Search

We prove that the well-studied triangulation flip walk on a convex point set mixes in time O(n^3 log^3 n), the first progress since McShine and Tetali’s O(n^5 log n) bound in 1997. In the process we give lower and upper bounds of respectively Omega(1/(sqrt(n) log n)) and O(1/sqrt(n))---asymptotically tight up to an O(log n) factor---for the expansion of the associahedron graph K_n---the first o(1) expansion result for this graph. We show quasipolynomial mixing for the k-angulation flip walk on a convex point set, for fixed k >= 4, and a treewidth result for the flip graph on n x n lattice triangulations.We show that the hardcore Glauber dynamics---a random walk on the independent sets of an input graph---mixes rapidly in graphs of bounded treewdith for all fixed values of the standard parameter lambda > 0, giving a simple alternative to existing sampling algorithms for these structures. We also show rapid mixing for analogous Markov chains on dominating sets and b-edge covers (for fixed b >= 1 and lambda > 0) in bounded-treewidth graphs, and for Markov chains on the b-matchings (for fixed b >= 1 and lambda > 0), the maximal independent sets, and the maximal b-matchings of a graph (for fixed b >= 1), in graphs of bounded carving width.To obtain these results, we introduce a decomposition framework for showing rapid Markov chain mixing. This framework is a purely combinatorial analogue that in some settings gives better results than the projection-restriction technique of Jerrum, Son, Tetali, and Vigoda.

3D multiple-view reconstruction is an important topic with applications in robotics, surveillance, augmented reality, and other fields. The ubiquity of reconstruction makes it a vital component in many systems, which need hardware and algorithms capable of processing the vast data found in reconstruction. In this dissertation, we first propose a method for performing a stage of reconstruction, triangulation, on the GPU that does not require second-order optimization and yields an order-of-magnitude speedup over a multi-core CPU processor. Next, we accelerate triangulation further on the GPU by discussing a method that leverages the path of a moving camera as a constraint and thus avoids doing non-linear optimization altogether. Subsequently, we shift to the problem of dense stereo, where we use GPU processing power to create more complete dense reconstructions while again leveraging scene constraints to keep runtime tractable. Finally, we devote a large portion of this dissertation to studying the use of multiple GPUs to accelerate the most expensive stage in reconstruction, bundle adjustment. The strategy is to partition the scene and optimize the subproblems in parallel. This approach minimizes communication across GPUs and removes the need for multi-GPU synchronization, which can be costly when there are many GPUs. We analyze multiple parallel, partitioned bundle adjustment strategies and their advantages and disadvantages. We develop an alternate method that parallelizes more efficiently and is scalable on large datasets with more GPUs. We compare the performance of the partitioned, parallel implementation against that of the original, full-problem implementation. We confirm our hypothesis that our approach can obtain large speedups with competitive accuracy for certain scenes but is less robust to ill-conditioned problems and the presence of local minima.

Objective To provide an overview of the challenges of conducting mixed methods research (MMR) in the context of health services research (HSR) and to discuss a case study example of the triangulation procedures used in a MMR study on task-shifting in the Netherlands. Method A narrative literature review of publications between January 2000 and February 2020 on the use of mixed methods in the context of HSR and a description of the triangulation procedures in an HSR study with a MMR design on task shifting in the Netherlands. Results The narrative review identified eight challenges. Those related to publishing and appraisal of MMR within HSR were most frequently reported (e.g. ‘lack of MMR examples’, ‘lack of recognition’ and ‘triangulation issues’). Also, practical problems for conducting MMR within HSR were identified (e.g. ‘lack or resources’, ‘teamwork’ and ‘lack of quality criteria’). Methodological challenges (e.g. ‘sampling’ and ‘paradigm wars’) were less frequently reported as a challenge. Conclusion While increasing in popularity, there remain a range of challenges for the design, conduct and reporting of MMR designs in HSR. Using a triangulation protocol can potentially help address some of these challenges.

