Search

This paper starts with how college students’ consumers accept the new technology model. Based on the technology acceptance model of e-commerce industry and the unique factors, this paper constructs the influencing factors model of consumers’ acceptance behavior under the mode of O2O, and obtains samples for scientific analysis through data survey for structural equation analysis. Finally, this paper gets the influencing factors of college students’ consumer buying behavior under the mode of O2O.

Communication of the human brain with the surroundings became reality by using Brain- Computer Interface (BCI) based mechanism. Electroencephalography (EEG) being the non-invasive method has become popular for interaction with the brain. Traditionally, the devices were used for clinical applications to detect various brain diseases but with the advancement in technologies, companies like Emotiv, NeuoSky are coming up with low cost, easily portable EEG based consumer graded devices that can be used in various application domains like gaming, education etc as these devices are comfortable to wear also. This paper reviews the fields where the EEG has shown its impact and the way it has proved useful for individuals with severe motor disorder, rehabilitation and has become a means of communication to the real world. This paper investigates the use of Cubic SVM algorithm In the EEG classification. EEG feature extraction is Implemented by maximum overlap discrete wavelet transform (MODWT) to reduce the dimensionality of data. The Sliding Window Technique is used to calculate the mean within each window samples. The feature vectors are loaded into the support vector machine (SVM) and optimize tree.

s This paper presents algorithm for draping 2D textile fabric on curved surface. Using computer analyze to predicting strength and stiffness of textile reinforced composite details allows to achieve better characteristics of received parts. Part of this task is stacking initial cloth on the surface. Modeling of draped fabrics on surface produced by representation initial cloth by pin-jointed net model, which are describes position of each thread. This algorithm also provides to analyses angles between each pair of threads in considered object. It is used to find areas with critical tension, or places of formation of folds of fabrics. In this paper threads of fabrics are inextensibility.

Embedded system is a development trend of computer technology, which is a low-power, specialized computer technology. Embedded system is widely used in industrial production and daily life, which is a very cheap computer system. Data collection is a kind of commercial behavior, which can provide basis for product decision-making, management and control. Therefore, data acquisition through embedded system will reduce the cost of the whole system, which can also guarantee the expansibility and flexibility of the whole system according to specific needs. Therefore, the intelligent collector based on embedded technology is an important application. Firstly, this paper analyzes the importance of intelligent collector based on embedded technology. Then, this paper puts forward the main technology of system development. Finally, an example is given.

The main aim of this research paper is to provide multi security for the pedestrians/older using smart stick using IOT and GPS. This stick having IOT, voice module and attached with multiple sensors to provide high security to the blind peoples while walking. Now a day’s safety is main important cause to the peoples while walking or driving and many more places. This smart stick provides the high security and show way to walk, by using this system we can monitor the blind person position using web application/mobile application and also we can get emergency alert message along with exact location. This system has obstacle sensor, water sensor and MEMS sensors, so that it can detect obstacles sizes automatically and gives voice alert. By using water sensors, it can detect the floor condition is dry or wet and shows the way to walk. In case of any emergency person suddenly fall at floor/any place then this system immediately detects using MEMS tilt sensor and automatically send the message to respective numbers with location and also gives buzzer alarm continuously to alert the neighbours. So that this smart stick can be very useful to peoples to show correct path while walking on the floor or steps and many more places. In this paper, the system can be interconnected with the microcontroller and alert the respective persons when any emergency occurs. This tracking system is composed of a GPS receiver, Microcontroller. The Microcontroller processes this information and this processed information is sent to the respective numbers using web page.

Artificial intelligence is an effective way to promote the intelligent development of education and teaching, and also an important concept of the development of quality education. This paper mainly studies the new teaching method of free combat based on artificial intelligence technology. This paper analyzes the innovation brought to education by intelligent image recognition, speech recognition, big data analysis, deep learning, intelligent teaching robot and other related technologies in the era of artificial intelligence. Meanwhile, it analyzes and discusses the influence of teaching reform in the era of artificial intelligence development. From the experimental results of this paper, it can be seen that from the perspective of students’ free combat sports skills, using artificial intelligence technology can more effectively improve students’ free combat sports skills than using conventional teaching methods to conduct elective free combat teaching. In the elective teaching of free combat in colleges and universities, the application of artificial intelligence skills can effectively improve the excellent rate and good rate, control the pass rate and reduce the failure rate of students’ examination results of free combat course.

