Development Of The Internet Research Articles

Advanced MiniMax Optimality Strategy in Bandit Problems

Nowadays, with the development of the Internet, recommending personalized information for every user becomes economically valuable. How to properly recommend to users the content they prefer is important. Mostly, bandit strategies are useful for this problem. As one of the most time-saving algorithms, Minimax Optimal Strategy (MOSS) performs well in most data sets. However, the traditional MOSS algorithm applies a conservative strategy in order to minimize the cumulative regrets in the worst situations. This strategy will over-explore the bandit models and spend too much time exploring every arm at the initial stage. This means the MOSS strategy cannot fully take advantage of the known information and then the accuracy and efficiency will be lower. In real life, people have a lot of Internet information to look through and they will not stay on one website or one advertisement for a long time. So, designing an efficient algorithm that performs well in all situations and can make good use of the known knowledge to do quick exploitation becomes so important. Therefore, this research aims to develop an advanced MOSS algorithm that can properly explore each of the bandit arms and improve the performance of the exploitation phase. By achieving this goal, this research adds an enhancement factor on the confidence bound part to speed up the exploration process. The research bases on the MovieLens data set and the data set is divided into 18 categories (arms) according to its genre attribute. Then apply this new advanced MOSS strategy to the designed data set and compare its performance with normal MOSS and UCB algorithms. Results display that the advanced MOSS strategys selection provides higher total rewards and lower average cumulative regrets than others with the advantage of time-saving. This shows the improvement of the advanced MOSS strategy in balancing the exploitation and exploration phases.

Revolutionary discourses from the past: a digital hermeneutical analysis of widely read academic publications on the social impact and significance of the internet

ABSTRACT From the start, the academic community was deeply involved in both the technological and conceptual development of the internet. Works by Rheingold, Castells, and others put forward influential, intellectual imaginaries. Over thirty years later, these sources offer valuable insights, reflecting the novelty and excitement of the time. Often infused with rhetoric of radical transformation, these authors either consciously or unconsciously foregrounded a revolutionary period marked by digital utopianism, while also presenting critical views. This paper aims to identify and historicize common themes and concepts in influential academic publications on the internet's significance and social impact. By adopting a longitudinal and comparative approach, we aim to provide a historically informed understanding of Internet Studies. Our paper contributes to a tradition of media historical scholarship, examining how new technologies were socially constructed, how dominant discourses shaped popular imaginaries, and their role in the evolution of Internet Studies.

High Performance and Colorful Polymer Thermoelectrics with Imprinted Porous Film.

The rapid development of the Internet of Things and wearable electronics has generated growing interest in creating high-performance and visually striking polymer thermoelectric (TE) devices. However, existing polymer TE materials have yet to fully meet these diverse demands. In this study, imprinted porous polymer films are introduced that exhibit both high TE performance and a spectrum of structural colors. The porous architecture not only preserves excellent charge transport properties but also significantly enhances phonon-like scattering, resulting in a more than 50% reduction in thermal conductivity for the PDPPSe-12 film. This leads to a 170% increase in the figure of merit (ZT), achieving a peak value of 0.52 at 363K. Furthermore, the highly ordered porous structure imparts the PDPPSe-12 films with both a wide range of structural colors and remarkable stretchability, making them ideal for wearable TE generators. This approach is widely applicable to various polymeric systems, offering a novel strategy for advancing state-of-the-art plastic TE materials through microstructural engineering.

Douyin—— the leading application in short video in the next decade

In recent years, along with the comprehensive innovation of communication technology, new media has also achieved rapid development and gradually penetrated into various fields. According to the 48th Statistical Report on the Development of the Internet in China released by the China Internet Network Information Center, as of June 2021, the number of Internet users in China has reached 1.011 billion, of which 888 million are short video users, accounting for 87.8% of the total Internet users. According to the survey results of the products most commonly used by short video users from 2020 to 2021, Douyin ranked first with 45.2%. As one of the emerging social media, Douyin short video APP is different from the previous simple graphic social, but the combination of music, special effects and video, so as to closely connect users of different ages, industries and identities. Based on this, this paper will discuss the possibility of Douyin platform to achieve fine operation and further expand market share by optimizing user generated content (UGC) model and analyzing the personality and commonality of audience psychology.

