Information Service Platform Research Articles

Study on Internet Service Providers' Duty of Care for Copyright Infringement under Algorithmic Recommendation Technology

The liability of ISPs under algorithmic recommendation technology is examined from two aspects: whether there is fault (knowingly or recklessly) and whether necessary measures have been taken: firstly, whether the algorithmic recommendation technology has aggravated the duty of care of the ISP; secondly, whether filtering measures should be regarded as “necessary measures” that should be taken by the ISP. First, whether the algorithmic recommendation technology has aggravated the duty of care of the network service provider; second, whether the filtering measures are considered as “necessary measures” that should be taken by the network service provider. Nowadays, when algorithmic recommendation technology is widely used, it is even more urgent for network information service platforms to fulfill their due diligence obligations in accordance with the law, which not only concerns the balance of interests between right holders and platforms, but also involves the issue of how to fairly and reasonably distribute the benefits and risks brought about by the development of science and technology. Currently, under the algorithmic recommendation mode, the process of uploading content by users is separated from the dissemination process, and the role of the platform has changed from a passive “neutral” to an active “participant”, at which time, the platform still adopts an ex post facto “notification and deletion” approach. At this point, it is difficult for the platform to claim that it has fulfilled its responsibility by adopting the behavior of “notification and deletion” after the fact. The platform can use algorithmic technology to realize accurate pushing, but also has the ability to realize copyright filtering and monitoring at a more economical cost to reduce the risk of infringement. According to the principle of balance of interests, the current technical conditions and the development of reality, it should be changed from the passive “notice and deletion” rule to the stage of increasing the main responsibility of the platform, i.e., the platform establishes the rules of intellectual property rights protection, and obtains the authorization based on the principle of the utmost good faith in order to exercise the duty of care of the good administrators.

The Planning and Design of Digital Smart Campus

Under the background of “Digital Liaoning, Smart Province,” as the application of a new generation of network information technology in colleges and universities, the digital smart campus is an important part of digital Liaoning education informationization. Combined with the overall actual situation of the university campus, in line with the principle of “People-oriented, Service-oriented, Information Interoperability and Data Sharing,” through the idea of “management + service,” the traditional application system with management as the core to the service as the core is realized. On the basis of digital information and networks, a new digital smart campus is built based on several information technologies. From the aspects of architecture design, platform and application integration, systematic overall design and scientific and reasonable deployment, to create an efficient one-stop digital intelligent information service platform to fully optimize the use of digital information resources, to provide timely, accurate and efficient campus information services for teachers, students and staff, and to provide cross-departmental business management and convenient information services for the whole school users through the virtual digital means for display and publicity. The overall planning of the campus is carried out step by step, and the campus network, digitalization, virtualization and intelligence are gradually realized. Expand the time and space dimension of the real campus, improve the overall operation efficiency, and then improve the quality of talent training, management level and management efficiency.

Design and Implementation of Quality Inspection System for Image on National Platform for Geospatial Information Services in China

Abstract. This article is based on the data update characteristics of the online service for National Platform for Geospatial Information Services (TIANDITU) imagery data, and it designs and implements a full-process imagery data quality inspection system specifically for imagery tile data. The development and application of this system have made the quality inspection and update process of TIANDITU imagery data more scientific and efficient, significantly enhancing the efficiency of the quality inspection and update process for TIANDITU imagery data. The article provides a detailed introduction to the system’s architecture, design, implementation, characteristics and application. It also proposes optimizations to be made in algorithm optimization, user interface, and system stability. This article provides new ideas for quality inspection and publishing based on image tile data.

