User Preference Based Spatial Skyline Query Method

2014 ◽  
Vol 530-531 ◽  
pp. 832-838
Author(s):  
Yong Gui Zou ◽  
Zhi Wang
Keyword(s):  
Spatial Data ◽  
Road Network ◽  
User Preference ◽  
Skyline Query ◽  
Data Set ◽  
Second Stage ◽  
Processing Data ◽  
Data Volume ◽  
Definition Of ◽  
Query Algorithm

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.

A New Quadtree-Based Skyline Query Algorithm

2014 ◽  
Vol 981 ◽  
pp. 175-178
Author(s):  
Run Tao Liu ◽  
Yuan Jing Chen ◽  
Da Yong Cao ◽  
De Yu Liu
Keyword(s):  
Detailed Analysis ◽  
Spatial Data ◽  
Index Structure ◽  
Skyline Query ◽  
Set Up ◽  
Query Algorithm

In this paper, the index structure, PR-quadtree for spatial data, is used to store data for a database. The properties of the quadtree are studied. With the properties prunning rules are set up for searching the Skyline set of the data stored in the quadtree. Through detailed analysis for the tree the method of finding some approximate skyline points is designed, by which a new skyline searching algorithm is given. The new algorithm is more effective.

scholarly journals A Power Grid Fault Diagnosis Method in the Case of Alarm Information Loss Based on the Top-k Skyline Query Algorithm

Energies ◽  
2021 ◽  
Vol 14 (19) ◽  
pp. 6223
Author(s):  
Lei Jin ◽  
Qing Chen ◽  
Jinjie Ji ◽  
Xiaotong Zhou
Keyword(s):  
Fault Diagnosis ◽  
Power Grid ◽  
Circuit Breaker ◽  
Information Loss ◽  
Uncertain Information ◽  
Skyline Query ◽  
Data Set ◽  
Information Set ◽  
Diagnosis Method ◽  
Query Algorithm

After the failure of the power system, a large amount of alarm information will flood into the dispatching terminal instantly. At the same time, there are inevitable problems, such as the abnormal operation of the protection and the circuit breaker, the lack of alarm information, and so on. This kind of uncertainty problem brings great trouble to the fault diagnosis algorithm. As a data processing algorithm for an uncertain information set, Top-k Skyline query algorithm can eliminate the data points that do not meet the requirements in the information set, and then output the final K results in order. Based on this background, this paper proposes a power grid fault diagnosis method based on the Top-k Skyline query algorithm considering alarm information loss. Firstly, the fault area is determined by using the information of the electrical quantity and switching value. Then, backward reasoning Petri nets are established for the nodes in the fault area to form the data set of fault hypotheses. Then, the Top-k Skyline query algorithm is used to sort the hypotheses and choose the hypothesis with higher reliability. Finally, an IEEE 39-bus system example is given to verify the reliability of the proposed method.

scholarly journals Text Detection in Natural Image By Connected Component Labeling

2019 ◽  
Vol 30 (1) ◽  
pp. 111
Author(s):  
Zamen Abood Ramadhan ◽  
Dhia Alzubaydi
Keyword(s):  
Spatial Data ◽  
Natural Image ◽  
Connected Component ◽  
Data Set ◽  
Stroke Width ◽  
Second Stage ◽  
Street Sign ◽  
Third Stage ◽  
Stroke Width Transform ◽  
Canny Edge

The process of detect the text from the natural image is complex and difficult process because the variance by the devises that take the images and different the texts that found in images in the orientation, size and style. Given the importance the texts in images in the several of application of computer vision. In this paper dependent on the spatial natural images and on the spatial data set for the street sign that include the texts by the different size and different orientation. In this paper detected the texts in images by using robust method by using several algorithms, at the first stage making preprocessing for the image to blur the image and reduce the nose on it by Gaussian blur, second stage making processing that include canny edge detection to detect the edges and dilation, third stage applying connected component to filling all objects in image then applying stroke width transform(SWT) to detect the letter candidate and applying the system on the several images that include different types of texts.

scholarly journals Has the Credibility of the Social Sciences Been Credibly Destroyed? Reanalyzing the “Many Analysts, One Data Set” Project

