Supervision Platform Research Articles

The Design of a Strategic Platform for the Smart Supervision of Public Expenditure for Colombia in the Context of Society 5.0

The overarching vision of Society 5.0 seeks to integrate technology to enhance quality of life and address social issues, with the primary goal of creating human-centered communities, which nowadays represent the inhabitants of smart cities. In this context, this work addresses the design of a modular strategic platform for the smart supervision of public expenditure, to be used by the Directorate of Information, Analysis, and Immediate Reaction (DIARI) of the General Comptroller of the Republic (CGR) of Colombia as a significant contribution towards the country’s transition into Society 5.0. The design was performed by conducting a detailed literature review on fiscal control; performing a comprehensive analysis of the legal, organizational, and technological aspects of the country and the CGR; and developing six functional modules focused on topics such as continuous learning, strategic decision making, distinctive value, strategic achievements, capacity building, and organization, within a three-year implementation plan, through a participatory approach. This plan aims to integrate the platform to enable real-time monitoring, early detection of irregularities, and increased transparency in the management of data and public resources; since the start of the operation of the strategic platform in 2024, the DIARI increased the number of alerts generated by 29% over a three-month period with respect to the year 2023. The strategic platform for the DIARI of the CGR is useful for smart cities and the transition into Society 5.0 since it ensures efficient public expenditure management, enhancing transparency and citizen empowerment through modern technologies, data analytics, and active participation in governance processes.

Quality and Quantity of School Lunch in Nanjing: Based on Data from the Sunshine Restaurant Supervision Platform.

School lunch plays an important role in children's healthy growth. Previous investigations revealed many problems with school lunches, including unreasonable dietary structure and insufficient micronutrients. This study aimed to assess the dietary structure and nutritional quality of lunches in Nanjing primary and middle schools. A stratified cluster random sampling method was used to select 44 schools that supply lunch in 12 districts in Nanjing, with two primary and two middle schools in each district. Twenty-four primary and twenty middle schools were selected. The Mann-Whitney U test was used to explore the influencing factors. Findings revealed a serious shortage of milk and fruit in school lunches; supply of eggs, fish, shrimp, and shellfish was less than half of the recommended quantity; livestock and poultry supply exceeded the recommended level by over four times. Energy and nutrition intake were suboptimal. Provision of energy, carbohydrates, vitamins (A, B1, B2, and C), calcium, and iron in urban primary schools was significantly higher than that in non-urban primary schools. The same pattern of significantly higher nutrients was equally seen in urban middle schools compared with non-urban middle schools, indicating that food supply was affected by regional economies. Therefore, it is urgent to improve the quality of lunches, with a particular focus on those in non-urban areas.

The Construction of University Scientific Research Supervision Platform under the View of Data Middle Platform

The system platform of colleges and universities has been developed from the informatization perspective based on data sharing via the reshaping of new content and the creation of technological architecture. The creation of the University Scientific Research Supervision Platform based on the Data Middle Platform attempts to analyze and address the issues above from the data sharing and service level perspective. These issues include Complicated scientific research fund reimbursement, Historical data hoarding, Late supervision & early warning, Slow system data update, Risk of data leakage, and Inconsistent inter-departmental data. The platform's technological architecture has transformed from a straightforward stacking of business processes to one that allows for the sharing and interchange system data. The solutions include:●Data sharing policies.●Managing data dictionaries.●Organizing historical data.●Integrating platforms.●Optimizing analytical functions.●Ensuring data security, among others.

Human resource practices and labour process of movie projection in China's rural areas in the digital era

PurposeRegarding human resource and labour relations management, academia focuses mainly on cities; however, rural areas are an integral part of China's economic structure. This study focuses on the movie projection industry in China's rural areas and explores how human resource practices (HRPs) are transformed and the labour process is reconstructed in digital transformation.Design/methodology/approachWe adopt a case study of a rural movie projection company. The company's HRPs reconstructed the labour process of movie projection, and they have been promoted as national standards. Data were collected from in-depth interviews, files and observations.FindingsRural movie projection companies combine high-performance and paternalistic HRPs in the media industry's digital transformation. HRPs and digital technology jointly reconstruct the labour process. First, the HRPs direct labour process practices towards standardisation. Second, the digital supervision platform guides the control style from simple to technical, placing projectionists under pressure while increasing management efficiency. Third, rural movies made using digital technology have disenchanted rural residents. Accordingly, the conventional relationships between the “country and its citizens,” “individuals themselves,” and “models and individuals” have been removed, and a new relationship between “individuals themselves” is formed thanks to the novel HRPs.Originality/valueThis research plays a crucial role in exposing researchers to the labour process of rural movie projection, which is significant in China but often ignored by Western academia and advances the Chinese contextualisation of research on labour relations.

