Development Of Internet Research Articles

The conservation and utilization of museum relics based on internet of things and fuzzy control

With the development of Internet of Things and fuzzy control theory, there are new opportunities for the conservation and utilization of museum artifacts. The traditional way of heritage restoration lacks the overall harmony of heritage restoration, which leads to the stagnation of heritage restoration level. At the same time, traditional heritage conservation is also limited to manual management, which seriously hinders the development of the overall level of museums. Artifacts are of great commemorative and research value and are objects that have been handed down to mankind for thousands of years and have been subjected to the natural environment for a long time before being excavated. Heritage conservation requires not only restoring artifacts to the greatest extent possible, but also securing the environment in which they are displayed and stored to ensure that they can be preserved for as long as possible. But the following problems exist in the conservation of cultural relics (1) the lack of strict standards for the environment in which cultural relics are stored. (2) the professional competence of the staff is not strong. (3) The lack of a strict management system (4) heritage conservation technology is backward. To solve these problems our team constructed a fuzzy control method based on fuzzy control theory to assist in the restoration of cultural relics. The model constructed by fuzzy control theory solves this problem. The fuzzy control theory constructs a model for restoration of cultural relics, taking into account the overall harmony of the relics and the accuracy of the points, which is of great significance for the restoration of museum relics. At the same time through the Internet of Things technology to build a library heritage protection system, the main content of the system is (1) the use of Internet of Things technology to build a security protection system for cultural relics (2) the use of Internet of Things technology to detect the storage environment of cultural relics (3) the use of Internet of Things technology to optimize the management process of cultural relics (4) the use of Internet of Things technology to achieve real-time monitoring of the flow of information on cultural relics. And based on this, suggestions are made to (1) improve the museum heritage protection and utilization system (2) improve the infrastructure of museum heritage protection and build a good environment for heritage storage (3) improve the quality of heritage managers. The model constructed in the article has been tested in practice and is feasible, with certain practical and theoretical values.

SOCIAL MEDIA AND THEIR EFFECT ON POLITICAL PARTICIPATION

The swift information-communication technologies development, especially the Internet in the last part of the XX century, had a significant degree of influence on human life around the world. It considered the internet evolution path and its effect on the possibilities increasing for communication and getting large quantity information, as well as the democracy establishment and open politics implementation. It analyzed further technologies growth, related to the internet in the XXI century beginning, stressed the role of modern technologies for the interaction perspectives widen, connection establishment in the society and favor in different social media creating, that is: social media has got broad spread around the world thanks to its flex possibilities for communication enhancement, as well as producing, transmitting, following information. It considered several researchers’ points of view on the possibilities of Internet influence on politics and its role as a path of communication for information exchange. It provided examples of early research on the impact of the early Internet on political participation and noted the ambiguity of scientists' opinions on this topic. It provided examples of research on the impact of the early Internet on political participation and noted the ambiguity of scientists' opinions on this topic. It scrutinized social media in the context of their effect on society's behavior, particularly on the political participation level. It described social media as a product of internet development and considered its main features. It is noted that social media, thanks to their interactivity, can theoretically have a positive impact on the political aspect of people's lives, as well as a negative one. It reviewed the results of empirical studies devoted to the topic of social media's influence on the political participation level and stressed the complexity of the specified problem.

Has the healthy city pilot policy improved urban air quality in China? Evidence from a quasi-natural experiment

Air pollution has caused serious consequences, and improving air quality has become a major global challenge. The environmental improvement of a healthy city is widely recognized, but quantitative assessment of its effect is still relatively rare. In the context of the “Healthy China” strategy, this paper considers the healthy city pilot (HCP) policy in China as a “quasi-natural experiment.” Based on the panel data of 288 prefecture-level cities from 2009 to 2020, a difference-in-differences strategy is used to examine the effect of the HCP policy on urban air quality. Our results show that the HCP policy effectively decreases PM2.5 by 6.8%, dust by 6.0%, SO2 by 2.4%, and CO2 emissions per capita by 8.8%. The findings continue to hold after a series of robustness tests. Mechanism analysis shows that the HCP policy significantly decreases industry pollutant discharge, increases city innovation, promotes efficient energy use and transformation, and improves public transport system and green infrastructure. These mechanisms play an important role in improving air quality. Furthermore, the HCP policy greatly improved air quality in regions with substantial populations, low financial pressure, high Internet development, and medical levels. In summary, the government must review the results of implementing the HCP policy and incrementally expand the number of healthy cities. Increasing the weighting of air quality in policy assessment and strictly implementing a mechanism that combines incentives and disincentives.

