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Teaching technical writing to engineering researchers particularly post graduate students is a demanding and complex task. Often the challenge faced by the language instructor is in having inadequate understanding on students' expected writing output which is engineering research publication. While the language instructors may find the language use aspect manageable, it is the understanding on expected writing output for engineering discipline that is a challenge; therefore, supporting language module developers to understand those expected outputs is essential and needed for the advancement in language teaching. In view on the need for the description of the targeted output which is engineering publication, this study focuses on supporting the understanding of engineering research publication specifically on drones. This study is aimed to describe the perimeter of research publication on drones written by prolific engineering writers. This paper uses bibliometric analysis method which is based on identifying the core research and authors, as well as the works that cited them. This study examines 275 research publications indexed in SCOPUS database and also investigates 1947 research publications that cited the 275 publications as reference source. The findings show that the publications are mostly articles, conference papers and reviews deriving mostly from the US, China and the UK whereas the citing documents are mostly from China, the UK and the US. This paper presents the description on the perimeter for both groups. Such description provides a ready narrative to language instructors as well as ready narratives and guidance on writing/content dimension for young scholars embarking on writing scholarly articles on drone research. [ABSTRACT FROM AUTHOR]

Health and medicine has gained a lot of importance in today's digital world, where evolving technology is being used to fight against almost all the known diseases thoroughly. But, according to reports, more than two lakh people in China and one lakh in United States of America are dead every year due to the mistakes made while prescribing errors. This paper aims to propose a system which takes as input the symptoms from the patient to predict the disease, which is followed by recommending the correct medicine. This system consists of database system module where disease dataset contains attributes like "DiseaseID", "Disease", "Symptoms" and "count of occurrences" and drug dataset has additional attributes such as "drug" and "drug_rating". In the data preparation module, a new data frame is created where each disease with its associated symptom is given "1" and "0" if it is not the symptom related. After all these steps of preprocessing are performed on the raw dataset, the dataset is now ready to be acted upon by a machine learning algorithm. Models like Decision Tree, Random Forest and Naive Bayes were applied on the training-dataset. Entire knowledge database was fitted in models and it was seen if not much dataset is used Random Forest And Naïve Bayes classifiers showed 84% accuracy whereas Decision Tree gives 92%. But Random Forest also gives accuracy similar to Decision Tree for large dataset. Hence for disease prediction we use Decision Tree. The recommendation is done on the basis of the rating of the drug. After this, only the drug with the highest rating is included in a newly formed dataset and the rest of the drugs are ignored. The system is implemented for user access by making use of Tkinter a python GUI Library for constructing the desktop end user interface. This paper deals with the design and implementation of a system which performs the function of prediction of diseases and the recommendation of medicines, which adds to the capabilities of the present systems in health infrastructure. [ABSTRACT FROM AUTHOR]

The United States and China are strong trading partners of Malaysia, with about 23% of total exports in 2017. Therefore, the trade war pressures since 2018 between the United States and China have affected the Malaysian economy. Thus, this paper aims to analyse the effects of the war on the Malaysian stock market using a threshold network approach. Then, the networks examine the changes of important stocks before, during and after the trade war in which the periods are taken from 16th March 2017 until 31st May 2021. The important stocks are determined by four standard centrality approaches, namely degree centrality, closeness centrality, betweenness centrality, and eigenvector centrality. This paper uses 240 companies of the FTSE Bursa Malaysia Emas Index to create the Malaysian stock market networks. The results show that Dagang Nexchange Berhad and Jaya Tiasa Holdings Berhad have higher connectivity with other stocks during the turmoil period and after the turmoil period respectively. Besides, Dagang Nexchange Berhad acts as the most important stock according to all centrality measures. The findings of this study give an insight to the government regulators and investors with information regarding the current topological structure of Malaysia's stock market. [ABSTRACT FROM AUTHOR]

WeChat is the most popular social media in the world, especially in China. There is no overview of publications in the area of WeChat Research which shows the big picture using data from all countries. This paper aims to review the status and visual map position of WeChat publication indexed by Scopus used a Bibliometric. The research was carried out using Bibliometric techniques. Data analysis as well as visualization utilizing VOS Viewer program and the Scopus function for analyze search results. In this review, the details collected applied to 1.264 documents issued from 2012 through 2019. The study reveals that He, L. and Sun Yat-Sen University were the most active individual scientists and affiliated institutions in WeChat Research. In WeChat Research, the Computer Science and Lecture Notes in Computer Science Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes In Bioinformatics were the most areas of study and dissemination sources. There were three worldwide group maps with collaborative researchers. In order to identify the body of knowledge created from seven years of publication, this study constructed a convergence axis grouping comprising of WeChat Research: Social Networking, Education, Human, Article, WeChat. abbreviated as the SEHAW theme. [ABSTRACT FROM AUTHOR]