With the progress of science and technology, big data technology has penetrated into all aspects of life. The topic of this paper is how to develop students’ concept innovation and learn to learn in Chinese painting teaching under the background of big data, mainly focusing on how to develop and guide students’ concept change in their activity process. This paper uses the research method of case analysis. The research object is the students of a university in our city. I get the necessary data through the questionnaire survey data collected before the course, the communication data with students after class and the creation of works of two parallel classes. Then the questionnaire answers to the data list, after class talk statistics, comparative description and analysis of students’ works. The purpose of this paper is that through the practice of Chinese painting, students can learn to learn, use their brains spontaneously, improve their ability of autonomous learning and innovative ideas, and make different works. Teachers can use their own knowledge and creative experience and Research on the implementation strategy of Chinese painting class to improve their ability to better guide students’ concept innovation.

With the continuous and stable growth of China’s national economy, the demand of the whole society for the total power supply is higher and higher, which requires the power enterprises to continuously improve the power supply. However, if the total power supply is increased, the power enterprises need to invest a lot of power transmission facilities, which requires a huge investment in the distribution network. Therefore, different economic development levels among regions will lead to the difference of distribution network investment, which is also an important content of distribution network investment decision. Therefore, we must control the whole process through big data, which will provide a better evaluation system of distribution network investment benefits. Through the whole process management and control mode, the State Grid can build a systematic and complete distribution network investment decision-making system, which will improve the accuracy of distribution network infrastructure project investment. By analyzing the income ratio, the power grid can get scientific economic investment analysis report. Through big data technology, the power grid can realize a variety of data of distribution network operation, such as maintenance plan optimization, distribution network operation process optimization, project investment income, equipment health status analysis, etc., which can provide auxiliary decision support. Through the three aspects of technical benefit, social benefit and economic benefit, we can evaluate the operation efficiency of equipment, which can construct the index system of project investment benefit. Firstly, this paper constructs the whole process management and control system of distribution network based on big data. Then, this paper constructs the accurate investment index system of distribution network. Finally, some suggestions are put forward.

In present time, meta-heuristic algorithms have been widely adopted for solving diverse classes of optimization problems. These procedures/algorithms have advantage over classical algorithms due to strong exploration and exploitation capabilities. In recent time, a Bat algorithm is developed on the basis of echolocation characteristics of bat. This algorithm has applicability to solve number of constrained and unconstrained optimization problems. The bat algorithm gives state of art results as compared to same class of metaheuristics. The objective of this paper is to explore bat algorithm in terms of modifications, improvements, search strategies and nature of problems being solved. Hence, this paper presents the mini review on bat algorithm. Further, the applicability of bat algorithm in diverse filed has been discussed.

Paper considers educational digital tools development results for university level within geo-information management paradigm during Industry 4.0 era under climate change and COVID-19. While research, authors used modern web-technologies for educational platforms design. Recently, the ways of geo-information support for environmental economics have distinct features of digitalization with new concepts in data obtaining and presenting. In paper, preference is given to the use of open online platforms, which integrate heterogeneous hardware and software resources with the use of web-technologies in distributed networks and wide application of cloud services. There are considered examples of presented digital tools using. The presented research results have significant scientific novelty can be used in training and educational purposes at university level, including the preparation of Master’s programs.

With the popularization of the Internet and the rapid development of information technology, the types and quantities of data are increasing at an unprecedented rate. We are in an era of ever-increasing data penetration, and “big data” has arrived. Nowadays, all walks of life are using big data, and human production and life can no longer leave big data. It has been widely used in many fields, including large-scale hydropower and ceramic glaze. This article mainly introduces the literature reference research method, analytic hierarchy process and investigation research method. This paper uses the analytic hierarchy process to analyze the application of big data in ceramic glaze, and establishes a potential mathematical model. The model is solved by the analytic hierarchy process, and the application status of big data in ceramic glazes is studied, and the model is revised using historical data to improve the accuracy of the application status of big data in ceramic glazes. The experimental results of this paper show that the analytic hierarchy process increases the efficiency of the application research of big data in ceramic glazes by 13%, and reduces the rate of false alarms and false alarms. Finally, by comparing the application value analysis of big data in ceramic art glaze and the modernization demand analysis of ceramic art glaze, the influence of the application of big data in ceramic art glaze is systematically explained.

To solve the problem of low ratio success delivery, long latency caused by the rapid dynamic change of network topology, limited node buffer, large amount of data transmission and large user population density in delay-tolerant network (DTN). This paper propose a routing algorithm in DTN based on nodes’ sociality. In this paper, contact history was used to determine the node link quality; Markov model was used to predict the node position based on the nodes’ movement track; according to nodes’ social similarity to divide community, then calculated node betweenness centrality. Finally, the best forwarding nodes for message transmission were determined. Besides, to increase the ratio of successful delivery, message delivery probability in the relay node’s buffer was calculated. Experimental results show that compared with traditional routing algorithm, the proposed algorithm performs better on the delivery ratio and average end-to-end delay.

