Utilization of Nursing Defect Management Evaluation and Deep Learning in Nursing Process Reengineering Optimization

It was to explore the application of nursing defect management evaluation and deep learning in nursing process reengineering optimization. This study first selects the root cause analysis method to analyse the nursing defect management, then realizes the classification of data features according to the convolution neural network (CNN) in deep learning (DL) and uses the constructed training set and verification set to obtain the required plates and feature extraction. Based on statistical analysis and data mining, this study makes statistical analysis of nursing data from a macroperspective, improves Apriori algorithm through simulation, and analyses nursing data mining from a microperspective. The constructed deep learning model is used, CNN network training is conducted on the selected SVHN dataset, the required data types are classified, the data are analysed by using the improved Apriori algorithm, and nurses’ knowledge of nursing process rules is investigated and analysed. The cognition of nursing staff on process optimization and their participation in training were analyzed, the defects in the nursing process were summarized, and the nursing process reengineering was analyzed. The results show that compared with Apriori algorithm, the running time difference of the improved Apriori algorithm is relatively small. With the increase of data recording times, the line trend of the improved algorithm gradually eases, the advantages gradually appear, and the efficiency of data processing is more obvious. The results showed that after the optimization of nursing process, the effect of long-term specialized nursing was significantly higher than that of long-term nursing. Health education was improved by 7.57%, clinical nursing was improved by 6.55%, ward management was improved by 9.85%, and service humanization was improved by 8.97%. In summary, the reoptimization of nursing process is conducive to reduce the defects in nursing. In the data analysis and rule generation based on deep learning network, the reoptimization of nursing process can provide reference for decision-making departments to improve long-term nursing, improve the quality and work efficiency of clinical nurses, and is worthy of clinical promotion.

SP1.1.15Long-term Outcomes of Open Verses Closed Rectal Defect After Transanal Endoscopic Microscopic Surgery

Aims Management of rectal defect after TEMS is a matter of debate. Data are lacking on the effect of these techniques on long term outcomes and continence of patients. We sought to analyse these in our patient cohort. Methods Patients who underwent TEMS between 2012 and 2019 were examined retrospectively from a prospectively maintained database. These were divided into two groups – open and closed rectal defect. Patient demographics were recorded and outcomes assessed including oncological staging, morbidity, mortality, length of stay and FISI scores. Results 170 matched patients were included, with 70 patients in the open and 100 in the closed rectal defect group. Short-term complications were 18.8% with no significant difference between the two groups. Most of the defects were well healed upon endoscopic follow-up; more unhealed/sinus formation was noticed in the open group (p = 0.01); more strictures were encountered in the closed group (p = 0.04). Overall, there was a significant difference in pre and post TEMS FISI scores in all three groups (p < 0.00001, p < 0.00001, p = 0.02). Comparing the open and closed defect groups, there was no difference in the functional outcome of patients in those who developed sinus or stricture but a significant difference in those with healed scar, with those in closed rectal defect group with worsening function (p = 0.02) Conclusion Both the approaches of rectal defect management are associated with pros and cons. Long term complications should be expected and actively followed up for. Patients should be thoroughly counselled about these and possible deterioration in continence post-TEMS

Procurement of Maintenance Management for Public High Rise Residential Buildings

In response to the Malaysian housing shortage, various interventions introduced. However, while the housing gap is widening, problems relating to the performance and condition of the buildings on account of defects and poor maintenance is increasing unabated. This study investigated the selection criteria of maintenance procurement methods for public high-rise residential buildings through a survey involving eight (8) maintenance managers of PRIMA housings. The five (5) main selection criteria are working relationship intuition and experience, quality level, condition of the existing building, and clarity of scope. The research prompts a need for strategic defect management for public housing. Keywords: PR1MA housing, low-cost housing, AHP, outsourcing eISSN: 2398-4287© 2021. The Authors. Published for AMER ABRA cE-Bs by e-International Publishing House, Ltd., UK. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). Peer–review under responsibility of AMER (Association of Malaysian Environment-Behaviour Researchers), ABRA (Association of Behavioural Researchers on Asians/Africans/Arabians) and cE-Bs (Centre for Environment-Behaviour Studies), Faculty of Architecture, Planning & Surveying, Universiti Teknologi MARA, Malaysia. DOI:

Implementation of Defect Management Principle in Maintenance Practice at Local Authority

The purpose of this project is to develop processes for defect control in Malaysian public buildings. As a result, two objectives were established to achieve the goal: the study of defect management principles and analysis of defect management principles implementation levels in public building maintenance practises. Three local governments in the state of Selangor were the subjects of case studies. Using a systematic interview process, three building maintenance personnel were interviewed. Overall, the findings of this study revealed that each case study utilised defect management principles in a distinctive method. Despite the management and technical constraints, they are nevertheless able to manage the fault effectively. Keywords: Building maintenance, defect management, public building, local authority eISSN: 2398-4287© 2021. The Authors. Published for AMER ABRA cE-Bs by e-International Publishing House, Ltd., UK. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). Peer–review under responsibility of AMER (Association of Malaysian Environment-Behaviour Researchers), ABRA (Association of Behavioural Researchers on Asians/Africans/Arabians) and cE-Bs (Centre for Environment-Behaviour Studies), Faculty of Architecture, Planning & Surveying, Universiti Teknologi MARA, Malaysia. DOI: https://doi.org/10.21834/ebpj.v6iSI4.2919