Research on The Construction of Big Data Supervision Platform for Public Power in Universities

With the rapid development of information technology and the increasing public power in universities, it has become necessary to establish a big data supervision platform for public power in universities. Based on the analysis of the existing supervision mechanism of public power in universities, this paper puts forward the necessity of building the big data supervision platform of public power in universities and discusses the key problems and challenges of platform construction. Through the research, we can provide effective technical support for the supervision of public power in universities and promote the transparency and efficiency of public power in universities and colleges.

Quality control of manufacturing enterprises based on computer and big data technology

AbstractThe traditional manufacturing industry is facing the impact of Big Data, and all aspects of product research and development, process design, quality management, production and operation are urgently looking forward to the birth of innovative methods to cope with the challenges of big data in the industrial background. Although traditional manufacturing enterprises have initially established quality control information system, there are still many problems and limitations in the existing quality control system, which cannot meet the operation needs of manufacturing enterprises. This paper chooses the quality management of manufacturing enterprises as the research object, and uses advanced technologies such as computer, internet, big data and cloud computing to build a data system model of quality control of manufacturing enterprises. this paper optimizes the quality data processing process by establishing the quality monitoring model, and builds an intelligent quality supervision platform, and sets up the quality alarm rules for manufacturing enterprises. If the deviation between the actual value and the predicted value of the quality monitoring index is mapped between [0,1], the quality monitoring system can generate an outlier probability score. In this study, the traditional manual quality management is transformed into the management mode of the “internet + quality data” in order to realize the information, digital and intelligent quality management of manufacturing enterprises. This comprehensive research method combines modern digital technology and relevant theories of quality management to explore the optimization scheme of quality management of manufacturing enterprises, and also provides reference experience for the information construction of other similar enterprises.

Improving the quality of counseling and clinical supervision in opioid treatment programs: how can technology help?

BackgroundThe opioid epidemic has resulted in expanded substance use treatment services and strained the clinical workforce serving people with opioid use disorder. Focusing on evidence-based counseling practices like motivational interviewing may be of interest to counselors and their supervisors, but time-intensive adherence tasks like recording and feedback are aspirational in busy community-based opioid treatment programs. The need to improve and systematize clinical training and supervision might be addressed by the growing field of machine learning and natural language-based technology, which can promote counseling skill via self- and supervisor-monitoring of counseling session recordings.MethodsCounselors in an opioid treatment program were provided with an opportunity to use an artificial intelligence based, HIPAA compliant recording and supervision platform (Lyssn.io) to record counseling sessions. We then conducted four focus groups—two with counselors and two with supervisors—to understand the integration of technology with practice and supervision. Questions centered on the acceptability of the clinical supervision software and its potential in an OTP setting; we conducted a thematic coding of the responses.ResultsThe clinical supervision software was experienced by counselors and clinical supervisors as beneficial to counselor training, professional development, and clinical supervision. Focus group participants reported that the clinical supervision software could help counselors learn and improve motivational interviewing skills. Counselors said that using the technology highlights the value of counseling encounters (versus paperwork). Clinical supervisors noted that the clinical supervision software could help meet national clinical supervision guidelines and local requirements. Counselors and clinical supervisors alike talked about some of the potential challenges of requiring session recording.ConclusionsImplementing evidence-based counseling practices can help the population served in OTPs; another benefit of focusing on clinical skills is to emphasize and hold up counselors’ roles as worthy. Machine learning technology can have a positive impact on clinical practices among counselors and clinical supervisors in opioid treatment programs, settings whose clinical workforce continues to be challenged by the opioid epidemic. Using technology to focus on clinical skill building may enhance counselors’ and clinical supervisors’ overall experiences in their places of work.

Can TV Politics Improve the Trust Pattern of “Intimate Central Government and Alienate Local Government”?