The paper designs a square hole model and uses a delta3D printer to carry out printing experiments with different process parameters. It mainly conducts experimental research on four process parameters, including printing speed, layer thickness, filling density and platform temperature. The paper carries out the analysis of the influence of process parameters on the external dimensions of the hole, the inner depth of the hole, etc., and graspes the law of the influence of different process parameters on various sizes in order to provide a certain reference for the research of the 3D printing process of special parts.

Chinese traditional manual embroidery has a long history, which is one of the important intangible cultural heritage in China. However, with the increasing social demand for embroidery, the traditional manual embroidery production capacity is too small and the price is high, computer embroidery and embroidery technology has an important market. With the optimization of artificial intelligence algorithms such as deep learning, computer embroidery skills have been gradually optimized, which has replaced manual embroidery in some aspects. In the clothing industry, computer embroidery skills have been widely developed. Through computer technology, designers can carry out three-dimensional modeling design, which is not achieved by traditional plane decoration. Therefore, computer embroidery technology can be gradually applied to the behavior and social factors of modern society, which will encourage the inheritance of national costume culture. First of all, this paper analyzes the current computer embroidery design. Then, this paper analyzes the steps of computer embroidery. Finally, this paper puts forward the application of computer embroidery techniques in modern Chinese fashion design.

The construction of local high-level universities is an important part of the comprehensive reform of higher education in China. With the coming of the computer “Internet +” era, major strategic tasks such as cloud computing, big data and new generation of artificial intelligence have been gradually laid out, which will further achieve the goal of educational modernization and the development of a powerful educational country. Promoting the development of education informatization in the Internet era has become the top priority in the development of national education. Based on the background of high-level universities, this paper first analyses the necessity of the educational informatization development. Then, this paper puts forward some problems. Finally, some suggestions are put forward [1].

In recent years, big data is used in finance, education, biotechnology, and other fields. In the field of education, thanks to the overall characteristics of big data, it can be applied to understand the objective learning rules of students, to provide effective decision-making suggestions for educators. With the development of electronic communication and media technology, Massive Open Online Courses (MOOC), which contains a large number of user behaviors and information, has gradually become one of the mainstream ways of education. However, MOOC have also been criticized for their high dropout rate. Through the analysis of big data contained in MOOC real data set, it can help teachers master students’ learning rules and learning behaviors in time, which is of great significance to improve the level of education and the dropout rate of MOOC. First, it is helpful for teachers to adjust the course content in time according to the learning status. Second, teachers can carry out benign interventions on students’ learning behavior. In this paper, based on the analysis of the real MOOC data of students’ learning behaviors, we find that different groups of students have the same learning behavior at the same learning period, and students’ learning situations can be divided into three stages. Then ARIMA model is used to predict the learning behaviors of students, to further analyze the factors causing the difference in prediction accuracy, we propose an error analysis method based on MSE. Through the experimental observation, the method proposed in this paper can effectively find and predict the characteristics of students’ learning behavior, to give suggestions for improving the quality of teaching.

With the rapid development of computer technology (hereinafter referred to as CT), China’s e-commerce has achieved great success, which also applies a variety of modern computer, electronic, control and other aspects of technology. Therefore, e-commerce is in urgent need of professional talents, which requires colleges and universities to cultivate more logistics management (hereinafter referred to as LM) talents. Through specialized division and cooperation and collaborative education, colleges and universities can cultivate professional talents more suitable for modern LM. Through computer software, we can control the sorting system of logistics. At the same time, we can optimize the distribution network and routing. Therefore, LM has become a hot emerging specialty, which has become an indispensable specialty in E-Commerce teaching. Therefore, colleges and universities can improve the teaching effect of e-commerce through multimedia, simulation software and other modern technologies, which can cultivate the practical ability and innovative spirit of college students. First of all, this paper analyzes the important role of CT in LM teaching. Then, this paper puts forward some problems in the teaching process. Finally, some suggestions are put forward.

In recent trends, digital images are commonly used for communication, storage, medical imaging, etc. These images may contain confidential data. Image encryption and steganography are popular techniques to provide information security. In image encryption, a secret image is encoded using an encryption key, and in image steganography, a secret image is embedded in some cover media. Encrypted images are visually recognizable as these are noise-like, but stego images are visually unrecognizable. In this concern, some visually secure encryption techniques are developed, known as Meaningful Image Encryption (MIE). It includes the advantages of both image encryption and steganography. This paper provides a thorough review of existing MIE techniques. A comparative assessment based on various performance parameters is presented. Further, this paper provides the main application areas of MIE techniques. Moreover, the future research perspective to enhance the existing MIE techniques are discussed in detail.

