Indicator Selection for Quality Measurement in Maternal Neonatal and Child Health Services: Application of Random Forest Classifier

Quality of Maternal, Neonatal and Child (MNCH) care is an important aspect in ensuring healthy outcomes and survival of mothers and children. To maintain quality in health services provided, organizations and other stakeholders in maternal and child health recommend regular quality measurement. Quality indicators are the key components in the quality measurement process. However, the literature shows neither an indicator selection process nor a set of quality indicators for quality measurement that is universally accepted. The lack of a universally accepted quality indicator selection process and set of quality indicators results in the establishment of a variety of quality indicator selection processes and several sets of quality indicators whenever the need for quality measurement arises. This adds extra processes that render quality measurement process. This study, therefore, aims to establish a set of quality indicators from a broad set of quality indicators recommended by the World Health Organization (WHO). The study deployed a machine learning technique, specifically a random forest classifier to select important indicators for quality measurement. Twenty-nine indicators were identified as important features and among those, eight indicators namely maternal mortality ratio, still-birth rate, delivery at a health facility, deliveries assisted by skilled attendants, proportional breach delivery, normal delivery rate, born before arrival rate and antenatal care visit coverage were identified to be the most important indicators for quality measurement.

Software Coupling and Cohesion Model for Measuring the Quality of Software Components

Measuring software quality requires software engineers to understand the system’s quality attributes and their measurements.The quality attribute is a qualitative property;however,the quantitative feature is needed for software measurement,which is not considered during the development of most software systems.Many research studies have investigated different approaches for measuring software quality,but with no practical approaches to quantify and measure quality attributes.This paper proposes a software quality measurement model,based on a software interconnection model,to measure the quality of software components and the overall quality of the software system.Unlike most of the existing approaches,the proposed approach can be applied at the early stages of software development,to different architectural design models,and at different levels of system decomposition.This article introduces a software measurement model that uses a heuristic normalization of the software’s internal quality attributes,i.e.,coupling and cohesion,for software quality measurement.In this model,the quality of a software component is measured based on its internal strength and the coupling it exhibits with other component(s).The proposed model has been experimented with nine software engineering teams that have agreed to participate in the experiment during the development of their different software systems.The experiments have shown that coupling reduces the internal strength of the coupled components by the amount of coupling they exhibit,which degrades their quality and the overall quality of the software system.The introduced model can help in understanding the quality of software design.In addition,it identifies the locations in software design that exhibit unnecessary couplings that degrade the quality of the software systems,which can be eliminated.

Quality Management Research on the Purchasing of Food Processing Enterprises

In order to improve the purchased goods quality management level of food processing enterprises, the causes of quality management problems were ana- lyzed, which were classified into four categories, namely, natural toxins in raw ma- terials, quality problems in planting and breeding, quality problems in transportation, quality problems in delivery acceptance. Then, based on the causes, eight measures to improve goods purchasing management were put forward, and graphs were used to illustrate the corresponding countermeasure to each cause. This study is of theo- retical significance for the food processing enterprises to improve the quality man- agement of purchased goods through formulating improvement measures based on their operating states.

Framework for assessing quality of care for inflammatory bowel disease in Sweden

AIM: To create and apply a framework for quality assessment and improvement in care for inflammatory bowel disease (IBD) patients. METHODS A framework for quality assessment and improvement was created for IBD based on two generally acknowledged quality models. The model of Donabedian (Df) offers a logistical and productive perspective and the Clinical Value Compass (CVC) model adds a management and service perspective. The framework creates a pedagogical tool to understand the balance between the dimensions of clinical care (CVC) and the components of clinical outcome (Df). The merged models create a framework of the care process dimensions as a whole, reflecting important parts of the IBD care delivery system in a local setting. Clinical and organizational quality measures were adopted from clinical experience and the literature and were integrated into the framework. Data were collected at the yearly check-up for 481 IBD patients during 2008. The application of the quality assessment framework was tested and evaluated in a local clinical IBD care setting in Jnkping County, Sweden. RESULTS: The main outcome was the presentation of how locally-selected clinical quality measures, integrated into two complementary models to develop a frame-work, could be instrumental in assessing the quality of care delivered to patients with IBD. The selected quality measures of the framework noted less anemia in the population than previously reported, provided information about hospitalization rates and the few surgical procedures reported, and noted good access to the clinic. CONCLUSION: The applied local quality framework was feasible and useful for assessing the quality of care delivered to IBD patients in a local setting.