The Role of AI Technology Plays in Chinese Students’ Spoken English Learning

With the popularization and development of the Internet, artificial intelligence as a common tool has been widely used in Chinese students’ spoken English learning. Language learning assisted by AI technology is developed from information technology-assisted language learning. Although it has many advantages, it has not been fully developed and applied, and there is a research gap in the field of technology and ethics. This paper is a systematic review that describes in detail how information technology-assisted language learning has developed step by step from computers to artificial intelligence Apps and even robots, and summarizes the advantages of AI technology in spoken language learning, such as vividness, accuracy, and convenience, as well as the limitations of difficult application, high cost, low error-tolerant rate and neglect of cultural differences. Through literature investigation and comparative analysis, this paper summarizes the relevant suggestions and improvement plans for AI technology-assisted spoken English learning.

The role of big data technology in project schedule management: the case of Amazon

With the rapid development of the Internet, big data technology has received widespread attention in the field of management. Traditional project schedule management methods cannot adapt to the complex and changing environment, and some researchers believe that big data technology has become a key tool to improve and optimize project management. However, there is a lack of mature theoretical systems and practical experience to guide the application of big data technology. Based on the case of Amazon, this paper analyses how the company uses big data technology to optimize project schedule management. It is found that the application of big data technology in project management brings significant benefits. It is able to provide empirical and innovative support for project schedule management. This paper discusses the application of big data technology in project schedule management, highlighting its capability to enable timely adjustments. Real-time monitoring and forecasting facilitate proactive management of project directions and potential risks. Moreover, it leverages real-time data to optimize resource allocation and enhance resource utilization. Furthermore, the paper addresses the challenges and proposes countermeasures associated with big data technology in this context. To tackle the issue of uneven data quality, a robust data collection mechanism should be established.

Isokinetic Force Modeling in Sports Based on Embedded System of Motion Recognition Model

With the gradual deepening of sports research, sports training methods integrating more scientific and technological means can greatly improve athletes’ professional ability. Combined with the isokinetic strength training method, it can effectively alleviate muscle recovery and body flexibility, which requires an analysis of the level of sports body promotion, and a more efficient training program for various sports parameters. In this study, taking strength enhancement as an example, the convolutional neural network is innovatively integrated into isokinetic strength training. Using the motion data obtained by wearable sensors in the training, we trained the neural network model by real-time analysis of data samples through an embedded system. Further, we optimized the network parameters to realize the extraction and recognition of EMG depth features. Compared with the traditional isokinetic strength classification model, this model lays a foundation for further constructing personalized strength training guidance methods. After the simulation test, the difference of the model’s accuracy requirement before and after the pre-training is 4.6%, and the difference of the test set before and after the pre-intensive training is [Formula: see text]1%. It is 16.2% higher than the TCAM algorithm, and the gap with STA-LSTM remains between [Formula: see text]. It is verified that the attention concentration control scheme can not only reduce the error rate in visual recognition tasks, but also improve the complexity of the neural network model. The optimized lightweight data structure is especially suitable for embedded systems with limited computing power. All kinds of test projects verify its rationality and make full use of the control ability of the embedded system and the characteristics of parallel computing and programmability, which has great practical application value for the development of the Internet of Things system network. The research results have made a thorough study of the physiological guidance of existing strength training, the identification and evaluation methods of exercise-induced muscle fatigue, and the current situation of the existing isokinetic equipment.

A Study on the Influencing Factors of New Media Short Video Platforms on Adolescent Mental Health

With the rapid development of the Internet and mobile technology, new media short video platforms have rapidly become popular around the world and have become an important part of adolescents ‘s daily lives. Short video platforms are popular among adolescent for their rich content and strong interactivity. However, the popularity of short video platforms also brings potential impacts on the mental health of adolescents. This study aims to discuss the specific influencing factors of new media short video platforms on adolescents’ mental health. It uses a combination of questionnaire surveys and literature searches to study factors such as the frequency of adolescents’ short video use, content preferences, and interactive behaviors The results of this study show that new media short video platforms have a multi-faceted negative impact on the mental health of adolescents, mainly manifested in increased psychological stress, decreased sleep quality, and decreased academic performance. The research further concluded that when adolescents overuse short video platforms, their academic and social pressures increase significantly. In response to this type of problem, it is recommended that parents and educators provide more guidance, use short video platforms reasonably, and create a healthy online environment.

