Quality Ranking Research Articles

Selection of Handloom Fabrics Based on Thermo-Physiological Characteristics Using Multi - Attributes Decision Making Algorithm

ABSTRACT Dissolution of one component from multi-component yarn by suitable chemical treatment brought a significant change in structure that ultimately enhance the performance in terms of thermo-physiological behavior of fabrics. In this study, attempt has been made to develop a ranking of handloom fabric quality, which can be used for selecting fabrics based on thermo-physiological characteristics like thermal resistance, air permeability, water vapor permeability, compressibility, drying capacity, and bending rigidity. Technique for Order Preference by Similarity to Ideal Solution Method (TOPSIS) and Grey Relational Analysis Method (GRA) has been used for ranking 48 handloom samples (before and after treatment) made up of same warp yarn and different filling (for both machine and hand spun) prepared according to mixture design from different percentages of wool, polyester and poly vinyl alcohol (PVA). Ranking results obtained through TOPSIS and GRA show that after treatment of handloom fabric made up of hand spun yarn having less percentage of wool as a weft can be used in place of treated handloom fabric having machine spun yarn with higher percentage of wool. Results also indicate that dissolution of PVA component improves ranking in both fabrics either having machine spun or hand spun yarns as a weft.

Energy and Emission Quality Ranking of Newly Produced Low-Sulphur Marine Fuels

Abstract The article describes the methodology of engine tests on new types of low-sulphur marine fuels in laboratory conditions in order to conduct a comprehensive assessment of their suitability for powering full-size marine engines. The innovativeness of the proposed solution consists of adapting the laboratory Diesel Engine Test Bed to carry out experimental tests using residual and alternative fuels so that it is possible to imitate the real operating conditions of the ship engine. The main aim of the research program was to assess the energy efficiency of six different low-sulphur marine fuels and their impact on the chemical emissivity of engine exhaust gases and air pollution with toxic and harmful chemical compounds. In order to achieve the research purpose formulated in this way, it was necessary to: (1) equip the constructed laboratory stand with highly specialised measuring equipment and (2) develop a technology for determining diagnostic parameters representing the basis for developing a ranking of the energy and emission quality of the tested marine fuels according to the proposed physical model. The model distinguishes 10 diagnostic parameters that, after normalisation, form two subsets of evaluation parameters - stimulant and destimulant. Determining their values made it possible to estimate a synthetic variable, according to which all the tested fuels were adjusted in the order from the “best” to the “worst”, in accordance with the adopted qualitative criteria of such an assessment. The results of the laboratory tests show that among the considered fuels, i.e., MDO, MGO, RMD 80/L, RMD 80/S, RME 180, and RMG 380 type, the best solution is to use MDO distillate fuel to power full-size marine engines. However, taking into account its high purchase price, a rational alternative decision is to choose RMG 380 type residual fuel, which ranks second in the ranking of the functional quality of the tested marine fuels.

Google pagerank algorithm: using efficient damping factor

A vital feature of modern web search engine is the ability to display relevant and reputable pages near the top of the list of query results. A well-used search engine nowadays is Google search engine, it is the world's most popular search engine, rely on PageRank technology to determine a website's ranking. We put our attention on important benefactions to improving the quality of rankings via the value which is called damping factor, commonly the original suggestion d=0.85 by Brin and Page is the most common choice. In this paper, we suggest a new value which plays an important role to rank web sites accurately, our work focuses on damping factor value which improves the efficiency of PageRank value for each website. Our results show that the suggested value can get greater performance. Finally, we will show satisfactory result without link spam and dangling node applying PageRank algorithm on graphs with over 5000 links.

Quality assessment of colour fundus and fluorescein angiography images using deep learning

Background/aimsImage quality assessment (IQA) is crucial for both reading centres in clinical studies and routine practice, as only adequate quality allows clinicians to correctly identify diseases and treat patients accordingly....

