Objective Quality Measures Research Articles

Citizens’ satisfaction with public service: A question of quality and expectations?

Satisfaction surveys are increasingly used to inform citizens and decision makers about the quality of public services. This use of satisfaction surveys demands a close relationship between citizens’ satisfaction and the actual quality of the service. Research is mixed on this point, which may have large implications for the use of citizen satisfaction surveys. In this study, I investigate two aspects of the relationship between quality and satisfaction: Does an objective measure of service quality and the citizens’ expectations to the public service affect the citizens’ satisfaction levels? This question is investigated using satisfaction data from schools in the City of Aarhus from 2011 and 2013 as well as data from the national tests. The results show that both the objective measure of quality and citizens’ expectations affect satisfaction with Danish schools.

Evaluation of the Quality of Music Signals Limited by the Frequency Band

In this paper, the results of the musical signals quality assessment, with the use of objective and subjective measures, are presented. The topics covered in this paper are relevant because the growing needs of users of communication lines leading to the gradual increasing demands for bandwidth that is given to the signals. Nowadays, frequency band 300-3400 Hz (Narrow Band) in analog and mobile telephony is used. However, with the development of mobile technologies and network communications, it becomes possible to expand the bandwidth to WideBand (50-7000 Hz), Super-WideBand (50-14000 Hz) and even to Full-Band (20-20000 Hz). Such an extension of the frequency band can be explained by the desire to transmit musical signals on communication channels in a qualitative way. On the other hand, the average person may not notice the difference between two complex musical works, the spectrum of one of which extends to 20 kHz, and for another is limited to 14 kHz or even 7 kHz. Subjective music signals quality assessment was carried out by 23 students with an average age of 22 years, without hearing impairments. For objective evaluation, 4 quality measures were used, including segment signal-to-noise ratio, log-spectral distortions, bark-spectral distortions, as well as "perceptual evaluation of audio quality" measure specifically designed to evaluate the quality of music signals. The last measure is of particular interest, since the algorithm of its calculation takes into account the features of the human auditory system. The validity of the results of previous studies is confirmed, where it was stated that the frequency band of 12-14 kHz is sufficient to ensure that the musical signal is not different from the reference signal by ear. However, it should be borne in mind that the indicated result is true on average, so it is not excluded that individual listeners will assume that such a band is not wide enough for the quality reproduction of musical signals. In view of this, the results obtained in this article should be expanded, in the future, by the law of the distribution of the bandwidth limits. The examples of the "segmental signal-to-noise ratio" and “logarithmic spectral distortion” indicators demonstrated the need to take into account the peculiarities inherent in certain objective quality measures, as well as the need to provide a sufficiently large statistical volume of various musical material to obtain reliable estimates of the quality of musical signals. In particular, when using the measure "segmental signal-to-noise ratio," it is advisable to increase the sampling rate by 2-4 times, using the interpolation of the compared signals. Correspondence maps for subjective and objective measures of quality are constructed, which allows calibrating of objective estimation systems of musical signals quality. In contrast to the correlation coefficient, the use of correspondence maps suggests the existence of a nonlinear relationship between subjective and objective estimates, which contributes to improving the accuracy of the evaluation.Ref. 13, fig. 3, tabl. 2.

Influence of gender and age on the Dysphonia Severity Index: A normative study in a Shanghainese population

ABSTRACTDysphonia Severity Index (DSI) is an objective multi-parametric measurement of voice quality, which has been widely used in different countries. Studies indicate that DSI may be influenced by vocal pathology, age and geographical factors, whereas gender does not significantly affect DSI. The purpose of this study was to investigate the effects of gender and age on the DSI and related parameters in a Shanghainese population. The present study measured the DSI and the parameters maximum phonation time (MPT), highest fundamental frequency (HF0), lowest intensity (LI) and Jitter in 187 Shanghainese subjects, including 106 young adults aged 18–23 years (52 males and 54 females) and 81 children aged 7–9 years (44 boys and 37 girls). Two-way analysis of variance indicated that HF0 was significantly higher in female subjects than in male subjects, in both young adults and children. Gender was not significantly associated with MPT, LI, jitter or DSI. With regard to age, MPT and DSI were significantly higher in young adults than in children, and HF0 and LI were significantly lower. No significant associations between age and jitter were detected. In terms of clinic significance, the results of this study may contribute to the establishment of a normal reference range for Shanghainese DSI values, and the influence of gender and age on DSI and its separate components.

