Quality Supervision Research Articles

Research of blockchain-embedded agricultural quality credit regulation influencing factors

PurposeThe credit of agricultural product quality and safety reflects the ability of the main actors involved in the supply chain to provide reliable agricultural products to consumers. To fundamentally solve the problem of agricultural product quality and safety, it is worth studying how to make the credit awareness and integrity self-discipline of the supply chain agriculture-related subjects strengthened and the role and value of credit supervision given full play. Starting from the application of blockchain in the agricultural product supply chain, this paper aims to investigate the main factors affecting the credit regulation of agricultural product quality.Design/methodology/approachUsing the DEMATEL-ISM (decision-making trial and evaluation laboratory–interpretative structural modeling) method, we analyze the credit influencing factors of agricultural quality and safety empowered by blockchain technology, find the causal relationship between the crucial influencing factors and deeply explore the hierarchical transmission relationship between the influencing factors. Then, the path analysis in structural equation modeling is utilized to verify and measure the significance and effect value of the transmission relationship among the crucial influencing factors of credit regulation.FindingsThe results show that the quality and safety credit regulation of agricultural products is influenced by a combination of direct and deep influencing factors. Long-term stable cooperative relationship, Quality and safety credit evaluation, Supply chain risk control ability, Quality and safety testing, Constraints of the smart contract are the main influence path of blockchain embedded in agricultural product supply chain quality and safety credit supervision.Originality/valueCredit supervision is an important means to improve the ability and level of social governance and standardize the market order. From the perspective of blockchain embedded in the agricultural supply chain, the regulatory body is transformed from the product body to the supply chain body. Take the credit supervision of supply chain subjects as the basis of agricultural product quality supervision. With the help of blockchain technology to improve the effectiveness of agricultural product quality and safety credit supervision, credit supervision is used to constrain and incentivize the behavior of agricultural subjects.

Behavioral decision-making of government, agricultural product producers, and consumers on agricultural product quality and safety regulation in a digital environment.

The quality and safety of agricultural products are related to people's lives and health, economic development, and social stability, and have always been a hot issue of concern to the government and society. The rapid development of digital traceability technology in the digital environment has brought new opportunities for the supervision of agricultural product quality and safety, but the frequent occurrence of agricultural product safety incidents in recent years has exposed many problems such as the lack of governmental supervision, unstandardized production process of enterprises, and weak consumer awareness. To improve the cooperation efficiency of stakeholders and ensure the quality and safety of agricultural products, this paper proposes a dynamic model based on evolutionary game theory. The model incorporates the government, agricultural product producers, and farmers, and evaluates the stability and effectiveness of the system under different circumstances. The results of the study show that there are multiple evolutionary stabilization strategies in the tripartite evolutionary game model of agricultural product quality and safety supervision, and there are corresponding evolutionary stabilization conditions. There are several factors affecting the stability of the system, the most important of which are government regulation, severe penalties for agricultural product producers, and incentives. When these factors reach a certain threshold, the stakeholder cooperation mechanism can establish an evolutionarily stable strategy. This study contributes to the understanding of the operational mechanism of stakeholder cooperation in agricultural product quality and safety regulation in the digital environment and provides decision support and policy recommendations for stakeholders to promote the sustainable development and optimization of agricultural product quality and safety regulation.

Design of Safety Evaluation and Risk Traceability System for Agricultural Product Quality

The quality and safety of agricultural products involve a variety of risk factors, a large amount of risk information data, and multiple circulation and disposal processes, making it difficult to accurately trace the source of risks. To achieve precise traceability of agricultural product quality and safety, the monitoring and supervision level of agricultural product traceability systems needs to be improved. In this paper, the agricultural product quality- and safety-related detection data are taken as the research object, the agricultural product supply chain and business process are sorted out, the agricultural product risk factors under the influence of heavy metals are analyzed, and the agricultural product quality and safety risk evaluation model is established. The agricultural product risk traceability system was designed based on the six-layer architecture of the equipment layer, data layer, service layer, application layer, display layer, and user layer. Combined with the agricultural product quality and safety risk evaluation model, the system data were stored and modified by using the MySQL relational database, and the agricultural product risk traceability system was developed, which realized the accurate traceability of the risk link of the quality and safety of agricultural products. The research results of this paper provide an effective information means for the quality and safety supervision of agricultural products, and provide a technical reference for the development of a traceability system of risk factors related to agricultural products, which has good practical significance.