Is the Size of the City Important for the Quality of Urban Life? Comparison of a Small and a Large City

In the recent past, the question of determining the optimal city size in relation to the quality of urban life (QoUL) was raised of city inhabitants. This article has evaluated the correlation of the QoUL index in cities in relation to the number of inhabitants. We also deal with selected variables for which we assume a relationship with QoUL. The authors who calculated the indices of the quality of urban life equated the quality of life with its objective dimension considered as the quality of the place. It turned out that growth in the number of inhabitants of Slovak cities did not correlate with improving quality of life. Our article examined QoUL in two different countries on a scale of 0–10 through questionnaires. The obtained values are a subjective assessment. From a global point of view, one city is small and the other is big. The small city achieved better results in international rankings of quality of life, and it was assumed that this fact would also be reflected in the quantification of the quality of urban life. One hypothesis was that a small city will achieve better urban life quality values than a large city. The paper presents the results of measurement and correlation.

Dealing with textual noise for robust and effective BERT re-ranking

The pre-trained language models (PLMs), such as BERT, have been successfully employed in two-phases ranking pipeline for information retrieval (IR). Meanwhile, recent studies have reported that BERT model is vulnerable to imperceptible textual perturbations on quite a few natural language processing (NLP) tasks. As for IR tasks, current established BERT re-ranker is mainly trained on large-scale and relatively clean dataset, such as MS MARCO, but actually noisy text is more common in real-world scenarios, such as web search. In addition, the impact of within-document textual noises (perturbations) on retrieval effectiveness remains to be investigated, especially on the ranking quality of BERT re-ranker, considering its contextualized nature. To mitigate this gap, we carry out exploratory experiments on the MS MARCO dataset in this work to examine whether BERT re-ranker can still perform well when ranking text with noise. Unfortunately, we observe non-negligible effectiveness degradation of BERT re-ranker over a total of ten different types of synthetic within-document textual noise. Furthermore, to address the effectiveness losses over textual noise, we propose a novel noise-tolerant model, De-Ranker, which is learned by minimizing the distance between the noisy text and its original clean version. Our evaluation on the MS MARCO and TREC 2019–2020 DL datasets demonstrates that De-Ranker can deal with synthetic textual noise more effectively, with 3%–4% performance improvement over vanilla BERT re-ranker. Meanwhile, extensive zero-shot transfer experiments on a total of 18 widely-used IR datasets show that De-Ranker can not only tackle natural noise in real-world text, but also achieve 1.32% improvement on average in terms of cross-domain generalization ability on the BEIR benchmark.

Quality Performance Indicators Evaluation and Ranking by Using TOPSIS with the Interval-Intuitionistic Fuzzy Sets in Project-Oriented Manufacturing Companies

Project-oriented manufacturing companies aim to produce high-quality products according to customer requirements and a minimum rate of complaints. In order to achieve this, performance indicators, especially those related to product quality, must be measured and monitored by managers. This research proposes a fuzzy multi-criteria model for the selection of key performance indicators that are critical to product quality. The uncertainties in the relative importance of decision-makers, performance indicators, and their values are described by sets of natural language words that are modeled by the interval-valued intuitionistic fuzzy numbers. The assessment of the relative importance of the decision-makers and the determination of their weights are based on the inclusion comparison probability between the closeness intuitionistic fuzzy sets. The determination of the weights vector of performance indicators is based on the integration of an interval-value fuzzy weighted geometric operator and the inclusion comparison probability between the closeness intuitionistic fuzzy sets. TOPSIS expanded with interval-valued intuitionistic fuzzy numbers for ranking performance indicators is proposed. The developed model was tested on the real data collected from three manufacturing companies in the Republic of Serbia. Based on the obtained results, the top-ranked performance indicators were marked as critical for product quality and selected as quality key performance indicators.