The 21st century is the era of multimedia, which has been applied to all walks of life, especially the education industry. With the rapid development of economy, the process of global economic integration is faster and faster, which requires higher quality of English Teaching (hereinafter referred to as ET). Therefore, multimedia technology (hereinafter referred to as MT) has become an important tool in College ET, which can not only promote the cultivation of language expression ability and thinking logic ability, but also enhance students’ interest in learning. Through MT, colleges can change the traditional teaching methods and means, which will improve students’ interest and enthusiasm. Through the introduction of computer MT, colleges effectively improve the students’ learning quality. First, this paper analyzes the important role of computer MT in ET. Then, this paper constructs the important teaching platform function of MT in Colleges. Finally, some suggestions are put forward.

The development of computer technology promotes the reform of engineering industry. People gradually realize the convenience of computer technology. Civil engineering is the main specialty of construction engineering. Civil engineering includes many kinds of engineering. With the emergence of computer software development technology, many problems in civil engineering have been solved. Experts have developed a lot of computer software [1]. These softwares are widely used in civil engineering technology. This paper mainly lists the application of four kinds of computer software in civil engineering. In this paper, the main application skills of computer aided design, finite element software, GIS software and virtual reality software are mentioned.

With the development of information technology, the traditional paper knowledge information has been toward the trend of informatization. Therefore, the library materials information also gradually information zed. This paper first explains the development trend of library in China, and discusses the existing problems and optimization of library information, so as to provide readers with reference.

The traditional sculptures are all from the artist’s careful carving, which is also the artistic presentation. With the rapid development of computer technology, digital technology has been applied to art landscape sculpture. Through RPM technology and 3D printing technology, we can rapidly shape and mass produce art landscape sculpture. Through computer aided technology, RPM technology and 3D printing technology, we can save the labor cost and mold opening cost of traditional sculpture, which shortens the production cycle and improves the precision and structure of sculpture. At the same time, we can also develop personalized sculpture, which has seriously impacted the traditional sculpture industry. Computer aided design is in line with the digital age of new technical concepts, which has become the main means of landscape sculpture creation. Through computer software, designers can complete the virtual sculpture design intention and intention. Through the generation of VR, manufacturers can better communicate with customers, which makes up for the shortcomings of traditional sculpture in construction. Firstly, this paper analyzes the related concepts. Then, this paper puts forward the necessity of applying computer aided technology to modern landscape sculpture. Finally, some applications are proposed.

Now a Days Microwave MINI-LINK are widely used for point to point communication. Microwave link has become an essential form of communication network because of frequent interruption of Optical Fiber Cable network due to other sector development work, non-feasible area for Optical Fiber Cable laying (digging is difficult for OFC) or any unseen reason, on the other hand mini link network become so adaptable because their small wavelength allows conveniently sized antenna to direct them in narrow beam which can be pointed directly at receiving end. This allows nearby mini link equipment to use same frequencies without interfering any other link. The aim of this paper is to create a mini link network in such a way so that operation and support maintenance work can be done from a central location without moving at site and without purchasing any software. Another objective of this paper is to describe how to use installed equipment completely (i.e. 100% utilization of equipment) which are being used by network..

This century is described as Cloud Computing Technology over the Information Technology Business. Cloud computing advancement mostly relies on the Internet possesses the most advanced planning of computation. It records as piles of correlated and schmoozed hardware, software, and internet infrastructure. It blends grid computing and other computing as a community. A short overview of cloud computing is obtained from this research paper by consulting several papers on cloud technologies. The substance conveyed by this represents the perspective of shaping IT businesses and the idea of cloud computing.

In the era of big data, traditional data compression methods cannot complete data compression with features of large volume, rapid growth and complex structure, especially in the processing of real-time data compression. The compression algorithm proposed in this paper is improved on the basis of a lossless bit-swap compression coding algorithm. The coding algorithm is based on VAE model and uses classical ANS compression technology to code multiple potential variables, so as to realize the rapid compression and decompression of data. The experimental results show that the algorithm proposed in this paper can compress data with a high compression rate(47.65%), which is higher than LZAM algorithm and Bit-Swap algorithm.

Deep Learning (DL) models have tested to be very powerful in solving many hard problems. Especially, those are related to computer vision, text, speech, and classification. However, the blueprint of such models requires large space and elaboration that needs to be examined. Convolutional Neural Network (CNN) is the most popular neural network that can extract the features automatically as compared to conventional machine learning algorithms (CMLA). Our aim in this paper is to lessen the human attempt required to layout architectures by the use of a gadget architecture development process that allows the exploration of huge design space by automating sure version construction, alternative generation, and assessment. The main operations in CNN are Convolution, Pooling, Flattening, Full Connection between the input and output layer. The dataset taken as CIFAR 10 having 60,000 color images of 10 different classes is considered for the study where, various classes represent the images of cars, trucks, frogs, horses, trucks, cats, cars, airplanes, ships, and deer. It is expected that the performance of the CNN model can be further improved by using the deeper network architecture, or by an increasing number of epochs or data augmentation. In this paper, an attempt has been made to explain simple and deeper CNN models on the CIFAR 10 dataset and the comparison has been carried out to check the accuracy achieved from both the models.

