Management System Platform Research Articles

Health and nutrition emergency response among internally displaced persons at Ranch collective site, Chagni, Ethiopia: The role of emergency operation center, lessons from the field, and way forwards.

BackgroundIn October 2020, about 79,041 ethnically Amhara/Agew people had been internally displaced (IDPs) from Metekel zone of Benishangul-Gumuz region and lived in Ranch collective site, Chagni town, Ethiopia. Onsite PHEOC met the health and nutrition needs of the IDPs as per international humanitarian response standards.MethodsOn January 11/2021, the Amhara Public Health Institute (APHI) established an onsite Public Health Emergency Operation Center (PHEOC) at Ranch collective site. Health workers and vehicles were deployed. A temporary clinic having nine outlets was built. Drugs and medical supplies were mobilized from different sources. The overall response period lasted about 8 months, from December 2020 up to June 2021.ResultsA total of 33,410 IDPs had received free essential health services. Mental health and psychosocial support services had been given for 1,803 cases. Specialized medical services such as trachomatous trichiasis (30), cataract surgery (8) and sputum samples for mycobacterium tuberculosis (120) have been done. Moreover, 454 women received antenatal care services and 137 women gave birth at health facilities. About 837 children have got measles supplementary dose and 1,280 adults took a COVID-19 vaccination. A total of 1,448 children under five, 454 pregnant and 402 lactating women had been screened on monthly basis. Of which, severe and moderate malnutrition rate was 46 (3.2%) and 75 (5.2%), respectively. A total of 194 trench latrine seats, 74 shower rooms and 50 hand washing facilities had been constructed. There were no human feces present nor solid wastes accumulated around the shelters or settlements. Both active and passive surveillance activities were carried out throughout the camp life. We also conducted regularly Risk Communication and Community Engagement activities on priority health issues.ConclusionWe adequately met the health and nutrition needs of the IDPs as stated in the Sphere humanitarian handbook. We sought to have a strong Incident Management System and coordination platforms like PHEOC, a resilient health system, a training curriculum called Leading in Emergencies, and a multipurpose collective center with infrastructures, humanitarian response guidelines, training materials, and risk/vulnerability-based preparedness plan.

Four-Channel Vibrating Testbed Design for Full Vehicle Durability Simulation

The four-channel vibrating testbed for full vehicle durability simulation is indispensable for testing vehicle performance. This paper combines theoretical analysis with experimental verification, and the four-channel vibrating simulation testbed is designed. The hardware system consists of three parts: hydraulic mechanical components, sensors, and closed-loop control system, and the software system consists of platform configuration system, platform management system, and basic test system. Based on the design of the hardware system and software system, the emphasis is put on signal processing. Based on the least squares principle, the undetermined coefficients of trend items are determined, the trend items are transformed into the arithmetic mean of signal data, and the models that eliminate constant trend items are established to eliminate the trend items. In order to reflect the fatigue process of parts more truly, the anomaly points were identified and eliminated based on the two-parameter rain-flow counting method. By representing the transfer function in the frequency domain, the measured signal is changed quickly by Fourier, and the uniqueness of the transfer function is ensured by establishing an invariant system. Finally, test verification was performed on the designed testbed with the white powder noise taken as the driving signal. The test results agree well with field testing results. The design of the testbed can meet the requirements of engineering application, and its design method and signal processing method are reasonable, which has certain theoretical research significance and engineering application value.

Research and Application of Business Law Information Management System Based on Big Data

China’s manufacturing industry has set off a wave of digital transformation innovation, and the commercial law information management system, as one of the important tools to enhance the intelligent management ability of enterprises, will also face a new round of reform and upgrade. Building an “intelligent commercial law information management system platform” is the primary transformation path for traditional manufacturing enterprises to realize intelligent upgrading of commercial law information management system. The “intelligent commercial law information management system platform” is a management information sharing service platform that enables enterprises to achieve the goal of collaborative management by integrating their own business models and product technology needs with the help of emerging digital technologies, which can help enterprises realize the organic integration of business processes, risk management, value creation, and other management needs and change the original. The platform can help enterprises realize the organic integration of business processes, risk management, value creation, and other management needs and change the focus of the traditional financial shared service center, so that the enterprise business law information management system can be shifted to the enterprise strategy-oriented, focusing on risk control, decision support, and other high-level management. Therefore, it is particularly important to evaluate and optimize the “intelligent business law information management system platform” of manufacturing enterprises in the process of digital transformation. In this context, this paper conducts research and application of commercial law information management system based on big data, conducts an in-depth study on the current status of commercial law information management system in China, and provides an outlook on commercial law information management in China by establishing a relevant model system.

