Multi-attribute Index Research Articles

Research on optimization of index system design and its inspection method: data quality diagnosis, index classification and stratification

PurposeThe purposes of this research are to study the theory and method of multi-attribute index system design and establish a set of systematic, standardized, scientific index systems for the design optimization and inspection process. The research may form the basis for a rational, comprehensive evaluation and provide the most effective way of improving the quality of management decision-making. It is of practical significance to improve the rationality and reliability of the index system and provide standardized, scientific reference standards and theoretical guidance for the design and construction of the index system.Design/methodology/approachUsing modern methods such as complex networks and machine learning, a system for the quality diagnosis of index data and the classification and stratification of index systems is designed. This guarantees the quality of the index data, realizes the scientific classification and stratification of the index system, reduces the subjectivity and randomness of the design of the index system, enhances its objectivity and rationality and lays a solid foundation for the optimal design of the index system.FindingsBased on the ideas of statistics, system theory, machine learning and data mining, the focus in the present research is on “data quality diagnosis” and “index classification and stratification” and clarifying the classification standards and data quality characteristics of index data; a data-quality diagnosis system of “data review – data cleaning – data conversion – data inspection” is established. Using a decision tree, explanatory structural model, cluster analysis, K-means clustering and other methods, classification and hierarchical method system of indicators is designed to reduce the redundancy of indicator data and improve the quality of the data used. Finally, the scientific and standardized classification and hierarchical design of the index system can be realized.Originality/valueThe innovative contributions and research value of the paper are reflected in three aspects. First, a method system for index data quality diagnosis is designed, and multi-source data fusion technology is adopted to ensure the quality of multi-source, heterogeneous and mixed-frequency data of the index system. The second is to design a systematic quality-inspection process for missing data based on the systematic thinking of the whole and the individual. Aiming at the accuracy, reliability, and feasibility of the patched data, a quality-inspection method of patched data based on inversion thought and a unified representation method of data fusion based on a tensor model are proposed. The third is to use the modern method of unsupervised learning to classify and stratify the index system, which reduces the subjectivity and randomness of the design of the index system and enhances its objectivity and rationality.

Increasing the willingness to stay – a novel and comprehensive member satisfaction index (MSI) model tested in a leading German tennis club

PurposeThis study aims to address customer focus as an important component of total quality management (TQM) and explore the key drivers of member satisfaction in tennis clubs via a novel theory-based member satisfaction index (MSI) model with high explanatory and predictive power. Furthermore, the study aims to investigate the relationship between satisfaction and behavioral intentions (willingness to stay; WTS) with consideration of the mediating effect of identification with the club.Design/methodology/approachThis study uses variance-based partial least squares structural equation modeling (PLS-SEM) to estimate the MSI model, which was tested in a leading tennis club in Germany (n = 185).FindingsThe results reveal that club atmosphere, club facilities and the price/quality ratio of the membership fee are the most important drivers of member satisfaction in tennis clubs. Member satisfaction has a large influence on the WTS of tennis club members. Identification with the club, when included as a mediator in the model, increases the variance explained in WTS considerably.Research limitations/implicationsThe small sample limits the generalizability of findings, and further research is recommended.Practical implicationsThe MSI model is a useful benchmark tool for club managers who want to quantify the satisfaction and WTS of their club members. In addition, because of the integrated formative measurement models, the PLS-SEM results show which indicators can be used to positively impact satisfaction with each of the service quality dimensions, overall member satisfaction and WTS. The most important of these results are discussed in an importance-performance map analysis.Originality/valueThe MSI model is a multi-attribute index model through which members' evaluations of various dimensions of service and value are derived through multivariable linear function with each dimension weighted according to its importance in one holistic model. The model shows the strong impact of satisfaction on WTS of sports club members and reveals that findings of previous research on the relationship between fan and spectator identification and loyalty are transferable to sports club members. The MSI represents a new contribution to the literature; it was applied here to tennis clubs but is also suitable for application to other sports clubs.