The physical health of teenagers is of great importance to the prosperity of China. Under favorable conditions of life, teenagers have declined in physical health trends, which has aroused extensive attention. Based on the above issues, this paper employs the literature review and expert interview method to analyze teenagers' physical health in China. By formulating and implementing a physical health policy, evaluation mechanism, educational ideas, the Ministry of Education formulated the policy of "sunshine activity" for one hour every day to establish the health awareness of teenagers. It is systematic training that enhances teenagers' physical condition. [ABSTRACT FROM AUTHOR]

Insider trading has become a topic discussed globally. This trading is a criminal offence punishable by an attempt to gain profit using financial information that is not available to the public and can cause a significant market reaction. However, outlier detection studies using statistical approach on detecting insider trading practices are relatively scarce. Therefore, this study aims to identify outliers in the stock market in order to detect insider trading behaviour. This paper proposes an instrumental research regarding the using of sequential fences analysis in the identification of stock market anomaly values in China's stock market. In order to attain the objective of this research, we exemplified the sequential fences analysis on data related to the China's securities market insider trading. The results show the viability of sequential fences in detecting unusual behaviour in stock market data and showing abnormal activity in Chinese capital markets. [ABSTRACT FROM AUTHOR]

Since its original announcement in Wuhan, the (COVID-19) has become a well-known medical illness in China and around the world. The plague has wreaked social and economic outcomes all over the world. The increased number of COVID-19 testing provides additional information about the pestilence's spread, potentially allowing our environmental factors to prevent future pollution wearing a facial covering that prevents flying beads, maintaining sufficient separation between individuals, and limiting close contact can all help to combat the outbreak. Hence, this examination paper centers on utilizing As an implanted vision framework, the Face Mask, and the Social Distance Discovery concept are used. Individuals who were found disregarding the local area or not wearing a veil were found. After making and eliminating the models, the anointed one got 100 percent certainty focuses. This paper gives a relative investigation of facial recognition and facial veiling models. Framework execution is tried for precision, memory, F1 focuses, and support. [ABSTRACT FROM AUTHOR]

This paper studies the impact of a covid-19 pandemic on the global economy. The empirical analysis of the work is based on data before and after (2019-2021) covid-19 and uses OECD data figures. The paper uses comparative analysis to find out changes during the pandemic and at the height of the pandemic, the global economy has passed the lowest point of the crisis, and it began economic growth in the leading countries of the world. This growth, like the crisis, developed in different ways in the economies of the US, EU and China. Our results show that during the pandemic, as a result of the lockdown, almost simultaneously, there was an abrupt increase in unemployment and a decline in production in all countries. In OECD countries, unemployment jumped from 5.2% in February to 8.5% in April, in the US - from 3.5% in February to 14.4% in April, in China - from 5.3% in January up to 6.2% in February. In China, both the epidemic and the economic crisis began earlier than in all other countries, respectively, the economy began to grow earlier. Our findings come to conclusion in a such way, despite the fact that, according to the forecast, the damage in the medium term will be less than after the global financial crisis, it is still significant. So, in 2024, the expected level of world production will be about 3 percent lower than before the pandemic. Countries differ in the degree of expected scarring, depending on the structure of the economy and the scale of the policy response. Emerging market and developing economies are predicted to face more palpable scars than advanced economies. [ABSTRACT FROM AUTHOR]