Resource Cache Sharing System of Education Information Center Network Based on Internet of Things

The development of the internet of things has spawned new information concepts such as educational information sharing. Due to the openness of the internet of things, all kinds of mobile terminal devices can rely on the internet of things for data communication, information interaction, and resource sharing. Although the development of the internet of things has brought convenience to people’s lives, the internet of things is facing severe challenges in the fields of internal data sharing and cache sharing of educational information. The existing resource sharing systems do not fully consider the problems of privacy, shared data security, and data access control. This paper mainly studies the network integrated resource cache sharing system of the education information center based on internet of things. The data management system of the network education information center is developed on the basis of the school teaching management system and lifelong education public service platform, combined with the actual situation of student information. This paper combines the enrollment and information workflow of the student information management website, analyzes the problems existing in the current workflow, and then uses computer technology to standardize and transform the workflow, realize the information of the built-in resources in the data management, and solve the problems of data cache sharing and data statistics in the management of the education information center. The simulation results show that with the increase in the number of concurrent threads, the average response time of the edge cloud system deployed with two servers is smaller than that of the edge cloud system deployed with a single server, and the cloud system has good scalability.

Design of Enterprise Financial Management Cloud Platform Based on Neural Network Algorithm

As the business environment is constantly changing with the ever-changing economic and competitive growth trends, enterprises are more sensitive to market demand. Information management is the first thing that enterprises need to do well in order to effectively and timely communicate with the market, and then determine success or failure. The development and use of enterprise financing system software conform to this trend, which is conducive to implementing information management, and improving management quality and management level. Based on this point, this study designs a set of financial management cloud platform system according to the financial situation of an enterprise in a certain place. According to its business situation and business financial management characteristics, by integrating the neural network principle and Bayesian regularization algorithm, this study puts forward the construction of the Bayesian regularization algorithm based on the neural network model, then analyzes the BP neural network algorithm, evaluates and analyzes the asset management in the process of financial management, and puts forward cloud platform design, system analysis, system framework, etc. The organizational structure and system functions of the platform are introduced in detail for enterprise financial management. Finally, the function and performance of the system are tested in a reasonable testing environment, and the results are empirically analyzed. The test shows that the system is effective in realizing the financial management system, which proves that the financial cloud platform management system developed in this study is suitable for enterprises.

Improving Random Forest Algorithm for University Academic Affairs Management System Platform Construction

Using the data of students’ learning process recorded in the network teaching platform to predict students’ learning performance, assist teachers to analyze learning situation, formulate teaching strategies, and warn about students’ learning state is a hot spot in the field of mixed curriculum research in recent years. In view of the complexity, heterogeneity, and security of college educational administration data and the difficulty of predicting and analyzing college students’ achievements, this paper designs a college educational administration management system platform based on improved random forest algorithm. Combining the advantages of three data-driven prediction algorithms, namely, random forest, extreme gradient boosting (XGBoost), and gradient boosting decision tree (GBDT), a model based on improved random forest algorithm is proposed. It is proved that this method is a noninferior prediction method. Secondly, the model is applied to practical problems to solve the problem of predicting college students’ grades. An experiment is carried out on the real data set provided by a municipal education bureau. The results show that the proposed model not only achieves good prediction accuracy, but also solves the stability problem of the model after adding new data, which will contribute to the iterative optimization of the model, improve the universality of the model, and help continuously track the learning behavior characteristics of college students in different semesters.

Construction and Application of the Big Data Management System for Cultural and Creative Industries under the Background of Rural Revitalization

Rural cultural and creative industries continue to flourish. Because big data technology is fast and convenient, promoting the development of rural cultural and creative industries through the big data management system has attracted more and more attention. This paper constructs a big data management system platform and applies it to rural cultural and creative industries between different cities. Then, the paper systematically analyzes the development of rural creative industries and points out the corresponding measures to develop the rural creative industries. In general, this paper provides some research methods and experimental support for the cultural and creative industries.