Development and Modeling of the Internet of Things Network for Patients IT Diagnostics

The work of a network that implements algorithms for IT diagnostics of neurological diseases based on the Internet of Things technology has been developed and modeled. The network includes a smartphone, a platform, a neural network, and applications. First, the voices of sick patients are entered from the smartphone to train the neural network, and then the examined patients for IT diagnostics. Data is transferred between the smartphone and the platform (ThingSpeak) via the MQTT protocol. The smartphone’s mobile application extracts the voice functions of the examined patients and records them on the Internet of Things network platform. Recognition is performed using the trained neural network. The structure and algorithm of the ThingSpeak platform are presented. IT diagnostics data are displayed in the application on the smartphone. The patient data used in the study are taken from the ADReSS 2020 Challenge program, which contains speech data of patients with Alzheimer’s disease and healthy people.

التعريف بجريمة الدخول غير المشروع إلى النظام المعلوماتي وجهود المملكة في مكافحتها

This research aims to study the definition of the crime of unauthorized access to information systems and to highlight the efforts of the Kingdom of Saudi Arabia in combating it. Since this crime is closely related to cybercrimes, and given the novelty and significant evolution of cybercrimes in the modern era with the development and spread of the Internet, the threat of cybercrimes in various forms and types has increased. This has led to a concerted international effort to combat these crimes and address their infiltration and spread in all countries of the world. The Kingdom of Saudi Arabia has made intensive efforts to combat cybercrimes and has worked on developing legislative systems to keep pace with methods of combating all cybercrimes. The study adopted an analytical approach to the texts of the Saudi Anti-Cyber Crime Law, as well as a comparative approach to similar laws and legislative systems, aiming to reach conclusions and recommendations related to the study. The research addressed the extent of the development of legislative systems and the efforts made to combat cybercrimes at the international level in general and in the Kingdom of Saudi Arabia in particular. The research then discussed the definition of the crime of unauthorized access to information systems by dividing the study into two main sections. The first section focused on the development of legislative systems in combating cybercrimes, which the study addressed through two subsections: the first subsection provided an overview of international efforts to combat cybercrimes, and the second subsection discussed the development of the efforts of the Kingdom of Saudi Arabia in combating cybercrimes. The second section dealt with the definition of the crime of unauthorized access to information systems, divided into two subsections: the first subsection covered the concept and philosophy of the crime of unauthorized access to information systems, and the second subsection distinguished between the crime of unauthorized access and related offenses.

Research on Blended Learning Mode of College English based on the Chaoxing Learning Platform

College English is one of the public courses in many majors in universities. Traditional teaching often adopts the traditional large class approach, with face-to-face teaching between teachers and students. In the context of the development of the Internet, online courses have begun to rise. In addition to the influence of many objective factors, online teaching mode has been favored by many schools. At present, applying the information technology teaching mode to subject teaching has become a trend. This article focuses on college English courses and researches the blended learning mode under the application of the Chaoxing Learning Platform to improve teaching efficiency.

Research on the Development Status and Countermeasures of Rural E-commerce in China

Abstract: With the rapid development of the internet, the rural e-commerce in China has also evolved prominently. And it becomes increasingly widespread as well. Concurrently, various issues have surfaced in rural areas, which hinder further development of rural e-commerce in China. Recognizing this complexity, the dissertation delves into the current landscape of rural e-commerce, exploring both its inherent strengths and weaknesses, as well as the opportunities and threats it currently faces. The dissertation aims to clarify the fundamental development ideas and direction for the rural e-commerce in China, not just in theory but also in practical application. To illustrate this, it utilizes the example of Pinduoduo, a prominent e-commerce platform, to analyze how such platforms can effectively contribute to the advancement of rural e-commerce. Finally, the dissertation offers a set of forward-looking suggestions for the future of rural e-commerce, such as intensifying policy promotion, cultivating professional talents, and strengthening network infrastructure.

Cultural Analysis of Female Cross-Gender Expression in Social Networks: A Case Study of Image Presentation in Douyin Short Videosv

With the continuous development of the internet and the growing awareness of women's social consciousness, the forms of self-expression by women on digital platforms have become increasingly diverse. Among these, female cross-gender performance has emerged as a key strategy of self-presentation in social networks. This paper analyzes two distinct expression strategies on the Douyin short video platform to explore and critically reflect on current female cross-gender expressions. The explicit expression strategy employs makeup, cross-dressing, and role-playing to simulate male personas, challenging traditional gender stereotypes. The implicit expression strategy, on the other hand, mocks male “ bad habits ” through the imitation of male behaviors and the use of symbolic metaphors, carrying a satirical undertone. However, these strategies have their limitations: male images are often idealized and trivialized, reinforcing gender norms; and constrained by patriarchal frameworks, they fail to genuinely subvert gender roles and the gender binary. As a result, while female cross-gender expression challenges gender stereotypes, it also faces risks of being disciplined and misinterpreted.

