scholarly journals Optimized Query Algorithms for Top- K Group Skyline

2022 ◽  
Vol 2022 ◽  
pp. 1-11
Author(s):  
Jia Liu ◽  
Wei Chen ◽  
Ziyang Chen ◽  
Lin Liu ◽  
Yuhong Wu ◽  
...  

Skyline query is a typical multiobjective query and optimization problem, which aims to find out the information that all users may be interested in a multidimensional data set. Multiobjective optimization has been applied in many scientific fields, including engineering, economy, and logistics. It is necessary to make the optimal decision when two or more conflicting objectives are weighed. For example, maximize the service area without changing the number of express points, and in the existing business district distribution, find out the area or target point set whose target attribute is most in line with the user’s interest. Group Skyline is a further extension of the traditional definition of Skyline. It considers not only a single point but a group of points composed of multiple points. These point groups should not be dominated by other point groups. For example, in the previous example of business district selection, a single target point in line with the user’s interest is not the focus of the research, but the overall optimality of all points in the whole target area is the final result that the user wants. This paper focuses on how to efficiently solve top- k group Skyline query problem. Firstly, based on the characteristics that the low levels of Skyline dominate the high level points, a group Skyline ranking strategy and the corresponding SLGS algorithm on Skyline layer are proposed according to the number of Skyline layer and vertices in the layer. Secondly, a group Skyline ranking strategy based on vertex coverage is proposed, and corresponding VCGS algorithm and optimized algorithm VCGS+ are proposed. Finally, experiments verify the effectiveness of this method from two aspects: query response time and the quality of returned results.

Neurosurgery ◽  
2012 ◽  
Vol 72 (3) ◽  
pp. 353-366 ◽  
Author(s):  
Francesco Cardinale ◽  
Massimo Cossu ◽  
Laura Castana ◽  
Giuseppe Casaceli ◽  
Marco Paolo Schiariti ◽  
...  

Abstract BACKGROUND: Stereoelectroencephalography (SEEG) methodology, originally developed by Talairach and Bancaud, is progressively gaining popularity for the presurgical invasive evaluation of drug-resistant epilepsies. OBJECTIVE: To describe recent SEEG methodological implementations carried out in our center, to evaluate safety, and to analyze in vivo application accuracy in a consecutive series of 500 procedures with a total of 6496 implanted electrodes. METHODS: Four hundred nineteen procedures were performed with the traditional 2-step surgical workflow, which was modified for the subsequent 81 procedures. The new workflow entailed acquisition of brain 3-dimensional angiography and magnetic resonance imaging in frameless and markerless conditions, advanced multimodal planning, and robot-assisted implantation. Quantitative analysis for in vivo entry point and target point localization error was performed on a sub-data set of 118 procedures (1567 electrodes). RESULTS: The methodology allowed successful implantation in all cases. Major complication rate was 12 of 500 (2.4%), including 1 death for indirect morbidity. Median entry point localization error was 1.43 mm (interquartile range, 0.91-2.21 mm) with the traditional workflow and 0.78 mm (interquartile range, 0.49-1.08 mm) with the new one (P < 2.2 × 10−16). Median target point localization errors were 2.69 mm (interquartile range, 1.89-3.67 mm) and 1.77 mm (interquartile range, 1.25-2.51 mm; P < 2.2 × 10−16), respectively. CONCLUSION: SEEG is a safe and accurate procedure for the invasive assessment of the epileptogenic zone. Traditional Talairach methodology, implemented by multimodal planning and robot-assisted surgery, allows direct electrical recording from superficial and deep-seated brain structures, providing essential information in the most complex cases of drug-resistant epilepsy.


2015 ◽  
Vol 8 (2) ◽  
pp. 203-211 ◽  
Author(s):  
Wilfredo Robles ◽  
John D. Madsen ◽  
Ryan M. Wersal

Waterhyacinth is a free-floating aquatic weed that is considered a nuisance worldwide. Excessive growth of waterhyacinth limits recreational use of water bodies as well as interferes with many ecological processes. Accurate estimates of biomass are useful to assess the effectiveness of control methods to manage this aquatic weed. While large water bodies require significant labor inputs with respect to ground-truth surveys, available technology like remote sensing could be capable of providing temporal and spatial information from a target area at a much reduced cost. Studies were conducted at Lakes Columbus and Aberdeen (Mississippi) during the growing seasons of 2005 and 2006 over established populations of waterhyacinth. The objective was to estimate biomass based on nondestructive methods using the normalized difference vegetation index (NDVI) derived from Landsat 5 TM simulated data. Biomass was collected monthly using a 0.10m2 quadrat at 25 randomly-located locations at each site. Morphometric plant parameters were also collected to enhance the use of NDVI for biomass estimation. Reflectance measurements using a hyperspectral sensor were taken every month at each site during biomass collection. These spectral signatures were then transformed into a Landsat 5 TM simulated data set using MatLab® software. A positive linear relationship (r2 = 0.28) was found between measured biomass of waterhyacinth and NDVI values from the simulated dataset. While this relationship appears weak, the addition of morphological parameters such as leaf area index (LAI) and leaf length enhanced the relationship yielding an r2 = 0.66. Empirically, NDVI saturates at high LAI, which may limit its use to estimate the biomass in very dense vegetation. Further studies using NDVI calculated from narrower spectral bands than those contained in Landsat 5 TM are recommended.