The hierarchical and descending trust pattern among Chinese citizens toward governments at all levels, characterized by a stronger trust in the central government and a weaker trust in local governments, often leads to the “Tacitus trap” in local government governance. As a new platform for public participation and local government supervision, can TV political programs improve the trust pattern of “intimate central government and alienate local government,” and achieve a balance of trust between the central and local governments? Using data from the Social Consciousness Survey Data of Netizens 2018, we conducted an empirical analysis of the impact of TV political programs on residents’ trust patterns toward different levels of government. The results of this study show that: first, the opening of TV political programs can significantly narrow the trust gap between the central and local governments. This primarily achieved by significantly increasing the level of trust that residents have in the provincial government. Second, influence mechanism reveals that the introduction of of TV political programs can reduce the residents’ trust gap between central and local governments mainly by bolstering government transparency, fortifying government responsiveness, and boosting residents’ political efficacy. Third, the heterogeneity analysis indicates that TV political programs can significantly improve the trust gap between central and local governments among various groups, including women, youth, democratic party members and the public, high digitalization ability, residents in the east and provincial capital cities. Fourth, during the COVID-19 pandemic, the opening of TV political programs significantly increase residents’ trust in the central government but do not significantly raise residents’ trust in local governments. This may, to some extent, reinforce the trend of “intimate central government and alienate local government” among the public .

Enabling Integrity and Compliance Auditing in Blockchain-Based GDPR-Compliant Data Management

The General Data Protection Regulation (GDPR) is a European Union (EU) data protection and privacy law. According to the GDPR, the data on a hosting platform must meet semantic consistency and data integrity requirements. Semantic consistency means that the data operation should comply with the GDPR, while data integrity is meant to ensure that the outsourcing data should be intact. The two terms are not interchangeable. For example, if a cloud service provider migrates data to foreign storage nodes without authorization of the data owner, the data integrity requirement of the GDPR is met but the semantic consistency requirement is not. How to ensure data integrity and compliance is the main challenge for a GDPR-compliant data supervision platform. To achieve this aim, we leverage a blockchain based data management framework to check the data compliance, which can break the black box of the data hosting platform and demonstrate its logic to data owners, allowing for inspection. We propose a new provable data possession (PDP) scheme for the aforementioned framework that can check for semantic consistency and data integrity simultaneously. The verifier does not need to hold any audited data, which can reduce bandwidth usage. The verification result can be regarded as the proof for subsequent data recovery and accountability. Experimental results show higher efficiency of the PDP scheme.

Home-administered transcranial direct current stimulation with asynchronous remote supervision in the treatment of depression: feasibility, tolerability, and clinical effectiveness.

Depression is an often chronic condition, characterized by wide-ranging physical, cognitive and psychosocial symptoms that can lead to disability, premature mortality or suicide. It affects 350 million people globally, yet up to 30% do not respond to traditional treatment, creating an urgent need for novel non-pharmacological treatments. This open-label naturalistic study assesses the practical feasibility, tolerability, and clinical effectiveness of home-administered transcranial direct current stimulation (tDCS) with asynchronous remote supervision, in the treatment of depression. Over the course of 3 weeks, 40 patients with depression received psychotherapy and half of this group also received daily bi-frontal tDCS stimulation of the dorsolateral prefrontal cortex. These patients received tDCS for 30 min per session with the anode placed over F3 and the cathode over F4, at an intensity of 2 mA for 21 consecutive days. We measured patients' level of depression symptoms at four time points using the Beck Depression Inventory, before treatment and at 1-week intervals throughout the treatment period. We monitored practical feasibility such as daily protocol compliance and tolerability including side effects, with the PlatoScience cloud-based remote supervision platform. Of the 20 patients in the tDCS group, 90% were able to comply with the protocol by not missing more than three of their assigned sessions, and none dropped out of the study. No serious adverse events were reported, with only 14 instances of mild to moderate side effects and two instances of scalp pain rated as severe, out of a total of 420 stimulation sessions. Patients in the tDCS group showed a significantly greater reduction in depression symptoms after 3 weeks of treatment, compared to the treatment as usual (TAU) group [t(57.2) = 2.268, p = 0.027]. The tDCS group also showed greater treatment response (50%) and depression remission rates (75%) compared to the TAU group (5 and 30%, respectively). These findings provide a possible indication of the clinical effectiveness of home-administered tDCS for the treatment of depression, and its feasibility and tolerability in combination with asynchronous supervision.

Integrated and effective management of muck waste under the platform governance mode for a circular economy.