Spatiotemporal distribution of newly diagnosed echinococcosis patients in Qinghai Province from 2016 to 2022

To investigate the spatiotemporal distribution characteristics and potential influencing factors of newly diagnosed echinococcosis cases in Qinghai Province from 2016 to 2022, so as to provide insights into the formulation of the echinococcosis control strategy in Qinghai Province. The number of individuals screened for echinococcosis, number of newly diagnosed echinococcosis cases, number of registered dogs and number of stray dogs were captured from the annual reports of echinococcosis control program in Qinghai Province from 2016 to 2022, and the detection of newly diagnosed echinococcosis cases was calculated. The number of populations, precipitation, temperature, wind speed, sunshine hours, average altitude, number of year-end cattle stock, number of year-end sheep stock, gross domestic product (GDP) per capita, and number of village health centers in each county (district) of Qinghai Province were captured from the Qinghai Provincial Statistical Yearbook, and county-level electronic maps in Qinghai Province were downloaded from the National Platform for Common Geospatial Information Services. The software ArcGIS 10.8 was used to map the distribution of newly diagnosed echinococcosis cases in Qinghai Province, and the spatial autocorrelation analysis of newly diagnosed echinococcosis cases was performed. In addition, the spacetime scan analyses of number of individuals screened for echinococcosis, number of newly diagnosed echinococcosis cases and geographical coordinates in Qinghai Province were performed with the software SaTScan 10.1.2, and the spatial stratified heterogeneity of the detection of newly diagnosed echinococcosis cases was investigated with the software GeoDetector. A total of 6 569 426 residents were screened for echinococcosis in Qinghai Province from 2016 to 2022, and 5 924 newly diagnosed echinococcosis cases were found. The detection of newly diagnosed echinococcosis cases appeared a tendency towards a decline over years from 2016 to 2022 (χ2 = 11.107, P < 0.01), with the highest detection in Guoluo Tibetan Autonomous Prefecture in 2017 (82.12/105). There were spatial clusters in the detection of newly diagnosed echinococcosis cases in Qinghai Province from 2016 to 2018 (Moran's I = 0.34 to 0.65, all Z values > 1.96, all P values < 0.05), and the distribution of newly diagnosed echinococcosis cases appeared random distribution from 2019 to 2022 (Moran's I = -0.09 to 0.04, all Z values < 1.96, all P values > 0.05). Local spatial autocorrelation analysis showed high-high clusters and low-low clusters in the detection of new diagnosed echinococcosis cases in Qinghai Province from 2016 to 2022, and space-time scan analysis showed that the first most likely cluster areas of newly diagnosed echinococcosis cases in Qinghai Province from 2016 to 2022 were mainly distributed in Yushu Tibetan Autonomous Prefecture and Guoluo Tibetan Autonomous Prefecture. GeoDetector-based analysis of the driving factors for the spatial stratified heterogeneity of detection of newly diagnosed echinococcosis cases in Qinghai Province showed that average altitude, number of village health centers, number of cattle and sheep stock, GDP per capita, annual average sunshine hours, and annual average temperature had a strong explanatory power for the spatial distribution of newly diagnosed echinococcosis cases, with q values of 0.630, 0.610, 0.600, 0.590, 0.588, 0.537 and 0.526, respectively. The detection of newly diagnosed echinococcosis cases appeared a tendency towards a decline in Qinghai Province over years from 2016 to 2022, showing spatial clustering. Targeted control measures are required in cluster areas of newly diagnosed echinococcosis cases for further control of the disease.

A systematic solution of distributed and trusted chain-network integration

Blockchain, with its characteristics of decentralization, transparency, openness, and intangibility, has become the preferred choice for enhancing the credibility of the industrial cluster network platform. Industrial clusters are an important organizational form for developing small and medium-sized enterprises, and the information service platform plays a key role. This paper constructs a trusted paradigm model and a new trusted framework for the industrial cluster network platform and proposes an adaptive distributed network scheme. Specifically, it includes a decentralized and non-repudiable solution for the autonomous scenario of the industrial cluster Industrial Internet, promoting the transformation of the network into a self-adjusting and self-managing distributed network, enhancing the credibility of the platform, and reducing the negative impact of distrust and information asymmetry; it proposes three models (private chain, alliance chain, and public chain) for the integration of blockchain and the Industrial Internet, providing a secure and reliable support platform for the development of industrial clusters, solving the problem of information asymmetry, promoting trust and synergy, and maximizing the synergistic effect; from the perspective of security and reliability, it deeply analyzes the industrial cluster network platform, proposes a trusted framework, and realizes the data layer and application layer of the network with the help of blockchain technology. The experimental results show that these models meet the requirements of the industrial cluster in terms of data privacy, control, and credibility and have a positive significance for promoting the development and digital transformation of the industrial cluster.