Author(s):  
WIRAT KESRARAT ◽  
THOTSAPON SORTRAKUL

This research proposed a methodology for specifying the location of an object with image processing. The objectives of this methodology are to capture the target area, and specify the location of the object by using image. In order to locate the dropping object on the image plane efficiently, consecutive images are analyzed and a threshold operation is proposed. Because the accuracy of the dropping objects location on the difference of consecutive images image plane is usually influenced by noise. Moreover, transformation unit is adopted to map the XY coordinate on image plane into the world coordinate for an accuracy of the dropping objects position. After we get the actual XY coordinate of the dropping object, we can find the distance from the target point (center) and clock direction of the dropping object related to the center also. In addition, by using one digital video camera set on the tower and pan to capture the image on the target area to detect the dropping object from the air to the ground. It made the proposed methodology provide easier portability to detect the dropping object in any area.


2016 ◽  
Vol 78 (11) ◽  
Author(s):  
Amolkumar Narayan Jadhav ◽  
Gomathi N.

Clustering finds variety of application in a wide range of disciplines because it is mostly helpful for grouping of similar data objects together. Due to the wide applicability, different algorithms have been presented in the literature for segmenting large multidimensional data into discernible representative clusters. Accordingly, in this paper, Kernel-based exponential grey wolf optimizer (KEGWO) is developed for rapid centroid estimation in data clustering. Here, KEGWO is newly proposed to search the cluster centroids with a new objective evaluation which considered two parameters called logarithmic kernel function and distance difference between two top clusters. Based on the new objective function and the modified KEGWO algorithm, centroids are encoded as position vectors and the optimal location is found for the final clustering. The proposed KEGWO algorithm is evaluated with banknote authentication Data Set, iris dataset and wine dataset using four metrics such as, Mean Square Error, F-measure, Rand co-efficient and jaccord coefficient. From the outcome, we proved that the proposed KEGWO algorithm outperformed the existing algorithms.   


Author(s):  
Marcelo Keese Albertini ◽  
André Ricardo Backes

We study the problem of visualization of clusters in an educational data set based on convex-hull shape preservation algorithm. This problem considers multidimensional data with pre-established classes with the requirement of elements of different classes must be presented at distinctive regions. Such problem is commonly found on economic and social data, where visualization is important to understand a phenomenon before further analysis. In this paper, we propose an algorithm that uses a nonlinear transformation to preserve some data distance properties and display in a convenient format to interpretation. The proposed visualization algorithm is a partition-conforming projection, as defined by Kleinberg [An impossibility theorem for clustering, Adv. Neural Inform. Processing Syst. 15: Proc. 2002 Conf., 2003, The MIT Press, p. 463.], and completely separates the convex hull of data classes by applying locally linear operations. We applied this algorithm to visualize data from an important exam applied for over four million students of the Brazilian educational system Exame Nacional do Ensino Médio (ENEM). Results show that the proposed algorithm successfully separates unintelligible data and presents it more accessible to further visual analysis.


2013 ◽  
Vol 3 (4) ◽  
pp. 61-83 ◽  
Author(s):  
Eleftherios Tiakas ◽  
Apostolos N. Papadopoulos ◽  
Yannis Manolopoulos

The last years there is an increasing interest for query processing techniques that take into consideration the dominance relationship between items to select the most promising ones, based on user preferences. Skyline and top-k dominating queries are examples of such techniques. A skyline query computes the items that are not dominated, whereas a top-k dominating query returns the k items with the highest domination score. To enable query optimization, it is important to estimate the expected number of skyline items as well as the maximum domination value of an item. In this article, the authors provide an estimation for the maximum domination value under the dinstinct values and attribute independence assumptions. The authors provide three different methodologies for estimating and calculating the maximum domination value and the authors test their performance and accuracy. Among the proposed estimation methods, their method Estimation with Roots outperforms all others and returns the most accurate results. They also introduce the eliminating dimension, i.e., the dimension beyond which all domination values become zero, and the authors provide an efficient estimation of that dimension. Moreover, the authors provide an accurate estimation of the skyline cardinality of a data set.