As an inevitable part of construction and demolition (C&D) waste, muck has a dreadful environmental impact due its inadequate management by the traditional governance process. This paper therefore focuses on the management of muck generated from C&D waste by utilizing platform governance as an alternative process, which should more effectively contribute to China's circular economy. The study explores the feasibility of providing such a platform governance mode by using Petri net to compare the traditional governance process and platform governance process for the management of muck trucks, and by using Nanjing's muck smart supervision platform as a case study to assess the effectiveness of the platform governance mode. Results from Petri net simulation modeling reveal that the platform governance mode is more effective than the traditional mode, and from the case study it is found that the success of Nanjing's muck waste management can be attributed to the platform governance mode. The platform management approach can therefore contribute to the sustainability of muck waste governance, and is suitable as an integrated and effective management mode for current practices of muck waste management and resource recovery in China. The main finding from the study is that the platform governance mode significantly improves the efficiency of muck waste management as compared with the traditional governance mode and can therefore provide greater economic and environmental benefits as part of a circular economy.

Construction of intelligent supervision platform for college students’ physical health for intelligent medical service decision-making

Construction of intelligent supervision platform for college students’ physical health for intelligent medical service decision-making

Research on construction site violation monitoring platform with target detection

This mainly describes the construction site supervision platform design purpose, determine in different areas of internal detection and target detection of site violations in the supervision of the link, should be done to visualize the market site standard model, early warning type violation of work and safety class risk hidden danger, real-time monitoring of the site. With this as the basis condition, the systematic structure design of the supervisory platform is launched, and the intelligent voice recognition technology and in-depth learning technology of monitoring images are used to establish a sound design of this system, which maximally meets the requirements of construction site violation monitoring and supervision.

Research on the Intervention of Smart Tourism in the Sustainable Development of Poor Rural Areas in Sichuan Province after 2020

In the period of poverty alleviation, smart tourism plays an important role in helping poor rural areas and poor people get rid of poverty. With the perfect end of the task of poverty alleviation, how to practice "poverty alleviation is not the end, but the starting point of a new struggle", and realize the sustainable development of smart tourism in poor rural areas after 2020 has become an urgent problem to be solved. According to the current situation of smart tourism involvement in poor rural areas in Sichuan, the reasons were analyzed, and four suggestions were put forward: increasing special fund investment, building an intelligent supervision platform, strengthening personalized marketing, and improving the service quality of tourists.

Cost-effectiveness analysis of imatinib versus dasatinib in the treatment of pediatric Philadelphia chromosome-positive acute lymphoblastic leukemia when combined with conventional chemotherapy in China

BackgroundTyrosine kinase inhibitors combined with conventional chemotherapy (CC) in treating Philadelphia chromosome-positive acute lymphoblastic leukemia (Ph-positive ALL) has achieved promising efficacy and safety outcomes. The study was conducted to compare the cost-effectiveness between imatinib (HANSOH Pharma, Jiangsu, China) and dasatinib (CHIATAI TIANQING Pharma, Jiangsu, China) in treating pediatric Ph-positive ALL when combined with CC from the perspective of the health system in China.MethodsA Markov model was established to simulate a hypothetical cohort of pediatric Ph-positive ALL patients receiving imatinib or dasatinib, combined with CC. The model was designed using a 10-year horizon, a 3- month cycle, and a 5% discount rate. Three health states were included: alive with progression-free survival, progressed disease, and death. Patient characteristics and transition probabilities were estimated based on clinical trials. Other relevant data, such as direct treatment costs and health utility data were extracted from published literature and Sichuan Province’s centralized procurement and supervision platform. One-way sensitivity analysis and probabilistic sensitivity analysis were performed to assess the robustness of the results. The willingness-to-pay (WTP) was set as three times China’s GDP per capita in 2021.ResultsIn the base-case analysis, the total medical costs were $89,701 and $101,182, and the quality-adjusted life years (QALYs) gained were 1.99 and 2.70, for imatinib and dasatinib regimens, respectively. The incremental cost-effectiveness ratio for dasatinib versus imatinib was $16,170/QALY. The probabilistic sensitivity analysis indicated that treatment with dasatinib combined with CC achieved a 96.4% probability of cost-effectiveness at a WTP threshold of $37,765/QALY.ConclusionsDasatinib combined with CC is likely to be a cost-effective strategy compared to imatinib combination therapy for pediatric Ph-positive ALL in China at a WTP threshold of $37,765/QALY.