Construction of Information Service Platform Based on Blockchain Technology

In order to improve the efficiency of archives management in modern archives information management, blockchain technology can be used to carry out the architecture of archives information service platform, and according to the work requirements of archives information management, relevant operation functions are designed, such as management module design, blockchain data protection module design, file security monitoring module design, etc. This paper analyzes and discusses the realistic path of the construction of information service platform based on blockchain technology.

Research on Intelligent Heating for Urban Systems Based on Digital Twin

Abstract This article focuses on the intelligent heating platform driven by digital twins, analyzing the overall framework of the system according to the sensor layer, application layer, and network layer, and building an information service platform for intelligent heating networks. The data of the entire heating system, including heat sources, primary networks, heating stations, secondary networks, and heat users, is remotely collected, analyzed, and diagnosed. Subsequently, statistical analysis is conducted on the energy consumption of each heat source and heating station, achieving data sharing and data mining among various business systems. This article conducts research on several key technologies for optimizing decision-making methods of heating system operation scheduling based on simulation models and develops software systems to support the intelligent upgrading of heating systems. The results show that intelligent heating system based on digital twins can better meet the balance between supply and demand in urban heating systems, and optimize the overall operating costs and environmental benefits of the system under multiple constraints.

Communication security of intelligent information service platform combining AES and ECC algorithms

ABSTRACT The rapid progress of information technology has made the status of information service platforms increasingly prominent in social operations. However, their communication security is also facing unprecedented challenges. In response to the issues of insufficient security and efficiency in traditional encryption algorithms, this study combines advanced encryption standard algorithms with elliptic curve cryptography algorithms to generate encryption key pairs through elliptic curve cryptography algorithms. It utilizes advanced encryption standard algorithms to generate symmetric keys, and then encrypts the keys of the advanced encryption standard using the public key of the elliptic curve cryptography algorithm. Based on this, it implements advanced encryption standard encryption on data and designs a hybrid encryption algorithm. The results showed that the throughput of this method was 4000bit/s, with a delay of 550 m, which is higher than other algorithms, proving its high efficiency in processing data. The average bit change of the ciphertext in the hybrid encryption algorithm was 55.8 bits, with a range of bit changes of [69.3, 82.7], which is significantly higher than other algorithms, proving its high security. The designed algorithm has significant benefits in communication security of information service platforms and plays an important role in promoting the development of future network security defense technology.

Bibliometric Analysis of Forensic Human Remains Identification Literature from 1991 to 2022.

To describe the current state of research and future research hotspots through a metrological analysis of the literature in the field of forensic anthropological remains identification research. The data retrieved and extracted from the Web of Science Core Collection (WoSCC), the core database of the Web of Science information service platform (hereinafter referred to as "WoS"), was used to analyze the trends and topic changes in research on forensic identification of human remains from 1991 to 2022. Network visualisation of publication trends, countries (regions), institutions, authors and topics related to the identification of remains in forensic anthropology was analysed using python 3.9.2 and Gephi 0.10. A total of 873 papers written in English in the field of forensic anthropological remains identification research were obtained. The journal with the largest number of publications was Forensic Science International (164 articles). The country (region) with the largest number of published papers was China (90 articles). Katholieke Univ Leuven (Netherlands, 21 articles) was the institution with the largest number of publications. Topic analysis revealed that the focus of forensic anthropological remains identification research was sex estimation and age estimation, and the most commonly studied remains were teeth. The volume of publications in the field of forensic anthropological remains identification research has a distinct phasing. However, the scope of both international and domestic collaborations remains limited. Traditionally, human remains identification has primarily relied on key areas such as the pelvis, skull, and teeth. Looking ahead, future research will likely focus on the more accurate and efficient identification of multiple skeletal remains through the use of machine learning and deep learning techniques.