Design of Intelligent Management Platform for Industry–Education Cooperation of Vocational Education by Data Mining

Data are playing an increasingly important role in the development of industry–education cooperation strategies in vocational education and training. The objective of this study was to promote the comprehensive progress of an industry–education cooperation system and improve the effect of the application of big data technology in this system. First, we designed of a big data technology application in an intelligent management platform system for industry–education cooperation. Second, we analyzed the synthetical design of the system. Finally, we optimized and designed a support vector machine (SVM) data mining (DM) algorithm model based on big data, and evaluated the model. The results revealed that the designed algorithm model provides outstanding advantages compared with similar algorithm models. In general, the highest average computation time of the designed SVM algorithm model is about 95 ms. The overall average calculation time linearly decreases around 200 iterations and tends to be stable, and the lowest overall average computation time is about 20 ms. In the DM process, the highest accuracy rate of the model is about 97%, and the lowest is about 92%. The DM accuracy rate is always stable as the number of iterations of the model continues to increase. The designed model slowly increases the occupancy rate of the system in the process of increasing computing time. At about 60 min, the system occupancy rate of the model tends to be stable, and the highest is maintained at about 23%. This study not only provides technical support for the optimization of DM algorithms with big data technology, but also contributes to the integrated development of industry–education cooperation systems.

A platform management system that links commuters with shared or service taxis

A platform management system that links commuters with shared or service taxis

Interactive Design and Management Method of Art Teaching System in Colleges and Universities under the Background of Big Data

Now, there are some problems in the art teaching system of colleges and universities, such as low management efficiency. However, with the development of big data technology, big data has been applied to the design and management of art teaching systems in colleges. Firstly, a model of art teaching system through the relevant big data was established; then the process of establishing the model was also discussed. Subsequently, based on the interactive design method and Hyperlink-Induced Topic Search (HITS) algorithm as the web design mode, this paper establishes the teaching system management platform and applies it to the art teaching in colleges and universities. The teaching evaluations of students and teachers of different grades were analyzed, and the application prospect of the teaching system design and management platform was obtained. In general, this paper indicates a theoretical reference for optimizing the effect of art teaching and realizing the design and management method of art teaching system under the background of big data.

Improving Online Learning through the Use of Learning Management System Platform: A Technology Acceptance Model-Technology Readiness Index Combination Model Approach

The COVID-19 pandemic push the learning revolution. The previous onsite learning is suddenly change to online learning. Current technological developments support the online learning application through the use of Learning Management System Platform. However, some problems are found during the application of online learning. Thus, this research aims to improve online learning through the use of Learning Management System Platform. The Technology Acceptance Model and the Technology Readiness Index model were combined to identify the critical factors influencing the intention to use Learning Management System. Fourteen hypotheses were proposed and tested using the Structural Equation Modelling method run in Partial Least Square software. The results indicated that eight hypotheses were accepted. The accepted hypothesis represents the criticality to consider innovativeness, job relevance, perceived enjoyment, perceived security and subjective norm in the Learning Management System usage during online learning during the COVID-19 Pandemic

Using TBLT Framework in Technology-mediated Environments to Enhance Students’ Vocabulary Retention and Interpreting Skills

Interpretation is a demanding skill, especially for specific fields in business such as marketing, accounting, trading, etc. Students majoring in Business English Language at Van Lang University reported that they are faced with the dilemma of choosing the right definition for a keyword. This has prevented them from understanding and analyzing the message before rendering it into the target language. To remedy the problem, vocabulary quizzes were administered on the university's Learning Management System (LMS) platform. The focus is on enhancing vocabulary retention. The course followed the Tase-Based Language Teaching (TBLT) framework to maximize the comprehension of the context of the vocabulary and the students. Code-mixing was used to design vocabulary quizzes. The study is a quantitative experiment with the aim of finding a correlation between the use of TBLT and the improvement of students in their vocabulary retention. The results indicate that there is a direct and positive connection between them.

Rates and influencing factors of hospitalization after diagnosis among HIV infection cases in Yinzhou district of Ningbo, 2012-2020

Objective: To understand the hospitalization rates and influencing factors after diagnosis among HIV infection cases, based on real-world data in Yinzhou district of Ningbo. Methods: A retrospective cohort study was conducted based on the databases of National AIDS Comprehensive Response Information Management System and Yinzhou Health Information Platform. The information about the following-up results, antiviral treatment data, electronic records of inpatient of the HIV cases reported during 2012-2020 were collected to analyze the rates, causes and influencing factors of hospitalization. Results: Among the 763 HIV infection cases reported in Yinzhou from 2012 to 2020, the hospitalization rate was 6.95% (53/763), and the number of inpatient was 2.59 per 100 person years. The hospitalization rate and the number of hospitalization per 100 person years in HIV infection cases were 3.16% (10/316) and 0.81 in those aged <30 years, 6.07% (15/247) and 1.59 in those aged >30 years, 7.86% (11/140) and 4.05 in those aged >45 years and 28.33% (17/60) and 17.40 in those aged ≥60 years respectively. Logistic multivariate regression analysis indicated that being aged ≥60 years was the influencing factor for hospitalizations in HIV infection cases (аOR=14.44, 95%CI:3.57-58.46). The hospitalization rates due to AIDS related diseases, cardiovascular diseases and metabolic diseases, and other diseases were 1.83% (14/763), 1.05% (8/763), and 3.93% (30/763), respectively. Conclusions: The hospitalization burden due to HIV infection was still mainly caused by those aged ≥60 years in Yinzhou, similar to that in general population and less proportion of hospitalizations were due to AIDS related diseases. The overall increase of hospitalizations due to AIDS was not obvious in Yinzhou.