Quality control measures for lowering the seroconversion rate of hemodialysis patients with hepatitis B or C virus

BACKGROUND: Hemodialysis (HD) patients are at high risk of infection by hepatitis B virus (HBV) or hepatitis C virus (HCV). The present study was designed to determine the impact of quality control measures on the prevention of transmission of blood-borne viruses. METHODS: A total of 6182 adult maintenance HD patients from all HD units in Zhejiang Province were recruited on January 1, 2007. The baseline demographic and clinical characteristics were recorded and all patients were followed up until death or survival at 4 years later. The Quality Control Standards of Hemodialysis were gradually implemented in HD units. The HBV or HCV seroconversion rates of the recruited patients were calculated and compared every year during the observation period. RESULTS: The prevalence of HBV was 8.3% at the beginning of the study, and 6.6% for HCV. With the implementation of the HD quality control measures, the HBV seroconversion rate tended to decrease year by year (χ 2 =6.620, P=0.085), and the HCV seroconversion rate decreased significantly (χ 2 =10.41, P=0.015). Compared with the data in 2007, the HBV seroconversion rate (χ 2 =4.204, P=0.040, relative risk ratio 0.393, 95% CI 0.156-0.991) and the HCV seroconversion rate (χ 2 =7.373, P=0.007, relative risk ratio 0.386, 95% CI 0.189-0.787) decreased significantly in 2010. CONCLUSION: Quality control measures for HD decreased the seroconversion rates of HBV or HCV in HD patients, showing that updated quality control measures reduce the risk for transmission of blood-borne viruses in the HD population.

Exploring the Sample Quality Using Rough Sets Theory for the Supervised Classification of Remotely Sensed Imagery

In the supervised classification process of remotely sensed imagery, the quantity of samples is one of the important factors affecting the accuracy of the image classification as well as the keys used to evaluate the image classification. In general, the samples are acquired on the basis of prior knowledge, experience and higher resolution images. With the same size of samples and the same sampling model, several sets of training sample data can be obtained. In such sets, which set reflects perfect spectral characteristics and ensure the accuracy of the classification can be known only after the accuracy of the classification has been assessed. So, before classification, it would be a meaningful research to measure and assess the quality of samples for guiding and optimizing the consequent classification process. Then, based on the rough set, a new measuring index for the sample quality is proposed. The experiment data is the Landsat TM imagery of the Chinese Yellow River Delta on August 8th, 1999. The experiment compares the Bhattacharrya distance matrices and purity index zl and △x based on rough set theory of 5 sample data and also analyzes its effect on sample quality.

A Software Quality Evaluation System: JT SQE

JT SQE system is a software quality and measurement system. Its design was based on the Chinese national standards of software product evaluation and quality characteristics. The JT SQE system consists of two parts. One is the model for software quality measurement, which is of hierarchical structure. The other is the process of requirements definition, measurement and rating. The system is a feasible model for software quality evaluation and measurement, and it has the advantage of a friendly user interface, simple operation, ease of revision and maintenance, and expansible measurements.

Efficacy of Alternative Service Quality Measures to Predict Satisfaction and Future Intention

Purpose:This research focuses on comparing various service quality measures including disconfirmation measures(performance-minus-importance and performance-minus-expectation),performance-only measure,and importance-weighted measures(importance-weighted performance-only and importance-weighted disconfirmation)in a festival setting.It also explores the relationship between the constructs of service quality and other variables including visitors’perceptions of overall service quality,overall satisfaction,and future intentions.Reliability,convergent validity,discriminant validity,and predictive validity of five service quality measures are tested and compared.The result shows that the importance-weighted performance-only measure exhibits the highest reliability and validity.