Preventive conservation, which originated from the field of heritage conservation in Europe, is a concept developed from modern conservation theories and practices. In the field of architectural heritage conservation, it aims to ensure that the value and historical information of architectural heritage are authentically and completely preserved to the maximum extent through minimal intervention. After being introduced into Chinese academia in the early 21st century, preventive conservation as a professional theory has gradually become a research hotspot with extensive discussions. Although preventive conservation is a foreign concept, throughout Chinese architectural heritage conservation history, a fact can be discovered: some practices in China from ancient times to the present have reflected the concept of preventive conservation. In ancient China, cyclical maintenance and regular repairs were important traditions of architectural conservation. The Qing court established the annual repair system, and there were also craftsmen engaged in building maintenance in the folk. In modern times, in response to the needs of protection and management, some protected cultural heritage entities in China carried out various forms of work such as monitoring and periodic inspection to conduct practical explorations of preventive conservation. Moreover, drawing on the international experience of preventive conservation, professionals preliminarily discussed the related issues of architectural heritage conservation in China. Based on years of research and efforts, the concept of heritage conservation in China is changing from "rescue conservation mainly" to "emphasis on both rescue conservation and preventive conservation". This paper gives an overview of preventive conservation of architectural heritage in China, including historical context, theoretical research, policies, and regulations. Furthermore, this paper analyzes the current status of architectural heritage conservation in China in combination with practical projects and conducts in-depth discussions of the existing problems, in order to explore effective methods for preventive conservation of architectural heritage in China. [ABSTRACT FROM AUTHOR]

Indiscriminate discharge of heavy metals into the environment is of great concern globally, especially in developing countries. The health risk caused by heavy metals pollution due to its toxicity, non-biodegradation, bioaccumulation, and complex operation with different sources and routes has accelerated as some industries expand with little investment plan around treatment. Over the years, research has been carried out on different aspects of heavy metals pollution, including-, emissions, impact on human health and environment, and mitigation processes. In this study, bibliometric and visualization analysis were used to analyze and evaluate the term heavy metal pollution, health risk, and its treatment approach was analyzed to acquire the overview of the heavy metal pollution on groundwater sources, health risk and treatment, and or removal approaches in different countries of the world from the web of science 1995-2020 publication. The outcome showed that China had a major interest in heavy metal pollution and its impact on lives and ecosystems in the past years as the highest publishers relating to heavy metal treatment technology.VOS viewer software and MS Excel were used as bibliometric tools for the examination of the researcher's certification in their research trends, progress, and publication performance. This, in turn, reveals the publication trends, subject categories and influential journals, country performance, most cited keyword and co-occurrence, author, and co-authorship collaboration network in heavy metals research, which would be of value to new researchers in the field. This paper highlights the trend in heavy metal removal from wastewater. [ABSTRACT FROM AUTHOR]

As of today, the People's Republic of China is one of the world leaders in space exploration. Relevance of this topic is determined by the New Space Chinese innovational private companies emerging in the aerospace technologies and services market, as well as by increased competition and growing demand in the economic use of outer space, other planets and space objects resources from business and governments. This paper provides a review aimed at analyzing the ongoing transformation of the Chinese space industry ecosystem. Review results demonstrated that China has every chance of taking a leading position in the international space race. [ABSTRACT FROM AUTHOR]

China's urban railway network already covers 80 percent of the country. The support of a continuous line is inextricably linked to the rapid expansion of railways. The seamless line has a complex structure, a long working period, and is susceptible to environmental and other factors. This paper mainly studies the design and implementation of seamless line displacement data detection by using image recognition technology and machine learning technology. This topic trains and learns the digital content in the seamless line displacement scale through the machine learning SVM classification algorithm, and then identifies the scale mark and other data by image analysis to calculate the final displacement. In this way, the accuracy of the identified displacement data is very high. This study detects the displacement of the seamless line and gives early warning when the displacement exceeds the safety range. After receiving the early warning information, the management personnel can handle it in time to avoid danger. Some railway portions in Harbin have been subjected to the study. The research can assist railway management departments in detecting seamless line facilities and improving maintenance efficiency. At the same time, it can provide timely warnings of potentially risky information, reducing the likelihood of accidents. [ABSTRACT FROM AUTHOR]

Higher vocational education in the field of rail transit has entered a new period of development owing to the reform and opening up. Based on the current situation of "One Belt, One Road", the higher vocational education in the field of rail transit conforms to the overall situation of service, and helps China's higher vocational education enter into the international market. This paper analyzes the development prospects of rail transit, then discusses the sustainability and feasibility of the internationalization of higher vocational education and concludes the ways of sustainable development. [ABSTRACT FROM AUTHOR]

In recent years, the area of arable land in China has been decreasing year by year. This is in sharp contrast to the massive infrastructure construction program. This raises a question: how to make full use of limited land resources for large-scale construction. Fortunately, the sustainability concept has been increasingly accepted to be a key aspect of engineering design and construction. Based on this important background, concepts of foundation treatment technology development are introduced in this paper. [ABSTRACT FROM AUTHOR]