Analysis of disease burden in socially disadvantaged areas: Mapping of geographical inequalities in COVID-19 morbidity and mortality using a social disadvantage index in Tennessee

Social vulnerability is directly addressed by contemporaneous health research to improve social equity. Existing disadvantage indices capture vulnerability to COVID-19 pandemic less accurately. Health-related studies apply the indices to relate overall vulnerability to health outcomes including severe COVID-related health outcomes leading to hospitalization and death. The multi-variable indices are based on various attributes, some unrelated to COVID-19 severity. Some studies that use multi-attribute indices don't find meaningful association with COVID-19 health outcomes. Additionally, current research is lacking on health impacts of social disadvantage during various COVID-19 stages. Thus, due to variations in inequality in exposure and pandemic susceptibility, community health should be assessed at different time points. To fill this gap, we develop an index using six indicators capturing pandemic vulnerability. We apply it in a retrospective case study of a relationship between social disadvantage and morbidity and mortality due to COVID-19 focusing on disadvantaged communities set in Tennessee with a concentration of vulnerability and rurality. COVID-19-related health outcomes were tested for associations with a social disadvantage index (SDI) for earlier (2021) and later (2022) pandemic stages. First, we describe a methodology to create a social disadvantage index to identify communities at risk for severe COVID-19-related health outcomes based on the CDC guidance. Second, we highlight the differences in COVID-19 health outcomes over time as we examine health disparities associated with social disadvantage during various pandemic stages. To understand how the findings would differ if the same analyses were to be carried out using other vulnerability indices, we apply analyses to areas based on the CDC's-based Social Vulnerability Index and find strong statistical association between the two indices and substantial overlap regarding disadvantaged areas identified and similar health outcome findings. A better understanding of whether residents of socially disadvantaged areas experience worse COVID-related health outcomes can help determine whether policies need to target not only individuals but entire communities to improve outcomes. The developed index based on six indicators is thus especially suitable during the COVID-19 disaster to efficiently identify vulnerable communities and address social equity.

An Efficient Data Analysis Framework for Online Security Processing

Industrial cloud security and internet of things security represent the most important research directions of cyberspace security. Most existing studies on traditional cloud data security analysis were focused on inspecting techniques for block storage data in the cloud. None of them consider the problem that multidimension online temp data analysis in the cloud may appear as continuous and rapid streams, and the scalable analysis rules are continuous online rules generated by deep learning models. To address this problem, in this paper we propose a new LCN-Index data security analysis framework for large scalable rules in the industrial cloud. LCN-Index uses the MapReduce computing paradigm to deploy large scale online data analysis rules: in the mapping stage, it divides each attribute into a batch of analysis predicate sets which are then deployed onto a mapping node using interval predicate index. In the reducing stage, it merges results from the mapping nodes using multiattribute hash index. By doing so, a stream tuple can be efficiently evaluated by going over the LCN-Index framework. Experiments demonstrate the utility of the proposed method.

Multi-objective optimal operation of reservoir group in Jialing River based on DREAM algorithm

Abstract With the implementation of the most stringent water resources management system and the advancement of the construction process of reservoir terrace basins, the research and application of the theory and method of joint operation of reservoir groups are becoming more and more important. The Differential Evolution Adaptive Metropolis (DREAM) algorithm is a sampling algorithm based on the Markov Chain Monte Carlo method proposed in recent years. The algorithm satisfies ergodicity and is good at handling problems with multivariate nonlinearity, high dimensionality, and multi-peaks, and as such the algorithm is a new global optimization solution. This paper elaborated the solution mechanism of the standard DREAM algorithm, and the algorithm was applied to the optimal operation model of the reservoir group in Jialing River. First, we optimized and analyzed the multi-objective supply operation model of the reservoir group water in Jialing River. Then the multi-attribute decision-making and evaluation index system of water supply operation rules for the reservoir group to assess the optimization of the operation model was adopted. Finally based on the results of the evaluation, the best water supply operation scheme for the reservoir group of Jialing River was selected. The results show that the Baozhusi Reservoir can fully meet the planned water supply requirements in dry years, while the two reservoirs, Shengzhong and Tingzikou, need to be weighed against the evaluation indexes of water supply operation. The research provides a theoretical basis for the DREAM algorithm in the optimal operation of the reservoir group and the actual operation scheme for the reservoir group of Jialing River.