Analysis of Influencing Factors of Public Crowdfunding Based on Social Media- -Take “Water Drop Fund” as An Example

With the popularity of mobile phone clients and the rapid development of Internet, social media has infiltrated into people’s daily lives. In this context, China’s public crowdfunding has developed and grown, forming a unique operating mode under the impact of the times. Many public crowdfunding platforms based on social media such as Weibo and WeChat have emerged. “Water Drop Fund” is a typical new public welfare under the combination of social media and public welfare. By studying the “Water Drop Fund” platform, we can discover the epitome of this new form of public welfare under the context of the new era. This article takes “Water Drop Fund” as an example, collects relevant information about applicants on the public welfare platform, and uses regression analysis to describe the different influencing factors in this crowdfunding project. It summarizes the relationship between various factors and the crowdfunding rate, and further discovers that the target amount, the number of confirmations, and the number of reposts are the key factors affecting this new type of public welfare crowdfunding. Suggestions for the future development of the public welfare crowdfunding system are made based on these key factors.

A Study of Peer Academic Support Mechanism Based on the Context of Dual-Line Integrated Teaching

In recent years, students' academic pressure has grown exponentially due to various factors, including epidemics. This paper takes the Henan University of Chinese Medicine as an example and the educational requirements in implementing "the 14th Five-Year Plan for the Development of the Digital Economy" in higher Chinese medicine colleges and universities as the defined goal. The peer mutual aid mechanism is used as the main core, systematically elaborating the construction of the academic support mode of Chinese medicine colleges and universities under the academic background of dual-line fusion teaching. It is aimed to explore a method of academic support suitable for the current situation and help students get rid of academic pressure, which can contribute more to our society. It is argued that secondary colleges need to change the conventional idea of academic support. In the context of the rapid development of the Internet, we should take full advantage of the Internet development and combine it with the current education mode and student characteristics. As a result, we have proposed the "Two-multiple, One-precise, Both-balanced" concept of academic support. It provides a new way of understanding the academic support of Chinese medicine colleges under the background of dual-line fusion teaching.

Perkembangan Teknologi E-Business Terhadap Globalisasi Modern Pada Saat Ini

Current technological advances reflect significant changes from the previous technological era to the present. Especially, internet development has become a trend among local and international communities. For example, e-business is in the spotlight because it makes things easier and gives business entities a lighter burden, especially for those who have the ambition to achieve success. E-business not only increases marketing networks, but also increases employee productivity within the company. Information technology provides the ability to initiate business creativity and innovation quickly and efficiently. It is important for businesses to see new opportunities amidst continued development, with the key to success returning to motivation and innovation, thereby creating technology that is always up to date.

Application of Short Video Semantic Understanding Technology Based on Big Data Analysis in Education Management

With the emergence of short video and the development of mobile internet, short video software, such as TikTok and Kwai, has emerged. Based on the semantic understanding technology of teaching short videos, a teaching management platform was built to push healthy and positive short video for students' content in a targeted way. Taking the 21st grade students majoring in Chinese in Guizhou Normal University as an example, the authors discusses the effect of teaching management platform on college students. In this process, the following conclusions are drawn: (1) Among college students, the viewing rate of short videos has exceeded 95%, and short videos have become an indispensable entertainment for most college students. (2) Through short video semantic understanding technology and short video screening program, excellent short video can be effectively pushed to students. (3) The actual effect shows that the short video teaching management platform can effectively improve the values of the cultural level of students.

A Survey on IoT Task Offloading Decisions in Multi-access Edge Computing: A Decision Content Perspective

The rapid development of Internet of Things (IoT) technologies has led to increasingly complex software systems on Terminal Devices (TDs). This increases the computational load and battery consumption of TDs. The emergence of Multi-access Edge Computing (MEC) and computing offloading technology allows TDs to delegate computing-intensive tasks to the MEC network for remote execution. However, the computing and communication resources of MEC networks are limited and heterogeneous. In addition, some TDs may have a higher mobility. Therefore, IoT networks need to dynamically decide to offload some or all of the computational tasks to appropriate nodes in the MEC network. Existing reviews do not fully cover the multiple decision-making content of task offloading, and some studies do not clearly define the boundary between task offloading decision-making and task offloading scheduling optimization. This study investigates the similarities and differences between the enabling technologies, deployment architectures, and decision items of various decision mechanisms from the perspective of offloading decision content. Thus, the development and existing challenges of task offloading decision-making methods are comprehensively demonstrated, and future research directions are proposed for IoT task offloading decision-making in MEC.