The Impact of Artificial Intelligence Technology on Market Public Administration in a Complex Market Environment

Artificial intelligence (AI) technology is applied to various fields and industries with the rapid development of Internet technology. This study aims to promote the intelligent popularization of market public management strategies based on data analysis through the development and promotion of AI. AI technology is used to optimize the integration of the Market Public Administration organizational structure system, and machine algorithms process the data set. A public utility platform management system is established, and a complete public utility management assessment system and platform are based after classifying the data. Research has found that AI technology has been used in the Market Public Administration field to effectively improve work efficiency and solve the duplication and complexity of work in the management process. This has also opened a new chapter for the use of AI technology innovation. The results show that AI technology uses two driving logics of data and algorithms to intelligently solve the management problems and form a complete operating system to reflect the role of AI in the management system.

A Personalized Learning Service Compatible with Moodle E-Learning Management System

Among the numerous learning management platforms, Moodle is free, open-source software supporting expanding and modularized system functions and services to facilitate online courses or online resources and interactive activities. This study enhanced a personalized learning service for the Moodle e-learning management system, which synchronizes the user’s identity according to the user information database of the third-party user management platform system. According to the user’s demand to provide a personalized e-course, including personalized learning process, e-materials, and learning path to improve learning efficiency. This study adopted the pre-test and post-test achievement to compare the benefit of the personalized e-learning platform. Research samples were students in the “programming” course at the Technology University in central Taiwan. The experiment results indicate: (i) The average post-test result after using the proposed platform was higher than the average pre-test result (before using the proposed platform). (ii) The learning effect gap in the post-test between students was less than in the pre-test result. Hence, the proposed personalized e-learning platform was beneficial.

Building and Realizing the Obstetrics and Gynecology Nursing Management Platform by Computer Information Technology under the Concept of Mindfulness Intervention.

Nursing management of the gynecology department is one of the challenging issues and needed to be resolved through effective utilization of the available technology. In this paper, we are going to address this issue and try to establish an obstetrics and gynecology nursing management platform used to monitor and evaluate the mental health of pregnant women. Firstly, computer information technology is adopted, and the obstetrics and gynecology nursing management system is established. Secondly, after adopting the system to intervene in the mental state of patients with mindfulness, the system timely monitors the pregnant women's physical health indicators and mental health level data. With the help of the computer data analysis system, the obstetrics and gynecology management platform is built to carry out timely mindfulness interventions for pregnant women. The established system can reach high accuracy in identifying negative emotions of pregnant women, and the accuracy can reach 89.7%. It shows that the established system can timely and accurately intervene and regulate the pregnant woman's bad psychological state, effectively improve the pregnant woman's sleep quality during pregnancy, and enhance the pregnant woman's sleep effect. The effectiveness and feasibility of Internet mindfulness interventions for improving sleep quality during pregnancy has been confirmed. This has important practical significance for the digital and intelligent development of the medical care management platform.

Analysis of the use of edu-learning in basic programming competencies at SMK Ketintang Surabaya in the Covid-19 Pandemic era

Learning Management System (LMS) technology is a web-based technology developed to improve the learning process through proper planning, application and evaluation in educational institutions. The use of LMS in the learning process helps facilitate e-learning because it provides educational material without time or place constraints. SMK Ketintang is a vocational high school under the auspices of the Widya Dharma Surabaya Foundation. SMK Ketintang seeks to implement edu-learning, a Learning Management Systemplatform (LMS)equipped with chat andfeatures teleconference which are used as online learning media in the era of the Covid-19 pandemic. Edu-learning was developed with the aim of being a bridge between teachers and students in organizing and implementing learning. The analysis of the use of edu-learning as anlearning medium online in the Covid-19 pandemic era has 4 (four) indicators, including: (1) ease of use; (2) delivery of information; (3) media attractiveness; (4) media features. The results of this study indicate that the level of effectiveness in using edu-learning reaches 79.5%. So it can be concluded that edu-learning is effectively used as an online learning medium in the era of the Covid-19 pandemic.