Ancient Chinese Character Image Retrieval Based on Dual Hesitant Fuzzy Sets

The complex and changeable structures of ancient Chinese characters result in the decreasing accuracy of their image retrieval. To resolve this problem, a new retrieval method based on dual hesitant fuzzy sets is proposed. Dual hesitation fuzzy sets that can express uncertain information more comprehensively are employed in the feature extraction process of directional line elements. The multiattribute evaluation index of adjacent grids for the current grid and its corresponding membership and nonmembership functions are established, and the weight of each attribute is calculated by the dual hesitation fuzzy entropy, such that the proposed features can fully reflect the topological structure of ancient Chinese characters. Using the dual hesitation fuzzy correlation coefficient to measure the similarity between the ancient Chinese character images to be retrieved and the candidate images, the retrieval of ancient Chinese character images is realized. Experiments show that when the t0hreshold value of the correlation coefficient is 0.9, the average retrieval accuracy is 90.4%.

When, how, and how long do adults in Germany self-reportedly wash their hands? Compliance indices based on handwashing frequency, technique, and duration from a cross-sectional representative survey.

BackgroundHand hygiene is an efficacious behaviour to prevent community-associated infections. Estimates of the proportion of populations who wash their hands have indicated limited compliance. While biases of self-report items for hand hygiene, such as the tendency to overestimate one's behaviour, represent a limitation, direct survey questions remain important. This study aims to compare indices of handwashing compliance based on single vs. combined handwashing attributes, i.e., its frequency, technique, and duration.MethodsData of a representative survey on hygiene and infection control by the German Federal Centre for Health Education were analysed. In a cross-sectional, computer-assisted telephone interview design, the resident population in Germany aged 16–85 years was surveyed in 2012. For handwashing, duration, frequency in different situations, and technique (use of soap, washing interdigital spaces, and drying hands) were self-reported. Self-reports were rated as (non-)compliant based on national recommendations and combined into single- and multi-attribute indices. Use of hand disinfectants, recall of handwashing instruction plates in public restrooms, and socio-demographics were also assessed. In total, N = 4483 persons participated (response rate: 49.7%). Data were weighted to compensate for sampling bias and analysed by cross-tabulation and multiple logistic regression. Primarily due to missing data, the analysis was confined to N = 4093 respondents (i.e., 91%).ResultsAmong women, the proportion of those who reported to wash hands “almost always” in at least seven of nine situations was 30.8% (men: 20.3%). In contrast, 51% of men reported always using soap, drying hands, and washing interdigital spaces (women: 43.5%; p < 0.001). Compliance based on indices that included “frequency” was higher in women by 5.2% for “frequency + technique” (17.6% vs. 12.4%), and 2.5% for “frequency + duration” (13.1% vs. 10.6%) and “frequency + duration + technique” (8.8% vs. 6.3%; p < 0.02). Socio-demographic differences were most consistent regarding higher compliance among healthcare workers. Finally, especially men recalling handwashing instruction plates in public restrooms had higher compliance than those with no recall, namely, for “frequency + technique” (15.4% vs. 10.6%; OR: 1.9), all three attributes (7.6% vs. 5.3%; OR = 1.7), and “technique” (56.9% vs. 47.7%; OR = 1.6). The highest odds ratio was noted for disinfectant use among men (OR = 2.5; 12.2% vs. 4.9%).DiscussionWhile being representative for Germany, limitations include the survey's cross-sectionality, response rate, and the study representing the situation in 2012. Nonetheless, indices based on combined attributes allow better comparison to scarce compliance estimates for Germany based on observation. Socio-demographic differences add to existing evidence, e.g., higher compliance by healthcare workers. Finally, although reverse causation is possible, it is notable that although handwashing instruction plates in public restrooms focus on duration and technique, women recalling them reported higher frequency, and men more often report hand disinfectant use, suggesting possible carry-over effects.ConclusionSelf-reported handwashing compliance assessment may be improved by partitioning the behavioural domain into different attributes and using indices based on combinations of these.