2021 ◽  
Vol 7 ◽  
pp. 237802312110244
Author(s):  
Katrin Auspurg ◽  
Josef Brüderl
Keyword(s):  
Social Sciences ◽  
Causal Reasoning ◽  
Research Question ◽  
Social Science Research ◽  
Science Research ◽  
Skin Tone ◽  
Data Set ◽  
The Social ◽  
The Many ◽  
Definition Of

In 2018, Silberzahn, Uhlmann, Nosek, and colleagues published an article in which 29 teams analyzed the same research question with the same data: Are soccer referees more likely to give red cards to players with dark skin tone than light skin tone? The results obtained by the teams differed extensively. Many concluded from this widely noted exercise that the social sciences are not rigorous enough to provide definitive answers. In this article, we investigate why results diverged so much. We argue that the main reason was an unclear research question: Teams differed in their interpretation of the research question and therefore used diverse research designs and model specifications. We show by reanalyzing the data that with a clear research question, a precise definition of the parameter of interest, and theory-guided causal reasoning, results vary only within a narrow range. The broad conclusion of our reanalysis is that social science research needs to be more precise in its “estimands” to become credible.

Personalised attraction recommendation for enhancing topic diversity and accuracy

2021 ◽  
pp. 016555152199980
Author(s):  
Yuanyuan Lin ◽  
Chao Huang ◽  
Wei Yao ◽  
Yifei Shao
Keyword(s):  
Real World ◽  
Information Overload ◽  
Two Stage ◽  
Misclassification Cost ◽  
Second Stage ◽  
Low Visibility ◽  
Recommendation Diversity ◽  
Optimisation Model ◽  
Definition Of ◽  
Improved Methods

Attraction recommendation plays an important role in tourism, such as solving information overload problems and recommending proper attractions to users. Currently, most recommendation methods are dedicated to improving the accuracy of recommendations. However, recommendation methods only focusing on accuracy tend to recommend popular items that are often purchased by users, which results in a lack of diversity and low visibility of non-popular items. Hence, many studies have suggested the importance of recommendation diversity and proposed improved methods, but there is room for improvement. First, the definition of diversity for different items requires consideration for domain characteristics. Second, the existing algorithms for improving diversity sacrifice the accuracy of recommendations. Therefore, the article utilises the topic ‘features of attractions’ to define the calculation method of recommendation diversity. We developed a two-stage optimisation model to enhance recommendation diversity while maintaining the accuracy of recommendations. In the first stage, an optimisation model considering topic diversity is proposed to increase recommendation diversity and generate candidate attractions. In the second stage, we propose a minimisation misclassification cost optimisation model to balance recommendation diversity and accuracy. To assess the performance of the proposed method, experiments are conducted with real-world travel data. The results indicate that the proposed two-stage optimisation model can significantly improve the diversity and accuracy of recommendations.

Virtual fit evaluation of pants using the Adaptive Network Fuzzy Inference System

2021 ◽  
pp. 004051752110205
Author(s):  
Xueqing Zhao ◽  
Ke Fan ◽  
Xin Shi ◽  
Kaixuan Liu
Keyword(s):  
Fuzzy Inference System ◽  
Fuzzy Inference ◽  
Test Accuracy ◽  
Adaptive Network ◽  
Data Set ◽  
Inference System ◽  
Second Stage ◽  
Simulated Environment ◽  
Two Stages ◽  
Fold Cross Validation

Virtual reality is a technology that allows users to completely interact with a computer-simulated environment, and put on new clothes to check the effect without taking off their clothes. In this paper, a virtual fit evaluation of pants using the Adaptive Network Fuzzy Inference System (ANFIS), VFE-ANFIS for short, is proposed. There are two stages of the VFE-ANFIS: training and evaluation. In the first stage, we trained some key pressure parameters by using the VFE-ANFIS; these key pressure parameters were collected from real try-on and virtual try-on of pants by users. In the second stage, we evaluated the fit by using the trained VFE-ANFIS, in which some key pressure parameters of pants from a new user were determined and we output the evaluation results, fit or unfit. In addition, considering the small number of input samples, we used the 10-fold cross-validation method to divide the data set into a training set and a testing set; the test accuracy of the VFE-ANFIS was 94.69% ± 2.4%, and the experimental results show that our proposed VFE-ANFIS could be applied to the virtual fit evaluation of pants.

