Based on Entropy Weight Set-Pair-Analysis
The Aerospace Service Network (ASN) provides communication of voices, video, data. Its performance is the key to satellite launching. In order to comprehensive assessment of Aerospace Service Network’s performance, this paper presented evaluation index based on network analysis data and calculated index weight by entropy method. Furthermore, a network performance evaluation model based on interval number Set-Pair-Analysis is established. The analysis and comparison showed that this model is objective and effective, and it provides decision support for network maintenance.
Research on the Semantic Architecture of Cultural Heritage Images Based on CIDOC CRM
An image is a visual medium that describes information about objects. The amount of data n in cultural heritage images is constantly amplified in the process of historical development and circulation. It has been significant challenges. The research is based on the international standard ontology reference model CIDOC CRM in the field of cultural heritage. It designs Semantic ontologies and specifications from the perspective of describing, correspondence paths and semantic architecture. The aim is to integrate and correlate the information of cultural heritage images with semantic information. And facilitate the integration and exchange of image information for traditional humanities and social science research.
Research and Implementation of EM Clustering Algorithm Based on Latent Variable Mining
Clustering analysis is one of the hot research fields in data mining. EM algorithm is an effective method to realize maximum likelihood estimation, which is mainly used for parameter estimation of incomplete data. It greatly simplifies the likelihood function equation by assuming the existence of latent variable, while maximum likelihood estimation is a commonly used parameter estimation method, and the EM algorithm makes its application more extensive. This paper takes clustering algorithm as the main research object, introduces the basic idea of maximum likelihood estimation, describes the basic theory of EM algorithm, and realizes EM algorithm. The experimental results show that compared with the traditional clustering algorithm, the EM algorithm has better convergence and clustering ability.
Research on Model and Algorithm of User Access Pattern Data Mining
The era of big data has come. Today, all kinds of information and data are showing explosive growth. Internet activities of different scales are struggling to catch up with the pace and pace of the development of "big data. This paper uses time series mining algorithms, and uses Microsoft's data mining tools to model the data sets collected from data halls, so as to discover the user's online behaviour patterns and potential online rules within a certain period of time. we made reasonable suggestions for the scientific management of the campus network. A new clustering method based on the improved Kohonen self-organizing feature mapping neural network is proposed. A Gaussian-shaped membership function has introduced to output several neurons with a degree of membership greater than the threshold, thereby solving the problem of mining users' multiple interests.
Research on Editions Digitization of Ancient Books Using IIIF and TEI—With Tokyo University “Water Marginâ€ Various Editions as an Example
After more than 30 years of development, the digitization of ancient Chinese books has accumulated a lot of resources. However, the construction of various institutions lacks standards, and it is difficult to exchange and reuse resources and technologies. In order to alleviate the dilemma of version research in the digital construction of Chinese ancient books, this paper uses the literature research method and case study method to analyze the digital practice of the engraved versions of the Water Margin at the University of Tokyo in Japan, discuss the significance of the application of IIIF and TEI, and propose the resources of Chinese ancient books Suggestions for improving digital construction.
Research on Electric Kettle Temperature Control System Based on MATLAB/Simulink
Constant technology control has been widely used in modern agriculture and industry and daily life, control performance affects the safety, the industry productivity and product quality. Based on MATLAB/Simulink software, take the electric kettle as the control object, the simulation model of constant temperature control system is proposed in the paper, the PID controller is used to calibrate the system, and realize constant temperature control of electric kettle. The simulation results show that the PID controller is used to control temperature, which reduces the time of overshooting and adjusting, improves the control accuracy and system reliability, and has practical reference value.
Digital Watermarking Algorithm Based on Chaotic and Wavelet Transform
To protect the copyright of multimedia data effectively, the adaptive digital watermarking algorithm is presented in this paper, which based on chaotic sequence and two-dimensional wavelet transform. Firstly, a chaotic sequence generated by Logistic chaotic map is utilized to encrypt watermark image. Then the strength and position of watermark embedding are obtained by discrete wavelet transform of host image. Finally the encrypted watermark is embedded in the host image. The experimental results show this method has better effect: the watermark is invisibility and robust against common image. It can protect multimedia data effectively.