Effective link quality estimation as a means to improved end-to-end packet delivery in high traffic mobile ad hoc networks

Accurate link quality estimation is a fundamental building block in quality aware multi hop routing. In an inherently lossy, unreliable and dynamic medium such as wireless, the task of accurate estimation becomes very challenging. Over the years ETX has been widely used as a reliable link quality estimation metric. However, more recently it has been established that under heavy traffic loads ETX performance gets significantly worse. We examine the ETX metric＇s behavior in detail with respect to the MAC layer and UDP data; and identify the causes of its unreliability. Motivated by the observations made in our analysis, we present the design and implementation of our link quality measurement metric xDDR - a variation of ETX. This article extends xDDR to support network mobility. Our experiments show that xDDR substantially outperforms minimum hop count, ETX and HETX in terms of end-to-end packet delivery ratio in static as well as mobile scenarios.

Impact factors and improvement measures of enviroment quality in cleaning operating room

Objective To analyze the factors that impact the environment quality of cleaning operating room and to discuss improvement measurement. Methods Environment bacteria testing results and prevalence of surgical incision infection in cleaning operating room were retro-

Effects of Main Cultivation Factors on Rapeseed Oil Yield

[Objective] This study aimed to analyze the influence of six cultivation fac- tors： sowing date, plant density, nitrogen fertilizer amount, phosphate fertilizer amount, potash fertilizer amount and boron fertilizer amount on seed oil yield of Brassica napus. [Method] Statistical analysis was carried out based on the data from previous studies and our work. [Result] Oil yield shared a negative correlation with sowing date, a parabolic relationship with plant density mostly, parabolic rela- tionships with amount of applied nitrogen fertilizer and amount of applied boron fer- tilizer, straight-line relationships with amount of applied phosphate fertilizer and amount of applied potash fertilizer. The average amount of applied nitrogen fertilizer required to obtain the highest oil yield was 185.18 kg/hm2 for high-oil rape varieties （with oil content above 44.00%）, and under this condition, the average oil yield of low-oil rape varieties （with oil content below 42.00%） was 1 247.84 kg/hm2, while that of high-oil rape varieties was 1 442.60 kg/hm2, which was 15.61% more than the former. The average amount of applied nitrogen fertilizer required to obtain the highest oil yield for lower-oil rape varieties was 286.28 kg/hm2, and under this con- dition, the average oil yield of the low-oil rape varieties was 1 350.57 kg/hm2, while that of the high-oil varieties was 6.81% higher than it. There was a significant neg- ative correlation between rapeseed oil yield and the amount of applied nitrogen fer- tilizer to obtain the highest oil yield （0.980 0）. The optimum amount of applied ni- trogen, phosphate, potash and boron fertilizer were 187.5-195, 187.5-195, 105-120, 135-150 and 15-22.5 kg/hm2 for high-oil B. napus varieties. [Conclusion] This study determined the influence of sowing date, plant density and amount of applied nitro- gen fertilizer on oil yield of B. napus, and proposed an optimum cultivation pattern for high-oil varieties.

Outpatient Experience of Human Caring Scale （OEHC-Scale）： Improvement by Delphi Method