A node deployment and resource optimization method for CPDS based on cloud‐fog‐edge collaboration

AbstractWith the development of the Internet of Things (IoT) in power distribution and the advancement of energy information integration technologies, the explosive growth in network data volume caused by massive terminal devices connecting to the power distribution network has become a significant challenge. Multi‐terminal collaborative computing is a key approach to addressing issues such as high latency and high energy consumption. In this article, fog computing is introduced into the computing network of the power distribution system, and a cloud‐fog‐edge collaborative computing architecture for intelligent power distribution networks is proposed. Within this framework, an improved weighted K‐means method based on information entropy theory is presented for node partitioning. Subsequently, an improved multi‐objective particle swarm optimization algorithm (MWM‐MOPSO) is employed to solve the task resource allocation problem. Finally, the effectiveness of the proposed architecture and allocation strategy is validated through simulations on the OPNET and PureEdgeSim platforms. The results demonstrate that, compared to traditional cloud‐edge service architectures, the proposed architecture and task offloading scheme achieve better performance in terms of processing latency and energy consumption.

Utilizing Baidu Index Data to Investigate the Spatiotemporal Characteristics of Public Concern towards Lifelong Education

Background and purpose: With the advancement of Industry 4.0 and the vigorous development of the Internet, search engines have become one of the important platforms for the public to obtain information. As the world's largest Chinese search engine, Baidu is widely popular with the Chinese public. Similar to Google Trends, the Baidu Index is one of the most important databases on the Internet and even in the entire data age. This study adopted the Baidu Index to investigate the public's attention to "Lifelong Education" and analyze its changing trend and geographical distribution, to grasp the public's attention to it in a more comprehensive way. Materials and methods: The Baidu Index was used to obtain the attention of the keyword “Lifelong Education" from July to November 2023. The characteristics of attention are analyzed from three aspects: trend research, demand graph, and user portrait. Finally, it focuses on the comparison between the keyword "Lifelong Education" and the related word "Lifelong Education Platform". Results: The term "Lifelong Education" showed two fluctuations during the period, both of which showed an initial rise and then a decline. For the demand graph, the public pays the most attention to "Lifelong Education Platform", "Lifelong Learning" and "Compulsory Education". The group that pays more attention to "Lifelong Education" is mainly distributed in East China, mostly female, 20~29 years old. Conclusion: Similar to Google Trends, the Baidu Index is a useful tool to study the trend of keyword searches, insight into the change in netizens' demand and monitoring the trend of media public opinion. The results show that the main reasons for the two obvious changes in search volume are that the National Open University of China opens freely lifelong education platform and provides free and comprehensive learning resources, and "Lifelong Education" appears as a translation in the National College English Test Band 4 (CET-4) in June 2023.

A weighted hybrid indoor positioning method based on path loss exponent estimation

With the rapid development of the Internet of Things (IoT), location-based services (LBS) have gained significant attention due to their widespread applications in daily life. This paper addresses the indoor target positioning problem in wireless sensor networks (WSNs). A weighted constrained linear least squares algorithm based on path loss exponent estimation (PLE-WCLLS) with received signal strength (RSS) and angle of arrival (AoA) hybrid measurements is proposed. To address the challenges of unknown transmission power and path loss exponent (PLE), the proposed method employs a linear least squares (LLS) estimation approach based on the ranging maximum likelihood (ML) estimation model to estimate both parameters. Subsequently, a confidence weight adjustment strategy is designed to reduce positioning errors. To handle the highly non-convex and nonlinear nature of the RSS/AoA hybrid optimization model, a linearization method based on Taylor series expansion is presented. Accurate target position estimation is achieved by solving a constrained quadratic programming problem. The effectiveness of the proposed algorithm is validated through numerical simulations and experimental evaluation in a real indoor environment. Compared to traditional positioning methods, the PLE-WCLLS algorithm improves positioning accuracy by 13.2%, and it performs exceptionally well even in scenarios with fewer sensor nodes. This gives it broad application prospects in areas such as IoT device management, personnel tracking in smart buildings, and asset localization in industrial automation.