The influence of supervisors and peers on PhD students’ sense of belonging and their success at Kenyan universities

Purpose Given declining tuition funds and government grants, Kenyan universities need to develop strategies, including increased research grants and collaborations, to diversify their income sources. Well-managed doctoral students can boost a university’s teaching and research outputs. However, numbers of students enrolled in doctoral programmes at Kenyan universities are low, and graduation rates and time-to-graduate statistics are disturbing. Research undertaken elsewhere underline the important role played by supervisors and peers in facilitating students’ sense of belonging and their success. Therefore, this study aims to investigate the influence of supervisory and peer support on PhD students’ sense of belonging and their success at Kenyan universities. Design/methodology/approach In this cross-sectional study, data were gathered through an online questionnaire from 614 students admitted to doctoral programmes at Kenyan universities between 2010 and 2018. We used multi-item scales to collect data on PhD students’ self-efficacy, supervisory and peer support and a sense of belonging. Findings Structural equation modelling results revealed that PhD students’ modes of study and self-efficacy were significantly associated with the quality of supervision, peer support and a sense of belonging. However, only age, a sense of belonging and the quality of supervision were directly linked to their success. Originality/value This study contributes to the literature on doctoral-level education, responding to the need for research on the influence of relationships with supervisors and peers on PhD students’ sense of belonging and their success, especially in developing countries.

Apakah Kepemimpinan Memiliki Peran Moderasi dalam Kualitas Pengawasan pada Auditor Internal Pemerintah?

This research aims to analyze the influence of competence, independence and integrity on the quality of supervision carried out by auditors at the BPKP Representative Office of Banten Province. This research used 35 Functional Auditor Officials (PFA) at the BPKP Representative Office of Banten Province as respondents. This quantitative research uses SEMPLS with the SmartPLS application as a supporting application in data processing. This research shows that auditor competence has a positive effect on the quality of supervision, while auditor independence and integrity have no effect on the quality of supervision. The research also concludes that leadership does not strengthen the positive influence of the partial relationship between auditor competence, independence and integrity on supervisory quality. It is hoped that the results of this research can provide input for the Banten Province BPKP Representative so that they can implement policies that focus on developing PFA competencies to improve the quality of supervision. This research contributes to the literature on public sector internal auditing, which is still rare in previous research, especially when using Indonesian data. This research also places leadership moderating variables in the relationship between independent and dependent variables, which have rarely been used in previous research.

Rapid quantitative analysis of cotton-polyester blended fabrics using near-infrared spectroscopy combined with CNN-LSTM

Accurate and rapid quantitative analysis of fiber content is important for blended fabric quality control and supervision. In this paper, a deep learning method based on an improved hybrid network of convolutional neural network (CNN) and long short-term memory (LSTM) to fast and accurate determine cotton content of cotton-polyester blended fabrics using near-infrared (NIR) spectroscopy. The cotton-polyester blended fabric samples were partitioned into training set, validation set and testing set in the ratio of 6:2:2 to develop the quantitative model of cotton content of blended fabric. Firstly, a one-dimensional CNN architecture is designed and modeled to obtain the CNN parameters and to evaluate the spectral preprocessing methods. Then, the CNN structure is modified and improved using LSTM to obtain a CNN-LSTM structure. The root mean square error (RMSE) of the validation set obtained by CNN model is 0.83%, which is 34.03% lower than that of the traditional partial least squares (PLS) model, and the RMSE of the testing set obtained by CNN model is 0.88%, which is 25.88% lower than that of the PLS model. The RMSE of the validation set obtained by CNN-LSTM model is 0.65%, which is 47.85% lower than that of the PLS model, and the RMSE of the testing set obtained by CNN-LSTM model is 0.75%, which is 36.57% lower than that of the PLS model. Compared with PLS and CNN models, the CNN-LSTM model can more accurately analyze the cotton content proportion of cotton-polyester blended fabrics, which provides a new fast and non-invasive method for the quantitative detection of fabrics.

Optometry student clinical practice at public health facilities: A systematic review.