Quality control for engineers

In 2011 ‘Quality Control Measurements for digital X-ray detectors’ was published by Marshall, Mackenzie and Honey. These outlined a series of objective measurements that could be done in a short period of time and with limited equipment that would pick up most foreseeable issues with image quality. Obtaining these images could be done by service engineers on routine service visits thereby tripling the frequency with which certain measurements are taken (potentially reducing the number of patients imaged on equipment that has failed a QC test). A program written in Matlab for engineers will be presented which analyses; uniformity, SNR, STP curve, dark noise, image lag (ghosting), MTF, NPS and DQE. Initial results compared to manufacturer specifications for both mammography and conventional DR imaging detectors will be presented. Objective image quality measurements benefit from highly reproducible and not operator dependent, which will hopefully increase confidence in the validity of these reports. The algorithms used in the program and potential collaboration will be discussed as well as pitfalls- particularly around NPS measurements. In 2011 ‘Quality Control Measurements for digital X-ray detectors’ was published by Marshall, Mackenzie and Honey. These outlined a series of objective measurements that could be done in a short period of time and with limited equipment that would pick up most foreseeable issues with image quality. Obtaining these images could be done by service engineers on routine service visits thereby tripling the frequency with which certain measurements are taken (potentially reducing the number of patients imaged on equipment that has failed a QC test). A program written in Matlab for engineers will be presented which analyses; uniformity, SNR, STP curve, dark noise, image lag (ghosting), MTF, NPS and DQE. Initial results compared to manufacturer specifications for both mammography and conventional DR imaging detectors will be presented. Objective image quality measurements benefit from highly reproducible and not operator dependent, which will hopefully increase confidence in the validity of these reports. The algorithms used in the program and potential collaboration will be discussed as well as pitfalls- particularly around NPS measurements.

Infrared and Visible Images Fusion with Multi-visual Cues

Image fusion is an important technique which combines the original information from multiple input images into a single composite image. The fused images will be more beneficial to human visual perception or further computer processing tasks than any individual input. Most of the traditional infrared and visible fusion approaches perform the fusion on the assumption that the original information is measured by local saliency features such as contrast or gradient. There is little consideration of the “interesting” or “useful” information in global. In this paper, an infrared and visible image fusion method is proposed by considering the final aim of image fusion, the human visual perception and further image processing tasks. The fusion is implemented under the non-subsampled contourlet transform based image fusion framework. The low frequency sub-band coefficients which represent the intensity of the scene are fused with the weight map which is constructed by considering both visual saliency uniqueness and task-oriented objectness, and refined by spatial consistency with guide filter. The new fusion strategy ensures that the objects being “interesting” or “useful” are preserved in the fused image. Sixteen pairs of infrared and visual images are used to test the validation of the proposed method. The experimental results show obvious improvement of the proposed method in terms of both objective and subjective quality measurements corresponding to other methods.

Adequate Sleep in Adolescents Reduces Obesity and Improves Cardiometabolic Health

In a cross-sectional study, researchers used objective measurements of sleep characteristics and quality to evaluate their effect on cardiometabolic

Objective HDR image quality assessment

Although there is a lot of literature about generating HDR images, very limited research has been conducted on the issue of HDR image quality based on people’s feeling and preferences. The goal of this paper is to identify an objective quality measurement of an HDR image. The key features of HDR images that affect people’s preferences are uncovered through a survey in which testers judge different sample images of different scenes. The experimental results show that the proposed quality measurement for HDR images generates scores consistent with the true feelings of observers.