Man versus machine: intraoperative versus elastography assessment of the quality of the rotator cuff

Introduction: The most common complication of arthroscopic rotator cuff repair is retear, and retear or failure to heal is more common in larger tears in older patients. We hypothesised that the quality of the torn tendon is important in protecting against retear. Surgeons have traditionally assessed the quality of repaired tissue with a four-point Likert scale. Shear Wave Elastography Ultrasound (SWEUS) is a recent technological advancement which can quantify soft tissue stiffness. The aim of this study was to determine how closely a surgeon’s intraoperative rankings of tissue quality correlate to postoperative supraspinatus tendon stiffness as measured by SWEUS.

Deep metric learning with mirror attention and fine triplet loss for fundus image retrieval in ophthalmology

Fundus image retrieval can help ophthalmologists make evidence-based medico-decision by providing similar cases. Its basic task is to learn highly discriminative visual descriptors from image space, in which lesion features are the main differentiating clue. Lesions in fundus images appear small in size, similar in textures, and scatter around vessels, such as microaneurysms and hemorrhages. Hence, although a single small lesion has a saliently visual manifestation, its discriminative information is hard to reserve in the last image descriptors. For fundus images, the optic disc of the left and right eyes are symmetric, and the macular area lies in the central axis from the vertical view. Based on such spatial structure and lesion characteristics, we present a novel deep metric learning framework equipped with mirror attention to enhance the discriminative features of small and scattering lesions and encode them into image descriptors. The mirror attention can give lesions high attention scores by capturing spatial dependency of vertical and horizontal views, especially the relations between lesions and vessels. Based on the mirror attention, we further propose a new fine triplet loss to confine distances of positive pairs by exploiting the learned relevant degrees of positive pairs in a self-supervised manner. The fine triplet loss can help detect the subtle differences of positive pairs to improve the ranking performance of hit items. To demonstrate the effectiveness of improving retrieval performance, we conduct comprehensive experiments on the largest fundus dataset of diabetic retinopathy (DR) detection and achieve the best precision compared to counterparts. The experiments show that our method produces significant performance improvements for fundus image retrieval, especially the ranking quality of DR grades containing microaneurysms and hemorrhages. Our proposed mirror attention can be applied to off-the-shelf backbones and trained efficiently in an end-to-end manner for other medical images to obtain highly discriminative image descriptors.

A machine learning approach to investigate the build-up of surface ozone in Mexico-City

Ground-level ozone is an important pollutant regarding air quality and climate. Mexico City frequently experiences severe ozone episodes due to a combination of strong ozone precursor emissions and its specific topographical environment which critically impacts meteorological conditions. High ozone levels during these episodes cause harmful effects to the public health and the environment. This necessitates ranking air quality and meteorological variables according to their contributions towards the build-up of ozone. In this study, three machine learning models are used to learn a prediction function with hourly data of eight predictors as input and hourly ground-level ozone mixing ratios as output. One-year hourly data of eight predictors collected in Mexico-City from March 2015 to February 2016 is employed to train and test the models. The best model, capturing ozone peak levels with 92% accuracy during 6–18 March 2016, is used to rank the predictors according to their importance in the build-up of ozone applying a shapley additive explanations approach based on the game theory shapley values. This 6–18 March 2016 period encompassed different meteorological and emission conditions and included a severe ozone smog episode from 12 to 17 March 2016. Such ranking of the air quality and meteorological variables is crucial for policy-making decisions regarding the prevention and mitigation of ozone detrimental effects during severe ozone episodes and provides insight into the functional dependency of ozone on its predictors. The proposed approach showcases Mexico City, but its principles can be applied for ozone episodes at any other location.

