indexing model
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Residing in the data age, researchers inferred that huge amount of geo-tagged data is available and identified the importance of Spatial Skyline queries. Spatial or geographic location in conjunction with textual relevance plays a key role in searching Point of Interest (POI) of the user. Efficient indexing techniques like R-Tree, Quad Tree, Z-order curve and variants of these trees are widely available in terms of spatial context. Inverted file is the popular indexing technique for textual data. As Spatial skyline query aims at analyzing both spatial and skyline dominance, there is a necessity for a hybrid indexing technique. This article presents the review of spatial skyline queries evaluation that include a range of indexing techniques which concentrates on disk access, I/O time, CPU time. The investigation and analysis of studies related to skyline queries based upon the indexing model and research gaps are presented in this review.

Value engineering is a method of selecting the optimum design by evaluating the value of the original design and the alternative design. However, if the function score and the cost score of the evaluation subject are indexed, the range of the function index, the cost index and the value index calculated according to the functional attribute and the cost attribute may vary. The client is confused in the decision-making process of selecting the optimum design because the calculation range of the function, cost and value scores are different according to the evaluation subject. The necessity of indexing the cost score and the function score has been constantly raised, but it has been regarded as a difficult problem. This study presents a model that can index the function, cost and value scores using vector normalization method. Additionally, by applying this study model to the case of selecting finishing materials for the office automation floor of a building, the consistency of the study model was verified.

With continuous improvement of earth observation technology, source, and volume of remote sensing data are gradually enriched. It is critical to realize unified organization and to form data sharing service capabilities for massive remote sensing data effectively. We design a hierarchical multi-dimensional hybrid indexing model (HMDH), to address the problems in underlying organization and management, and improve query efficiency. Firstly, we establish remote sensing data grid as the smallest unit carrying and processing spatio-temporal information. We implement the construction of the HMDH in two steps, data classification based on fuzzy clustering algorithm, and classification optimization based on recursive neighborhood search algorithm. Then, we construct a hierarchical “cube” structure, filled with continuous space filling curves, to complete the coding of the HMDH. The HMDH reduces the amount of data to 6–17% and improves the accuracy to more than eight times than traditional grid model. Moreover, it can reduce the query time to 25% in some query scenarios than algorithms selected as the baseline in this paper. The HMDH model proposed can be used to solve the efficiency problems of fast and joint retrieval of remote sensing data. It extends the pattens of data sharing service and has a high application value.

Mental models or situation models include representations of people, but much of the literature about such models focuses on the representation of eventualities (events, states, and processes) or (small-scale) situations. In the well-known event-indexing model of Zwaan, Langston, and Graesser (1995), for example, protagonists are just one of five dimensions on which situation models are indexed. They are not given any additional special status. Consideration of longer narratives, and the ways in which readers or listeners relate to them, suggest that people have a more central status in the way we think about texts, and hence in discourse representations, Indeed, such considerations suggest that discourse representations are organised around (the representations of) central characters. The paper develops the idea of the centrality of main characters in representations of longer texts, by considering, among other things, the way information is presented in novels, with L’Éducation Sentimentale by Gustav Flaubert as a case study. Conclusions are also drawn about the role of representations of people in the representation of other types of text.

Measuring and comparing sustainable development levels of cities, regions, and projects is an essential procedure in creating and maintaining sustainable urban futures.Introducing a new urban sustainable development assessment model: The Live and Work (LaW) City Model, as an indicator-based sustainable development indexing model, it aims to assist planners and policy makers in their decision-making procedures and development of cities by providing an integrated assessment framework. Several efforts were done to develop composite indicators, but it was concluded that most of them focused on environmental dimensions and neglected the overlapping of the other influential ones.The paper gives an overview of the nature and importance of composite indicators and how it can be structured and implemented precisely; overcoming its drawbacks, to gauge and rank the performance of cities across the demands of people, planet, and profit, as a way of achieving the live and work balance criteria.The methodology of the model is developed by following a set of logical steps such as; weighing, normalization, and aggregation of individual indicators. From here, a functional form for aggregation was derived to compute the index. Also, the structure of the model was illustrated in the form of a Pie/Radar chart.The visualized LaW City Index has the communicative advantage of being easy to convey comparative levels of different values. The total values computed could be used to rank cities in a tabular format and gauge their comparable sustainable development performance accordingly.The model can also estimate the sustainable development outcomes of alternative development scenarios during different year’s intervals. This can be achieved by stacking up different model scenarios; making it a relatively simple exercise for both the general public and decision-makers to comprehend