Assessing the Validity of Consumer Ratings for Higher Education: Evidence from a New Survey

This analysis assesses the validity of using consumer surveys to measure the quality of colleges using new survey data from the Strada‐Gallup Education Consumer Survey. I develop an individual consumer rating based on responses to 14 items related to the quality of education and implement two validity tests: Do higher ratings predict higher welfare, and do they correspond to objective quality measures? I conclude that they do. Indeed, the mean ratings of at least 20 other alumni provide a better prediction of individual satisfaction than popular college rankings from media sources. Consumers rate their experiences higher after attending not‐for‐profit colleges that generate better economic opportunities, enroll students with higher test scores, employ well‐paid faculty, and graduate a higher percentage of students who eventually earn doctorates. I conclude that survey‐based consumer ratings of postsecondary institutions can provide valid and reliable quality comparisons.

Noise reduction algorithm with the soft thresholding based on the Shannon entropy and bone-conduction speech cross- correlation bands.

BACKGROUND: The conventional methods of speech enhancement, noise reduction, and voice activity detection are based on the suppression of noise or non-speech components of the target air-conduction signals. However, air-conduced speech is hard to differentiate from babble or white noise signals.OBJECTIVE: To overcome this problem, the proposed algorithm uses the bone-conduction speech signals and soft thresholding based on the Shannon entropy principle and cross-correlation of air- and bone-conduction signals.METHODS: A new algorithm for speech detection and noise reduction is proposed, which makes use of the Shannon entropy principle and cross-correlation with the bone-conduction speech signals to threshold the wavelet packet coefficients of the noisy speech.RESULTS: The proposed method can be get efficient result by objective quality measure that are PESQ, RMSE, Correlation, SNR.CONCLUSION: Each threshold is generated by the entropy and cross-correlation approaches in the decomposed bands using the wavelet packet decomposition. As a result, the noise is reduced by the proposed method using the MATLAB simulation. To verify the method feasibility, we compared the air- and bone-conduction speech signals and their spectra by the proposed method. As a result, high performance of the proposed method is confirmed, which makes it quite instrumental to future applications in communication devices, noisy environment, construction, and military operations.

Development of an objective measure of quality and commercial value of Japanese-styled green tea (Camellia L. sinensis): the Quality Index Tool.

A novel approach to evaluate the commercial value of green tea products is explored in this paper. The green tea Quality Index Tool (QI-Tool) is based on high performance liquid chromatography (HPLC), capable of identifying and understanding the constituents that are important to create superior consumer and commercially valuable green tea beverages in the Japanese-style. This tool will allow producers to better identify a product's potential value within the various levels of green tea retail quality structure. Via the quantification of theanine, caffeine and the catechins: epicatechin (EC), epicatechin gallate (ECG), epigallocatchin (EGC), epigallocatechin gallate (EGCG) and gallocatechin gallate (GCG) within a green tea beverage, the QI-Tool provides categorisation of a product against the green tea market retail competitive set. This allows a better understanding of the product's potential commercial value, as well as a comparison to other products within that market category. The QI-Tool is an alternative and promising method for objectively evaluating commercial value of green tea products using HPLC analysis.

A model for predicting emergency physician opinion of electrocardiogram tracing data quality

BackgroundLimited work has established an objective measure of ECG quality that correlates with physician opinion of the study. We seek to establish a threshold of acceptable ECG data quality for the purpose of ruling out STEMI derived from emergency physician opinion. MethodsA panel of three emergency physicians rated 240 12-Lead ECGs as being acceptable or unacceptable data quality. Each lead of the ECG had the following measurements recorded: baseline wander, QRS signal amplitude, and artifact amplitude. A lasso regression technique was used to create the model. ResultsThe area under the curve for the model using all 36 elements is 1.0, indicating a perfect fit. A simplified model using 22 terms has an area under the curve of 0.994. ConclusionsThis study demonstrated that emergency physician opinion of ECG quality for the purpose of ruling out STEMI can be predicted through a regression model.