Features of changes in the quality of life in cystic fibrosis patients against the background of its effective treatment

For the determination of characteristics of LQ ofpatients with cystic fibrosis (CF) and evaluation of the efficacy of the management there was used Health Utilities Index (HUI) questionnaire. The study involved 99 CF patients at the age of from 5 to 18 years. The comparison group - 102 conditionally healthy peers of the same age. All children underwent to a comprehensive medical examination and treatment. LQ assessment was carried with the aid of the HUI questionnaire. CF patients were found to have a significant decline in overall LQ in 84,8% of cases in comparison with their healthy peers. Analysis of the «way of life cohort» showed the fall in multiattribute utility indices in children at the age of 6.12 and 16 years. There was also noted a pronounced decline of indices on attributes: «pain» in 55,6%, «emotions» - in 65,6% and the «self-care» - in 20,2% of cases. Factors significantly affecting on LQ of CF patients were established to be: the presence of homozygous or heterozygous delta F508 mutation, disturbances of the respiratory function and malnutrition, which contributed to a decrease as in the overall index as well in specific aspects of LQ. Against the background of the management during the one hospitalization there was noted the positive dynamics due to the gain in the index of the emotional background. A similar situation was revealed after 6 months in re-hospitalization. Pronounced positive dynamics was noted after the management of patients with severe course of the disease, the worst values of radiological indices and a decline in FEV1 indices. The authors believe the study of LQ of CF patients to be important not only for the evaluation of the impact of the disease on the patient’s LQ, but also for the determination of the efficacy of the management.

Geo-parcel-based geographical thematic mapping using C5.0 decision tree: a case study of evaluating sugarcane planting suitability

Geographical thematic mapping based on spatial information can effectively support scientific decision-making in Geosciences. To obtain finer spatial decision information, this paper proposes a geo-parcel-based thematic mapping methodology for evaluating cash crop planting suitability using C5.0 decision tree (DT). In this study, geo-parcels are utilized as basic mapping units. Multi-source data are firstly employed to increase geo-parcel units’ attributes and a decision table then is constructed under a multi-attribute index system. Next, rules are mined using a C5.0 DT algorithm according to local geo-parcels in this decision table. Finally, rules are referred as thematic-distinguishing knowledge for inferential mapping in global geo-parcels. A case study of sugarcane planting suitability evaluation is conduct based on the proposed methodology. The experimental results showed that the cross-validation accuracy of the rules is 81.34% and the sum of the very suitable area and suitable area in the generated evaluation map is close to that of historical selected high-yield and high-sugar-content sugarcane bases, which indicated that the mapping result is in good agreement with the actual selection situation. These also demonstrate the effectiveness of our method and thus may be extended to other domains requiring fine geographical thematic mapping of cash crop planting suitability.

TOPSIS approach for multi-attribute decision making problems based on n-intuitionistic polygonal fuzzy sets description

Abstract The polygonal fuzzy set describes a type of fuzzy information with the aid of the orderly representation of real numbers. It can approximate general fuzzy sets and overcome the complexity of arithmetic operations of fuzzy sets based on the Zadeh’s extension principle. This research proposes the concept of an n-intuitionistic polygonal fuzzy set based on intuitionistic fuzzy and polygonal fuzzy sets. It then presents its arithmetic operation and Hamming distance formula. In addition, it adopts the standardized and weighting method to obtain the attribute matrix of the positive (negative) ideal solution, and calculates the Hamming distance between each scheme and the positive (negative) ideal solution to provide the TOPSIS (technique for order preference by similarity to an ideal solution) approach for the multi-attribute decision-making problem that describes the multi-attribute index information by n-intuitionistic polygonal fuzzy set. Finally, this research implements optimized ordering on the alternative solutions according to the degree of relative similarity and verifies its effectiveness and practicability through examples.

The Evaluation of Decision Support Tools Requires a Measure of Decision Quality That Has Content and Construct Validity in Person-Centred Care.