Design, Construction, and Curing Integrated Management of Defects in Finishing Works of Apartment Buildings

The site analysis performed in the last ten years has found that building defects result from inconsistent decision-making and performance in the design, construction, and curing (DCC) processes. Therefore, for sustainable quality control, DCC integrated analysis and the management of causes by type and response measures should be in place. The objective of this study is to propose DCC integrated management of defects in finishing works of apartment buildings. To this end, the study surveyed 69,944 defects from 3299 apartment households and analyzed the defect types and causes by project stage. As a result, in the case of opening work (WT1), opening and closing (DT1) accounted for the highest proportion at 35.7%. In the case of furnishing work (WT2), floor installation (DT1) has the most defects. Moreover, the proposed integrated defect management technique was applied onsite, which resulted in an improvement where the defect frequency decreased by 56.80%. The results of this study will be used as the basic data for high-quality finishing projects, and the proposed management concept can be used as reference data in the establishment of a defect management system.

Quality and reliability studies in software defect management: a literature review

PurposeThis paper is focused at studying the current state of research involving the four dimensions of defect management strategy, i.e. software defect analysis, software quality, software reliability and software development cost/effort.Design/methodology/approachThe methodology developed by Kitchenham (2007) is followed in planning, conducting and reporting of the systematic review. Out of 625 research papers, nearly 100 primary studies related to our research domain are considered. The study attempted to find the various techniques, metrics, data sets and performance validation measures used by researchers.FindingsThe study revealed the need for integrating the four dimensions of defect management and studying its effect on software performance. This integrated approach can lead to optimal use of resources in software development process.Research limitations/implicationsThere are many dimensions in defect management studies. The authors have considered only vital few based on the practical experiences of software engineers. Most of the research work cited in this review used public data repositories to validate their methodology and there is a need to apply these research methods on real datasets from industry to realize the actual potential of these techniques.Originality/valueThe authors believe that this paper provides a comprehensive insight into the various aspects of state-of-the-art research in software defect management. The authors feel that this is the only research article that delves into the four facets namely software defect analysis, software quality, software reliability and software development cost/effort.

Artificial Intelligence & the steel industry: Developing an automated quality inspection system

This thesis explores possible improvements to the existing defect detection sys-tems used by Tata Steel Europe in South Wales. Exploring the possibilities of ac-curacy increases and further uses for in-house surface quality systems presents Tata Steel Europe with methods and considerations on how to improve their current surface defect management tools. This research considers three dif-ferent aspects of the defect management process and tests alternatives to the systems either currently used or not yet in place.The first section considers an ensemble object detection method using Gabor filters, histograms, and a random forest classifier. The algorithm was applied originally as an ensemble method and then as a case-study it was split into two combinations of the methods to determine what level of ensemble complexity was optimal. The images used were a set of various types of steel defect im-ages provided by Tata Steel Europe. The ensemble method achieved acceptable results compared to the existing systems, but the medium-complexity method was optimal regarding overall accuracy, false negative rate, and speed. The sec-ond section used a set of weld hole images which were split into three quality grades by defining characteristics of the feature. These images were used to test three different neural networks, an R-CNN version of GoogLeNet, and Faster R-CNN versions of ResNet-50 and ResNet-101. These networks were tasked with classifying the quality of weld holes in steel. Accurately detecting weld holes is vital in steel production as certain production processes require speed changes for welds. As the hole punches degrade over time, so does the quality of the weld hole. When weld holes are of poor quality, they can be missed or wrongly detected. All three networks detected the weld holes very well, but classifying the quality grade was approximately 60% accurate for both ResNets and 79% accurate for the GoogLeNet. These tests highlighted the importance of data quantity and quality, including lack of bias in data. The third section looks at how colour filters and greyscale methods can affect the images used for detection and classification. An investigation into coloured light sources has not been fully explored at Tata Steel in South Wales before. Having worked with the image data for sections one and two, it highlighted how important the quality of these images is. Steel defect samples were supplied, alongside their lab-confirmed defect label. Scans were taken of clean and oiled steel samples with different coloured filters and a variety of common greyscale methods were used to turn these images from RGB colour to greyscale images. The greyscale values of defect to clean steel were calculated for a specific region of interest on each steel sample. This value was used as a measure of contrast between clean and defect steel. The yellow filter with the Decolorize method produced the highest contrast image, higher than using no filter at all. For oiled sam-ples, using no filter with the Decolorize method produced the best contrast and the orange filter with the Decolorize method produced the best contrast out of the filtered images. The greyscale methods used had significant effect on the contrast of the image.The significance of this thesis is that it informs of the difficulties in developing surface inspection of steel defects due to several factors, such as environment and variation of defect shape, size, colour, and frequency. The work undertaken in this study has highlighted the need for a larger pilot line to further research both the capturing of the perfect image, and finding the most accurate detection and classification methods for each grade of steel.