Design of Visualization System for Horizontal Transportation Operation of Container Terminal
Aiming at the problem of resource allocation and planning of container trucks in container terminals, the visualization system for horizontal transportation operation of container terminals is designed based on virtual reality technology. The system mainly includes task allocation module, statistical analysis module and visualization module. Based on the real-time communication interface, the synchronous operation of physical scene and virtual scene is realized, which is convenient for remote and real-time control of field operation; based on the principle of the shortest total operation time, the vehicle transfer task is allocated to maximize the resource utilization; with the FCFS (first come first service), priority level and other scheduling strategies, the vehicle path planning is realized to avoid accidents such as collision; through statistics and analysis of data, workers can get real-time information such as vehicle status and total working hours. The scale-down experiment is designed to simulate the container transfer operation of the terminal, which verifies the function of the system. The overall solution of horizontal transportation operation for the container terminal is provided, which can promote the intelligent construction of the terminal.
Research on Intelligent Community Home- Based Elderly Supporting System Based on Blockchain Technology
The Aging of the Population has become a major challenge facing the community of shared future for mankind, and solving the problem of old-age care in the context of population aging has become an unavoidable social problem and a worldwide issue. In view of the problems existing in the model of community home-based elderly supporting in China, combined with the characteristics of decentralization and non-tampering of blockchain technology, the inevitability of the application of blockchain technology in the field of elderly supporting and its specific application form in Intelligent community are analyzed. The Intelligent community home-based elderly supporting system based on blockchain technology realizesâ€ providing for the elderly and enjoying the fun", and provides data support for the development management and service quality monitoring of the industry of elderly supporting.
The Analysis of Engine Noise and Noise Reduction Measures
With the rapid development of automobile industry, the impact of engine noise on the social environment and human body can’t be ignored any longer. Noise pollution has become an important source of environmental pollution. This paper analyses the harm and classification of engine noise, putting forward noise reduction measures of the engine in view of the increasingly serious noise pollution. The noise reduction technology of engine plays an important role in the rapid development of automobile industry.
Advantages of Interactive Public Service Advertising and Analysis of its Audience Preferences
The propose of this article is to research the presentation and spread advantage of public service ads; exploring the opportunities and challenges of interaction methods used in public service ads; researching weather interaction public service ads can set up information communication with audiences by sensory contact and make efficient message communication. The article mainly research and analyse the benefits of applying interaction techniques in public service ads by case analysis and questionnaire survey. Article also researches the variation of audience liking in different religions. The conclusion of this article includes a widely interaction technique research like facial recognition, cloud databases, virtual reality and augmented reality. Researching how to set up interactive information communication with audience form diversity sense and dimension to meet people's needs for the development of public service advertising. The innovation of this article lies in the combination of interactive technology research and public service advertising communication, and the combination of interactive public service advertising audience and regional differences research. The application of interactive technology is an inheritance and development of the traditional public service advertising, which make the public service advertising information more vivid in the eyes of the public. At the same time, it also enhances audience’s initiative to receive information.
Regression Method Based on ACE for Humidity Measurement on Colorimetric Sensor Array
Colorimetric sensor is designed for indicating category or quantity of some substance via colour changing. It is essential to establish a mapping that can convert colour information into measurement. In this paper a regression method was proposed for relatively humidity measurement on a type of phage-based colorimetric sensor array with multiple array units. The method was based on alternating conditional expectations (ACE) algorithm, dealing with extracting features from highdimension colour information. And support vector regression (SVR) was applied to achieve humidity measurement. Compared with extracting features by PCA, the proposed method has better accuracy of recognizing relative humidity beyond 0.85 when dimensions of colour information increase. It will enable colorimetric sensor array for quantitative measurement under high-dimension colour information.
Study of the COVID-19’s Impact on the Online Customer Flow of Daily Commodities: A Big Data Approach
The Covid-19 pandemic has hit the brick-and-mortar business hard, but how would it affect the online business? The research group collected big data on the customer flow of 1,000 daily commodities for two weeks before and after the pandemic outbreak from Taobao online shopping platform. It was found that: the Covid-19 has caused a significant negative impact on the online customer inflow, and its overall growth rate decreased. The products related to personal care, gifts and business stationery experienced the most significant decline, while daily necessities maintained a relatively stable customer flow, with little or no decline. In contrast, the products related to pandemic-control exhibited substantial growth in both customer flow and page views. Accordingly, the research group believes that developing contactless logistics and contactless production, building a time-space separation balanced supply system for pandemic-control products, and promoting altruistic social spending are necessary countermeasures to restore the negative impacts of the pandemic on online business.