The experience of designing a single information and educational environment of the university "NMU Digital"

The publication considers theoretical and practical approaches to the design and creation of a single information and educational environment of the Bogomolets National Medical University. The main factors that were taken into account in the development of information and educational environment of the university are identified and substantiated. The basic educational and methodical resources that ensure the functioning of the information and educational environment of modern Medical (Pharmaceutical) Higher Educational Establishment (M(P)HEE) are given. The peculiarities of the educational process at the university are analyzed and the scheme of interaction of the educational-methodical department with the faculties of the university is given.A model of information and educational environment of the Bogomolets National Medical University "NMU Digital". The list of works related to the educational process performed by the structural units of the university in the automated control system is highlighted. The main advantages of use and functionality of the automated control system, electronic document management system and distance learning platform are revealed and analyzed. The results of an online survey of research and teaching staff and students of different faculties on determining the level of digital orientation are analyzed.

COVID-19 hot-spot strategy: a special innovation in pandemic response, Oyo State Nigeria

BackgroundCOVID-19, caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has evolved into a pandemic. Oyo state, Nigeria with a population of 9,233,010, recorded the first case of COVID-19 on the 12th of March 2020 and it is among the highest contributing States to the nation’s burden of the disease with 3267 confirmed cases, including 40 deaths as of date, with an overall test positivity rate of 18.1%, far higher compared to the National average within a limited period from recorded index case. A ‘Hotspot strategy’ was designed by the Presidential Task Force on COVID-19 and Oyo State was selected to implement the strategy through upscaling case detection, isolation and treatment, quarantine of contacts and strengthening public health and social measures.MethodsWe used a descriptive cross-sectional survey of 3 identified hotspot Local Government Areas (LGAs) in Oyo State using mobile phones under Surveillance, Outbreak Response Management and Analysis System (SORMAS) platform to collect data from October to December 2020. Interventions comprised of enhanced active case search, contact line listing, contact investigation, and contact follow-up as well as to facilitate data collection and entry, community sensitization and management of alert/rumors. Baseline information and that after the 3-month period was then analyzed with the descriptive statistics presented.ResultsThe implementation of the hotspot strategy was shown to have had a major impact in Irepo LGA, where more than a 100% increase in samples tested, confirmed cases, contacts listed and contacts followed were recorded, while there were no significance changes noticed in Ibadan North and Lagelu LGAs. However, test positivity rates among contacts were found to be quite high in Ibadan North LGA (48%), compared to the other two, even though Lagelu LGA (5.7%) tested more contacts than Ibadan North.ConclusionThe observed increase in number of samples tested, cases confirmed, contact listed and investigated as well as test positivity rate in the 3 LGAs after the intervention implies that the hotspot strategy can be said to have contributed positively to the sensitivity of COVID-19 surveillance in Oyo State, Nigeria. This implies that strengthening this ‘hotspot strategy’ may be a key area of focus to improve COVID-19 surveillance sensitivity and response and in turn may help in breaking the transmission and bringing the pandemic to a halt.

Assessment of the effectiveness of management of innovative development institutions at the meso level

The purpose of the study is to identify the specifics of the management of technological platforms, in particular, in the light and textile industries, and to evaluate the effectiveness of innovation development institutions' functioning at the meso level. The methodological basis of the study was modern scientific approaches to aevaluating the effectiveness of innovation development institutions' functioning, evaluating the effectiveness of technology platform management systems: descriptions, structural-functional and system analysis, cause-and-effect relationships, cluster and factor analysis. To achieve this goal, a simulation of evaluating the effectiveness of technological platforms has been carried out, because of which 3 types of Russian platforms were revealed, the management of the development of which requires a differentiated approach. Since the technological platform “Textile and Light Industry” occupies a leading position in the rating of Russian technological platforms, the industry development's dynamics, allowing to evaluate the impact of communication platform functioning on Russian industrial complex development, was studied. To assess the effectiveness, it was planned to form a comprehensive indicator of of light industry development based on the results of factor analysis (by the method of principal components). It has concluded that the creation and development of a technological digital environment contribute to the effective interaction between various sectors of the economy and market entities, which is based on regulatory and legal regulation, ensuring information security, developing innovative infrastructure, providing highly qualified personnel in the industry.