Production safety is the most important problem in coal mine production, which requires us to monitor and monitor the coal mine production process in real time. Therefore, under the computer technology, we can carry out multi-sensor acquisition, including gas concentration, carbon monoxide content, environmental pressure, humidity, etc., which can collect and monitor the underground operation in real time. Through computer technology, coal mining enterprises can monitor and control safety production in real time. Through the sensor, we can monitor the working state of equipment, such as circulating fan, high-pressure water pump, winch and motor, which can deal with a variety of abnormal production problems, such as over-voltage, power loss of current, lack of phase. With the application of various sensors, the information system will collect more and more data, which will lead to great challenges for coal mine safety monitoring system. Therefore, we must enhance the data processing system, which will better coordinate the data interaction of various subsystems. Through the data processing system, we can improve the efficiency of coal mine safety monitoring, which will ensure the smooth operation of coal mining enterprises. Firstly, this paper analyzes the coal mine safety monitoring system. Then, this paper analyzes the source of the data. Finally, this paper analyzes the processing method.

Computer network technology promotes the update and progress of new media. It has brought great changes and influences to the whole news and entertainment media. The continuous improvement of computer science and technology level has led to the long-term progress of electronic information technology. In this way, the status and value of computer information technology in the media industry continue to rise [1]. In today’s era of new media prosperity, the most far-reaching impact of computer technology industry is the media industry we are familiar with. This paper briefly analyzes the status quo of media and its development. Through the cognition of media industry and new media computer, this paper describes the research on the role of computer technology in the media field in the new media era, and finally draws the corresponding conclusions.

With the rapid development of computer technology, BIM has become the most common tool in the construction industry, which occupies an important position in the virtual construction of Prefabricated building (hereinafter referred to as PB). Through the establishment of virtual construction engineering model, we can provide a complete construction engineering information base combined with digital technology. In the virtual construction of construction engineering, we can check the collision through BIM. At the same time, through BIM, we can carry out 3D model drilling of virtual construction. Through collaborative management, we can improve the production efficiency, which will save the cost and shorten the construction period. At present, the application of BIM in China is still in the exploratory stage, which requires us to give full play to BIM Technology. Through the Revit software, this paper simulates the construction site, buildings, tower crane, secondary masonry, etc., which can make the application of PB more clear. Firstly, this paper analyzes the related concepts. Then, this paper analyzes the application of BIM in the virtual construction of PB. Finally, some suggestions are put forward.

Metamaterials are synthetic special structural units, usually in the wavelength or subwavelength range. When the incident light is coupled with the structural element, the free electrons on the surface can generate surface plasmons under the periodic drive of electromagnetic wave. In this paper, we mainly study the transparency of dynamically adjustable plasma-induced periodic graphical graphene nanoribbons. This paper discusses the geometric parameters that affect the variation of PIT. The gap distance G and the disc moving distance S can change the coupling strength of the light and dark modes, and the variation of coupling strength can adjust the transparency and frequency band width of PIT window. The Fermi energy of graphene can be changed by adjusting the electrical conductivity of graphene, and the change of Fermi energy can also regulate the PIT effect.

With the continuous progress of The Times, the traditional paper graphic design has been unable to meet the needs of graphic design, through the use of computer aided technology in graphic design visual aesthetics, can effectively improve the aesthetic sense of the work. In this paper, first of all, the visual aesthetics of graphic design and graphic design of the construction type and computer aided technology analysis, at the same time, the specific application of computer aided technology in graphic design, for the reader’s reference.

In this paper, the numerical simulation method is used to study the aerodynamic characteristics of the runoff turbine expander, the key equipment in the natural gas pressure energy recovery power generation system. The geometric structure of the turbine expander under the condition of sub-high pressure natural gas expansion was designed and the flow characteristics of the internal flow field during its operation were obtained by numerical simulation. It is found that the expansion process of fluid in the runoff turbine expander mainly occurs in the guide vane channel and the inlet section of the rotor channel. The turbine expander designed in this paper can well meet the working requirements under design conditions, and the flow in the whole channel is good. When the flow channel in the moving impeller changes from radial to axial, the flow field is complex and there is a poor flow. The research results of this paper provide a reference for the design and optimization of runoff turbine expander in natural gas pressure energy power generation system.

