Hybrid Fuzzy Multi-Criteria Analysis for Selecting Discrete Preferable Groundwater Recharge Sites

This study proposes a hybrid fuzzy multi-criteria methodology for the selection of the most preferable site for applying managed aquifer recharge (MAR) systems by utilizing floodwaters. The use of MAR can increase water resources for later water utilization in case of drought. In this multi-criteria problem, seven recharge sites are under consideration, based on nine criteria, aiming to make a final list of their relative ranking. A fuzzy analytic hierarchy process (FAHP) based on the logarithmic fuzzy preference programming (LFFP) method is used to determine the weights of criteria. LFFP is an optimization-based method that produces a priority vector from a fuzzy pairwise comparison matrix. Furthermore, fuzzy inference systems (FIS) based on the Mamdani approach are used to estimate the rating of each alternative with respect to the criterion examined, and then the final evaluation of the alternatives is obtained. A FIS is a fuzzy if–then rule-based system where the experts’ qualitative knowledge is translated into numerical reasoning for each individual criterion. The proposed methodology is applied in the aquifer system of the agricultural plain located to the southeast of the city of Xanthi in the Prefecture of Xanthi, NE Greece.

Development of a Multi-criteria Decision Model for Nigerian Refinery Bottlenecks

Production systems are continually surrounded by bottleneck problems that limit their overall performances. The petroleum industry today faces a lot of challenges which border on production bottlenecks that tend to limit production throughput and hence output. The purpose of this study is to provide a decision support strategy for refinery operators and mangers as well as other stakeholders. The multi-criteria models used were the Analytical Hierarchy Process (AHP) and the Test of Preference by Similarity to Ideal Solution (TOPSIS). A 9-point saaty scale and 10-point linguistic scale questionnaires were used to elicit responses from experts in the refinery. The statistical computations with the Multi-criteria Decision Model were carried out with the aid of (AHP -OS) BPMSG software on nine criteria which are bottleneck variables which impact on refinery operations and the comparison was made by nine decision makers who are refinery experts while TOPSIS was used for alternatives selection. The result of the AHP showed the contributing weights of individual criterion with “Government Interference” ranking first, exerting a weight of 19.84%. The result also generated a normalized total matrix which is approximately one (1), consistency index of 0.09694 and a consistency ratio of 0.06685 which is within acceptable limit and finally from TOPSIS modeling, “Denationalization” with the highest value of 0.7598 was found to be closest to the ideal solution for the optimal refinery performance. This study has developed a multi-criteria decision model for selecting the best alternative for optimal performance based on inputs from experts and this provides a veritable framework that serves as a decision support strategy for policy makers and stakeholders in the operations of the refinery.

Adjusting Trade-Offs in Multi-Criteria Decision-Making Problems

In multi-criteria decision-making (MCDM) methods, allowing trade-offs between the decision criteria may result in inappropriate conclusions. Allowing trade-offs implies that the weaknesses of an alternative in some criteria may be compensated by its strengths in other criteria. While, with some problems, there are no concerns with regard to allowing a full trade-off, in other cases, such a trade-off may not follow the actual decision-making problem. This paper proposes a new approach based on defining an upper and lower expectation level for each decision-making criterion. Indeed, the proposed approach is a framework by which the requirements of a decision-maker are considered in the criteria involved in MCDM problems. That distinction generates two primary and secondary performance matrices. The primary matrix includes the values of the alternatives with respect to the individual criterion up to the upper expectation levels of the decision-maker, while the secondary matrix, which is defined by the amounts above the upper levels and below the lower levels of the decision-maker’s expectations, contains each alternative in all the criteria and, to some extent, can exceed the upper levels of the decision-maker’s expectations. The final result of each alternative is calculated by adding its outcome in the two matrices. The results of a numerical example involving cellphone selection show how controlling the trade-offs could affect the results.