scholarly journals THE CULTURAL HERITAGE SPATIAL DATA SET OF KLAIPĖDA OLD TOWN / SAUGOMŲ KLAIPĖDOS SENAMIESČIO OBJEKTŲ ERDVINIŲ DUOMENŲ RINKINYS / НАБОР ПРОСТРАНСТВЕННЫХ ДАННЫХ ОХРАНЯЕМЫХ ОБЪЕКТОВ СТАРОГО ГОРОДА КЛАЙПЕДЫ

2012 ◽  
Vol 37 (4) ◽  
pp. 172-176
Author(s):  
Lina Kuklienė ◽  
Dainora Jankauskienė ◽  
Indrius Kuklys
Keyword(s):  
Cultural Heritage ◽  
Spatial Data ◽  
Road Construction ◽  
Heritage Management ◽  
Data Set ◽  
Management Planning ◽  
Cultural Heritage Management ◽  
Input Devices ◽  
Relevant Point ◽  
Cultural Heritage Objects

The purpose of the thesis is to analyze the main geodetic databases of Lithuania and to create a geodetic database of cultural heritage objects in Klaipėda using program ArcGIS 9.3. The problem is that the geodetic database storing graphical and attributive information about cultural heritage in Klaipeda city has not been created yet. Thus, in order to incorporate GIS technologies into the management of cultural heritage, starting the creation of such a database seems to be a relevant point. The fully completed and regularly updated geodetic database can be used for cultural heritage management, planning, design, road construction, etc. Therefore, the following objectives have been set: 1) describing geo-data collection and input devices; 2) stimulating the geodetic database that introduces information about buildings, building complexes, cemeteries, locations of archaeological and cultural heritage; 3) giving a detailed description of the database creation process; 4) analyzing the need for establishing a geodetic database of cultural heritage objects in Klaipėda. Santrauka Lietuvoje GIS pagrindu sukurta daug įvairiems tikslams skirtų georeferencinių bei teminių erdvinių duomenų rinkinių. Viena iš šių rinkinių panaudojimo sričių – valstybės registruose esančių duomenų kaupimas. Tokiu principu yra sukurta Kultūros vertybių registro duomenų bazė, kurios pagrindiniai duomenys buvo panaudoti kuriant Klaipėdos miesto kultūros paveldo objektų erdvinių duomenų rinkinį. Siekiant kuo operatyviau įtraukti GIS technologijas į kultūros paveldo objektų tvarkybą, aktualu Klaipėdoje pradėti kurti kultūros paveldo objektų erdvinių duomenų rinkinį. Nuolat atnaujinamas erdvinių duomenų rinkinys palengvins įvairių sričių specialistų atliekamus kultūros paveldo objektų administravimo, teritorijų planavimo, projektavimo, kelių tiesimo ir kitus darbus. Резюме В Литве на основе ГИС для различных целей создано множество гео-ссылок, а также тематических наборов пространственных данных. Область использования одного из множеств – сбор данных, имеющихся в государственном учете. По такому принципу создана регистрационная база культурных ценностей, основные данные которой были использованы при создании набора пространственных данных объектов культурного наследия города Клайпеды. С целью оперативно обеспечить управление объектами культурного наследия технологиями ГИС следует начать создание набора пространственных данных объектов культурного наследия в Клайпеде. Полностью заполненный и постоянно обновляемый набор пространственных данных облегчит работу специалистов в различных областях: администрировании объектов культурного наследия, планировании территорий, проектировании, строительстве дорог и других.

scholarly journals Leveraging Road Characteristics and Contributor Behaviour for Assessing Road Type Quality in OSM

2021 ◽  
Vol 10 (7) ◽  
pp. 436
Author(s):  
Amerah Alghanim ◽  
Musfira Jilani ◽  
Michela Bertolotto ◽  
Gavin McArdle
Keyword(s):  
Machine Learning ◽  
Spatial Data ◽  
Classification Accuracy ◽  
Supervised Machine Learning ◽  
Machine Learning Techniques ◽  
Data Set ◽  
Semantic Inference ◽  
Road Type ◽  
The Impact