Clinical training, supervision and practice are the most important aspects of health profession education, including optometry. Institutions implore various methods for students to gain access, exposure and experience in different clinical environments, away from their normal academic settings. This review aimed to investigate studies and related documentary evidence to determine existing standards and methods for educational institutions in conducting optometry clinical training at the external sites. The electronic databases - ProQuest One, Scopus, EBSCOhost, Sabinet, Science Direct and Google Scholar - were searched systematically for studies on the implementation of workplace clinical training of undergraduate optometry students. The study followed the Joanna Briggs Institute (JBI) systematic review methodology and a systematic search of various electronic databases was conducted for studies on implementation of workplace clinical training. Of the 450 full-text studies searched, 13 studies were found to be reputable sources of evidence and were included in this systematic review. Four themes relating to student clinical training emerged, namely, clinical training approaches implemented, expected minimum standards at the training sites, clinical training environment wherein students and supervisors find themselves and clinical competence of the supervisors and students. They encompass important factors to consider in the planning and provision of quality, efficient and effective student clinical supervision at the external training facilities. There is a dearth of scholarly studies to guide clinical training of optometry training within the public health sector. However, more studies are undertaken in other health disciplines, and they provide generic guidelines, which can be adapted for optometry. The article highlights the need for further studies in optometry student clinical training, focussing on programme designs and standardisation of clinical training in multi-institutional, low-income contexts.

KEPUASAN KERJA PEGAWAI SEKSI PENDATAAN DAN PENETAPAN PAJAK DALAM PELAYANAN PUBLIK

This study aims to analyze employee job satisfaction in public service, and to analyze the implications of employee job satisfaction on public service in the Mataram City SAMSAT Office. The theory used in this research is satisfaction theory and motivation theory. The method used in this study is qualitative which is described in detail through observation and interviews with informants. This study uses two (2) types of data sources, namely primary data sources and secondary data sources. The data was obtained by means of interviews, observation, documentation, and methods of literature. The results of the study show that employee job satisfaction has not been fully fulfilled or is not satisfied, there are still some that have not been fulfilled, in employee job satisfaction there are 5 (five) indicators, namely; working conditions, wages, security, quality of supervision, and relationships with others. And employee job satisfaction has implications for public services in the Mataram City SAMSAT Office. This shows that the better the employee's job satisfaction, the better the employee's performance and vice versa, the less employee job satisfaction, the less employee performance job.

Providing Clinical Psychology Training and Trauma-Focused Treatment via Telehealth During COVID-19.

To slow the spread of COVID-19 many mental health providers transitioned to telehealth delivery of trauma-focused treatment for maltreated children. However, these providers faced myriad challenges, including equitable access to equipment and technical demands of telehealth software. Training clinics overseeing pre-doctoral clinical psychology interns experienced the added challenge of providing quality supervision and training via telehealth. This study involves a retrospective application of the Exploration, Preparation, Implementation, and Sustainment (EPIS) framework to describe the innovative adaptation to a telehealth service delivery model in a training clinic providing evidence-based trauma-focused treatment to children and their families. Mixed methods data from clinic records and intern evaluations indicate that compared to pre-COVID (February 2019 - February 2020), during early COVID (April 2020 - April 2021) more patients accessed clinic services, interns reported fewer hours of individual supervision, and interns reported greater satisfaction with their training experiences. Implications for ongoing provision of telehealth services are discussed.

Peanut origin traceability: A hybrid neural network combining an electronic nose system and a hyperspectral system

Peanuts, sourced from various regions, exhibit noticeable differences in quality owing to the impact of their natural environments. This study proposes a fast and nondestructive detection method to identify peanut quality by combining an electronic nose system with a hyperspectral system. First, the electronic nose and hyperspectral systems are used to gather gas and spectral information from peanuts. Second, a module for extracting gas and spectral information is designed, combining the lightweight multi-head transposed attention mechanism (LMTA) and convolutional computation. The fusion of gas and spectral information is achieved through matrix combination and lightweight convolution. A hybrid neural network, named UnitFormer, is designed based on the information extraction and fusion processes. UnitFormer demonstrates an accuracy of 99.06 %, a precision of 99.12 %, and a recall of 99.05 %. In conclusion, UnitFormer effectively distinguishes quality differences among peanuts from various regions, offering an effective technological solution for quality supervision in the food market.

Patient and Operational Factors Do Not Substantively Affect the Annual Departmental Quality of Anesthesiologists' Clinical Supervision and Nurse Anesthetists' Work Habits.