Efficient collision detection is critical in 3D geometric modeling. In this paper, we first implement three parallel triangle-triangle intersection algorithms on a GPU and then compare the computational efficiency of these three GPU-accelerated parallel triangle-triangle intersection algorithms in an application that detects collisions between triangulated models. The presented GPU-based parallel collision detection method for triangulated models has two stages: first, we propose a straightforward and efficient parallel approach to reduce the number of potentially intersecting triangle pairs based on AABBs, and second, we conduct intersection tests with the remaining triangle pairs in parallel based on three triangle-triangle intersection algorithms, i.e., the Moller’s algorithm, Devillers’ and Guigue’s algorithm, and Shen’s algorithm. To evaluate the performance of the presented GPU-based parallel collision detection method for triangulated models, we conduct four groups of benchmarks. The experimental results show the following: (1) the time required to detect collisions for the triangulated model consisting of approximately 1.5 billion triangle pairs is less than 0.5 s; (2) the GPU-based parallel collision detection method speedup over the corresponding serial version is 50x - 60x, and (3) Devillers’ and Guigue’s algorithm is comparatively and comprehensively the best of the three GPU-based parallel triangle-triangle intersection algorithms. The presented GPU-accelerated method is capable of efficiently detecting the potential collisions of triangulated models. Overall, the GPU-accelerated parallel Devillers’ and Guigue’s triangle-triangle intersection algorithm is recommended when performing practical collision detections between large triangulated models.

The learning process is inseperable from the application of information and communication technology in order to maintain the quality of learning. This study aims to describe the implementation of information and communication technology-based learning in the Fine Arts Expertise Program at Vocational Senior High School (Sekolah Menengah Kejuruan/SMK Negeri 5 Yogyakarta. This research use qualitative approach with case study. Data collection is taken through observation, interviews, and documentation. Data were analyzed qualitatively using the interactive analysis techniques of the Miles and Huberman models with the steps of data collection, data reduction, data display and conclution / verification. The data validity technique is triangulation technique. The results figured out that the Fine Arts Expertise Program at SMK Negeri 5 Yogyakarta had implemented Information and Communication Technology (ICT) based learning using multimedia presentations, computer equipment, laptops and LCD projectors, and learning resources from the internet.

Triangulation is an important task in the 3D reconstruction of computer vision. It seems simple to find the position of a point in 3D space when its 2D perspective projections in multi-view images are given and the corresponding camera projection matrices are known. However, in practice, multiple lines in 3D space do not intersect at one point because of noise. Then how to calculate the optimal 3D point of intersection becomes difficult. While there have been multiple methods trying to solve this problem, there is no systematic comparison between them. In this paper, we reviewed various currently existing variants of triangulation method and compared them through extensive experiments. The speed and accuracy of these methods have been compared using both synthetic and real datasets. We presented the results of experi-ments and summarized the advantages, limitations, and applicability of these methods so that to provide a guide for users when they need to choose an appropriate triangulation method for their given applications. Moreover, based on above analysis we proposed an improved method which shows better performance.

Machine learning and statistical methods can help model meteorological phenomena, especially in a context with many variables. However, it is not unusual that the measurement of those variables fails, generating data gaps and compromising data history analysis. The framework combines the predictions provided by three machine learning methods: decision trees, artificial neural networks and support vector machine, together with values calculated through five triangulation methods: arithmetic average, inverse distance weighted, optimized inverse distance weighted, optimized normal ratio and regional weight. Each machine learning algorithm generates eight regression models. One of the machine learning models makes predictions based only on the date. The remaining seven models make predictions based on one weather parameter (max. temperature, min. temperature, insolation, among others), in addition to the respective date. The triangulation methods use the climatic data from three neighboring cities to estimate the parameter of the target city. The generated dataset is, posteriorly, optimized by meta-learning algorithms. The results show that the additional information provided by the new machine learning models and the triangulation methods offered a significant increase in the accuracy of the imputed data. Moreover, the statistical analysis and coefficient of determination R² showed that the meta-learning model based on regression trees successfully combined the base-level outputs to generate outputs that best fill in the missing values of the time series studied in this paper.

Due to pathologies or age-related problems, in some disabled people, motor impairment is associated with cognitive and/or visual impairments. This combination of limitations unfortunately leads to an inability to move around independently. Indeed, their situation does not allow them to use a conventional electric wheelchair, for safety reasons, and for the moment there is no other technological solution providing safe movement capacity. This lack of access to an autonomous travel solution has the consequence of weakening the intellectual, personal, social, cultural and moral development, as well as the life expectancy, of the people concerned. In this context, our team is working on the development of an optoelectronic system that secures the displacement of electric wheelchairs. This is a large project that requires the development of several functionalities such as: the anti-collision of the wheelchair with its environment, the prevention of falls from the wheelchair on uneven levels, and the adaptation of the system mechanically and electronically to the majority of commercially available electric wheelchair models, among others. In this article, we introduce our solution for detecting dangerous height differences, also called “negative obstacles”, through the creation of a dedicated sensor. This sensor works by optical triangulation and can embed several laser beams in order to extend its detection zone. It has the particularity of being robust in direct sunlight and rain and has a sufficiently high measurement rate to be suitable for the displacement of electric wheelchairs. We develop an adapted algorithm, and point out compromises, in particular between the orientation of the laser beams and the maximal speed of the wheelchair.