Design and Research of Key Technology of Coriolis Flowmeter’s Signal Processing System
This paper innovatively presents DSP processor- TMS320F28335 and CYCLONE series FPGA-EP3C16F484 as a dual-core processor to design Coriolis flowmeter’s signal processing system. This paper introduces key techniques of Coriolis flowmeter’s signal processing system in details from hardware to software, using phase difference based on DTFT with negative frequency and sliding DTFT to detect phase difference, then give then give Cumulative mass flow measurement results.
Design of Brushless DC Motor Controller with the Hall Position Sensor
In the paper, the controller uses a MCU (dsPIC30F) to detect the position of the BLDCM by Hall Position Sensor, which can get the corresponding coding value. Each combination of values represents the current position of the BLDCM rotor. When the rotor position changes, the sensor level will change and the MCU will be interrupted. According to the position code, the corresponding power tube is opened or closed to drive the BLDCM. Changing the duty cycle of PWM can control the conduction time of power tube to adjust the BLDCM speed. If the voltage temperature and speed sampling signals exceed the allowed range, the PWM signal will be blocked to protect the controller and the BLDCM.
An Analysis Method for Software Deployment Conflict Detection
This paper proposes an analysis method for software deployment conflict detection. First, we analyze the possible dependencies in the process of software deployment. Based on these dependencies, we find out the factors that may lead to software deployment conflict.
High-Tc rf SQUIDs with Large Flux Focusing
The high-Tc rf SQUID (superconducting quantum interference device) sensor, in which the rf SQUID was placed face to face with superconductor flux concentrator/dielectric resonator, was designed and fabricated. The SQUID sensor was made up of a SQUID washer (with an area of 9.6 mm2 and an inductance of 150 pH) and a flux focusing/dielectric resonator (with an area of 100 mm2 and an resonant frequency varied from 430 to 650 MHz). The author conducted a test to prove that with a white flux noise spectral density of SΦ 1/2=3×10-5Φ0/ Hz1/2 and field sensitivity of BNï¾100 fT/Hz1/2, this flux focusing/dielectric resonator-type rf SQUID sensor can work stably where electromagnetic interference is smaller.
Study on Dynamic Adaptive Bitrate Selection Algorithm for Mobile Streaming Media
An energy-aware dynamic adaptive Bitrate selection algorithm (EDABS) was proposed to solve the problem of rate switching frequency and low energy utilization efficiency while receiving streaming media data. According to the monitored network bandwidth and streaming media coding rate, the algorithm adaptively adjusted the lower limit threshold of the terminal cache area, so that the size of the cache space was more fit the current bandwidth and streaming media coding rate. And then, it set a dynamic security boundary and response delay factor, and adaptively selected the next target video block's code rate. The experimental results show that proposed algorithm can better reduce rate switching frequency and improve the utilization efficiency of the energy.
Price Prediction of Traditional Chinese Medicine Based on ARIMA and Improved Elman Neural Network
The price’s change of traditional Chinese medicine contains linear, non-linear and other miscellaneous factors. It is difficult for people to use a separate model such as neural network model to judge its price trend. Based on the background, a combined forecasting model is proposed in this paper, it consists of Autoregressive Integrated Moving Average model and Elman neural network which is improved by correlation analysis. The combined forecasting model can use its two algorithm model to deal with the linear and nonlinear factors. Meanwhile, the innovation of this paper is using correlation analysis to import extra additional parameters for the neural network, which can increase its accuracy. A large number of traditional Chinese medicine’s price data was collected to be training samples, the final results show that the combined forecasting model has advantages over stability and accuracy than ARIMA or Elman neural network.
Knowledge Retrieval of Chinese Medicinal Materials Based on Extension Semantics
There are many varieties of Chinese medicinal materials, and the retrieval is complicated. In this paper, knowledge retrieval of Chinese medicinal materials is proposed, and semantic similarity is considered on the basis of information retrieval. The algorithm in this paper calculated the similarity from the three aspects of information content, semantic distance, and attributes. Introduced extenics, considered the importance of different attributes from the perspectives of scientific research and medical treatment, and used dynamic matter-element weights to achieve comparison and retrieval of Chinese herbal medicines. The calculation process is convenient, which improves the calculation efficiency and storage space utilization. Finally, the accuracy and feasibility of the algorithm in this paper are verified through algorithm comparison and algorithm sensitivity calculation.