Fast and robust homography estimation method with algebraic outlier rejection

To solve the homography estimation problem containing outliers and noise, a fast, robust, and accurate method is proposed. In this method, the outliers are rejected based on the differing characteristics of algebraic errors between outliers and inliers, and the homography is estimated by minimising the residual vector. The advantage of this method is in integrating the outlier rejection into the estimation pipeline. The computational complexity of the proposed method is not increased, and the random sample consensus algorithm is not needed to extract the inliers, as was previously necessary. Since the outlier rejection process is based on an algebraic criterion without computing the re-projection error at each step, the speed of the proposed method is improved. Several simulations based on synthetic and real images illustrate the performance of the proposed method in terms of subjective visual quality, objective quality measurement, and computational time. The experimental results demonstrate that the proposed method achieves accurate, efficient and robust homography estimation under different image transformation degrees and different outlier ratios.

Adaptive Partition-Cluster-Based Median Filter for Random-Valued Impulse Noise Removal

As the most popular nonlinear denoise technique, the median filter has attracted significant attention in recent years. In this paper, a novel adaptive median filter is presented to remove random-valued impulse noise in images, named Adaptive Partition-Cluster-Based Median (APCM) Filter. Based on the partition cluster idea, the noise detector classifies pixels into different groups and identifies the noisy pixels in different regions adaptively without iterations. According to the results of noise detection, an improved adaptive decision-based filter is presented to restore the pixels which are corrupted by random-valued impulse noise. The proposed filter technique is open to any impulse noise. Extensive simulation results demonstrate that the proposed method substantially outperforms other state-of-the-arts impulse noise filter techniques both visually and in terms of objective quality measures. Furthermore, the proposed method is much friendly to the hardware parallel implementation of image processing because of its low computation complexity and simple realizable structure.

Abstract P322: The Relationship Between Neighborhood Food Environment and Adiposity Measures: Data From the Dallas Heart Study

Background: Existing research has established a link between dietary intake and adiposity measures, including body mass index (BMI) and waist circumference (WC). However, less is known about the relationship between objective food environment quality measures and adiposity [BMI and WC], particularly in diverse populations. Methods: Using cross-sectional data from the 2007-2009 Dallas Heart Study multi-ethnic cohort, we examined the relationship between local food environment quality and adiposity. We measured individuals’ census tract-level food environment quality using the CDC’s Modified Retail Food Environment Index (mRFEI), a ratio of healthy to unhealthy food stores within a ½ mile radius of each census tract (higher mRFEI=more healthy food access). We characterized BMI and WC as continuous measures. Using linear regression, we investigated the relationship between mRFEI and BMI/WC adjusting for confounders [age, gender, race/ethnicity, income, education, smoking status, and neighborhood deprivation index (NDI)]. Models were stratified by NDI to identify if these relationships were moderated by neighborhood deprivation. Results: The study population (n=1835) was 58% non-Hispanic blacks, 27% non-Hispanic whites, and 15% Hispanics. The mRFEI ranged from 0 to 50 across census tracts. In the fully adjusted model, higher mRFEI was associated with higher BMI (β=0.06 p=0.01), but not WC (β=0.09 p=0.13). When stratified by NDI, higher mRFEI was associated with greater BMI and WC in low deprivation areas, but not in medium or high deprivation areas (Figure). Conclusions: Better neighborhood food environment quality was paradoxically associated with higher adiposity in low NDI areas among a diverse population in Dallas County, Texas. Our findings contribute to growing literature around aggregate measures of food environment quality, highlighting potential limitations of the mRFEI in characterizing the impact of the spatial distribution of healthy food outlets on adiposity in lower resource environments.