The security of digital information has become increasingly vital in the digital world, which is currently evolving and changing at such a quick speed. With the rapid growth of hidden contact and communication around the world, the need for communication security is becoming increasingly important. The main motive of cloud service providers is to collect the information and details of the material uploaded on their cloud servers. One of the major concern is security of the contents uploaded on the cloud servers. Although, they challenge about the security provided by them to the individuals but they are the owner of servers and the information on it. The same has been observed when one of our server crashed and we consulted about the incident with the customer care department of our CSP. We use to back up our university servers backup on cloud for which we pay some amount as decided by our management as well as CSP. The aim of this research is that the cloud owners cannot have access to data of the users. I proposed a new robust encryption technique in this paper to improve the security of the key generating algorithm. To achieve this, an algorithm has been implemented which performs much better than renowned algorithm i.e. RSA algorithm. This algorithm achieves better response time than RSA algorithm which is described and proved in this paper. This paper uses ASCII and EBCDIC codes while encryption and decryption.

Nowadays, China’s power demand system reform has gone through many stages. With the rapid growth of China’s population, China’s power demand is also increasing rapidly. After experiencing the heavy pressure growth period, the power system really provides us with great convenience. However, it will also bring a lot of bad problems. In order to solve these problems, we must innovate the electric power industry [1]. Data acquisition and sharing in side management mode is the basic part of power demand management. Nowadays, the development of big data has gradually become prosperous. Many experts believe that data mining can be used to support data acquisition and sharing of power side management. This paper briefly summarizes the theory of power big data and power side management. On this basis, this paper proposes a data source and data sharing model based on data mining.

China’s education attaches great importance to the learning of English courses. Many parents pay attention to students’ English learning. With the gradual increase of international communication activities, many schools carry out English teaching activities [1]. In this process, the topic of English teaching has been pushed to the upsurge. With the rapid development of computer teaching technology, people gradually realize the important role of computer. The mode of English information teaching based on Internet will be opened soon. This paper analyzes the current situation of traditional English teaching. According to the current trend, this paper puts forward the main application of English information teaching mode.

Heart disease is the most dangerous disease among all the non-communicable diseases. Annually 17900 thousand of peoples die due to heart problems. Cardiovascular disease (CVD) is the general term used for most of the heart diseases. There are two types of methods for diagnosing a CVD: (i) Invasive Methods (ii) Non-Invasive Methods. Coronary angiography is an invasive method for diagnosing a CVD which is a costly, painful and complicated process. A variety of Non-Invasive (NI) methods are available for diagnosing a CVD. NI methods generate a lot of data which is mainly of 3 kinds :(i) data based on clinical parameters, lab tests and symptoms (ii)data based on raw heart signals (ECG and PCG) (iii)data based on heart images. Majorly, three different machine learning (ML) frameworks may be developed based on the 3 types of data. First framework is simple and main concern is feature selection and classification. Second and third framework is complicated and requires a lot of techniques (preprocessing, segmentation and feature extraction) prior to classification of heart signals and images respectively. In this paper a comprehensive review is presented that summarizes some recent and prevalent machine learning methodologies in all the frameworks. Most of the papers reviewed in this study are from IEEE Explorer, Science Direct, PubMed, Springer, Hindawi, ACM digital library and MDPI libraries. It is found that Support Vector Machines (SVM) and Artificial Neural Networks (ANN) are superseding in most of the studies in all the frameworks. Deep neural network is comparatively newer machine learning methodology which is giving prominent results in classifying heart sound signals and cardiovascular images. The present study will help to automate diagnosis process of heart disease by providing guidelines and avenues to new researchers in domain of machine learning.

Friction stir spot welding is a new type of connection technology developed on the basis of the friction stir welding process. It uses a high-speed rotating stirring head to generate heat by friction with the plate to make the welding material reach a thermoplastic softened state, forming a lap joint similar to resistance spot welding. The purpose of this article is to analyze and analyze the current situation of numerical simulation of friction stir welding after deformation under big data analysis. Algorithm mining commonly used for analysis of big data. This paper proposes to use the classic algorithm FP-growth algorithm. The FP-growth algorithm has the widest application range. It compresses the transaction database into a FP tree for processing. It also uses the Apriori algorithm, which eliminates the need to generate candidate frequent itemsets, which improves the efficiency of use. In addition, this article uses data mining technology and data fusion technology commonly used in big data analysis, and their application strengthens the analysis of the current situation of numerical simulation after friction stir welding deformation under big data analysis. Experimental research shows that the dynamic FSSW technology used in this paper simulates the numerical change after friction stir welding deformation, and the simulated data effect is better than the traditional GPC algorithm by about 20%.

English billboards are common in our daily work and life, and how to effectively recognize them is a problem worthy of study. This paper mainly uses Progressive Scale Expansion Network (PSENet) and Convolutional Recurrent Neural Network (CRNN) to conduct text recognition experiments on English billboards. The English billboards are divided into four categories: text distortion, larger background, special text font, and normal format. PSENet is used for text detection, and CRNN is used for text recognition. The identification results of PSENet and CRNN revealed differences among the four groups of English billboards: normal format text recognition is the best, and large background text recognition is the worst, and the recognition effect of text distortion and special text font is less accurate. Finally, the work of this paper is analyzed and summarized, and the future work is prospected.

