Exploring the Differences Between Tourists and Locals in Urban Settings Through Multi-labeled Geotagged Photos: The Case of Tokyo

Understanding the behaviors of both locals and tourists is essential for good city planning, especially in tourism-dependent cities. This study aimed to explore the disparities between the two groups on the basis of their geotagged photos taken in Tokyo during the last decade (2009–2019). The photos were collected from the photosharing platform Flickr. Locals and tourists were then identified. Next, a transfer-learning-based convolutional neural network model was developed to multi-label photos into eight general categories reflecting the major frequented activities/locations, including nature, amusement, and culture. Additional information was assigned to these records, including distances to various nearest points of interest. Qualitative and quantitative methods were used to investigate the differences between locals and tourists. Results showed that tourists have a strong preference for amusement while locals are attracted to nature. In contrast to tourists who are not followed by job obligations, locals’ photos are mostly taken during the weekends. Given their familiarity with the area, locals tend to cover a wider spatial extent compared to tourists who are concentrated near the Yamanote railway loop line connecting most of the tourist attractions.

Studying the homogeneity of the coordinate base SSC-2011 at arranging a special-purpose geodetic network

The results of studies on the SSC-2011 coordinate base homogeneity carried out in the process of linking a special-purpose geodetic network’s points to this coordinate system are presented. The research consisted of multiple determinations of the differential geodetic stations (DGS) coordinates in GSK-2011 from different types of the coordinate base of this system. In the first version, they were obtained through their binding to the nearest points of the SGN with known coordinates in the SSC-2011. In the second one, the DGS was linked to SSC-2011 by GNSS vectors to four FAGS points. In the third variant, in order to obtain these coordinates in SSC-2011 the reference were four points of the IGS network. The grid coordinates of the DGS determined in GSK-2011 from the FAGS and IGS points coincided within 1,3 cm. Those of the DGS in SSC-2011, from points of the SGN, differ from the ones obtained in the FAGS and IGS by maximum values up to 21,8 cm, 22,2 cm, 27,2 cm in the abscissa, ordinate, and position, respectively. The derived data on the degree of heterogeneity of the SGN in SSC-2011 enable concluding the impracticality of using it as the coordinate basis of this system at carrying out works, requiring positioning accuracy at the level of several centimeters.

Preference Oriented Mining Techniques for Location based Point Search

With the development of internet and wireless technologies, location based search is among the most discussed topic in current era. To address issues of location based search a lot of research has been done but it mainly focused on the specific aspects of the domain like most of the studies focused, on the search of nearby restaurants, shopping malls, hospitals, stores etc., by utilizing location of users as searching criteria. Problem with these studies is that users might not be satisfied by their results and the sole reason behind this might be the absence of user preferences in the search criteria. There exists some studies which focused user preferences along with user location and query time and proposed some frameworks but they are only limited to stores and their research cannot be scaled to other points like schools, hospitals, doctors , petrol pumps, gas station etc. Moreover there exist scalability issues in their recommended algorithms along with some data credibility issues in their public evaluations strategies. Our proposed research is going to present a novel location based searching technique not only for stores but for any point. The presented solution has overcome issues faced in previous research studies and possesses capability to search for “K” nearest points which are most preferable by user, by utilizing searching time as well as query location. Our research has proposed two feedback learning algorithms and one ranking algorithm. To increase the credibility of public evaluation score, system have utilized Google ranking approach while calculating the score of the point. To make user recommendations nonvolatile along with improving recommendations algorithm efficiency, proposed system have introduced item to item collaborative filtering algorithm. Through experimental evaluations on real dataset of yelp.com presented research have shown significant gain in performance and accuracy.