CiteSpace III is used to do the knowledge map analysis to all the innovation diffusion research literature collected in the Web of Science core set database. Time and space distribution, key national network, co-cited reference and co-word knowledge maps, such as in the field of innovation diffusion is analyzed on the distribution, change trends and hop topics. The study results show 1) China and the USA are leading in the field of innovation diffusion research, 2) earlier studies mainly focused on the macro level to forecast the new product sales by using the Bass model and its extended model, 3) the current research has focused on from micro level to analyze the evolution of the innovation diffusion behavior by simulation method 4) the hot topics of innovation diffusion research mainly includes the acceptance and adoption of innovative technology, the influencing factors of innovation diffusion, innovation diffusion power, innovation diffusion model and simulation study. [ABSTRACT FROM AUTHOR]

In recent years, the production and the export rate of tea has shown a non-convincing result when compared to other leading tea producing nations like China. China is still the leading tea producing country and for India to compete, the production rate and export rate must be improved. Tea produced in India are one of the finest across the globe and it is because of climate, the way of maintaining tea gardens and also the importance given by people towards tea farming although can be improved by large. An attempt by factor analysis is done to prioritize the factors and focus on those top prioritized factors namely material processing of tea for improving export rates and achieving sustainable productivity. This research paper focuses on this problem by collecting and analysing the sustainability factors in tea material processing using COPRAS and WASPAS tool. [ABSTRACT FROM AUTHOR]

(COVID-19) is an epidemic disease with symptoms similar to the flu. Since December 2019, the new Coronavirus has appeared in China and spread all around the world. As a result, the rapid and severe spread. For example, computed tomography (CT) and x-rays are utilized to find an available and accurate diagnostic tool. Artificial intelligence technologies make a significant contribution to the diagnosis and analysis of medical images. As a consequence, it was used to detect and diagnose Covid-19. Thus, the entire major medical scanning will be covered in this review paper, especially Focus mostly on last year's combination of Artificial Intelligence with CT and X-ray. Both are commonly used on front-line medical clinics to identify the recent results of fighting COVID-19. [ABSTRACT FROM AUTHOR]

The major problem, nowadays is the novel coronavirus or covid-19 pandemic which has and still infecting people and causing the death of many around the world. Although strict and severe actions have been taken by the government of all over the world to control and minimize the spread of this virus by lockdown, suspending, all travel and sport activity, economic and social activity, quarantines, travel restriction at stations and airport, etc, many of the people around the world have lost their lives and many are suffering. Recently, a conducted study has reported that in China the number of cases that were not documented is 79% as they show no symptom of the virus. In many other countries, the real representation of the patient infected by the virus was different from the real number which was higher in number. Hence, patients with asymptomatic conditions are the major reason for the fast and large covid-19 spread and are also the major reason that caused the people too afraid of the situation. To contribute this global pandemic, in this paper, we propose an investigation which is IoT based system designed to detect both symptomatic-asymptomatic infected people, undocumented, and the place of the pandemic. The aim is to make the authority and people aware of the situation by providing the total numbers of the cases registered, totally recovered, and death of the people caused by the pandemic. In the proposed system, we have used the IoT (internet of things) technology with the NODEMCU-ESP8266, LCD, and Wi- Fi connection to provide information of the important numbers of the patients of covid: cases, recovery, and death of the people in India. This system may keep people more informative, protected, and aware of the danger of the virus so they can take care of themselves and their families in every possible way. [ABSTRACT FROM AUTHOR]

Current situation in our country is been suffering from a dangerous disease called corona virus which is seen both creatures and human beings. SARS (Severe Acute Respiratory Syndrome) -COV is an example for corona virus.Retrosepective observation by Chinese people have seen many number of cases with start of manifestation in the month of December 2019[1].The first case was seen in china with different types of symptoms and it is known that it was a transmittable disease.Many people who are suffering with this will have an illness which is related to respiration part and it will be cured after taking the period of quarantine for 14 days, with any different kinds of treatments at home or an advice of doctors. Some people who are been affected others health issues will develop serious illness. Around 90% of the people are recovered without undergoing any special treatments because they themselves taking quarantine at home by following home remedies. But some people are being suffering with trouble breathing [5].In the month of March 11 2020 (WHO) recognized and declared it as an pandemic which has spread in many parts of the country within less span of time. This virus was first seen in a city called Wuhan, state of China. In the month of December 2019 the reports of the first COVID-19 cases have started. Yet, it is undecided exactly the spread of this virus and it is spreading very faster in humans. This paper tells about control and safety measures regarding water, sanitation, wash in covid-19 pandemic [1] and following the prevention methods critically is very essential to avoid the spread of this virus.Maintaining cleanliness, following all the rules, and advising your loved ones to do likewise for averting the transmission of SARS-CoV-2. [ABSTRACT FROM AUTHOR]