Wireless Sensor Missing Value Estimation Algorithm Based On Multi-Attribute
Because the wireless sensor is arranged in the environment of unmanned management and complex, in the process of collecting data and transmitting data, it often leads to data loss due to the influence of itself or external environment. The best way to reduce the impact of missing value is to estimate the missing value. In this paper, we propose a missing value estimation algorithm based on time attribute and trust mechanism. We use Arima to predict the time attribute, and use the relationship between current value, historical value and error to predict the future data. We use subjective logic to convert the interaction information between nodes into trust value, and then Linear Regression prediction value by selecting the number of trust nodes. Finally, according to the optimal fit degree, weight distribution is carried out to form the final prediction value. Because the algorithm not only considers the node data of the trusted neighbor, but also predicts the future data changes through the changes of its own historical data, it has higher accuracy and lower error when compared with other algorithms.
Communication Equipment Condition Based Maintenance Decision
In order to develop a scientific and cost reasonable maintenance strategy to solve the current high cost problem of running and maintenance management for communication equipment, introduce the same type set which has the similar running condition with the object set as the reference set and propose a life prediction method for communication equipment. The method solves the similarity factor of life evaluation parameters (running time, times of starting and stopping) in actual and benchmark running condition by using experience running data. In order to accurately calculate the running life of the object set under the actual running conditions and overcome the shortcomings of the traditional artificial statistics, the calculation method of real time and historical life is presented. Then based on the product of the maintenance factor and service factor of running time and the times of starting and stopping, the concept of the key parameters of the decision of condition-based maintenanceequivalent service factor is put forward; According to the relationship between the equivalent service factor in running time and to predict period, four kinds of decision models of condition-based maintenance are established. The historical data of communication equipment running were perioded to predict when given equivalent service factor.
Flat Research on the Design and Application of Icon Design in Mobile Phone UI Interface
Flat icon design has been widely applied in web pages and mobile phone UI interface, and has been widely praised for its simplicity, clear color, and directness of information. With the rapid development of Internet e-commerce, according to the survey report of China Internet Network Information Center CNNIC (the 45th), until March 2020, the scale of China's mobile phone netizens has reached 897 million. Mobile phone has become an indispensable part of People's Daily life. It not only provides convenience for people's life and shopping, but also becomes a platform for people's work, study and education. The development of multimedia mobile phones has promoted the flat icon design to flourish. Through analysis and research in this paper, it is concluded that the UI interface flat icon has distinct visual characteristics: concise graphic design elements, strong visual impact color design, distinct order, and so on. According to the visual performance characteristics of the flat icon, a large number of cases are analyzed to obtain the style classification and specific design method of the flat icon design. Therefore, this paper hopes to provide references for relevant designers by analyzing and studying the features of flat icon and design method.
Research on the Quality of Internal Governance and Accounting Information Disclosure
This paper focuses on the effect of ownership structure and management structure on the quality level of accounting information disclosure. Through empirical research methods, this paper applied the Shenzhen stock exchange information disclosure evaluation results as concerns the quality of accounting information disclosure standards, and nine years’ data of 2010-2018 as the research range. The empirical results show that the degree of equity concentration, management shareholding, institutional shareholding and the quality of accounting information disclosure are significantly correlated. The independence of the board of directors, the power characteristics of the management and the characteristics of the managers indicate a correlation with the quality of accounting information disclosure. This research found no significant relationship between the duality of the chairman's duty and the quality of accounting information disclosure.
Research on the Teaching Mode of Flipped Classroom of University Computer Under "Internet +"
This article in view of the current computer basic education present situation, under the background of "Internet +", combined with advanced information technology and demand of applied innovative talents training of higher education and teachers in a line of actual teaching experience, put forward the "Internet +" under "university computer" turn into the classroom, explore the teaching mode that suit the development of students, enhance students' motivation in learning, to promote the cultivation of interdisciplinary talents.