SMART GROW – Low-cost automated hydroponic system for urban farming

Urban farming has gained popularity in recent years, as more people have become interested in locally grown food and reducing their carbon footprint. Smart hydroponic systems can be an important tool for urban farming as they allow for precise control over plant growth and require less space and resources than traditional farming methods. Urban areas often lack access to land suitable for farming, making hydroponic systems a viable option for growing crops in limited space. Readily available hydroponic systems in the market are costly and not cost effective, thus hydroponic systems are usually only installed in larger scale farming. The challenge here is to connect multiple low-cost sensors to microcontrollers and to any store-bought hydroponic set. This paper describes the development of smart Internet of Things (IoT) hydroponic system integrated with an Android mobile application for small scale urban farming.The new set up of IoT hydroponic set, coined as SMART GROW, is used to monitor and control various aspects of the system based on the basic parameters important in growing a healthy plant. The challenges faced during this build were irregular reading of the analog sensor when connected to a single board microcontroller (ESP32). This issue was resolved. SMART GROW currently is capable of monitoring basic parameters such as pH, EC and water level and can cater to additional sensors for monitoring other parameters if required. SMART GROW can easily be replicated and built at home and customized to the needs of the plant’s requirement. SMART GROW is versatile as it can be used to grow a wide variety of plants, including herbs, vegetables, and fruits, and offers several benefits over traditional soil-based growing methods such as automated regulation of the water level.

A study on the impact mechanism of internet embedding on rural E-commerce entrepreneurship

In the context of the rapid development of global Internet and e-commerce, rural e-commerce entrepreneurship has become an important driving force for rural e-commerce development. Using micro-survey data from five national e-commerce demonstration counties in China, this paper empirically examines the impact of Internet embedding on rural e-commerce entrepreneurship and the mediation effect of social capital. The results show that farmers are more likely to choose an independent entrepreneurship channel than a cooperative entrepreneurship channel when the Internet is embedded in rural areas. Then, social capital plays a suppressing effect between Internet embedding and farmers’ e-commerce entrepreneurial choices. In addition, under the condition of Internet embedding, farmers with more social capital are more likely to choose cooperative e-commerce entrepreneurship channels.

Tracking household carbon inequality in China: Composition effect or coefficient effect?

Reasonable allocation of carbon emission reduction tasks requires addressing household carbon inequality. This study aims to track characteristics of household carbon inequality in China using the recentered influence function (RIF) based on the Household Tracking Survey data in 2018 and the multi-regional input–output table. The Oaxaca–Binder decomposition based on RIF further decomposes household carbon inequality based on spatial heterogeneity into composition and coefficient effects. The results indicate that (1) household carbon inequality is widespread in China, generally close to the 60/30 distribution, favouring high-income families. Furthermore, (2) increases in income, wealth and economic burden and declining marriage rate promote household carbon inequality, which is suppressed by the development of education and the Internet and the increase in car ownership. Additionally, (3) the carbon inequality of urban households is smaller than that of rural households, which is contributed by the composition effects of family size, education, car ownership, Internet development and the coefficient effect of income and housing. Finally, (4) under the composition effect of family size and the coefficient effect of income, the household carbon inequality in the eastern region is smaller than in the central and western regions.

Geomagnetic indoor localisation-based dilated convolution neural networks

ABSTRACT With the rapid development of mobile Internet, the demand for Indoor Location-Based Service (ILBS) keeps rising. Geomagnetic field fingerprinting-based positioning scheme, with low cost, high accuracy and good stability, has gradually earned the attention of researchers. There are many problems in the existing indoor localisation researches based on geomagnetic fingerprint recognition, such as heavy workload of fingerprint collection, insufficient positioning accuracy, high walking cost of positioning and long positioning delay. Therefore, a localisation system named DCGIL is proposed in this thesis. In DCGIL, a segmentation length estimation algorithm of geomagnetic fingerprint sequence is proposed to evaluate the minimum segmentation length, the shortest walking distance. Then, through an overlapping fingerprint segmentation method, the gap between coordinate points and the cost of fingerprint matching are reduced. Further, dilated convolutional neural networks is utilised for segmented fingerprint classification, which could improve the accuracy of fingerprint classification compared with the existing classification methods. Finally, DCGIL utilises the sliding window to align and match the segmented fingerprint. Experiments show that the localisation accuracy reached 1.21 metres at 3.8 m shortest walking distance derived from segmentation length estimation algorithm, which improved 28% compared to existing algorithms.