The evaluation of decision aids and support interventions requires a multi-attribute index which can be calculated for both aid and comparator/s. The Decision Conflict Scale (DCS) is such an index and has been widely used in this context, the recent Cochrane review Decision aids for people facing health treatment or screening decisions reporting its use in 63 of the 105 studies included. However, while the DCS may be a valid measure for the eponymous construct - decision conflict - it lacks both content and construct validity for the evaluation of decision aids. It lacks content validity for this task because of the 3 items which make up its Uncertainty subscale, which penalize an aid that correctly reports the situation is one of decisional equipoise or near equipoise. A 'false clarity' bias in aid presentation is encouraged by being rewarded. In this paper we confirm that the inclusion of the Uncertainty subscale in the DCS has inappropriate empirical consequences for decision aid evaluation. Excluding the Uncertainty items would address this content invalidity, but the DCS would still lack construct validity, since the construct being measured is being treated, and inappropriately psychometrically validated, as a reflective rather than formative one. The component scales (items) of an index for a formative construct need to be preference-weighted, in ethical person-centred care by the individual at the point of decision. We argue that the most appropriate formative construct for use in decision aid evaluation is decision quality, and suggest MyDecisionQuality (MDQ) as the first formative index that can claim to both possess content and construct validity for the measurement of decision quality. However, like all multi-criterial formative metrics, the construct that MDQ measures is constructed by the measure and has no existence independent of it.

Research on Interval Multiple Attribute Decision-Making Method Based on Gray Correlation Degree and TOPSIS

This paper investigates an interval multiple attribute decision making problem. In view of the fact that Euclidean distance and gray correlation degree can fully and faithfully reflect the proximity of the selected scheme to the ideal scheme from the distance and the different shape. So we propose a new decision making method based on grey correlation degree and TOPSIS. It accurately evaluates interval numbers multi-attribute index scheme. Finally, an example of a multiple attribute decision making problem with intervals is given to illustrate the feasibility and validity of the proposed method.

Assessing the Quality of Life Using the Health Utilities Index Questionnaire in Children With Severe Persistent Asthma During the Treatment With Omalizumab

Background. Quality of life (QoL) is an important parameter that provides additional information about changes in health status. Objective. Our aim was to study the change in QoL of patients with severe persistent bronchial asthma (BA) during the treatment with genetically engineered biological preparation (GIBP) omalizumab in addition to daily background therapy. Methods. The QoL assessment was conducted using the Health Utilities Index Mark 3 and Mark 2 (HUI3, HUI2) questionnaires at two points (1st point and 2nd point — in 6 months) in 47 children with severe BA at the age of 13 (7; 17) years, 72% of them are boys. At the same points, QoL was evaluated using the PAQLQ (S) specialized pediatric questionnaire (Standardized Pediatric Asthma Quality of Life Questionnaire). Results. Depending on the duration of omalizumab therapy, all children were divided into 5 groups: 1st group — children who did not receive treatment with monoclonal antibodies at the 1st point; in 2, 3, 4, 5-th groups, the QoL assessment was performed on GIBP treatment for different time. In children of the 1st group whose QoL was evaluated before starting GIBP therapy and in 6 months, a statistically significant change in scores on the Health Utilities Index questionnaire was noted: the multi-attribute indices HUI2 and HUI3 improved, respectively, by 21.3 and 10.71% (p = 0.041 and 0.086). According to the HUI2 classification system, a significant improvement in the emotion attribute was revealed, which positively correlated with the overall indicator and the emotion indicator of the PAQLQ (S) questionnaire. In the remaining groups, the indicators of the Health Utilities Index questionnaire did not change significantly. Conclusion. The study results showed that the dynamics of the quality of life in children with severe persistent BA is an important additional criterion in a comprehensive assessment of the efficacy of targeted bioengineering therapy.

Comparatively evaluating effect contribution of promoting blood circulation of herb pairs containing Angelicae Sinensis Radix on Xin-Sheng-Hua granule by withdrawal analysis