High-content, arrayed compound screens with rhinovirus, influenza A virus and herpes simplex virus infections

Viruses are genetically and structurally diverse, and outnumber cells by orders of magnitude. They can cause acute and chronic infections, suppress, or exacerbate immunity, or dysregulate survival and growth of cells. To identify chemical agents with pro- or antiviral effects we conducted arrayed high-content image-based multi-cycle infection screens of 1,280 mainly FDA-approved compounds with three human viruses, rhinovirus (RV), influenza A virus (IAV), and herpes simplex virus (HSV) differing in genome organization, composition, presence of an envelope, and tropism. Based on Z’-factors assessing screening quality and Z-scores ranking individual compounds, we identified potent inhibitors and enhancers of infection: the RNA mutagen 5-Azacytidine against RV-A16; the broad-spectrum antimycotic drug Clotrimazole inhibiting IAV-WSN; the chemotherapeutic agent Raltitrexed blocking HSV-1; and Clobetasol enhancing HSV-1. Remarkably, the topical antiseptic compound Aminacrine, which is clinically used against bacterial and fungal agents, inhibited all three viruses. Our data underscore the versatility and potency of image-based, full cycle virus propagation assays in cell-based screenings for antiviral agents.

An econometric approach to aggregating multiple cardiovascular outcomes in German hospitals

ObjectiveDevelopment of an aggregate quality index to evaluate hospital performance in cardiovascular events treatment.MethodsWe applied a two-stage regression approach using an accelerated failure time model based on variance weights to estimate hospital quality over four cardiovascular interventions: elective coronary bypass graft, elective cardiac resynchronization therapy, and emergency treatment for acute myocardial infarction. Mortality and readmissions were used as outcomes. For the estimation we used data from a statutory health insurer in Germany from 2005 to 2016.ResultsThe precision-based weights calculated in the first stage were higher for mortality than for readmissions. In general, teaching hospitals performed better in our ranking of hospital quality compared to non-teaching hospitals, as did private not-for-profit hospitals compared to hospitals with public or private for-profit ownership.DiscussionThe proposed approach is a new method to aggregate single hospital quality outcomes using objective, precision-based weights. Likelihood-based accelerated failure time models make use of existing data more efficiently compared to widely used models relying on dichotomized data. The main advantage of the variance-based weights approach is that the extent to which an indicator contributes to the aggregate index depends on the amount of its variance.

An Attention-Based Interactive Learning-to-Rank Model for Document Retrieval

The core issue of learning-to-rank (LTR) for document retrieval lies in finding an optimal ranking policy to meet the search intent of the user. The majority of proposed LTR approaches treat the ranking as a static process, employing a fixed ranking policy to immediately assign scores to documents. By contrast, ranking is not a static but an interactive process where the user continues interacting with the document retrieval system through information exchange such as search intent (e.g., rating or clicking for the retrieved items). We model the interactive ranking process (IRP), and propose an Attention-Based Interactive LTR model (AIRank) to constitute an intent-aware flexible ranking policy to gratify the user’s need. To enhance the ranking quality, the inherent relations among documents are procured by the self-attention method to contribute to an enriched user intent representation. Furthermore, we mend the policy gradient learning method to train the AIRank in the IRP. Experiments demonstrate the effectiveness of AIRank compared to the state-of-the-art methods in terms of normalized discounted cumulative gain and expected reciprocal rank.

Speech quality assessment with WARP‐Q: From similarity to subsequence dynamic time warp cost

Speech coding has been shown to achieve good speech quality using either waveform matching or parametric reconstruction. For very low bit rate streams, recently developed generative speech models can reconstruct high-quality wideband speech from the bit streams of standard parametric encoders at less than 3 kb/s. Generative codecs produce high-quality speech based on synthesising speech from a DNN and the parametric input. Existing objective speech quality models (e.g., ViSQOL and POLQA) cannot be used to accurately evaluate the quality of coded speech from generative models as they penalise based on signal differences not apparent in subjective listening test results. This paper presents WARP-Q, a full-reference objective speech quality metric that uses a dynamic time warping cost for MFCC representations of the signals. It is robust to low perceptual signal changes introduced by low bit rate neural vocoders. An evaluation using waveform matching, parametric, and generative neural vocoder-based codecs as well as channel and environmental noise shows that WARP-Q has better correlation and codec quality ranking for novel codecs compared to traditional metrics as well as the versatility of capturing other types of degradations, such as additive noise and transmission channel degradations.