Based on the outpatient interview and literature review, the initial framework of the outpatient experience of human caring scale was formed with 9 dimensions of outpatient process. The research aim was to improve the scale by Delphi method. Sixteen experts in medical management, human caring or medical education were invited to evaluate the importance of the dimensions and items of the scale and provided some expertise via filling out the DeLphi consultation questionnaires twice in the consulting round. In the first round, the recovery rate showing the experts＇ positivity was 80%; the coefficient of reliability （Cr） ascertaining the authority of the evaluation was 0.92; the mean and full mark ratios responding the concentration of the evaluation were 2.88-4.94 and 6.25%-93.75% respectively; the coefficients of variation （CV） and the Kendall＇s W determining the concordance of the evaluation were 5.06%-52.15% and 0.21-0.24 respectively. In the second round, the recovery rate was 93.75%; the Cr was 0.93; the mean was 3.93-4.93; the full mark ratios were 26.67%-93.33%; the Kendall＇s W was 0.14- 0.31, the CV was 5.25%-23.61%. Via the two-round Delphi study, the scale that included 10 dimensions and 61 items has been improved. Ten dimensions are pre-hospital medical service, guidance, registration, waiting, diagnosis ＆ treatment, paying, inspection ＆ assay, medicine receiving, therapy/injection/transfusion and global evaluation. It was concluded that Chinese scholars have paid high attention to human caring and outpatient experience. The experts have given high agreements about the dimensions which were established with Chinese outpatient process. The dimensions are different from the similar researches about outpatient experience study. In the future, it is necessary to survey the outpatients to test the construct validity, internal consistency reliability and others of the scale to improve the scale.

A RNN-based objective video quality measurement

Technology used to automatically assess video quality plays a significant role in video processing areas. Because of the complexity of video media, there are great limitations to assess video quality with only one factor. We propose a new method using artificial random neural networks （RNNs） with motion evaluation as an estimation of perceived visual distortion. The results are obtained through a nonlinear fitting procedure and well correlated with human perception. Compared with other methods, the proposed method performs more adaptable and accurate predictions.

Applying Force-Directed Placer to Wafer Scale Placement

A placement algorithm for discretionary wiring WSI system, WFDP, is proposed in this paper. WFDP employes force-directed placement algorithm. First the relative locations of macro circuit component are determined. In the phase of determining the real location of the circuit component, it avoids the problem of determining the real location of arbitrary component by employing divide-conquer strategy and removing the hierarchical division. Its computation is much more simpler than other homologous algorithm. A simple model used to estimate the quality of placement is also proposed. Although the WFDP is aimed at WSI, it can also be used in the placement of other redundancy-oriented device or system such as RVLSI, etc.

Geotechnical investigations and remediation design for failure of tunnel portal section： a case study in northern Turkey

Mass movements are very common problems in the eastern Black Sea region of Turkey due to its climate conditions, geological, and geomorphological characteristics. High slope angle, weathering, dense rainfalls, and anthropogenic impacts are generally reported as the most important triggering factors in the region. Following the portal slope excavations in the entrance section of Cankurtaran tunnel, located in the region, where the highly weathered andesitic tuff crops out, a circular toe failure occurred. The main target of the present study is to investigate the causes and occurrence mechanism of this failure and to determine the feasible remedial measures against it using finite element method(FEM) in four stages. These stages are slope stability analyses for pre-and postexcavation cases, and remediation design assessments for slope and tunnel. The results of the FEM-SSR analyses indicated that the insufficient initial support design and weathering of the andesitic tuffs are the main factors that caused the portal failure. After installing a rock retaining wall with jet grout columns and reinforced slope benching applications, the factor of safety increased from 0.83 to 2.80. In addition toslope stability evaluation, the Rock Mass Rating(RMR), Rock Mass Quality(Q) and New Austrian Tunneling Method(NATM) systems were also utilized as empirical methods to characterize the tunnel ground and to determine the tunnel support design. The performance of the suggested empirical support design, induced stress distributions and deformations were analyzed by means of numerical modelling. Finally, it was concluded that the recommended stabilization technique was essential for the dynamic long-term stability and prevents the effects of failure. Additionally, the FEM method gives useful and reasonably reliable results in evaluating the stability of cut slopes and tunnels excavated both in continuous and discontinuous rock masses.

Quality measure of color images based on properties ofvision psychology and color distortion in MPEG-21

In this article, a new way to evaluate the quality of color images is proposed, in which the properties of human vision psychology, objective fidelity, edge information, and color distortion will be combined through utilizing 3-D matrix transform. There exists color redundancy and structural similarity between three different frames of a color image, the definition of vision properties will be measured by 3-D submatrix integration transform （SIT）, in which three color components are integrated into one model and color redundancy can be exploited fully. The simulation results show that the measure index is very effective and objective in accord with vision properties.