Child–Computer Interaction (CCI) is a steadily growing field that focuses on children as a prominent and emergent user group. For more than twenty years, the Interaction Design for Children (IDC) community has developed, extended, and advanced research and design methods for children’s involvement in designing and evaluating interactive technologies. However, as the CCI field evolves, the need arises for an integrated understanding of interaction design methods currently applied. To that end, we analyzed 272 full papers across a selection of journals and conference venues from 2005 to 2020. Our review contributes to the literature on this topic by (1) examining a holistic child population, including developmentally diverse children and children from 0 to 18 years old, (2) illustrating the interplay of children’s and adults’ roles across different methods, and (3) identifying patterns of triangulation in the methods applied while taking recent ethical debates about children’s involvement in design into account. While we found that most studies were conducted in natural settings, we observed a preference for evaluating interactive artifacts at a single point in time. Method triangulation was applied in two-thirds of the papers, with a preference for qualitative methods. Researchers used triangulation predominantly with respect to mainstream methods that were not specifically developed for child participants, such as user observation combined with semi-structured interviews or activity logging. However, the CCI field employs a wide variety of creative design methods which engage children more actively in the design process by having them take on roles such as informant and design partner. In turn, we see that more passive children’s roles, e.g., user or tester, are more often linked to an expert mindset by the adult. Adults take on a wider spectrum of roles in the design process when addressing specific developmental groups, such as children with autism spectrum disorder. We conclude with a critical discussion about the constraints involved in conducting CCI research and discuss implications that can inform future methodological advances in the field and underlying challenges.

The detection of peaks (summits) as the upper parts of mountains and the delineation of their shape is commonly confirmed by inspections carried out by mountaineers. In this study the complex task of peak detection and shape delineation is solved by autometric methodological procedures, more precisely, by developing relatively simple but innovative image-processing and spatial-analysis techniques (e.g., developing inventive variables using an annular moving window) in remote sensing and GIS domains. The techniques have been integrated into automated morphometric methodological procedures. The concepts of peaks and their shapes (sharp, blunt, oblong, circular and conical) were parameterized based on topographic and morphologic criteria. A geomorphologically high quality DEM was used as a fundamental dataset. The results, detected peaks with delineated shapes, have been integratively enriched with numerous independent datasets (e.g., with triangulated spot heights) and information (e.g., etymological information), and mountaineering criteria have been implemented to improve the judgments. This holistic approach has proved the applicability of both highly standardized and universal parameters for the geomorphologically diverse Kamnik Alps case study area. Possible applications of this research are numerous, e.g., a comprehensive quality control of DEM or significantly improved models for the spatial planning proposes.

The purpose of this study is to improve the skills of teachers in making learning videos through iHT activities with the Zoom Cloud Meeting Application. This research is School Action Research (PTS). The research subjects were 18 subject teachers at SMAN 1 Siborongborong. Data collection techniques were observation and documentation techniques. Data validation with triangulation technique. The data analysis method in this study used qualitative data analysis. The results showed that iHT activities with the Zoom Cloud Meeting Application were proven to be able to improve the skills of teachers in making learning videos. Increasing the results of the assessment of the skills of teachers at SMAN 1 Siborongborong making learning videos in the initial conditions with an average score of 45.11 and included in the Less (K) category, increasing in the first cycle with an average value of 70.16 and entering the Enough category (C) and in the second cycle with an average value of 90.95 and included in the Good category (B).

This work describes a concise algorithm for the generation of triangular meshes with the help of standard adaptive finite element methods. We demonstrate that a generic adaptive finite element solver can be repurposed into a triangular mesh generator if a robust mesh smoothing algorithm is applied between the mesh refinement steps. We present an implementation of the mesh generator and demonstrate the resulting meshes via examples.