Xin-Sheng-Hua granule (XSHG) is a popular remedy commonly used in clinic for the treatment of lochiostasis after delivery. To comparatively investigate the roles of herb pairs containing Angelicae Sinensis Radix (Danggui) upon the formula by evaluating the blood coagulation and hemorheology function in acute blood stasis rats, acute blood stasis rat model was established by ice water bath and subcutaneous injection of adrenaline. And the blood stasis mice were administrated intragastrically with different samples of the formula minus herb pairs containing Danggui and the whole formula (XSHG, SHD, DY, DC, DT, DH, DJ and DZ). The whole blood viscosity (WBV), plasma viscosity (PV), erythrocyte sedimentation rate (ESR) and haematocrit (HCT) were applied to evaluate the effects of the formula minus herb pairs containing Danggui on hemorheology of blood stasis rats. The thrombin time (TT), activated partial thromboplastin time (APTT), prothrombin time (PT), and plasma fibrinogen (FIB) were used to observe the effects of the formula minus herb pairs containing Danggui on blood coagulation function of blood stasis rats. Additionally, the maximum aggregation induced by adenosine diphosphate (ADP) was tested to observe the effect of different samples on platelet aggregation index of blood stasis rats.Afterwards, multi-attribute comprehensive index methods and principal component analysis were both applied to comprehensively assess the total effects of the formula minus herb pairs containing Danggui on promoting blood circulation and dissipating blood stasis. Compared with normal group, the hemorheological parameters and coagulation indexes of model group had statistical differences (P<0.01). Compared with model group, different samples (XSHG, SHD, DY, DC, DT, DH, DJ and DZ) could improve the blood hemorheology indexes, coagulation parameters and platelet aggregation in acute blood stasis rats. According to multi-attribute comprehensive index methods and the principal component analysis, the effects of promoting blood circulation by removing blood stasis became poor when excluding herb pairs containing Danggui from the formula, the sample DY and DC had the weakest effect of activating blood circulation and dissipating blood stasis, and the effect of sample DY was slightly poorer than DC. The orders of contribution of herb pairs containing Danggui on the formula were Danggui-Yimucao>Danggui-Chuanxiong>Danggui-Honghua>Danggui-Zhigancao>Danggui-Taoren>Danggui-Jiangtan. In conclusion, various herb pairs containing Danggui played different roles on the effects of improving the abnormality of hemorheology and coagulation function. And the herb pairs Danggui-Yimucao were particularly important for the formula, which was consistent with the characteristics of XSHG and the traditional effect of Yimucao. Moreover, it could lay foundation to further reveal the compatibility mechanism of XSHG.

Design of a general evaluation scheme to measure hospital patients' satisfaction

Patient satisfaction is an important index of hospital quality evaluation and performance evaluation. This study established multi-attribute patient satisfaction index system based on the theory of customer satisfaction index, determined the index weight by combination weighting approach, and graded the hospitals and adjusted the weights by the RSR method. A set of comprehensive evaluation scheme is initially formed, which is suitable for patient satisfaction evaluation and performance evaluation. Key words: Patient; Satisfaction; General evaluation

A DHT-Based Discovery Service for the Internet of Things

Current trends towards the Future Internet are envisaging the conception of novel services endowed with context-aware and autonomic capabilities to improve end users’ quality of life. The Internet of Things paradigm is expected to contribute towards this ambitious vision by proposing models and mechanisms enabling the creation of networks of “smart things” on a large scale. It is widely recognized that efficient mechanisms for discovering available resources and capabilities are required to realize such vision. The contribution of this work consists in a novel discovery service for the Internet of Things. The proposed solution adopts a peer-to-peer approach for guaranteeing scalability, robustness, and easy maintenance of the overall system. While most existing peer-to-peer discovery services proposed for the IoT support solely exact match queries on a single attribute (i.e., the object identifier), our solution can handle multiattribute and range queries. We defined a layered approach by distinguishing three main aspects: multiattribute indexing, range query support, peer-to-peer routing. We chose to adopt an over-DHT indexing scheme to guarantee ease of design and implementation principles. We report on the implementation of a Proof of Concept in a dangerous goods monitoring scenario, and, finally, we discuss test results for structural properties and query performance evaluation.

Research on Group Decision-Making Optimization Model of Urban Railway Traffic Network Scheme

Aiming at the evaluation and optimization of urban rail transit network scheme, the optimization decision-making model based on group TOPSIS was advanced in this paper. The multi-attribute evaluation index system of urban rail transit network was established. Then the decision-making’s position matrix and the attribute weights were determined using the idea of group decision-making on the basis that group rationality was guaranteed , which aimed at the phenomenon that preference of decision-making existed and the reduction of decision-maker’s preference had influence on the result of decision-making. The network scheme was ranked based on TOPSIS method to arrive at a decision. The example in this paper has verified the effectiveness and practicability of the model.