Volunteered Geographic Information (VGI) is often collected by non-expert users. This raises concerns about the quality and veracity of such data. There has been much effort to understand and quantify the quality of VGI. Extrinsic measures which compare VGI to authoritative data sources such as National Mapping Agencies are common but the cost and slow update frequency of such data hinder the task. On the other hand, intrinsic measures which compare the data to heuristics or models built from the VGI data are becoming increasingly popular. Supervised machine learning techniques are particularly suitable for intrinsic measures of quality where they can infer and predict the properties of spatial data. In this article we are interested in assessing the quality of semantic information, such as the road type, associated with data in OpenStreetMap (OSM). We have developed a machine learning approach which utilises new intrinsic input features collected from the VGI dataset. Specifically, using our proposed novel approach we obtained an average classification accuracy of 84.12%. This result outperforms existing techniques on the same semantic inference task. The trustworthiness of the data used for developing and training machine learning models is important. To address this issue we have also developed a new measure for this using direct and indirect characteristics of OSM data such as its edit history along with an assessment of the users who contributed the data. An evaluation of the impact of data determined to be trustworthy within the machine learning model shows that the trusted data collected with the new approach improves the prediction accuracy of our machine learning technique. Specifically, our results demonstrate that the classification accuracy of our developed model is 87.75% when applied to a trusted dataset and 57.98% when applied to an untrusted dataset. Consequently, such results can be used to assess the quality of OSM and suggest improvements to the data set.

scholarly journals Change detection and building spatial geodatabase for Iraqi marshes

2018 ◽  
Vol 162 ◽  
pp. 03021
Author(s):  
Oday Jasim ◽  
Noor Hamed ◽  
Tamarra Abdulgabar
Keyword(s):  
Data Collection ◽  
Spatial Data ◽  
Satellite Images ◽  
The Other ◽  
Image Mosaic ◽  
Economic Potential ◽  
Second Stage ◽  
Area Of Interest ◽  
Natural Factors ◽  
Three Stages

The Iraqi Marshlands has natural and economic potential through its environment rich in various forms of lives. This region has suffered numerous setbacks due to human and natural factors, especially in the last two decades of the last century, which led to significant environmental degradation. The purpose of this paper is to prepare spatial data for the area of the marshes in Iraq as a base (Hour-al Hoveizah and central marshes and Hammar). Also, the other aim is to produce a digital geodatabase for the marshes for the years 1973, 1986, 1999, 2006 and 2016 by using ArcGIS. The process of building geodatabase has been through done in three stages: the first stage is including data collection. The second stage will be by merging the satellite images covering the Iraqi marshes and add to images in order to get the image mosaic process. Also, a georeferencing of satellite images is to be done with all the traditional maps of the same area of the marsh. Finally, complete the full geodatabase for the area of interest by using ArcGIS as the in Cartography Design. The results of this research would be a geodatabase for the Iraqi marshes.

scholarly journals HiBuffer: Buffer Analysis of 10-Million-Scale Spatial Data in Real Time

2018 ◽  
Vol 7 (12) ◽  
pp. 467 ◽  
Author(s):  
Mengyu Ma ◽  
Ye Wu ◽  
Wenze Luo ◽  
Luo Chen ◽  
Jun Li ◽  
...  
Keyword(s):  
Real Time ◽  
Spatial Data ◽  
High Performance ◽  
Large Scale ◽  
Computation Time ◽  
Buffer Analysis ◽  
Data Volume ◽  
Time Buffer ◽  
Real World Datasets ◽  
Spatial Indexes

Buffer analysis, a fundamental function in a geographic information system (GIS), identifies areas by the surrounding geographic features within a given distance. Real-time buffer analysis for large-scale spatial data remains a challenging problem since the computational scales of conventional data-oriented methods expand rapidly with increasing data volume. In this paper, we introduce HiBuffer, a visualization-oriented model for real-time buffer analysis. An efficient buffer generation method is proposed which introduces spatial indexes and a corresponding query strategy. Buffer results are organized into a tile-pyramid structure to enable stepless zooming. Moreover, a fully optimized hybrid parallel processing architecture is proposed for the real-time buffer analysis of large-scale spatial data. Experiments using real-world datasets show that our approach can reduce computation time by up to several orders of magnitude while preserving superior visualization effects. Additional experiments were conducted to analyze the influence of spatial data density, buffer radius, and request rate on HiBuffer performance, and the results demonstrate the adaptability and stability of HiBuffer. The parallel scalability of HiBuffer was also tested, showing that HiBuffer achieves high performance of parallel acceleration. Experimental results verify that HiBuffer is capable of handling 10-million-scale data.

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