With the rapid development of transportation, highway bridges as a transportation hub have played an important role and become the link of economic development in the region. In recent decades, my country has built many types of highway bridges. During the construction and operation of these bridges on highways, many inspection activities are required to ensure the quality of construction and operational safety. This article mainly introduces the highway bridge test detection technology and various application methods based on big data. This paper uses big data to detect the dynamics of the highway bridge structure and establish a load test model. The model is solved by the energy-releasing method to strengthen the rigid structure of the highway bridge, evaluate the road condition, and use historical data to revise the model to improve the accuracy of the highway bridge load. The experimental results in this paper show that the highway bridge detection technology based on big data reduces accidents by 23%, and the test and evaluation results under big data show that the performance of highway bridges is excellent and meets the design.

Recently, machine learning methods have a good performance in the field of classification tasks. Summarizing and comparing the performances of different classifiers in the application of their specific classification tasks has a reference significance. In this paper, five classical machine learning classifiers, including GMM, Random Forest, SVM, XGBoost, and Naive Bayes, are compared to show their computing characteristics. The advantages and disadvantages are analysed in this paper. Based on the different datasets, namely different specific classification tasks, the different classifiers perform similarly. However, the SVM-based classifier has the lowest accuracy while processing the text data to apply the text classification task. This result shows that if the classification task is difficult, the accuracy would not be high. This research summarizes the performances of different machine learning methods in the application of specific classification tasks. And this research has a reference significance for the machine learning-based classifiers.

In order to achieve long-distance measurement and control of deep space detectors, increasing the aperture is the most direct means to improve antenna performance. However, the increase in antenna size brings structural instability and is easily affected by external environments such as temperature, gravity, and wind gusts. Aiming at the problem that temperature changes affect the antenna pointing accuracy, this paper designs and implements an antenna pointing temperature compensation model, and conducts data collection and test verification. The results show that the antenna pointing accuracy can be compensated effectively under a large temperature environment by the method proposed in this paper, and the received signal strength is improved.

The host computer is an important part of the computer, which is the basic location for users to store data directly. Therefore, we must strengthen the host security, which will protect the security and privacy of user information. However, hackers, Trojans, worms and other network security threats often attack the computer, which has become an important threat to the application of network security. Therefore, we must strengthen the host network security protection, which will protect the host information from illegal network behavior. By ensuring the security of user host information, we can reduce the waste of resources. In the network security attack defense confrontation, both sides have natural asymmetry, which requires us to deal with network security threats. Through a variety of processing measures, we can protect the computer host security. Firstly, this paper analyzes the decision-making framework of network security threats and protection. Then, this paper puts forward the common types of network security threats. Finally, this paper puts forward the current mainstream treatment measures.

With the progress of information technology, Internet of things (hereinafter referred to as IOT) technology has been applied to all walks of life, especially in oilfield construction. With the rapid development of IOT technology, the system will produce a lot of data, which also leads to the arrival of big data (hereinafter referred to as DB). Therefore, DB and IOT technology has become an important application in the construction of offshore smart oilfield. Through the IOT technology, enterprises can save production costs, which can also improve oil and gas production. Therefore, Internet technology can make the management of oilfield enterprises more transparent, which will realize the intelligent exploitation of offshore oil. Through the construction of Marine Intelligent oilfield, we can form an open system platform, which will realize the sharing of production process and data. Therefore, this paper first analyzes the important role of DB and IOT technology. Then, this paper analyzes the construction of offshore smart oilfield.

Blackouts could occur due to various faults and in order to keep the power stations running constantly to avoid consumers losing power a backup plan is necessary. Black start is the process of restoring power to the electric power stations. The Modular Multilevel Converter (MMC) topology has been propitious technology in High Voltage DC (HVDC) system. The research in MMC technology has significantly increased. The MMC based HVDC system has many advantages when compared to the other technology based HVDC system. In this paper, Black Start Operation using a MMC Based HVDC system is proposed to provide continuous power to the load for a certain period of time within which alternative methods of power generation can be made ready. The paper also provides a mathematical model of a continuous equivalent circuit of the MMC Phase Leg. The efficiency of the proposed idea has been verified by MATLAB/Simulink Software and discussed.