Multi-Criteria Decision Making Approaches for Service Quality Evaluation in Technical Education Setting: Case Study

Quality and performance of an institute largely depends on faculty profile, academics, infrastructure and professional growth opportunities. If they are considered as inputs to the system then pass percentage, placement and extent of contribution towards academic fraternity (in terms of research publications, projects and industrial consultancy etc.) may be treated as outputs. The inputs and outputs interact in a complex manner and right combination of them determines overall quality level of the institute. The interrelationship among various inputs and outputs in this transformation system is really difficult to understand clearly. Moreover, there is no specific guideline for evaluation of institutional quality level. The present study defines quality as a multi-attribute estimate and aims to evaluate a unique quality index quantitatively. However, most of the attributes are qualitative rather than quantitative. Qualitative attributes can be analysed based on expert opinions. Respondents are asked to assign attribute values in terms of scaled response (generally in Likert Scale). Existing methodologies like AHP, Fuzzy logic, TOPSIS etc. are being utilised in order to tackle such types of qualitative data (or quantitative data converted to linguistic terms). The shortcoming of these approaches is that these methodologies are based on human judgment which may lead to erroneous result. On the contrary DEA method is capable of handing quantitative data but the process is very lengthy to apply, in order to calculate technical efficiency. It is, therefore, felt necessary to search a robust methodology by which quantitative data can be explored efficiently and multi-attribute quality indices can be quantified and finally be converted into a single comprehensive quality index. If it is achieved the decision making process would become very easy for selection, comparison or benchmarking of service sectors according to their quality. In order to ease the decision making process encountered in such a multi attribute decision making situation, two multi-criteria decision making (MCDM) techniques viz., grey relational analysis and VIKOR method have been used and results there of have been compared through a case study of service quality evaluation and benchmarking of technical institutes in Eastern part of India. The comparison process based on overall quality or performance index proposed in this work enables for benchmarking of the institutes and identifies areas which require attention for improvement of overall institutional quality. The application feasibility of proposed methods has been illustrated with the help of a case study. The proposed performance index is helpful for selection of an institute for various academic purposes.

A Data Mining Approach for Selecting Bitmap Join Indices

Index selection is one of the most important decisions to take in the physical design of relational data warehouses. Indices reduce significantly the cost of processing complex OLAP queries, but require storage cost and induce maintenance overhead. Two main types of indices are available: mono-attribute indices (e.g., B-tree, bitmap, hash, etc.) and multi-attribute indices (join indices, bitmap join indices). To optimize star join queries characterized by joins between a large fact table and multiple dimension tables and selections on dimension tables, bitmap join indices are well adapted. They require less storage cost due to their binary representation. However, selecting these indices is a difficult task due to the exponential number of candidate attributes to be indexed. Most of approaches for index selection follow two main steps: (1) pruning the search space (i.e., reducing the number of candidate attributes) and (2) selecting indices using the pruned search space. In this paper, we first propose a data mining driven approach to prune the search space of bitmap join index selection problem. As opposed to an existing our technique that only uses frequency of attributes in queries as a pruning metric, our technique uses not only frequencies, but also other parameters such as the size of dimension tables involved in the indexing process, size of each dimension tuple, and page size on disk. We then define a greedy algorithm to select bitmap join indices that minimize processing cost and verify storage constraint. Finally, in order to evaluate the efficiency of our approach, we compare it with some existing techniques.

Well-being and/or quality of life in EU countries through a multidimensional index of sustainability

The aim of my paper is to demonstrate that Sen's theory of well-being can be applied to make the concept of sustainable human development operational through the building of a multidimensional index of sustainability which takes into account, at the same time, economic, social and environmental variables. This index may be considered an alternative to the current measures of welfare/sustainability since not only conventional measures such as GDP, but also multi-attribute indices, such as Human Development Index (HDI), Genuine Savings, Index of Sustainable Economic Welfare (ISEW) etc., are found to be inadequate to make the concept of sustainable development operational. Therefore, the limitations of these measures of welfare/sustainability justify the search for a new index of sustainability. This index will show, at the operational level, how Sen's theory of well-being can be useful to sustainable development. It was applied to EU countries using the standardised deviation methodology being the closest and most suitable methodology to be adopted for building multidimensional indices. The factor analysis methodology will also be used in my paper. Lastly, the comparison between Sen's trend of sustainability and GDP trend index number–which are both of them applied to Italy–will show how much the criticisms and the limitations directed towards the indicator of GDP are founded.