Multi-Exposure Image Fusion by Optimizing A Structural Similarity Index

We propose a multi-exposure image fusion (MEF) algorithm by optimizing a novel objective quality measure, namely the color MEF structural similarity (MEF-SSIM $_c$ ) index. The design philosophy we introduce here is substantially different from existing ones. Instead of pre-defining a systematic computational structure for MEF ( e.g. , multiresolution transformation and transform domain fusion followed by image reconstruction), we directly operate in the space of all images, searching for the image that optimizes MEF-SSIM $_c$ . Specifically, we first construct the MEF-SSIM $_c$ index by improving upon and expanding the application scope of the existing MEF-SSIM algorithm. We then describe a gradient ascent-based algorithm, which starts from any initial point in the space of all possible images and iteratively moves towards the direction that improves MEF-SSIM $_c$ until convergence. Numerical and subjective experiments demonstrate that the proposed algorithm consistently produces better quality fused images both visually and in terms of MEF-SSIM $_c$ . The final high quality fused image appears to have little dependence on the initial image. The proposed optimization framework is readily extensible to construct better MEF algorithms when better objective quality models for MEF are available.

A Comparison of Various Data Reduction Procedures in a Multiple Sclerosis Sleep Study

Clinical studies often deal with datasets with numerous variables. As a result of the similarities between the variables, we frequently observe the presence of multicollinearity in the data. This study aimed to apply different data reduction strategies to sleep study variables in multiple sclerosis (MS) patients. The main objective was to use various data reduction strategies to explain a subjective measure of sleep quality (Pittsburgh Sleep Quality Index: PSQI) by the objective measures of sleep quality obtained during complete in-laboratory overnight polysomnography. Overall, we found that few objective measures of sleep quality were important in explaining the subjective PSQI, based on the results of various well-accepted statistical methods. Total sleep time was found to be the most important feature of objective sleep quality for explaining subjective sleep quality among all other investigated objective sleep quality variables in most of the approaches investigated in this study. The LASSO method for estimation worked best in terms of interpretability among all the approaches considered.

Heavily Calcified Coronary Arteries: Advanced Calcium Subtraction Improves Luminal Visualization and Diagnostic Confidence in Dual-Energy Coronary Computed Tomography Angiography.

The aim of this study was to evaluate a prototype dual-energy computed tomography calcium subtraction algorithm and its impact on luminal visualization in patients with heavily calcified coronary arteries. Twenty-nine patients (62% male; mean age, 64 ± 7 years) who had undergone dual-energy coronary computed tomography angiography were retrospectively included in this institutional review board-approved, Health Insurance Portability and Accountability Act-compliant study. Linearly blended (M_0.6) and calcium-subtracted images were reconstructed. Two independent observers assessed luminal visualization of the coronary arteries in a segment-based analysis, subjective image quality, and diagnostic confidence using 5-point Likert scales. Contrast-to-noise ratios for both data sets were calculated. Wilcoxon testing and Cohen's κ were used for statistical comparisons. Calcium-subtracted image series showed improved lumen visualization of the coronary arteries (P = 0.008), with excellent interreader agreement (mean score, 3.3; κ = 0.82), compared with M_0.6 series (mean score, 2.9; κ = 0.77). The calcium subtraction algorithm improved diagnostic confidence compared with the M_0.6 reconstructions (mean scores, 4.0 and 3.1, respectively; all P ≤ 0.002). The image quality analysis showed no significant differences between calcium-subtracted and M_0.6 data sets (subjectively: mean scores, 4.1 and 4.2, respectively, P = 0.442; objectively: mean contrast-to-noise ratio, 37.0 and 38.2, respectively, P = 0.733). A prototype algorithm for calcium subtraction improves coronary lumen visualization and diagnostic confidence in patients with heavy coronary calcifications without differences in conventional subjective and objective measures of image quality.

Analiza performansi objektivnih mera procene kvaliteta slika i videa sa potpunim referenciranjem

This paper presents the performance evaluation of image and video quality assessment metrics on two publicly available datasets with subjective quality ratings. In addition to the performance analysis at the global level - at the level of complete datasets, the paper presents the objective measures performance evaluation on subsets of signals inside them. The image dataset contains five subsets created by using different types of JPEG compression, while the video dataset contains six subsets of sequences - four created by compression of original sequences, and two subsets are with video signal transmission characteristic degradations. To determine the success of objective measures, i.e. comparison of subjective and objective quality scores, there were used measures accepted by the International Telecommunication Union - ITU (linear correlation coefficient, rank-order correlation coefficient, mean absolute error, root mean squared error and outlier ratio). It was shown that objective quality measures can reach a high level of agreement with the results of subjective tests on subsets of datasets. Objective measures performances depend on the type of degradation which significantly affects the performance at the complete dataset level. The difference in performances is more pronounced on video sequences due to considerable visual differences in sequences created by using compression, packet losses and additive Gaussian noise. Therefore, we can say that a universal objective measure, i.e. measure that is useful for different types of signal degradation, for different degradation levels, and for different applications currently does not exist.