The electric communication technology is gradually mature. With the technological breakthrough of Huawei, a Chinese science and technology enterprise, 5g technology has been gradually developed and popularized for commercial use in China. The 5g era of high speed, low delay and promoting the interconnection of all things is coming as promised. Technological innovation in the field of electric communication is also one of the standards to measure the national scientific and technological innovation ability. In order to seize this potential communication market and improve China's comprehensive competitiveness, China has continuously provided resources and platforms for scientific and technological enterprises to carry out industry university research cooperation. Taking Huawei as an example, this paper explores the innovation strategy behind the technological achievements in communication field from the perspective of industry university research collaborative innovation network, which has reference significance for other enterprises to optimize alliance network and realize efficient R & D. Not only that, the patent database is constantly improving and mature, patent measurement to a certain extent can deeply understand the technological innovation of enterprises, and it has great practical value and social significance to carry out patent Measurement Research on leading enterprises. Based on the patent perspective, through the analysis of applicants and inventors, this paper will deeply analyze Huawei's industry university research cooperation network with universities in the field of electric communication, explore its innovation strategy, summarize the characteristics of its innovation network, and put forward development suggestions for reference according to its shortcomings. [ABSTRACT FROM AUTHOR]

The concept of ritual originates from religion and has become a core concept of symbolic consumer behaviors. Symbolic value, as part of product value, may also play a role in promoting consumer loyalty. More importantly, this approach can be implemented by relying on a consumption ritualization process. Following the ritualistic path to discuss the realization of platform loyalty is even more urgent in the digital age. This may be attributed to the gamification trend and social features of digital platforms. In this paper, we focus on the symbolic value of digital product as an antecedent to the consumption ritualization process, which is expected to have a positive relationship with platform loyalty. This study has two purposes: (1) review the literature on symbolic value and consumption ritualization, and (2) propose a plausible conceptual model to illustrate the relationship between symbolic value, consumption ritualization, and platform loyalty in the context of digital platforms in China, as moderated by the platform's gamified feature and social feature. More detailed empirical research will be based on structural equation modeling approaches. The research findings will be particularly important for digital platform marketers to timely respond to external events and actively participate in the consumption ritualization practices. [ABSTRACT FROM AUTHOR]

As an integral part of marketing channel research, the research of marketing channel performance is conducive to reflect the current situation of marketing channel on the one hand and contributes to optimizing management process and improving enterprise management level on the other hand. Therefore, it has been the highlight of research for many years. For automobile producers, an effective marketing channel is a grind to promote product sales and redefine marketing costs, which enables them to gain a competitive edge in the market competition. Therefore, this paper intends to circumscribe the impact on the marketing channel performance from multiple aspects. It analyzes channel synergy as a mediating variable determines internal and external factors as independent variables. [ABSTRACT FROM AUTHOR]

In 2019, the world witnessed a rapid spread of the Coronavirus (COVID-19) disease in one of China's cities, Wuhan. The disease was announced in December 2019 to be a springboard for the whole world, where most countries were infected with it. It greatly affected the health of society and became a real danger to humans. Therefore, it is necessary to diagnose the infected people and quarantine them to combat this pandemic and limit its spread. This paper aims to give a review of COVID-19 diagnosis methods. According to the diagnostic methods, the previous works are classified into two categories for diagnosing Coronavirus; X-ray and Computed Tomography (CT)-Scan. Artificial intelligence (AI) is used to improve the diagnosis accuracy of the presented methods. On this basis, automated diagnostic tools have been developed that distinguish people infected with the Coronavirus from other diseases. Moreover, the performance parameters of the previous studies were compared in terms of diagnosis method, adopted algorithm, diagnosis accuracy, sensitivity, and specificity. Furthermore, the challenges and limitations of the existing methods for diagnosing Coronavirus were explored. AI has proven to be a reliable way to diagnose the spread of the epidemic through advanced algorithms based on blind and machine learning, especially the convolutional neural network (CNN), which plays a vital role in extracting sensitivity, specificity, and accuracy. [ABSTRACT FROM AUTHOR]