Exploring the Potential of Microservices in Internet of Things: A Systematic Review of Security and Prospects.

With the rapid growth of Internet of Things (IoT) systems, ensuring robust security measures has become paramount. Microservices Architecture (MSA) has emerged as a promising approach for enhancing IoT systems security, yet its adoption in this context lacks comprehensive analysis. This systematic review addresses this research gap by examining the incorporation of MSA in IoT systems from 2010 to 2024. From an initial pool of 4388 studies, selected articles underwent thorough quality assessment with weighted critical appraisal questions and a defined inclusion threshold. This study represents the first comprehensive systematic review to investigate the potential of microservices in IoT, with a particular focus on security aspects. The review explores the merits of MSA, highlighting twelve benefits, eight key challenges, and eight security risks. Additionally, the eight best practices for implementing MSA in IoT systems are extracted. The findings underscore MSA's utility in fortifying IoT security while also acknowledging complexities and potential vulnerabilities. Moreover, the study calls attention to the importance of incorporating complementary technologies including blockchain and machine learning to address identified gaps effectively. Finally, we propose a taxonomic classification for Microservice-based IoT security patterns, facilitating the categorization and organization of security measures in this context. Such a review can help researchers and practitioners identify existing gaps, highlight potential research directions, and provide guidelines for designing secure and efficient microservice-based IoT systems.

Ferroelectric Nanomaterials for Energy Harvesting and Self‐Powered Sensing Applications

AbstractThe rapid development of the Internet of Things has introduced new challenges for miniaturized, highly integrated energy harvesters and sensors, promoting the exploration of various novel nanomaterials. Ferroelectric nanomaterials, characterized by large remanent polarization, exceptional dielectric properties, outstanding chemical stability, and diverse electricity generation capabilities, are emerging as promising candidates in a variety of fields. Possessing various mechanisms for electricity generation, including piezoelectric, pyroelectric, photovoltaic, and triboelectric effects, ferroelectric nanomaterials demonstrate their capability for harvesting and sensing multiple energies simultaneously, including light, thermal, and mechanical energies. This capability contributes to the miniaturization and high integration of electronic devices. This article reviews recent achievements in ferroelectric nanomaterials and their applications in energy harvesting and self‐powered sensing. Different categories of ferroelectric nanomaterials, their ferroelectric properties, and fabrication methods are introduced. The working mechanisms and performance of ferroelectric energy harvesters and self‐powered sensors are described. Additionally, future prospects are discussed.

Analysis of Green Supply Chain Construction and Driving Factors in the Context of New Retail: Case Study of JD.com

The retail industry occupies an important position in the national economy and is a fundamental industry. With the development of the Internet, retail is constantly innovating, and online retail is developing rapidly. Retail enterprises under the new retail model represented by JD.com have embarked on a new journey in the retail industry. With the further development and acceleration of industrialisation, reducing resource waste and environmental pollution has become a problem that retail enterprises must face. This paper introduces the case of JD.com in building a green supply chain in the context of new retail and analyses. It summarises the driving factors of JDs establishment of a green supply chain by combining the interdisciplinary perspectives of new retail and green supply chains. At the same time, specific case evidence is provided from the perspective of each link in the supply chain. It aims to provide multi-dimensional guidance for the green supply chain transformation of new retail enterprises, which can help improve their market competitiveness, provide better consumer experience, enhance consumer trust, and help avoid potential legal risks.

The Walt Disney Companys Challenge

Walt Disney is the most famous and largest entertainment company in the world. However, it also met plenty of problems from the time it started until now. These problems can occur on the financial side, it can happen in the copyright of the films and characters, and it also can occur in the making of the movie and the relationship with their employees because no one company can be operated mainly without any challenges. Walt Disney Company met different problems during different periods. For example, in early 1940, the company had a severe financial problem. In the early 20th century, the company met the challenge of its film industry. In the 21st century, the company had the risk of being outdated with the rapid development of the internet and the entertainment platform. In 2019, the company was influenced by the covid-19, during the pandemic period, the global economy into recession, the tourism industry was declined significantly. This article analyzes Walt Disney's solution to face these challenges.