The impact of institutional proximity on digital technology innovation linkages: empirical evidence on the Guangdong-Hong Kong-Macao greater bay area of China

ABSTRACT Promoting digital technology innovation connections is crucial to establishing an international science, technology, and innovation hub in the Guangdong-Hong Kong-Macao Greater Bay Area, and institutional disparities influence the clustering and flow of digital technology as an innovation factor. Promoting digital technology links and cooperation across cities is a practical strategy to improve the region's innovation efficiency and capacity. However, detailed research on the flow of innovation determinants such as digital technology and there is no evidence of the influence of institutional proximity on digital technology innovation connections. Based on the patent transfer data of the National Key Industry Patent Information Service Platform from 2010 to 2021, this paper constructs a new institutional proximity indicator applicable to the Guangdong-Hong Kong-Macao Greater Bay Area and other cross-system regions, applies a spatial econometric model to investigate direct and spatial spillover effects of institutional proximity on the digital technological innovation linkages. It is proved that institutional proximity has significant positive direct and spatial spillover effects on digital technological innovation linkages. The study has significant theoretical and practical implications for increasing the association and collaboration of digital technology and other innovation elements across institutional boundaries.

Association of Four VEGFA Gene Variants with Rheumatoid Arthritis Risk: A Meta-analysis and Trial Sequential Analysis.

The association between rheumatoid arthritis (RA) risk and specific variants of the Vascular Endothelial Growth Factor A (VEGFA) gene remains contentious. This study sought to elucidate the correlations between RA risk and several VEGFA gene variants, including VEGFA-634 (rs2010963), VEGFA-C936 (rs3025039), VEGFA-2578 (rs699947), VEGFA-1154 (rs1570360), through a comprehensive meta-analysis. We systematically reviewed literature from the Cochrane Library database, Embase, PubMed, Web of Science, China National Knowledge Infrastructure, and the Wanfang Data Information Service platform to gather relevant case-control studies. Using odds ratio (OR) and 95% confidence interval (95% CI), we analyzed the data to assess potential correlations. Sensitivity analysis and the Egger's test were employed to ensure the results stability and to evaluate potential publication bias. Additionally, trial sequential analysis (TSA) was conducted to validate the findings. Our meta-analysis incorporated ten studies involving 2817 patients and 2855 controls. Results indicated that the AA genotype of VEGFA-1154 (rs1570360) is associated with a reduced risk of RA in the overall population (AG + GG vs AA: P = 0.032 OR = 1.932 95% CI 1.059-3.523). However, no significant association is found for VEGFA-634 (rs2010963), VEGFA-C936 (rs3025039), and VEGFA-2578 (rs699947) variants with RA risk. Subgroup analysis revealed a significant association between the VEGF rs3025039(C936) variant and RA risk in the PCR-RFLP group under the TC vs. CC model. TSA confirmed the sufficiency of the sample size for robust conclusions. These findings suggest that the G allele of VEGFA-1154 (rs1570360) may increase RA risk, whereas the A allele appears to confer a protective effect. This study enhances our understanding of the genetic predispositions to RA and underscores the potential role of VEGFA gene variants in its pathogenesis.

Agricultural Disaster Prevention System: Insights from Taiwan’s Adaptation Strategies

In response to the adverse effects of climate change-induced frequent extreme disasters on agricultural production and supply stability, this study develops a comprehensive agricultural disaster prevention system based on current adaptation strategies for mitigating agricultural meteorological disasters. The primary goal is to enhance disaster preparedness and recovery through three core platforms: a fine-scale weather forecast service system, a crop disaster early warning system, and an agricultural information service platform for disasters. The results show that every major agricultural production township in Taiwan now has dedicated agricultural weather stations and access to refined weather forecasts. Additionally, a disaster prevention calendar for 76 important crops is established, integrating cultivation management practices and critical disaster thresholds for different growth periods. Utilizing this calendar, the crop disaster early warning system can provide timely disaster-related information and pre-disaster prevention assistance to farmers through various information dissemination tools. As a disaster approaches, the agricultural information service platform for disasters provides updates on current crop growth conditions. This service not only pinpoints areas at higher risk of disasters and vulnerable crop types but also offers mitigation suggestions to prevent potential damage. Administrative efficiency is then improved with a response mechanism incorporating drones and image analysis for early disaster detection and rapid response. In summary, the collaborative efforts outlined in this study demonstrate a proactive approach to agricultural disaster prevention. By leveraging technological advancements and interdisciplinary cooperation, the aim is to safeguard agricultural livelihoods and ensure food security in the face of climate-induced challenges.