Formation of the quality of life index in Western and Eastern Europe within the sociological context

The complexity of determining the quality of life and the optimal selection of criteria for assessing this category is one of the challenges in public administration. The purpose of the study is to critically analyse the characteristics of the quality of life ranking in Western and Eastern Europe and modern approaches to its determination and monitoring. By analysing theoretical materials and studies, the article describes the history of the formation of the concept of quality of life, the development of methods for its assessment, and highlights the features of modern tools for assessing the quality of life. The article examines the main international and Ukrainian approaches to such monitoring; using the methods of comparison and system analysis, the author compares the indicators of Western and Eastern European countries in such sectors as income and purchasing power, life expectancy, access to education and jobs, income equality, safety of the population and environmental conditions. Through this analysis, the author identifies the advantages in the development of Western European countries over the countries of the Eastern European region, concludes that the economic development of countries is uneven and that there is a tendency to reduce imbalances through effective forms and instruments for implementing the development strategies of the European Union. The author identifies the importance of using the experience of the developed EU countries in Ukraine, highlighting the coexistence and interaction of market and state regulation mechanisms of economic development are emphasised, and the focus is on the goals of sustainable development, which is based primarily on dignified labour, creation of well-paid jobs, and efficient use of resources in consumption and production for economic growth. Equally important are the processes of resolving certain constraints for each country, such as reducing income inequality, access to healthcare, high levels of education, and reducing the number of people suffering from harmful addictions. The practical significance of the study lies in the possibility of applying the findings in the preparation of lecture materials for students of economic and historical specialities, future specialists in political science, etc.

A Comparison of the Content and Consistency of Methodological Quality and Transferability Checklists for Reviewing Model-Based Economic Evaluations.

The aim of this study was to examine whether and how the content of six checklists (Caro, Consensus on Health Economic Criteria [CHEC]-Extended, European Network of Health Economic Databases [EURONHEED], National Institute for Health and Care Excellence [NICE], Philips, Welte) affect the consistency in findings on methodological quality and transferability, using 10 model-based economic evaluations of genetic-guided pharmacotherapy for venous thromboembolism. Each checklist was categorised by domain (structure, data, consistency, etc.) and type of assessment (presence vs. appropriateness) and was applied to each study by two independent reviewers who agreed on ratings via consensus, and discussion with a third reviewer when necessary. Methodological quality scores and rankings were examined using Spearman correlation tests, with subgroup analyses for domains and types of assessment. We compared overall ratings of transferability qualitatively, including how content may affect what is considered 'transferable'. The checklists had similar proportions of items judging presence and appropriateness, but varying proportions of items across domains. For methodological quality, ranking consistencies were the highest between CHEC-Extended-Philips, Philips-NICE and NICE-Caro, with similar consistencies for domains and type of assessment. For transferability, NICE and Caro identified the same study, which scored high on EURONHEED, as transferable to the UK, while Welte, which considered methodological quality, identified none as transferable. We found that the choice of checklist can affect findings on study quality and decisions about whether study results are transferable, indicating that different checklists may shortlist different sets of studies in formulating policy recommendations, leading to different policy decisions. Our systematic approach for evaluating the content of methodological quality and transferability checklists of economic evaluations can be extended to other checklists.

Assessment on the Urbanization Quality of China’s Main Grain-Producing Areas under the SDGs

The Sustainable Development Goals (SDGs) adopted by the United Nations in 2015 guide the important direction of high-quality urbanization in China’s main grain-producing areas (MGPAs), and improving the quality of urbanization is also crucial to achieve the SDGs. China’s MGPAs not only undertake the task of promoting urbanization but also of ensuring food security. The establishment of an index system based on SDGs can more effectively measure the urbanization quality of MGPAs. For the specific targets of the SDGs, this study established two sets of multidimensional indicator systems, whether including the goals of food and agriculture, and tracked the progress toward improving urbanization quality of China’s MGPAs, including 128 prefecture-level cities, during 2010–2018. We found that the comprehensive urbanization quality and the index of economic efficiency, urbanization level, and environmental quality showed an upward trend with significant regional differences and spatial agglomeration distributions, but the level of agricultural development and urban–rural co-ordination have declined in recent years; the ranking and distribution of urbanization quality, including agricultural development, varied significantly, and the number of cities belonging to the good co-ordination mode decreased as some cities changed to a lower level; and urbanization that does not sacrifice the agricultural capabilities of MGPAs could improve urbanization quality and implement the SDGs.