Research on uncertainty in measurement assisted alignment in aircraft assembly

Operations in assembling and joining large size aircraft components are changed to novel digital and flexible ways by digital measurement assisted alignment.Positions and orientations（P＆O）of aligned components are critical characters which assure geometrical positions and relationships of those components.Therefore,evaluating the P＆O of a component is considered necessary and critical for ensuring accuracy in aircraft assembly.Uncertainty of position and orientation（U-P＆O）,as a part of the evaluating result of P＆O,needs to be given for ensuring the integrity and credibility of the result;furthermore,U-P＆O is necessary for error tracing and quality evaluating of measurement assisted aircraft assembly.However,current research mainly focuses on the process integration of measurement with assembly,and usually ignores the uncertainty of measured result and its influence on quality evaluation.This paper focuses on the expression,analysis,and application of U-P＆O in measurement assisted alignment.The geometrical and algebraical connotations of U-P＆O are presented.Then,an analytical algorithm for evaluating the multi-dimensional U-P＆O is given,and the effect factors and characteristics of U-P＆O are discussed.Finally,U-P＆O is used to evaluate alignment in aircraft assembly for quality evaluating and improving.Cases are introduced with the methodology.

The ClasSi coefficient for the evaluation of ranking quality in the presence of class similarities

Evaluation measures play an important role in the design of new approaches, and often quality is measured by assessing the relevance of the obtained result set. While many evaluation measures based on precision/recall are based on a binary relevance model, ranking correlation coefficients are better suited for multi-class problems. State-of-the-art rank- ing correlation coefficients like Kendall＇s T and Spearman＇s p do not allow the user to specify similarities between differ- ing object classes and thus treat the transposition of objects from similar classes the same way as that of objects from dissimilar classes. We propose ClasSi, a new ranking corre- lation coefficient which deals with class label rankings and employs a class distance function to model the similarities between the classes. We also introduce a graphical representation of ClasSi which describes how the correlation evolves throughout the ranking.

Measuring quality of life:A system of indicators

In this day and age,improving quality of life(QOL)remains a necessary prerequisite for social progress and the central goal of state policy in many countries worldwide,regardless of their economic development.The aim of this work is to propose a system of indicators able to describe the QOL of the population to the fullest extent possible.The research methodology includes an analysis of modern approaches to explaining the QOL concept and describing its main measurement criteria,as well as a matrix comparison of the fundamental characteristics of well-being.These methods’application and the subsequently obtained results allow developing the model for the QOL measurement.The system of indicators proposed within this model implies the consideration of both objective and subjective indicators distributed into two blocks for convenience:the Accepted Living Standard(material and environmental indicators)and the Quality of Life Opportunities(individual,cultural,and social indicators).The QOL level is determined by the balance or imbalance between the mean values of these blocks.In such a manner,the study advocates that the modern QOL measurement should consider both objective well-being indicators,collected from the reports of the analysed country’s national statistics service,and subjective indicators characterising the citizens’perceptions of well-being at the individual level.

A Review-Based Reputation Evaluation Approach for Web Services

Web services are commonly perceived as an environment of both offering opportunities and threats. In this environment, one way to minimize threats is to use reputation evaluation, which can be computed, for example, through transaction feedback. However, the current feedback-based approach is inaccurate and ineffective because of its inner limitations （e.g., feedback quality problem）. As the main source of feedback, the qualities of existing on-line reviews are often varied greatly from low to high, the main reasons include： （1） they have no standard expression formats, （2） dishonest comments may exist among these reviews due to malicious attacking. Up to present, the quality problem of review has not been well solved, which greatly degrades their importance on service reputation evaluation. Therefore, we firstly present a novel evaluation approach for review quality in terms of multiple metrics. Then, we make a further improvement in service reputation evaluation based on those filtered reviews. Experimental results show the effectiveness and efficiency of our proposed approach compared with the naive feedback-based approaches.