Slope stability prediction based on GSOEM-SV: A mobile application practicably deploy in engineering verification

Slope stability evaluation is a complex and uncertain system problem, and carrying out slope stability prediction is the prerequisite and foundation for slope disaster prevention. In order to achieve fast and accurate prediction of slope stability, this paper considers height, total slope angle, unit weight, cohesion, internal friction angle, and pore water pressure ratio as input features and proposes an intelligent slope stability prediction method based on grid search optimization ensemble learning model by soft voting (GSOEM-SV). First, 390 sets of on-site data were collected to form a dataset, and analyses including correlation coefficients, density estimates, and box lines were carried out. Then, the grid search optimization algorithm is used to optimize the hyperparameters of five algorithms—Gradient Boosting Decision Trees, Light Gradient Boosting Machine, Categorical Boosting, Support Vector Machine, and Random Forest, and integrates them through soft voting. Furthermore, this paper optimizes the hyperparameters of the above five algorithms based on grid search, particle swarm and simulated annealing algorithms, builds 15 improved models and 2 ensemble models and conducts comparison. The results reveal that the GSOEM-SV has the highest slope stability prediction accuracy, up to 91 %, the area under the curve (AUC) is 0.950, and its F1 score 0.917, which are better than the 15 improved and 2 integrated models. In addition, a set of slope stability prediction app based on uni-app is developed in the paper. It provides a technical foundation and an open and shareable information service platform for slope hazard prediction in geotechnical engineering.

Discuss on the Construction of Digital Rural Revitalization Information Service Platform in the New Era

If we want to assume digital rural areas, the focus must be on industrial prosperity, adhere to quality first, green agriculture, and take the structural reform of the agricultural supply side as a guide to further promote the construction speed of modern agricultural industrial system, management system, and production system, thereby improving agricultural productivity, competitiveness, and innovation, and promoting the realization of an agricultural power. In the new era, the system engineering of digital rural projects is relatively complex. It is necessary to adopt advanced system engineering ideas and methods, arrange top-level design, institutional setting, innovative technology, talent cultivation, and optimize operation modes, in order to achieve an information service platform and achieve digital rural revitalization.

Retracted: AI-Based Secure Construction of University Information Services Platform

Retracted: AI-Based Secure Construction of University Information Services Platform

Research on the Path and Empowerment Countermeasures for Cultivating Innovative and Entrepreneurial Talents in Applied Colleges from the Perspective of Industry -University -Research Cooperation

Industry-university-research cooperation is an important mission of higher education. It can meet the demands of multiple subjects, such as universities, scientific research institutes, and enterprises, and help integrate educational resources; thus, it is an important way to train technological innovation talent in application-oriented universities. Given the background of industry-university research, this paper analyzes the problems faced by application-oriented universities in the training of innovative talent in application-oriented universities, including the lagging concept of collaborative education, the immature collaborative education model and mechanism, the mismatch between the major setting and industry of collaborative education, and cooperation in collaborative education. We elaborated the development of innovative talent in application-oriented universities from the perspective of industry-university research from four aspects: improving the enthusiasm of the subject of collaborative education, deepening the supply-side reform of talent training, cobuilding an innovation platform for the integration of industry-university research, and building an information service platform for collaborative education. We propose three empowering countermeasures, namely, the creation of a good institutional environment, the establishment of a leading group for collaborative education, and the establishment of a joint industry-university-research fund, to provide beneficial suggestions for the training of high-quality innovative talent in application-oriented universities in China.