The traditional training mode of computer applied talents is not perfect. The course content of the school almost only includes theoretical study. The lack of practical teaching leads to many computer graduates do not meet the requirements of social enterprises [1]. Many school graduates of computer science will not flexibly use the knowledge they have learned. In order to effectively solve this problem, the Ministry of Education decided to adopt the mode of school and enterprise joint education to cultivate computer professional application-oriented talents. The combination of industrial enterprises and education is a key opportunity for school talent cultivation. This paper briefly introduces the traditional university enterprise cooperation of computer personnel training mode and puts forward its main shortcomings. On this basis, this paper puts forward the innovation strategy of computer application-oriented talents training mode under the school enterprise cooperation education mode.

Micropitting is a fatigue failure phenomenon that concentrates at the surface roughness level between interacting surfaces. This type of surface fatigue is commonly recognized to exist in gears and bearings, where specific film thicknesses are sufficiently low that the rough surfaces run in the EHL condition, where the direct asperity contacts are prominent. This paper is an experimental and theoretical study to investigate a number of fatigue failure theories concerning the multi-axial fatigue models which are depended on a critical plane analysis in the mixed lubrication regime. These failure theories are namely the Findley, the Matake, the Dang Van, McDiarmid and, Fatemi and Socie model, where they are used to perform fatigue investigation for Micro- EHL contacts problem. Numerical analysis to investigate the cumulative damage and fatigue parameter in a Micro- EHL contact is established in this paper. The results of applying failure theories have indicated that the different multiaxial fatigue criteria adopted provide significant results for contact analysis in lubricated conditions, and they are more relevant to the applications of the rough surface Micro-EHL mode.

Based on the perspective of ITT, the development of cross border e-commerce (hereinafter referred to as CBEC) is directly related to many industries, which promotes the employment and development of many industries, such as logistics, it, production, etc. Therefore, CBEC accounts for a large proportion in economic development. With the improvement of e-commerce platform, the traditional international trade (hereinafter referred to as ITT) has gradually changed to CBEC. In the perspective of ITT, the “Internet plus foreign trade” CBEC is a modern sales way, which caters to the characteristics of the fragmentation of sales orders and the individualization of product demand. Therefore, the average annual growth rate of CBEC in China exceeds 30%, which has become a new direction of ITT transformation and upgrading. Through CBEC, ITT has broken through the limitation of time and space, which has gradually reduced transaction costs. Therefore, computer CBEC has a positive impact on ITT. First of all, this paper analyzes the role of CBEC development. Then, this paper puts forward some problems. Finally, some suggestions are put forward.

Successful applications of ECT technology depend on the speed and precision of the image reconstruction algorithms. The image reconstruction for electrical capacitance tomography (ECT) is an inherently nonlinear and ill-posed inverse problem. To solve the problems, in this paper 12-electrode ECT system was set up to acquire real measurement capacitances under capacitance tomography that based on sensitivity field sensitivity matrix, which is T-LBP. In this paper four typical flow patterns are simulated, such as laminar flow, core flow, annular flow and bubbly flow, which in a circular section pipe. The simulation data indicate that the quality and the error, which was obtained in this paper, of the reconstructed images were better than the corresponding images obtained by the LBP and the Landweber algorithm. This new algorithm presents a feasible and effective way to research on image reconstruction algorithm for the industrial applications of Electrical Capacitance Tomography System.

With the wide application of information multi technology in the exhibition industry, the exhibition industry in developed countries presents a trend of intelligent development as a whole. The characteristics of the intelligent development of exhibition industry in developed countries are mainly manifested in the informatization of exhibition enterprises, the virtualization of exhibition projects and the intellectualization of exhibition venues. However, there are many disadvantages in the development of exhibition industry. China must learn from the development path of exhibition industry in developed countries. This paper first analyzes the Enlightenment of the intelligent management mode of exhibition venues in developed countries to China. Then, this paper puts forward some questions. Finally, some suggestions are put forward.

At present, reading and writing are divided into two independent courses in English teaching at most universities. According to the views of many scholars at home and abroad, it is more efficient to learn a language through integration of input and output, which advocates the integrated teaching of English reading and writing. The purpose of this paper is to verify whether the integration of reading and writing is helpful to the improvement of college students' ability through comparative experiment and random sampling method, and put forward an integrated learning mode of online reading and writing based on data algorithm. The main content of this paper is to elaborate the current situation of mobile reading and mobile writing in the era of big data, and then extract two groups of college students with similar learning conditions from two universities for empirical analysis, to study the differences in students' performance through comparison in the traditional reading and writing teaching mode and the new mode of integration of reading and writing teaching, and finally put forward the application of clustering algorithm based on K-Modes under the background of big data English learning scoring system, so that students can learn independently and efficiently on the Internet. The experiment shows that the average score of students in the integration of reading and writing is generally higher than that in traditional teaching. Under the integration of reading and writing, the students' reading accuracy is as high as 90%, which is 10% higher than that in the traditional way, and the score of writing is 5 points higher than that in the traditional way.