A successful vaccination program depends on secure vaccine storage as well as safe and effective vaccine delivery. An Internet of Things (IoT) based vaccine distribution and monitoring model, which is used to transport and monitor vaccines to locations where they will be properly kept for eventual use, is developed and tested. Coronavirus (COVID-19) was first identified in December 2019 in Wuhan city of China, but it is still spreading throughout the world. The impact of this virus is minimized by educating people about its causes and how it spreads is the best way to avoid and slow down transmission. Different technologies have already been developed to minimize the impact of COVID-19, and the Internet of Things (IoT) is one of them. It is a very popular technology that is being used to fight this virus. The vaccination process is already running across the world; maintaining the temperature of the vaccine during the supply chain logistics is the most important task to maintain the effectiveness of the vaccine. In this paper, an IoT-based architecture has been proposed for the effective monitoring and distribution of the vaccine. The developed model can also be utilized for the effective distribution of various types of vaccines and to minimize the wastage of vaccines. [ABSTRACT FROM AUTHOR]

This paper adopts a very convenient 3D CAD method to quickly assess the seismic vulnerability of existing masonry towers. The study selected five typical collapse mechanisms, vertical splitting, base rocking, overturning with diagonal cracks (according to Heyman's approach on tilting towers), a combination of splitting and diagonal overturning and base sliding. The Zhongjiang South pagoda in China is selected as the research case. Basing on the principle of virtu-al works, assuming that masonry behaves as a small cohesion and frictional material, the collapse acceleration is calculat-ed with a direct manual procedure. The research results show that vertical splitting is the easiest collapse mechanism to appear, which is in full compliance with the results of the on-site survey carried out after the Zhongjiang earthquake, fur-ther demonstrating the reliability of this method. Such approach does not require complex mathematical foundations, can be easily mastered by non-professionals, and at the same time greatly reduces the amount of simulations/calculations, a feature which is helpful for the promotion of seismic research of masonry structures. [ABSTRACT FROM AUTHOR]

In this paper, we bring a comparison study between the original genome sequence of SARS-CoV 2 virus, ID: MN908947, coming from China 2019, and sequences of SARS-CoV 2 virus - P.1 variant, coming from Brazil 2021. Using tools of stochastic processes and through the identification of each sequence as being a sample of a stochastic process, after finding the best model for each sequence, we build dendrograms using a metric introduced in [1] that show that the original sequence can be considered in a separated cluster when compared with the P.1 variant. [ABSTRACT FROM AUTHOR]

Coronavirus is a disease that has made a significant impact all around the world. Initially, its eruption occurred in Wuhan city in China, later on, its proliferation spread everywhere in the universe. The topological index is a numerical descriptor that combines the molecular structure with copious fields such as chemical, biological, medical and so on. Using these indices, it is possible to characterize and study the physico-chemical properties of drugs. The molecular structure of two pharmacological medications, chloroquine and hydroxychloroquine, is compared in this research, which is used to impede the coronavirus outbreak and, in the meanwhile, we compute some topological indices relating to the same. This paper forms a base for further analysis and to explore new vaccines and drugs in the future. The foremost intention of the work is to have a combined knowledge of graph theory and chemistry by using the topological indices and molecular structure of the chemical compound. [ABSTRACT FROM AUTHOR]

In recent years, the human population has reached its peak in both the developing countries and developed countries like India and China. An increase in personnel density ended up being a hard task to maintain or manage people flow in socio-public places. However, people flow management is out of control for humans, which may also cause some safety damages. This paper aims to give an optimal solution for people flow with the help of machine learning, deep learning, and also AI-cameras are used for counting the number of people entering and leaving a user-defined place. Here, also the centroid tracking and centroid detecting algorithms are used to count the number of people together with their direction. This technique helps to replace manual security,in-store traffic management, and much more. [ABSTRACT FROM AUTHOR]

Today, the whole world is fighting the war against Coronavirus. The spread of the virus has been observed in almost all the parts of the world. Covid-19 also known as SARS-Cov-2 was initially observed in China which rapidly multiplied all over the world. The disease is said to spread by cough, normal cold, sneezing or when a person is in close contact with someone who is already infected. Therefore, the spread of the virus can occur when there is direct contact with an infected person or with the objects touched by the infected person. Hence, it is important to detect the contiguous spread of the virus and control it by taking appropriate measures. Several deep learning models have been used in detecting many diseases like Malaria disease, Lung infection, Parkinson's disease etc. Likewise, CNN model along with other transfer techniques is best proven to detect whether a person is infected with covid positive or not. The dataset consists of 1000 images of covid positive and normal x-rays. The proposed model has been trained and tested on the image dataset with the help of transfer learning models in order to improve the performance of the model. The models VGG-16, ResNet-50, Inception v3 and Xception have achieved an overall accuracy of 93%,82%,96% and 92% respectively. The performance of all the 4 architectures are analyzed, understood and hence presented in this paper. It is hence important to classify and detect covid positive infection and contribute towards making the world Covid-free. [ABSTRACT FROM AUTHOR]