Passive ground emitter geolocation techniques are essential to electronic warfare systems, as they provide threat warnings in hostile environments, while ensuring the electronic silence of the mission platform. Geolocation of enemy emitters indicates the position of and type of adversary troops, and allows for the use of guided munition against enemy targets. Three-dimensional geolocation solutions based on least squares and particle filter estimation, using only azimuth and elevation measurements, were considered. Three batch-processing and one instantaneous solution algorithms, i.e., using a single pulse or a single observation point, were developed and investigated. The performance of the proposed solutions was demonstrated by simulations. Results showed that the batch-processing solutions achieved acceptable accuracies with a sufficient number of observation points. The performance degraded with fewer observation points. The instantaneous geolocation solution improved performance with increasing observation points, i.e., working in the sequential mode, and therefore could approach the accuracy of the batch-processing solutions.

Copyright © 2021 The Authors. This paper presents a novel work on localization of transmitters using triangulation with sensors at fixed positions. This is achieved when three or more sensors cover the whole area, a factor which enables the system to perform localization via triangulation. The network needs to keep a high detection rate which, in most cases, is achieved by adequate sensor coverage. Various tests using various grids of sensors have been carried out to investigate the way the system operates in different cases using a lot of transmitters. Detection complexity is tackled by finding the optimal detecting sensor radius in order the network to continue operate normally. The coverage quality changes in the area of interest and the network is able to detect new transmitters that might enter it's area. It is also shown that as the number of transmitters increases the network keeps its high performance by using additional groups of sensors in a sub-region area of that of interest. This way, even when the network is saturated by many transmitters in one region, new transmitters can still be detected.

To reconstruct the points in three dimensional space, we need at least two images. In this paper we compared two different methods: the first uses only two images, the second one uses three. During the research we measured how camera resolution, camera angles and camera distances influence the number of reconstructed points and the dispersion of them. The paper presents that using the two-view method, we can reconstruct significantly more points than using the other one, but the dispersion of points is smaller if we use the three-view method. Taking into consideration the different camera settings, we can say that both the two- and three-view method behaves the same, and the best parameters are also the same for both methods.

Despite progress made in the accuracy and robustness of the dense matching technique in past years, efficient occlusion detection remains an open problem. In this paper, we present a two-step occlusion detection method to remove false matches in dense matching fields. First, a statistical dense matching method is developed by considering the correspondence between the grids to identify most occlusion regions. Second, to handle the potential misjudgment match in the occlusion boundary, a double-threshold filtering method is first used to reduce the noise in the grid image, which ensures that the gradient operator can accurately extract the boundary grid in the grid image; then, misjudgment matches in the boundary grid region are corrected based on the triangulation with descriptors. The results of the experiments comparing the proposed method and existing occlusion detection methods by, respectively, using the MPI-Sintel and KITTI datasets’ test sequence show that the proposed method has higher accuracy and better robustness.

The goal of much observational research is to identify risk factors that have a causal effect on health and social outcomes. However, observational data are subject to biases from confounding, selection and measurement, which can result in an underestimate or overestimate of the effect of interest. Various advanced statistical approaches exist that offer certain advantages in terms of addressing these potential biases. However, although these statistical approaches have different underlying statistical assumptions, in practice they cannot always completely remove key sources of bias; therefore, using design-based approaches to improve causal inference is also important. Here it is the design of the study that addresses the problem of potential bias – either by ensuring it is not present (under certain assumptions) or by comparing results across methods with different sources and direction of potential bias. The distinction between statistical and design-based approaches is not an absolute one, but it provides a framework for triangulation – the thoughtful application of multiple approaches (e.g. statistical and design based), each with their own strengths and weaknesses, and in particular sources and directions of bias. It is unlikely that any single method can provide a definite answer to a causal question, but the triangulation of evidence provided by different approaches can provide a stronger basis for causal inference. Triangulation can be considered part of wider efforts to improve the transparency and robustness of scientific research, and the wider scientific infrastructure and system of incentives.

The reconstruction of real-world surfaces is on high demand in various applications. Most existing reconstruction approaches apply 3D scanners for creating point clouds which are generally sparse and of low density. These points clouds will be triangulated and used for visualization in combination with surface normals estimated by geometrical approaches. However, the quality of the reconstruction depends on the density of the point cloud and the estimation of the surface normals. In this paper, we present a novel deep learning architecture for point cloud upsampling that enables subsequent stable and smooth surface reconstruction. A noisy point cloud of low density with corresponding point normals is used to estimate a point cloud with higher density and appendant point normals. To this end, we propose a compound loss function that encourages the network to estimate points that lie on a surface including normals accurately predicting the orientation of the surface. Our results show the benefit of estimating normals together with point positions. The resulting point cloud is smoother, more complete, and the final surface reconstruction is much closer to ground truth.