Dynamic effect of smartness on environmental sustainability: Based on PVAR model for 72 Chinese cities

With the continuous implementation of the smart city concept, smart cities have become an important tool for the country's new urbanization. Therefore, it is of great concern whether smart cities can help promote environmental sustainability. Most of the existing studies mainly discuss whether the proposed smart policies are effective for environmental sustainability, but the specific impact paths are not clear and long-term dynamic implications for policy have not yet been explored in depth
 This study takes 72 cities in China as an example, and divides the impact path of smart cities into four aspects: internet technology, science and technology innovation(STI), smart environment and smart people's livelihood. Environmental sustainability is measured by energy consumption and air pollution, and the cities are divided into characteristic cities according to resource endowment and economic development, and the dynamic impact on environmental sustainability is explored based on the Panel Vector Auto-Regression (PVAR) model. The results indicate that STI has a negative effect on air pollution in all cities in the early stage and a positive effect in the later stage, with the overall effect being more significant in developed cities. Internet development has an impact on air pollution control in developed cities, but the effect is positive in the early stage and negative in the later stage. STI and Internet technology have very significant results on energy consumption reduction. But for developed cities, the effect of STI on energy consumption is positive. This paper provides policy suggestions for the sustainable development of environment in cities with different characteristics in China from the perspective of smart city development.

Health data security sharing method based on hybrid blockchain

With the rapid development of Internet of Things(IoT) technology, it is more and more common to use IoT devices to obtain health data. Health data sharing is a crucial component of health data utilization, yet it encounters serious privacy and security challenges. How to solve the problem of data security is the key factor to encourage users to participate, and existing data sharing methods generally have the problem of single point of failure. Based on this, this paper proposes a hybrid blockchain based health data sharing method HSHB, which divides sharing transactions into private chain data sharing and alliance chain data sharing according to different sharing entities. According to the identity and access purpose of different entities, HSHB has constructed the health data access control policy HDAC to avoid sharing interference among different entities. By building a b+ tree index of health data, HSHB provides users with an efficient and stable query scheme for historical health data. In addition, agent re-encryption and smart contract technology are used to share health data among institutions while ensuring the security of health data. Finally, the HSHB scheme is tested on XuperChain. The experimental results show that the health data sharing scheme HSHB proposed in this paper has advantages in computing overhead, throughput, and latency.

Internet development and renewable energy technological innovation: Does institutional quality matter?

Internet development and renewable energy technological innovation: Does institutional quality matter?

Analyzing and Applying Big Data Technologies Based on Industrial Internet Data

With the development of the industrial internet, data has gradually become the key engine driving the digital transformation of enterprises. The progress of the industrial internet is inseparable from the application of industrial data. To more effectively utilize data to empower businesses, many enterprises have put forward higher requirements for the real-time and reliability of industrial data collection. In the actual process of industrial data collection, issues such as large data volume, high real-time data processing requirements, and inconsistent data protocol standards are often encountered. In response to these problems, this paper, combined with practical engineering applications, proposes a big data construction technology solution based on industrial internet data processing. This solution aims to meet the high-concurrency data access needs of industrial equipment, using distributed messaging systems, high-throughput real-time stream processing frameworks, and distributed storage databases as the technical support for industrial data processing. This will help to complete the processing of massive industrial equipment data, thereby meeting the application requirements of various industrial big data processing business systems.

Reinforcement Learning-Based Particle Swarm Optimization for End-to-End Traffic Scheduling in TSN-5G Networks

With the rapid development of the Industrial Internet of Things (IIoT), massive IIoT devices connect to industrial networks via wired and wireless. Furthermore, industrial networks pose new requirements on communications, such as strict latency boundaries, ultra-reliable transmission, and so on. To this end, time-sensitive networking (TSN) embedded fifth-generation (5G) wireless communication technology (i.e., TSN-5G networks), is considered the most promising solution to address these challenges. TSN can provide deterministic end-to-end latency and reliability for real-time applications in wired networks. 5G supports ultra-reliable and low-latency communications (uRLLC), providing increased flexibility and inherent mobility support in the wireless network. Thus, the integration of TSN and 5G provides numerous benefits, including increased flexibility, lower commissioning costs, and seamless interoperability of various devices, regardless of whether they use a wired or wireless interface. Nonetheless, the potential barriers between the TSN and 5G systems, such as clock synchronization and end-to-end traffic scheduling, are inevitable. Time synchronization has been studied in many works, so this paper focuses on the end-to-end traffic scheduling problem in TSN-5G networks. We propose a novel integrated TSN and 5G industrial network architecture, where the 5G system acts as a logical TSN-capable bridge. Based on this network architecture, we design a Double Q-learning based hierarchical particle swarm optimization algorithm (DQHPSO) to search for the optimal scheduling solution. The DQHPSO algorithm adopts a level-based population structure and introduces Double Q-learning to adjust the number of levels in the population, which evades the local optimum to further improve the search efficiency. Extensive simulations demonstrate that the DQHPSO algorithm can increase the scheduling success ratio of time-triggered flows compared to other algorithms.