Coda

The coda to Transgression & Redemption considers how the knowledges, methods, and values of the book might contribute to further considerations of the American novel, with immediate emphasis on several canonical masterpieces of the 1930s, including William Faulkner’s Absalom, Absalom! (1936), Zora Neale Hurston’s Their Eyes Were Watching God (1937), and Nathanael West’s The Day of the Locust (1939); how, alternatively, the critical repertoire of this book might contribute to Hollywood scholarship beyond poststructuralist feminist critique, with emphasis split between the erotic-spiritual edginess of individual Criterion-canonized masterpieces (the not happily-ever-after: Casablanca, All About Eve, Blue Velvet) and the luminous achievement of “sexually ever after” in serial Hollywood films, featuring Bogey and Bacall, Katherine Hepburn and one of her men, or Myrna Loy and William Powell; and how, finally, the book’s critical reorientation can reveal the mythopoetic force of American popular music, beginning for illustration’s sake with the two greatest vocalists in that history, Billie Holiday and Frank Sinatra, whose vocalized radiance, entailing bent notes and captured lyric, express obsessively the twin dimensions of incarnate passion, sex and sentiment. Or, as the two of them (sort of Catholics, Marian both) liked to put it, body and soul.

Malnutrition Prevalence according to the GLIM Criteria in Head and Neck Cancer Patients Undergoing Cancer Treatment

Malnutrition is highly prevalent in people with head and neck cancer (HCN) and is associated with poorer outcomes. However, variation in malnutrition diagnostic criteria has made translation of the most effective interventions into practice challenging. This study aimed to determine the prevalence of malnutrition in a HNC population according to the Global Leadership Initiative on Malnutrition (GLIM) criteria and assess inter-rater reliability and predictive validity. A secondary analysis of data available for 188 patients with HNC extracted from two cancer malnutrition point prevalence studies was conducted. A GLIM diagnosis of malnutrition was assigned when one phenotypic and one etiologic criterion were present. Phenotypic criteria were ≥5% unintentional loss of body weight, body mass index (BMI), and subjective evidence of muscle loss. Etiologic criteria were reduced food intake, and presence of metastatic disease as a proxy for inflammation. The prevalence of malnutrition was 22.6% (8.0% moderately malnourished; 13.3% severely malnourished). Inter-rater reliability was classified as excellent for the GLIM criteria overall, as well as for each individual criterion. A GLIM diagnosis of malnutrition was found to be significantly associated with BMI but was not predictive of 30 day hospital readmission. Further large, prospective cohort studies are required in this patient population to further validate the GLIM criteria.

Assessment of health education infographics in Saudi Arabia

Objective: To evaluate the health education infographics posted on Twitter accounts by major health care institutions in Saudi Arabia. Method: Cross-sectional review of health education infographics using a semi-structured evaluation form. The scoring rubric included 10 criteria grouped under 4 main headings: (1) usefulness, (2) legibility, (3) graphics and illustrations and (4) aesthetics. Rated on a scale of 1 to 5, scored items were summed and converted into a percentage. Each infographic was classified as being of high quality (70%–100%), medium quality (40%–69%) or low quality (0%–39%). Results: A total of 297 infographics were evaluated. The most common topics concerned chronic diseases and associated risk factors ( n = 72) and healthy lifestyle ( n = 51). The highest re-tweets (524), likes (605) and replies (226) were received by government organisations. Overall, 249 (83.8%) infographics were categorised as of ‘high quality’, 46 (15.5%) as ‘medium quality’, and 2 (0.7%) as ‘low quality’. The highest proportion (93%) of ‘high-quality’ infographics came from government hospitals. Among individual criterion, drawings (17.2%) made up the highest proportion of the ‘low quality’ category followed by overall design (10.8%) and purpose (10.8%). Light text (covering < 50% of the infographic) showed a significant statistical association with the number of replies ( p = .007), number of likes ( p = .003) and number of retweets ( p = .018). Conclusion: The majority of infographics were rated as being of ‘high quality’. Government institutions were assessed as having better quality infographics than private hospitals. We recommend that social media design specialists and health education specialists collaborate to design clear infographics with better overall design.