An Information Service Platform for Decision Support in Academic Admissions Using Data Fabrics and Artificial Intelligence

This paper presents the architecture of an information service platform for decision support in academic admissions, utilizing data fabrics and artificial intelligence. The factors affecting students’ further education can be classified into four main types: (1) the course, (2) image, (3) personal reasoning of the student, and (4) public relations. The process of providing information for decision support in academic admissions can be divided into six stages: (1) collecting information, (2) matching study guidance, (3) recommending appropriate education, (4) confirming information, (5) assessing student admissions, and (6) providing feedback. Data fabric is an increasingly popular technology application for data management. The data fabric architecture consists of six layers: (1) an augmented data catalog, (2) a knowledge graph enriched with semantics, (3) metadata activation, (4) a recommendation engine for active metadata, (5) data preparation and integration, and (6) orchestration and data operations. A smart decision support system (DSS) technology is used to assist in decision-making. The results showed that this architecture has an excellent level of suitability (mean = 4.56, standard deviation = 0.35). It can be applied to a university to help it become a digital university and align with its mission.

The effectiveness of theory-based smoking cessation interventions in patients with chronic obstructive pulmonary disease: a meta-analysis

BackgroundSmoking cessation can effectively reduce the risk of death, alleviate respiratory symptoms, and decrease the frequency of acute exacerbations in patients with chronic obstructive pulmonary disease (COPD). Effective smoking cessation strategies are crucial for the prevention and treatment of COPD. Currently, clinical interventions based on theoretical frameworks are being increasingly used to help patients quit smoking and have shown promising results. However, theory-guided smoking cessation interventions have not been systematically evaluated or meta-analyzed for their effectiveness in COPD patients. To improve smoking cessation rates, this study sought to examine the effects of theory-based smoking cessation interventions on COPD patients.MethodsWe adhered to the PRISMA guidelines for our systematic review and meta-analysis. The Cochrane Library, Web of Science, PubMed, Embase, Wanfang, CNKI, VIP Information Services Platform, and China Biomedical Literature Service System were searched from the establishment of the database to April 20, 2023. The study quality was assessed using the Cochrane Collaboration's risk assessment tool for bias. The revman5.4 software was used for meta-analysis. The I2 test was used for the heterogeneity test, the random effect model and fixed effect model were used for meta-analysis, and sensitivity analysis was performed by excluding individual studies.ResultsA total of 11 RCTs involving 3,830 patients were included in the meta-analysis. Results showed that theory-based smoking cessation interventions improved smoking cessation rates, quality of life, and lung function in COPD patients compared to conventional nursing. However, these interventions did not significantly affect the level of nicotine dependence in patients.ConclusionTheory-based smoking cessation intervention as a non-pharmacologically assisted smoking cessation strategy has a positive impact on motivating COPD patients to quit smoking and improving their lung function and quality of life.Trial registrationPROSPERO registration Number: CRD42023434357.

The promotion path of high-quality development of rural tourism based on intelligent cloud platform system

Abstract With the continuous development of the economy and the level of science and technology, people are no longer satisfied with the old rural tourism model, and information technology is developing rapidly, which brings an opportunity for developing rural tourism innovation. As a product of the comprehensive development of the information age in recent years, “Internet+Rural Tourism” builds an intelligent cloud platform for rural information services relying on big data and other advantages and establishes a rural intelligent tourism service system to provide convenient, intelligent, and diversified services for tourists. This paper elaborates on the practical significance of “Internet + rural tourism” development opportunities”. It proposes to scientifically calculate the environmental capacity of rural eco-tourism areas, control the scale of visitors and reasonably invest in costs because of the problems of lagging infrastructure facilities and limited distribution of inputs and outputs in the process of its development. The results of this paper show that the satisfaction level of rural tourism tourists is the lowest, with the degree of “dissatisfaction” as high as 38.40%; in the rating of rural tourism indicators, the rating of rural ecological environment is only 52.41, the average rating of rural economic indicators is 60.12, and the average rating of comprehensive management indicators is 58.2. The results of this paper also illustrate that the current rural tourism development has three major problems: environment, economy, and management and that rural tourism should not blindly invest high costs if it wants to seek high-quality development but should seek long-term development of rural tourism based on its characteristics and rural ecological environment indicators.

RETRACTED ARTICLE: Development of personalized mobile information service platform of university library based on multi-core processor and cloud computing platform

RETRACTED ARTICLE: Development of personalized mobile information service platform of university library based on multi-core processor and cloud computing platform