In order to explore the influence of center location and indirect connection between provinces and cities in the regional innovation network on their innovation capability, the regional innovation network of 29 provinces and cities in China is represented by using the gravity model adjusted. The centrality is selected to characterize the center location characteristics of provincial nodes. The social network analysis and regression analysis are used to study the relationship between the provincial node centrality and indirect connection of the node and its innovation capability. This study shows that provincial node centrality can promote its innovation capability, and the indirect connection of provincial nodes inhibits the innovation capability of nodes. Moreover, the number plays a u-shaped role in regulating the centrality and innovation capability of provincial nodes. [ABSTRACT FROM AUTHOR]

Introducing cutting-edge Internet technology to set up a prototype ecosystem monitoring system using rapidly advancing smart devices and IoT technology for environmental tracking in remote environments. Dedicated to the management of ecosystem monitoring expertise and full-context object video smart, real-time, low-cost and rapidly changing ecosystems, first-rate evaluation algorithms that are now mixed are crucial when evaluating the latest display device homes. The latest application of this IoT monitoring ecosystem has been tested in three fragile ecosystems, including the Karst Rock desertification area, the National Park for the Amur Tigers, and the Oasis-Barren Area Ecoton in China. Advances in IoT surveillance environments include new statistics loggers and long-range Wi-Fi sensor community technology that can rapidly transmit advanced data from devices to wireless networks. By integrating these gadgets and technologies with the Ecosystem Tracking Statistics gadget, IoT allows continuous record collection, transmission, processing and alerts. With advances in cell technology, smart cellular computing devices have become more advanced, less expensive and more effective, leading to tremendous growth in both advanced cell users and their bandwidth requirements. [ABSTRACT FROM AUTHOR]

This study analyses return volatility for Malaysia and China's stock markets during the SARS and COVID-19 pandemics. Stock return volatility is estimated using GARCH family models (GARCH (1,1), TGARCH and EGARCH). Generally, GARCH (1,1) estimates symmetric conditions, whereas TGARCH and EGARCH estimate the asymmetric condition or leverage effect of return volatility. Stock return volatility in China and Malaysia are then compared to assess the severity of pandemic cases during the study period. Post pandemic, Malaysia is seen to experience higher decrements in leverage effect when using the TGARCH model. Conversely, the effect is higher for China when using the EGARCH model for the SARS pandemic. To aid in predicting future return volatility after the COVID-19 pandemic, return volatility after the SARS pandemic is forecast, with the forecast value serving as the basis for evaluating the error using the mean absolute error (MAE), root mean square error (RMSE) and Theil inequality coefficient (TIC) approaches. The forecast error performance is ranked to identify outperforming GARCH family models for the pandemic period: the TGARCH model for China's stock market but the GARCH model for Malaysia's stock market. [ABSTRACT FROM AUTHOR]

China is in the critical period of building a moderately prosperous society in an all-round way. It is the period of rapid economic transformation and the decisive battle for deepening the reform. China's development is facing new opportunities and challenges. The risk of foreseeable and unforeseen is increasing. Combined with the new coronavirus, (coronavirus disease 2019 is a new type of pneumonia, also named Covid-19) one of the global biological risk events, this paper analyzes the challenges faced by China in the future in response to biological risk, and discusses how to deal with microbial risk in the future, makes in-depth thinking and puts forward suggestions. [ABSTRACT FROM AUTHOR]

There is no substitute for the primary responsibility of parents in child discipline. We studied the situation of parents with two children in China, focusing on the comparison of parents with only children who are inadequate to the education of two children. The specific dilemmas of Child discipline vary. It is reasonable to analyze the rescue mechanism of child discipline in China. In the future, as having two children at home is a common phenomenon, parents need to have tutoring ability. To help parents of two children achieve the goal of successful tutoring, the government needs to take the lead in setting up the mutual aid system. [ABSTRACT FROM AUTHOR]