Comparison of 3 Knee-Specific Quality-of-Life Instruments for Patients With Meniscal Tears.

Background:Meniscal tears are a common cause of knee pain and disability. The objective measurement of the health-related quality of life of patients with meniscal tears plays a key role in clinical evaluation and therapeutic decision making. Several evaluation tools have been used to measure the effects of meniscal tears on knee function and quality of life. However, most of these tools are nonspecific for meniscal pathology.Purpose/Hypothesis:The purpose of the present study was to compare the capability of 3 commonly used knee assessment tools to measure the impact of meniscal tears on knee function and quality of life: the Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC), the Knee injury and Osteoarthritis Outcome Score (KOOS), and the Western Ontario Meniscal Evaluation Tool (WOMET). Our null hypothesis was that no difference would exist among the 3 assessment tools.Study Design:Cohort study (diagnosis); Level of evidence, 2.Methods:A total of 207 consecutive patients (mean ± SD: age, 52.6 ± 14.3 years) with arthroscopically confirmed meniscal tear were included. Preoperatively, 3 knee function and quality-of-life scores were obtained: KOOS, WOMAC, and WOMET. The relative outcome scores of the questionnaires were compared postoperatively.Results:The sum scores (relative scores) were as follows: 234.2 ± 92.5 (55.7%) for the KOOS, 132.6 ± 54.3 (55.5%) for the WOMAC, and 113 ± 30.8 (71%) for the WOMET. The relative score results for the WOMET were significantly higher than those for the WOMAC and the KOOS (both P < .01), while no significant difference was found between the WOMAC and the KOOS (P = .735).Conclusion:A greater impact on health-related quality of life for patients with meniscal tears can be measured with the WOMET when compared with the WOMAC and the KOOS. Therefore, using the WOMET can be recommended for the evaluation of knee function and quality-of-life impairment of patients with meniscal tears.

Use of a Hands Free, Instantaneous, Closed-Loop Communication Device Improves Perception of Communication and Workflow Integration in an Academic Teaching Hospital: A Pilot Study.

Efficient and effective communication between providers is critical to quality patient care within a hospital system. Hands free communication devices (HFCD) allow instantaneous, closed-loop communication between physicians and other members of a multidisciplinary team, providing a communication advantage over traditional pager systems. HFCD have been shown to decrease emergency room interruptions, improve nursing communication, improve speed of information flow, and eliminate health care waste. We evaluated the integration of an HFCD with an existing alphanumeric paging system on an acute inpatient medicine service. We conducted a prospective, observational, survey-based study over twenty-four weeks in an academic tertiary care center with attending physicians and residents. Our intervention involved the implementation of an HFCD alongside the existing paging system. Fifty-six pre and post surveys evaluated the perception of improvement in communication and the integration of the HFCD into existing workflow. We saw significant improvements in the ability of an HFCD to help physicians communicate thoughts clearly, communicate thoughts effectively, reach team members, reach ancillary staff, and stay informed about patients. Physicians also reported better workflow integration during admissions, rounds, discharge, and teaching sessions. Qualitative data from post surveys demonstrated that the greatest strengths of the HFCD included the ability to reach colleagues and staff quickly, provide instant access to individuals of the care team, and improve overall communication. Integration of an instantaneous, hands free, closed loop communication system alongside the existing pager system can provide improvements in the perceptions of communication and workflow integration in an academic medicine service. Future studies are needed to correlate these subjective findings with objective measures of quality and safety.