Although safety climate, teamwork, and other non-technical skills in operating rooms probably influence clinical outcomes, direct associations have not been shown, at least partially due to sample size considerations. We report data from a retrospective cohort of anesthesia evaluations that can simplify the design of prospective observational studies in this area.Associations between non-technical skills in anesthesia, specifically anesthesiologists' quality of clinical supervision and nurse anesthetists' work habits, and patient and operational factors were examined. Eight fiscal years of evaluations and surgical cases from one hospital were included. Clinical supervision by anesthesiologists was evaluated daily using a nine-item scale. Work habits of nurse anesthetists were evaluated daily using a six-item scale. The dependent variables for both groups of staff were binary, whether all items were given the maximum score or not. Associations were tested with patient and operational variables for the entire day. There were 40,718 evaluations of faculty anesthesiologists by trainees, 53,772 evaluations of nurse anesthetists by anesthesiologists, and 296,449 cases that raters and ratees started together. Cohen's d values were small (≤0.10) for all independent variables, suggesting a lack of any clinically meaningful association between patient and operational factors and evaluations given the maximum scores. For supervision quality, the day's count of orthopedic cases was a significant predictor of scores (P = 0.0011). However, the resulting absolute marginal change in the percentage of supervision scores equal to the maximum was only 0.8% (99% confidence interval: 0.2% to 1.4%), i.e., too small to be of clinical or managerial importance. Neurosurgical cases may have been a significant predictor of work habits (P = 0.0054). However, the resulting marginal change in the percentage of work habits scores equal to the maximum, an increase of 0.8% (99% confidence interval: 0.1% to 1.6%), which was again too small to be important. When evaluating the effect of assigning anesthesiologists and nurse anesthetists with different clinical performance quality on clinical outcomes, supervision qualityand work habits scores may be included as independent variables without concern that their effects are confounded by association with the patient or case characteristics. Clinical supervision and work habits are measures of non-technical skills. Hence, these findings suggest that non-technical performance can be judged by observing the typical small sample size of cases. Then, associations can be tested with administrative data for a far greater number of patients because there is unlikely to be a confounding association between patient and case characteristics and the clinicians' non-technical performance.

Penerapan Akuntansi Sektor Publik, Pengawasan Internal dan Transparansi terhadap Kinerja Instansi Pemerintah Provinsi Jakarta

This research was conducted to determine the influence of public sector accounting, internal supervision and transparency on the performance of the Jakarta Provincial Government's financial reports. This research uses the Jakarta Provincial Inspectorate as the population. This research sample used 45 respondents from the results of distributing questionnaires carried out at the Jakarta Provincial Inspectorate. Data were processed using SPSS software and analyzed using multiple linear regression analysis. The results of this research show that human resource quality competency, accountability and supervision have a positive effect on the quality of the financial report performance of the Jakarta Provincial Government

Identification of toxic Gelsemium elegans in processed food and honey based on real-time PCR analysis

Gelsemium elegans (GE) is a widely distributed hypertoxic plant that has caused many food poisoning incidents. Its pollen can also be collected by bees to produce toxic honey, posing a great threat to the health and safety of consumers. However, for the complex matrices such as cooked food and honey, it is challenging to perform composition analysis. It is necessary to establish more effective strategies for investigating GE contamination. In this study, the real-time PCR (qPCR) analysis combined with DNA barcode matK was proposed for the identification and detection of GE. Fifteen honey samples along with twenty-eight individuals of GE and the common confusable objects Lonicera japonica, Ficus hirta, Stellera chamaejasme and Chelidonium majus were gathered. Additionally, the food mixtures treated with 20-min boiling and 30-min digestion were prepared. Specific primers were designed, and the detection capability and sensitivity of qPCR in honey and boiled and digested food matrices were tested. The results demonstrated that the matK sequence with sufficient mutation sites was an effective molecular marker for species differentiation. GE and the confusable species could be clearly classified by the fluorescence signal of qPCR assay with a high sensitivity of 0.001 ng/μl. In addition, this method was successfully employed for the detection of deeply processed food materials and honey containing GE plants which even accounted for only 0.1 %. The sequencing-free qPCR approach undoubtedly can serve as a robust support for the quality supervision of honey industry and the prevention and diagnosis of food poisoning.