The importation of Malaysian durian provided a case study for the teaching and learning about market environment analysis for undergraduate students of Zhaoqing University. Working in two teams of 15 to 16 members the students investigated the factors affecting the market environment in China for Malaysian durians importation which included the production of Malaysian durian, a comparison between Thai and Malaysian durians, the regulatory framework governing the importation of Malaysian durian into China. The current market situations for durian in China as well as possible marketing options for whole fruit frozen Malaysian durians in China were also investigated. The study concluded that building a Malaysian durian brand in China and expanding the varieties available in the market to not overly dependent on the Musang King variety are key factors for the success of Malaysian durians in the China market amid formidable competition with Thai durians which have a substantial share of the market at present. [ABSTRACT FROM AUTHOR]

The construction of Jiqingli Tea Garden in Guangdong Province was rated as one of China's top ten beautiful tea gardens by the Ministry of Agriculture in 2014. In 2019, Jiqingli Tea Garden started a digital art project of 4D holographic projection to create Jiqingli's cultural landscape and created a tourism resource of the whole realm by taking advantage of the landscape and topography of the tea garden. The digital art project of 4D holographic projection for the cultural landscape of Jiqingli tea garden innovates its tourism cultural resources by using modern digital media design and integrating digital scientific and technological means to transform the singing and dancing, music, and tea picking culture into audio-visual works of 3D holographic projection. For example, the project uses digital acquisition, digital design, digital special effects, digital sound, 3D animation holographic laser projection, virtual reality technology, and other scientific and technological means to recreate the landscape culture and art of the Jiqingli tea garden. Digital technology allows forming a 3D three-dimensional work of large-scale acousto-optic holographic images and adding the situational language of scientific and technological means. It forms the effect of 4D holographic projection to allow the audience to be personally present. The project aims to create a brand-new visual, audio, and emotional cultural product for the space of Jiqingli tea garden to realize the creation of new eco-tourism resources combining ecological natural resources and digital media design. [ABSTRACT FROM AUTHOR]

The very rapid development of technology today cannot be separated from the role of artificial intelligence. Artificial intelligence is a thought process or intelligence like humans' that machines can use to do specific jobs. The use of artificial intelligence is very diverse in various fields, including the health sector. Recently the world's media has been shocked by the virus spread in China, namely the coronavirus. Corona can cause severe pneumonia for sufferers. Pneumonia itself is inflammation of the lungs caused by a virus. One of pneumonia sufferers' characteristics is that there is a fluid that looks like white spots on radiology or chest X-rays. However, it will be challenging to diagnose because at a glance, the radiological test results of lungs with pneumonia and normal lungs are similar. So, misdiagnosis is possible. Therefore, this study aims to create a machine learning model to classify lungs with pneumonia and normal lung on chest radiological images using the Convolutional Neural Network (CNN) algorithm. CNN is well known as a method in which the data process both image and video. The classification obtained for validation results in an accuracy value of 94%-99% for the pneumonia category, which suggests that the model can predict the image correctly. Meanwhile, for normal lung images, the accuracy rate is 84% -98%. This shows that the model can predict almost all of the images well; there is only one image that is not predicted correctly. [ABSTRACT FROM AUTHOR]

In recent years, acute myocardial infarction has become a public health problem attracting worldwide attention. Various countries have adopted various public health policies, among which the quality improvement plan for acute myocardial infarction is the most important part of the measures, which effectively reduces the occurrence of acute myocardial infarction. However, at the same time, the quality improvement plans of various countries still have many inadequacies, which are more worthy of our reflection and improvement. This article will compare the major public health policies of China and developed countries in the United States in dealing with acute myocardial infarction, and then provide reference for improving the quality of life of patients with acute myocardial infarction in China and improving the hospitalization rescue rate of patients. [ABSTRACT FROM AUTHOR]

In recent decades, China's renewable power generation has developed quickly. However, the randomness of output power causes wind and photovoltaic power curtailment. With the rapid development of renewable energy, renewable energy consumption has gradually become the focus of research. This article comprehensively reviews the current situation and practices of reducing the curtailment of renewable energy in China. From the perspective of methods used to stabilize the fluctuation characteristics of generation output, two modes are outlined: based on energy storage devices and complementary wind-solar system. Then, an Advanced Adiabatic Compressed Air Energy Storage (AA-CAES) system simulation model is proposed as a crucial solution to reduce renewable energy waste. Finally, the application and development trend of renewable energy and energy storage technology has prospected. [ABSTRACT FROM AUTHOR]