Research on the Sheep a Sheep Marketing Strategy

This paper aims to explore the marketing strategy for the "Sheep a sheep" mobile game. With the rapid development of the mobile internet, the gaming industry has become one of the most popular and thriving sectors. In this highly competitive market environment, effective marketing strategies are crucial for the success of a game. This study conducts market research and analyzes the "Sheep a sheep" game. It proposes marketing strategy recommendations to help the game stand out in the fiercely competitive market. This study identifies the unique selling points and challenges of the "Sheep a sheep" game by analyzing the target users and competitors and conducting a SWOT analysis. These findings suggest marketing strategies, including product positioning, pricing, distribution channels, promotion, and brand building. Implementation plans and evaluation metrics are also discussed to guide the execution and assessment of the marketing strategies. The findings of this study provide insights and recommendations for game developers, marketing professionals, and practitioners in the industry. Furthermore, it contributes to academic research on mobile game marketing strategies. By delving I nto the marketing strategy of the "Sheep a sheep" game, this research uncovers business opportunities and challenges, making a valuable contribution to the development of the gaming industry.

Strategic Analysis of the Merger Between Ctrip and Go.com: Motivation, Market and Outlook

With the increasing growth of the travel industry, many travel companies are partnering with other companies commercially because of their future growth. Ctrip and Where to Go considered that reason and the two companies merged in 2015. This article analyzes the merger of the two companies and through this analysis many methods of cooperation at the financial level can be derived, among others. in the process of the rapid development of Internet businesses driven by the Internet, the development of businesses from hostile competitive relationships to mergers and the gradual formation of new market patterns is also a growth process in the development of the Internet business market. By studying this article, it can be found that in many cases, companies that want to go to the next level in all aspects can choose to collaborate with various resources to amplify their respective strengths for mutual benefit. At the same time, only by maintaining the quality of service, the company will develop better.

Mask R-CNN aided fruit surface temperature monitoring algorithm with edge compute enabled internet of things system for automated apple heat stress management

Our prior study focused on development of internet of things (IoT) and edge-compute enabled crop physiology sensing system (CPSS) for apple sunburn monitoring. Edge compute algorithm on CPSS estimated sunburn susceptibility as fruit surface temperature (FST) through pixel-by-pixel multiplication of captured thermal infrared images with segmented fruits binary mask. The segmentation was performed using color-based K means clustering approach. This limited CPSS applicability to monitor sunburn of red colored cultivars only and when fruits develop color, typically late growing season. This is a key research gap as recent weather patterns have shown that sunburn can occur during early growing season when fruits are green to yellow. Therefore, aim of this study was to develop and field evaluate cultivar and color independent mask region-convolution neural network (R-CNN) aided fruit segmentation model and edge compute compatible FST estimation algorithm. Season long field data were collected in 2021 using eight CPSS nodes (three in cv. WA38 [Cosmic crisp] and five in cv. Honeycrisp). Collected data were used to develop and validate mask R-CNN based fruit segmentation model. Developed mask R-CNN based model was able to segment fruits of two apple cultivars and of varying colors with 91.4 % average precision. In orchard evaluations (2022 season), the resulting algorithm ported on CPSS was able to accurately segment (dice similarity coefficient = 0.89) and estimate apple FST with < 0.5 °C error compared to ground truth data. With compute time of about 37 s, data processing time was reduced by 22 % over previous algorithm. High ambient temperature (>35 °C) on a warmer day resulted in multiple throttling errors caused by excessive CPU temperature; however, the CPSS performance was uncompromised in FST estimation. Ambient air temperature did not affect RAM utilization and CPU clock frequency. Overall, developed FST algorithm can potentially be used as input to actuate water-based cooling system.