ПОРІВНЯЛЬНИЙ АНАЛІЗ МЕТОДІВ ПОШУКУ НАЙБЛИЖЧИХ ТОЧОК НА ЗОБРАЖЕННЯХ ОБ’ЄКТІВ ТЕХНІЧНИХ СИСТЕМ

The subject of the study is the process of mapping the construction of point clouds of technical systems using the algorithm of the nearest points. The goal is to minimize the alignment criterion by converting a set of cloud points Y into a set of cloud points X in a software product that uses an iterative closest point (ICP) algorithm. Objectives: to analyze the properties of input images that contain point clouds; to review the algorithms for identifying and comparing key points; implement a cloud comparison algorithm using the ISR algorithm; consider an example of the algorithm for estimating the approximate values of the elements of mutual orientation; implement software that allows you to compare files that contain point clouds and draw conclusions about the possibility of comparing them. The methods used are: search for points using the algorithm of iterative nearest points, the algorithm for estimating the approximate values of the elements of mutual orientation, the method of algorithm theory for the analysis of file structures STL (standard template library - format template library) format. The following results were obtained. The choice of the ICP algorithm for the task of reconstruction of the object of technical systems is substantiated; the main features of the ISR algorithm are considered; the algorithm of comparison of key points, and also optimization that allows reducing criterion of combination at the reconstruction of three-dimensional objects of technical systems results. Conclusions. The study found that the iterative near-point algorithm is more detailed and accurate when modeling objects. At the same time, this method requires very accurate values and when calculating the degree of proximity, the complexity of calculation by this algorithm increases many times. Whereas the algorithm for estimating the approximate values of the elements of mutual orientation does not require information about the approximate orientation of the point clouds, which simplifies the work and reduces the simulation time. It was found that not all files are comparable. Therefore, the software is implemented, which gives an opinion on the possibility of comparing points in the proposed two files, which contain clouds of points in the structure of the STL format.

Creation of linear-angular constructions in a closed area using satellite geodetic equipment

Invisibility between points can occur due to dense building location, terrain irregularities, intensive construction, and under polar night conditions. Forest thickets (the distance between the trunks up to 5 m, the closeness of the crowns start at 0,5 m) and undergrowth require cutting and clearing glades; terrain elevations, dense building setting, traffic flows and construction machines complicate the development of geodetic reference networks, the implementation of detailed surveys and construction layout. In the absence of visibility when the sides of the geodetic network make 200–500 m, it is recommended that two or more GPS receivers should work simultaneously under the same weather conditions, which compensates for errors at receiving radio signals, except for multipath and noise. With synchronous operation of the receivers, accurate coordinates and orientations for the upcoming electronic geodetic surveys are at mutually visible neighboring points obtained even without post-processing. Simultaneous GPS measurements enable finding the distance between them and horizontal angles in a closed area over the nearest points of the base and moving antennas in the building network for geodetic planning justification of detailed surveys and construction layout.

Design and Analysis of Spatial Skyline Queries Indexing

Dwelling in the information age permits nearly everybody needs to recover countless information and choices to gather from to fulfill their necessities. In distinctive cases, the quantity of information accessible and the speed of change may cover the ideal and required explanation. Spatial-textual queries provide the most acclaimed nearest points concerning a conveyed site and a keyword set. Current practice regularly thought on the most capable technique to expertly get the top-k resultset reestablished a spatial-scholarly query. A capable Spatial Range Skyline Query (SRSQ) algorithm is proposed which initially performsa spatial keyword query (SKQ) that relies upon an IRtree that documents the information. Skyline centers picked are not simply established on their partitions to a lot of inquiries and more subject to their significance to a social occasion of query keywords. Additionally, besides proposed range skyline (RS) methods based on R-tree multi-dimensional space including secondary- memory pruning tools for operating field skyline queries is accomplished. The advanced scheme is dynamic and I/O optimum. Ultimately, methodology presents a modern assessment that demonstrates the proficiency.

Nearest points on toric varieties

We determine the Euclidean distance degree of a projective toric variety. This extends the formula of Matsui and Takeuchi for the degree of the $A$-discriminant in terms of Euler obstructions. Our primary goal is the development of reliable algorithmic tools for computing the points on a real toric variety that are closest to a given data point.