Formation of the level of ability of future teachers of geography to the assessment of aesthetic landscapes

The article analyzes the formation of levels of ability of future geography teachers to the assessment of aesthetic landscapes. The relevance of the study of the problem of preparing future geography teachers for the aesthetic assessment of landscapes, as a condition for attracting the younger generation to the cultural heritage of society, is substantiated. Thus, the process of forming the readiness of future teachers of geography to assessment aesthetic landscapes involves taking into account the professional requirements and the set of available intellectual and psychological qualities of the individual necessary for the implementation of aesthetic education of students, the formation of love for their native land, the development of ecological culture. It is noted that on the basis of the analysis of educational achievement levels, criteria have been developed for characterizing the readiness levels of future geography teachers for the assessment of aesthetic landscapes. Each individual criterion may have a system of indicators that are observable and act as characteristic, intensive, qualitative criteria for identifying the criterion. In this regard, the readiness of future geography teachers to assessment aesthetic landscapes involves the formation of content, activity and value components that are closely related since they have a single purpose. Based on the analysis of scientific literary sources and the study of advanced pedagogical experience, it is determined that the essence of the readiness of future geography teachers to assessment aesthetic landscapes as a complex multilevel personal formation that arises on the basis of a combination of the system of specific geographic knowledge acquired, skills and abilities, synergistic geographical thinking, values and establishes a fundamental condition for the successful study of geography, environmental education, aesthetic education of students. The study substantiates such equal readiness of future geography teachers to the assessment of aesthetic landscapes: elemental, reproductive, reconstructive and creative.

Modern Slavery in the Global Supply Chain: An Analysis of Published Preventative Statements and Frameworks to Protect Businesses and Individuals

Modern slavery generates an estimated $150 billion in revenue annually. Derived from the exploited labor 40.3 million victims, this is one of the most profitable illicit industries. Of the estimated 24.9 million slaves institutionalized in forced labor, 16 million are exploited in the private sector. These 16 million are oppressed within corporate supply chains. This paper addresses the need for a common tool and set of criteria governing organizations’ actions. Such a tool and set of criteria are essential in not only combating modern slavery within corporations, but also throughout global supply chain tiers. Application of consistent tools and criteria will move the private sector forward in eradicating modern slavery by ensuring transparent reporting and effective action. The final deliverable consists of recommendations for adoption of publications and individual criterion—adaptable for all supply chain levels—for corporations to use in implementing, expanding, and improving their modern slavery and transparency initiatives.

Hybrid bag of approaches to characterize selection criteria for cohort identification

Objective The 2018 National NLP Clinical Challenge (2018 n2c2) focused on the task of cohort selection for clinical trials, where participating systems were tasked with analyzing longitudinal patient records to determine if the patients met or did not meet any of the 13 selection criteria. This article describes our participation in this shared task. Materials and Methods We followed a hybrid approach combining pattern-based, knowledge-intensive, and feature weighting techniques. After preprocessing the notes using publicly available natural language processing tools, we developed individual criterion-specific components that relied on collecting knowledge resources relevant for these criteria and pattern-based and weighting approaches to identify “met” and “not met” cases. Results As part of the 2018 n2c2 challenge, 3 runs were submitted. The overall micro-averaged F1 on the training set was 0.9444. On the test set, the micro-averaged F1 for the 3 submitted runs were 0.9075, 0.9065, and 0.9056. The best run was placed second in the overall challenge and all 3 runs were statistically similar to the top-ranked system. A reimplemented system achieved the best overall F1 of 0.9111 on the test set. Discussion We highlight the need for a focused resource-intensive effort to address the class imbalance in the cohort selection identification task. Conclusion Our hybrid approach was able to identify all selection criteria with high F1 performance on both training and test sets. Based on our participation in the 2018 n2c2 task, we conclude that there is merit in continuing a focused criterion-specific analysis and developing appropriate knowledge resources to build a quality cohort selection system.

Performance Evaluation of Sustainable Smart Cities in India

Indian cities have seen accelerated economic and social growth, attracting more and more people from all parts of the country. Growth achieved by cities is linked to their ability to address issues related to urbanization and associated social, environmental, and economic issues in a holistic manner, while making the most of future opportunities. In this chapter, using PROMETHEE and GAIA (geometrical analysis for interactive aid) approaches, an attempt is made to evaluate the performances of 20 smart cities in Indian context based on 10 critically important criteria. A GIS (geographic information system) method and an HSV (hue-saturation-value) color coding scheme-based on cartographic principles are also employed to identify the influence of individual criterion on the overall rank of the smart cities. This analysis would help the decision makers to identify the strengths and deficiencies of Indian smart cities with respect to considered criteria conditions so that proper promotional and growth actions can be implemented.