Local Threshold Adaptive Endoscope Intestinal Center Localization Method Based on Morphological Reconstruction
In order to solve the problem of inaccurate localization of intestinal center in the process of endoscopic navigation, a local threshold adaptive localization method based on morphological reconstruction is proposed in this paper. On the basis of image reconstruction and combined with local threshold, it is necessary to find the intestinal center point of the endoscope image and guide the movement of the endoscope in the intestinal tract through the guidance of the intestinal center point, which is an important basis for the navigation path planning of the endoscope by combining the endoscope with visual navigation. In this paper, 355 continuous real endoscope intestinal images were taken to locate the center point, and accurate intestinal center points were obtained. The center points were used to guide the front end of the endoscope, which played a navigation role in the endoscope and visual navigation.
Approach with Reducing Time-Delays to Rise Prediction Ability for Neural Networks
The time-delays induce instability, then the instability influences the prediction accuracy of neural networks, hence, time-delays should be considered as a key indicator for constructing neural networks. Based on above mentioned problem, we reconstructed time-dependent Lyapunov function. Next following, we found the sufficient condition which ensured the convergence of neural networks and prevented highfrequency oscillation, which effectively increased the prediction accuracy of neural networks. This results show that the prediction accuracy about raise 2.5% for neural networks after reducing time-delays, and the mean square error decreased about 0.02 for training samples using neural networks.
Design of Intelligent Test System of Navigation Equipment for a Type of Airplane
This article mainly introduces the design and implementation of the intelligent testing system on the aircraft navigation equipment based on PXI bus, the intelligent test system is described in detail the hardware structure and software design. The detection system bases on embedded industrial computer as the core, uses the unit modular structure to encourage input and output measurement method of navigation equipment of each failure mode by test, so as to achieve the purpose of fault location. The system has simple operation, high test precision and open system, etc. By using the intelligent integrated testing system, the technology is advanced, performance is superior. To ensure flight safety, and improve the battle effectiveness, the system has very important significance.
An Analysis and Empirical Study on the Generation Mechanism of Consumer Flow Experience in Brand Community
Brand community is a new type of community in the era of brand consumption formed by consumers with brand as the link, experience as the core, identity, sense of identity, belonging and selftranscendence as the goal. This paper mainly analyzes the phenomenon of flow experience produced by consumers in the brand community systematically, mainly from the basic connotation and generating mechanism of flow experience, discusses the factors and mechanisms that stimulate consumers to produce flow experience in brand community, and proves the phenomenon that consumers produce flow experience in brand community by combining with actual case analysis.
A New Method of Network Risk Assessment Based on Bayesian Model
In order to assist network administrators to assess network security risks, a new Bayesian model of network risk assessment method is proposed. Firstly, the model designs the quantitative method of attack revenue and attack cost index, introduces the atomic attack efficiency variable, and integrates the variable into the calculation of probability, obtains the prior risk probability of each node in the network, so as to carry out the static evaluation of network risk. Secondly, DNO_Alg of deleting node order is proposed to determine the order of eliminating elements, so that Bayesian model can be transformed into cluster tree. Finally, combined with the detected attacks, the cluster tree propagation algorithm is used to dynamically calculate the posterior risk probability of nodes, so as to evaluate the network risk in real time.
Knowledge Sharing Across Culture—Critical Review
Knowledge and culture are indissolubly linked together in organizations. Considerable evidence supports the importance of culture in the success or failure of knowledge management. Then, the effectiveness of knowledge sharing needs both cultural understanding and new considerations in the knowledge transfer of intercultural organizations. This paper reviews some critical literatures and identifies the influence of different dimensions of culture on knowledge transfer and sharing in different types of knowledge. The aim of this paper is to propose a theoretical framework for knowledge sharing processes based on differences in national culture for future research.
Sentiment Analysis of News Reports in the Period of New Coronavirus
The spread of new coronavirus has a significant impact on the world. To protect people from viruses, a large number of personnel and substances in research, production, medical treatment, and other aspects are used to deal with the virus. News reporting is an important way for people to obtain information about the coronavirus. Objective and immediate news reports can provide people with accurate information and correct response methods, thus playing their due role in defeating the coronavirus. In order to compare the emotional characteristics of news reports, the methods of natural language processing are used to conduct sentiment analysis on news reports, including the subjectivity and the polarity of news reports. We select the news websites of BBC and CNN, that have an important influence in the world, for comparative analysis. The results show that BBC news reports are more positive than CNN, and in terms of subjective, BBC News is more factual than CNN.