The Problems and Difficulties of Medical Devices in Chongqing in Response to Public Health Incidents in 2022

Background and Aim: In the face of emergencies such as large-scale infectious diseases, some medical device manufacturers either do not have enough practical research and development experience in related epidemic prevention medical devices or use cheaper raw materials to reduce product quality in the research and development stage to save costs and increase profits. purpose, and even use various channels and means to bypass market supervision and produce problematic medical devices from the very beginning. Or, to take advantage of the public's panic about unknown infectious diseases, some unscrupulous merchants falsely advertise products that do not meet medical requirements, confusing the masses without certain professional cognitive ability, blindly believing and following them, and causing sudden large-scale infectious diseases. It cannot effectively reduce and contain the spread of diseases or other public health events. Infectious diseases spread rapidly in various cities. This is the problem with the quality supervision of medical devices under public health emergencies. From this new crown pneumonia epidemic, it can be found that the existing system is still unable to meet the needs of emergencies such as public health. It is necessary to do a good job of system reserves for the accessibility of drugs and medical devices from the level of laws and regulations. This needs to be sorted out to achieve accessibility. The existing regulations and systems should be improved to meet the needs of medical device use in public health and other emergencies. Materials and Methods: Safety testing of medical devices used in 26 public health events using Chinese national standards Results: The histogram of sample scores in the operation link reveals a complex landscape with an increased sample size. This data accentuates the intricate scoring dynamics and intricate qualification rates within the operation link, showcasing variations even among identical products from the same manufacturer. The case of "LFR20B" and "LFR30B" infrared forehead thermometers exemplifies how subtle factors, such as the weighting of specific performance indicators, contribute to scoring distinctions. Despite the "LFR20B" model achieving a higher score, it falls short of the category's passing threshold, underscoring the intricate nature of sample evaluations. However, it is noteworthy that 58% of the samples successfully meet national standards and pass the inspection, indicating a substantial portion complying with regulatory requirements. Conclusion: Laws and regulations need to be improved, there are hidden dangers in regulation, the ability of regulatory teams needs to be improved, medical device enterprises have problems, medical devices should strictly follow national standards, and the public should actively participate in medical device regulation.

Exploring the Relationship between Ethical Conflicts and Psychological Distress among Social Workers: The Role of Social and Economic Exchange and Burnout

Abstract This study examines the association between ethical conflicts and psychological distress among social workers and the role of economic and social exchange in mediating this relationship. It also explores the moderating effect of burnout on the association between ethical conflicts and both social and economic exchange. The sample consisted of 568 Israeli social workers, where the majority were women. A moderated mediation model was employed to analyse the research data. The results indicate that the frequency of ethical conflicts was positively correlated with economic exchange, which in turn was positively correlated with psychological distress. Also, the frequency of ethical conflicts was negatively correlated with social exchange, which was negatively correlated with psychological distress. The effect of the frequency of ethical conflicts on both economic and social exchange was more pronounced at higher levels of burnout. The current study provides valuable insights into the complex processes social workers undergo when faced with ethical conflicts and underscores the importance of addressing burnout and exchanges in the social worker–organisation relationship. The study recommends that policymakers and welfare organisation managers allocate resources towards quality supervision and training programmes, promote teamwork and self-care activities for social workers and create an ethical work environment.

Nursing Students' Perceptions of the Quality of Teaching Supervision During Clinical Placements

Introduction: During their placements in healthcare establishments, nursing students are assigned to members of the nursing staff who, as tutors, are responsible for supporting and assessing them as part of their professional training [1]. As such, it is vital that the hospital environments hosting these students pay the utmost attention to how these placements are carried out. This study explored our respondents' perceptions of the quality of teaching supervision during their clinical placements at the Bandundu general referral hospital (HGR). We opted for a qualitative, case study approach. Data were collected from individual, semi-structured, face-to-face interviews with 9 third-year graduate students. The aim of these interviews was to gather information based on the students' previous experiences of their placements. Materials and Method: The analysis method used for this research was content analysis, also known as thematic content analysis. The data were analysed using ATLAS.ti7 software. A main theme was identified for this study. Three sub-themes emerged from this central theme: students' perceptions of their needs in terms of teaching support, their perceptions of the teaching strategies used by the support staff, and their perceptions of the quality of the training provided by the support staff in the field. Results: With regard to teaching support needs, it is important to emphasise the lack of prior and intermediate assessment, the inadequacy of care materials, the excessive number of trainees, the lack of support for assessment, the failure to comply with placement objectives and the lack of autonomy, all of which appear to hinder students' learning progress in the clinical environment. With regard to teaching strategies, it is interesting to note that the methods of education, training and advice were more frequently mentioned than those of confrontation. With regard to the quality of training, the majority of participants judged supervision at the placement to be satisfactory. Conclusion: Although the majority of students were satisfied with the quality of the supervision they received at their placement, the results suggest the need for innovation in current approaches to clinical teaching in order to foster student autonomy and enable them to develop essential skills.