2013 ◽  
Vol 1 (1) ◽  
pp. 7 ◽  
Author(s):  
Casimiro S. Munita ◽  
Lúcia P. Barroso ◽  
Paulo M.S. Oliveira

Several analytical techniques are often used in archaeometric studies, and when used in combination, these techniques can be used to assess 30 or more elements. Multivariate statistical methods are frequently used to interpret archaeometric data, but their applications can be problematic or difficult to interpret due to the large number of variables. In general, the analyst first measures several variables, many of which may be found to be uninformative, this is naturally very time consuming and expensive. In subsequent studies the analyst may wish to measure fewer variables while attempting to minimize the loss of essential information. Such multidimensional data sets must be closely examined to draw useful information. This paper aims to describe and illustrate a stopping rule for the identification of redundant variables, and the selection of variables subsets, preserving multivariate data structure using Procrustes analysis, selecting those variables that are in some senses adequate for discrimination purposes. We provide an illustrative example of the procedure using a data set of 40 samples in which were determined the concentration of As, Ce, Cr, Eu, Fe, Hf, La, Na, Nd, Sc, Sm, Th, and U obtained via instrumental neutron activation analysis (INAA) on archaeological ceramic samples. The results showed that for this data set, only eight variables (As, Cr, Fe, Hf, La, Nd, Sm, and Th) are required to interpret the data without substantial loss information.


2014 ◽  
Vol 530-531 ◽  
pp. 832-838
Author(s):  
Yong Gui Zou ◽  
Zhi Wang

With the increasing of data volume and data dimensions in road network query, the response gets slow in searching services, which cannot satisfy users demand for preference-based searching. This paper proposes a user preference-based Skyline query algorithm. At the first stage, this method is based on the fact that the static property of data does not change during the query processes. Therefore, Skyline starts its calculation in the non-spatial data set to have the candidate results and dominance relation. Then it calculates the total costs of routine by defining user preference function. At the second stage, compare the data connections with the total costs of preference to minimize time for processing data and searching. The experiment result shows that the definition of user preference meets the users demand, and Skyline query algorithm benefits to have quick response.


2020 ◽  
Author(s):  
Anna Platz ◽  
Ute Weckmann ◽  
Josef Pek ◽  
Svetlana Kováčiková ◽  
Radek Klanica ◽  
...  

<p>The West Bohemian Massif represents the easternmost part of the geo-dynamically active European Cenozoic Rift System. This region hosts different tectonic units, the NE-SW trending Eger Rift, the Cheb Basin and a multitude of different faults systems. Furthermore, the entire region is characterised by ongoing magmatic processes in the intra-continental lithospheric mantle. These processes take place in absence of active volcanism at surface, but are expressed by a series of phenomena, including e.g. the occurrence of repeated earthquake swarms and massive degassing of CO<sub>2</sub> in the form of mineral springs and mofettes. Active tectonics is mainly manifested by Cenozoic volcanism represented by different Quaternary volcanic structures e.g. the Eisenbühl, the Kammerbühl and different maars. All these phenomena make the Eger Rift a unique target area for European intra-continental geo-scientific research. Therefore, an interdisciplinary drilling programme advancing the field of earthquake-fluid-rock-biosphere interaction was funded within the scope of the ICDP. Magnetotelluric (MT) measurements are applied to image the subsurface distribution of the electrical conductivity from shallow surface down to depths of several tens of kilometres. The electrical conductivity is a physical parameter that is particularly sensitive to the presence of high-conductive phases such as aqueous fluids, partial melts or metallic compounds. First MT measurements within this ICDP project were carried out in winter 2015/2016 along two 50 km long perpendicular profiles with 30 stations each and a denser grid of 97 stations close to the mofettes with an extension of 10 x 5 km<sup>2</sup>. Muñoz et al. (2018) presented 2D images along the NS profile of one regional profile. They reveal a conductive channel at the earthquake swarm region that extends from the lower crust to the surface forming a pathway for fluids into the region of the mofettes. A second conductive channel is present in the south of the model. Due to the given station setup, the resulting 2D inversion allows ambiguous interpretations of this feature. 3D MT data and inversions are required to distinguish between different scenarios and to fully describe the 3D structure of the subsurface. Therefore, we conducted a large MT field experiment in autumn 2018 by extending the study area towards the south. Broad-band MT data were measured at 83 stations along three 50-75 km long profiles and some additional stations across the region of the maars, the Tachov fault and the suture zone allowing for 2D as well as 3D inversion on a crustal scale. To improve the data quality, advanced data processing techniques were applied leading to good quality transfer functions. Furthermore, the previously collected MT data were reprocessed using the new approaches. This entire MT data set across the Eger Rift environment together with old MT data collected within the framework of the site characterisation in the surrounding of the KTB drilling are used to compute 3D resistivity models of the subsurface, with combining different transfer functions. These 3D inversion results will be introduced and discussed with regard to existing geological hypotheses.</p><p> </p>


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