Aviation Rivet Classification and Anomaly Detection Based on Deep Learning

The shortage of personnel and the high cost have become a major pain point in the current safety supervision work of the inspectors. Aiming at the problem that the aircraft maintenance inspector could not visit the scene in person during the epidemic, a remote safety supervision platform was built based on intelligent glasses and 5G network, and the real-time monitoring of the aircraft skin rivet status was realized. And a method of aviation rivet classification and anomaly detection based on deep learning algorithm was proposed. Firstly, according to the appearance of rivet head, the aviation rivet is classified, the data set of aviation rivet is made, and the aviation rivet classification and anomaly detection model are constructed. Evaluate the detection results from such indicators as confidence, precision, recall rate, and mAP and compare the algorithm with the detection results of Yolox-s, Yolox-m, Yolov5-s, Yolov5-m, and Yolov4. The results show that (1) the algorithm proposed in this paper can realize the classification of aviation rivets and the detection of abnormal conditions, the confidence of the detection results is more than 90%, and the average precision, recall, and AP value are above 95%, 85%, and 88%, respectively. (2) The order of rivet classification and abnormal detection effect from good to bad is Philips screws, round head rivets, flat head rivets, countersunk head rivets, blind rivets, and abnormal condition. (3) Compared with other algorithms, the aviation rivet classification abnormal target detection based on deep learning has absolute advantages in accuracy and speed.

Computer Network Technology for the Construction of Engineering Safety Supervision and Management Systems

Background: Nowadays, the function of information construction in construction project quality supervision and management is increasingly prominent, and it has become a task that cannot be ignored by administrative departments. Objective: To supervise and manage engineering safety data effectively and display the system construction more intuitively, a method based on computer network technology is proposed. Methods: K-means clustering, random forest, neural network, and other artificial intelligence algorithms were used for data modelling, and classification model evaluation, regression model evaluation, and other evaluation tools were used to evaluate the quality of the built model, and the power engineering monitoring system was established. The functions of engineering safety supervision and management, data storage and query, deformation graphical display, data analysis and forecast, results report output, and so on are realized. Results: The results showed that the mean square error of K-means was 7.74, the mean square error of random forest was 27.5, and the error of neural network was 4.4. Conclusion: Neural network has the smallest error and the closest data. The establishment of the system provides a new research platform for power engineering safety supervision and management.

Visual supervision of large‐scope heat source factories based on knowledge graph

AbstractAs a result of limited resources and economic development acting as dual bottleneck constraints, optimizing industrial layout structures has been a general trend in heavy industry. The visual supervision of heat source factories based on integrated multidimensional information is important for optimizing an industrial layout. Based on Visible Infrared Imaging Radiometer Suite (VIIRS) I‐band 375‐m active fire product (VNP14IMG) data, point of interest data, enterprise attribute information and other data, combined with clustering regression, knowledge graphs (KGs), 3D geographic information systems, and other technical methods, the temporal and spatial variations in China's heat source industries are macroscopically analyzed, and a visual supervision platform for heat source industries with functions such as visualization, time‐series analysis, and knowledge discovery is established. The results show that: (1) overall, heat source factories exhibit a spatial pattern of dense in the east and sparse in the west, and the number of industrial heat source objects and the number of industrial fire hotspots decreased from 2013 to 2021, with rates of decline of 22.0 and 27.3%, respectively; (2) the enterprise KG, which contains basic enterprise information, dynamic enterprise risk information and enterprise equity structure information, can provide users with accurate and reliable enterprise knowledge; and (3) the remote sensing monitoring information platform for heat source factories performs well in terms of the discovery and management of heat source factories at large scale. In general, the platform constructed in this study can support the rapid monitoring and positioning of industrial heat sources over large areas to improve supervision in terms of finding problems and preventing risks and to provide a necessary reference for optimizing industrial spatial patterns and environmental governance.

A Teaching Supervision Platform Based on Deep Learning

A Teaching Supervision Platform Based on Deep Learning

Development of Comprehensive Acquisition Software for Measurement While Drilling Data Based on VUE Coal Mine

For the current coal mine directional drilling MWD equipment and system are independent of each other, resulting in different forms of MWD data at the bottom of the hole, forming data islands; Based on the B/S system architecture mode, by comparing the measurement while drilling mode and measurement data format, the requirement module of data comprehensive acquisition system is analyzed; the background database of the integrated collection system is set up to develop the development of the integrated collection system of directional drilling while drilling data in coal mine. The verification shows that the data acquisition system can meet the unified collection and processing of various MWD data, the overall analysis and evaluation function, and achieve real-time data upload. It provides data network transmission guarantee for directional drilling data supervision platform in coal mine, and improves the intelligent level of coal mine drilling.