Integrated Tunable Distributed Feedback Reflection Filter Based on Double-Layer Graphene
A silicon waveguide integrated electrically tunable distributed feedback grating device based on double-layer graphene is proposed and analysed by mode coupling theory and finite element simulation method. The theroresults show that with the graphene fermi energy level change from 0. 5eV to 0. 8eV, the center wavelength of TM mode reflection spectrum shifts from 1. 55um to shorter wave by 3. 9nm, and the center wavelength of TE mode reflection spectrum shifts from 1. 89um to shorter wave by 4. 8nm. The graphene electrically tunable distributed feedback grating device may has potential application in the integrated tunable wavelength selection device.
Research on Application of Big Data Technology in Cost Control of Medical Insurance For China
With the increasing aging of the population, medical insurance cost control has become a worldwide problem. In order to control the medical insurance fee, since 2009, China's medical insurance payment system has changed from the post payment system mainly based on projects to the prepayment system based on total amount control, but not only failed to control the growth of medical insurance expenditure, but also resulted in the phenomenon that the insured's right to medical treatment has been damaged. Using big data technology and other information-based means to fine manage medical insurance expenditure has become an urgent matter. The paper is divided into four parts. The first part introduces the characteristics of big data and the concept of big data technology; the second part, under the background of the reform of China's medical insurance payment system, analyzes the necessity and possibility of using big data technology to control medical insurance expenses; the third part, puts forward some measures of using big data technology to control medical insurance expenses; finally, the conclusion is drawn that the use of big data technology can realize the fine management of medical insurance control fee.
A Fast Reduction and Denoising Method of Scattered Point Cloud Data Based on Spherical Model
Aiming at the problems of high complexity, long computing time and high hardware requirements of common point cloud reduction and denoising algorithms, a fast point cloud data reduction and denoising method based on ball model is designed. The method of building the sphere model and including the scattered point cloud model of 3D object in the sphere model is introduced. The coding and sorting of the vertebral body region in the sphere and the distribution strategy of each coordinate point is discussed. The different distribution of point clouds in each cone region and the algorithm of data reduction and denoising is studied. A method to transform the scattered point cloud model of 3D object from spherical coordinate to rectangular coordinate is presented. Experimental simulation and analysis show that the method proposed in this paper can simplify and denoise the scattered point cloud at the same time, and the algorithm is simple, with low requirements for the hardware system. This algorithm is more suitable for embedded system operation.
Counting Matching Numbers in Catacondensed Polyomino Systems
The matching counting problem has its own significance in mathematics and interconnection network of parallel computer system. Let G be a graph, the total matching number is the total number of independent edge subsets inG . For general graphs, the matching counting problem has proven to be intractable and computing the total matching number is #P hard. This has led to an emphasis on studying this problem in particular classes of graphs. The polyomino system is a finite 2- connected plane graph such that each interior face (or say a cell) is surrounded by a regular square of length one. The catacondensed polyomino system is a chain polyomino system and its central line forms a tree. In this paper, the reduction formulas of computing the total matching number of any catacondensed polyomino system via three kinds of transfer matrices are obtained.
Research on the Right Identification and Right Description Standard of Service Data Based On ODRL
This article mainly solves the problem of standardization of ownership and rights description of the main stakeholders in the field of data circulation in the field of data governance: combining the status quo of data protection and ownership identification, starting with the logical relationship between data and information, deconstructs the service data for subject ownership identification; combs the relevant laws and regulations of data protection, and defines the rights of each subject. In order to realize the structure and machine-readable of the right language, we should refer to the ODRL information model of W3C to build the right description standard of service data, describe the application of the standard in the actual transaction scenario, and build the hierarchical right transfer model in the process of data transaction.
Research on Metadata Specification of Service Data Resources Under the Background of Data Transaction
This paper designs the service data resource metadata standard system and catalog vocabulary by investigating the status of service data resource descriptions of mainstream data trading platforms at home and abroad, and referring to W3C's official recommendation standard DCAT and Dublin core metadata. The service data resource metadata interaction model is designed by referring to the RDF/XML framework. The service data resource metadata standard applying RDF/XML grammar specification will effectively support the registration and authentication of data products, transaction process management, data demanders' understanding and use of purchased data, and market supervision.