An efficient and accurate surface defect detection method for quality supervision of wood panels

The wood panel processing sector is integral to the landscape of industrial manufacturing, and automated detection of wood panel surface defects has become an important guarantee for improving the efficiency and quality of processing production. However, due to the diverse scales and shapes of wood panel surface defects, as well as their complex and varied colors and texture characteristics, the efforts to efficiently and accurately detect surface defects in wood panels through existing methods have fallen short. Therefore, the paper proposes an enhanced YOLOx-tiny deep learning network for wood panel surface defect detection. We introduce new modules multi-pooling feature fusion module and comprehensive feature extraction module, instead of the original SPP and Bottleneck modules to enhance key feature extraction and reduce the number of computational parameters. The experimental results conducted on the self-constructed wood panel surface defects dataset show that the mAP of our proposed method is 95.01%, which is 9.58% higher than the original YOLOx-tiny network model, and the defects recall is 91.46%, which is 13.21% higher compared to the original network. Meanwhile, the method is able to reduce 12.22% of computational parameters, which effectively improves the efficiency of the detection of surface defects on wood panels. In summary, the proposed intelligent surface defect detection approach for wood panels, which utilizes an enhanced YOLOx-tiny deep learning network, has yielded notable outcomes in enhancing both accuracy and efficiency. This method holds significant practical relevance for the wood panel manufacturing sector, offering the potential to enhance both production efficiency and quality. It also explores the automation and intelligent technology in the process of man-made board processing, which provides a valuable reference for the research in related fields.

Mismatch in perceptions of the quality of supervision and research data management as an area of concern: Results from a university-wide survey of the research integrity culture at a Belgian university

ABSTRACT Researchers of KU Leuven, a large Belgian university, were invited to complete a bespoke questionnaire assessing their attitudes toward research integrity and the local research culture, with specific emphasis on the supervision of junior researchers. A total of 7,353 invitations were sent via e-mail and 1,866 responses were collected (25.3% response rate), of which 1,723 responses are reported upon here. Some of the findings are relevant to the broader research community. Whereas supervisors evaluated their supervision of junior researchers almost unanimously as positive, fewer supervisees evaluated it as such. Data management emerged as an area of concern, both in terms of reviewing raw data and of data storage. More female than male professors emphasized open communication and supported their supervisees’ professional development and personal well-being. At the same time, fewer female professors felt safe to speak up than male professors. Finally, researchers who obtained their master’s degree outside Europe evaluated their supervision and KU Leuven’s research culture more positively than researchers with a master’s degree from KU Leuven. The results of the survey were fed back to the university’s board and several bodies and served as input to update the university’s research policy. Faculties and departments received a detailed report.

Pangenomic analyses of tuberculosis strains to identify resistomes using computational approaches.

To locate resistomes in tuberculosis strains, to determine the severity of drug resistance, and to infer its implications with respect to high tuberculosis prevalence in a Third World setting. The pangenomic study was conducted from October 2022 to January 2023 in Sir Syed University of Engineering and Technology, Karachi, and comprised 2012-22 data on multiple sequence alignment to assess the genetic evolution of tuberculosis strains. Antibiotic resistance drug classes were identified using the Canadian Antibiotic Resistance Database, which entailed multidrug-resistant and extremely drug-resistant strains. Also, GenBank was used for tuberculosis genome FASTA (fast-all; nucleotide and protein sequence representation) files, prediction of resistome sequences on the basis of Canadian Antibiotic Resistance Database, and multiple sequence alignment was done in Mauve. Evolutionarily, the 6 strains identified were structurally similar with polymorphisms in their core chromosomal regions. Their resistome genes showed perfect hits for isoniazid, rifamycin, cephalosporin, fluoroquinolone, aminoglycosides, penem, penam and cephamycin. Drugs discovered in antibiotic resistance genes are now less effective in treatment, and have the potential to develop into more dangerous bacteria, if not monitored. For treatment, staying long durations in hospitals for quality healthcare and supervision in third world countries is unaffordable.

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.