Ranking the Hotel Website Service Quality according to Customer’s Perception: A Case Study of 4-Star Hotel

ABSTRACT The study aims to analyze and propose hotel website service quality ranking method; identify priority factors in website service quality improvement. The actual illustration of the study is based on collecting data from tourists at 4-star hotels in Vietnam. Using the integrated methodology (the gap-score scale, ratio-score scale, Entropy method), the study has established the website service quality ranking index in the hotel industry. The study results show four factors that directly improve the quality of website quality services include website design, website functionality, interactivity, and information quality. Implications were discussed to improve quality of hotel website services in order to increase customer’s satisfaction.

Are quality assurance and rankings useful tools to measure ‘new’ policy issues in higher education? The practices in Europe and Asia

ABSTRACT In the last years, ‘new’ policy issues, such as sustainability, have emerged, and old ones, such as social inclusion, have resurfaced on the political and public agendas. Higher education institutions (HEIs) are increasingly expected to respond to these ‘new’ challenges. But how are HE systems and HEIs (namely in Europe and Asia) looking at these ‘new’ policy issues and assessing them? This article focuses on what issues are being looked at by two of the most well-known tools or mechanisms used to assess the quality of HE – quality assurance and rankings – and how are these tools dealing with these ‘new’ challenges. This article concludes that the role of the ‘new’ policy issues in the assessment of institutional performance and quality is still very limited. Developing indicators that may be used for accountability purposes or improvement purposes is a major challenge that lies ahead. Facilitating the exchange of ideas, experiences, and knowledge on how to measure performance on the ‘new’ policy issues and on how to use that information in any of the rationale settings seems to be a promising way forward to get the ‘new’ policy issues embedded in quality assurance tools.

The differences in cocoon and silk qualities among sex-related mulberry and silkworm feeding groups.

Sexual dimorphism is seen in many dioecious plant and animal species, which may influence their trophic interactions. The differences in trophic interactions derived from sexual dimorphism in plants may influence herbivorous performance and population dynamics. Both silkworm (Bombyx mori L.) and mulberry (Morus alba L.) usually exhibit sexual dimorphism. However, few studies have been conducted on the effect of sex-related silkworm and mulberry pairings on cocoon and silk qualities, which are crucial in sericulture. Here, we compared the differences in cocoon and silk qualities under four feeding combinations (FS-FL: female silkworm fed with leaves from female mulberry trees; MS-FL: male silkworm fed with leaves from female mulberry trees; FS-ML: female silkworm fed with leaves from male mulberry trees; MS-ML: male silkworm fed with leaves from male mulberry trees). The results showed that silkworms exhibited male-biased herbivory with more male mulberry leaves digested. The FS-ML group had higher silk weight and silk ratio of fresh cocoons than the FS-FL group, and the MS-ML group had lower coarse points than the MS-FL group. Compared with groups FS-ML and FS-FL, both MS-FL and MS-ML had smaller cocoons with longer silk lengths and a higher silk ratio of the fresh cocoons. In addition, the Entropy Weight-TOPSIS method showed the cocoon quality rank as FS-ML > FS-FL > MS-FL > MS-ML, whereas silk quality rank was MS-ML > FS-FL > FS-ML > MS-FL. These results indicate that the quality of cocoon and silk is related to the interaction of silkworm and mulberry at the sex level. Furthermore, female silkworms fed with female and male tree leaves have a higher total yield in cocoon production, while male silkworms fed with male tree leaves produced higher silk quality.