Triangulation algorithms that conform to a set of non-intersecting input segments typically proceed in an incremental fashion, by inserting points first, and then segments. Inserting a segment amounts to: (1) deleting all the triangles it intersects; (2) filling the so generated hole with two polygons that have the wanted segment as shared edge; (3) triangulate each polygon separately. In this article we prove that these polygons are such that all their convex vertices but two can be used to form triangles in an earcut fashion, without the need to check whether other polygon points are located within each ear. The fact that any simple polygon contains at least three convex vertices guarantees the existence of a valid ear to cut, ensuring convergence. Not only this translates to an optimal deterministic linear time triangulation algorithm, but such algorithm is also trivial to implement. We formally prove the correctness of our approach, also validating it in practical applications and comparing it with prior art.

INTRODUCTION: A novel anchor-free localization technique for a single-hop wireless sensor network is proposed, which is based on internode distances only. The average of the internode distances is mainly used to localize the reference node in the proposed algorithm. Average localization error is used as the main performance metric. The simulation result shows that the proposed algorithm significantly reduces localization error as compared with conventional localization techniques with respect to node density variation and network size. OBJECTIVES: To find the location of the randomly deployed sensor nodes. METHODS: An anchor free localization method is used to find the location of the deployed sensor nodes. RESULTS: Location error is comparatively less in the proposed strategy. CONCLUSION: For single-hop wireless sensor networks using inters node distance, a novel anchor free localization technique is presented.

Damage on the aircraft structure can be caused by lightning strikes, hail, accidental impacts or ageing. Scratches or dents on the aircraft surface are typical indications of impact damage. General visual inspection (GVI) is the primary way in which to detect such forms of damage. The inspection process is time consuming, raises safety concerns for the inspector and is subject to variations due to human factors. Significant inspection automation remains challenging, mainly because GVI requires the critical human ability to assess anomalies. Also, damage specifications in maintenance manuals are influenced by human interpretation. Some automated tools are beginning to be available for aircraft inspection checks. However, none of them are capable of replacing the inspector judgement yet. Humans still need to manually assess the location or the data generated by the tools. Their performance is also affected by different environmental conditions, materials and the overall characteristics of the damage. This review presents the main methods for non-contact visual aircraft inspection, explaining their basic working principles and limitations. Their suitability for automation in aircraft inspection is also discussed.

The purpose of this research was to develop a simple, cost-effective, but enough efficient solution for locating, tracking and distribution analysis of people and/or vehicle flowing, based on non-intrusive Bluetooth sensing and selective filtering algorithms employing artificial intelligence components. The solution provides a tool for analyzing density of targets in a specific area, useful when checking contact proximities of a target along a route. The principle consists of the detection of mobile devices that use active Bluetooth connections, such as personal notebooks, smartphones, smartwatches, Bluetooth headphones, etc. to locate and track their movement in the dedicated area. For this purpose, a specific configuration of three BT sensors is used and RSSI levels compared, based on a combination of differential location estimates. The solution may also be suited for indoor localization where GPS signals are usually weak or missing, for example, in public places such as subway stations or trains, hospitals, airport terminals and so on. The applicability of this solution is estimated to be vast, ranging from travel and transport information services, route guidance, passenger flows tracking, and path recovery for persons suspected to have SARS-COV2 or other contagious viruses, serving epidemiologic enquiries. The specific configuration of Bluetooth detectors may be installed either in a fixed location, or in a public transport vehicle. A set of filters and algorithms for triangulation-based location of detected targets and movement tracking, based on artificial intelligence is employed. When applied in the public transport field, this setup can be also developed to extract additional information on traffic, such as private traffic flowing, or passenger movement patterns along the vehicle route, improved location in absence of GPS signals, etc. Field tests have been carried out for determining different aspects concerning indoor location accuracy, reliability, selection of targets and filtering. Results and possible applications are also presented in the final section of the paper.

There is an ever-increasing need to use an accurate and consistent geometric ground reference in the processing of remotely sensed data products, as this reduces the burden on the end-users to account for the differences between the data products from different missions. In this regard, the U.S. Geological Survey (USGS) initiated an effort to harmonize the Landsat ground reference with the Sentinel-2 Global Reference Image (GRI) to improve the co-registration between the data products of the two global medium-resolution missions. In this paper, we discuss the process, results, and the improvements expected from this harmonization of two ground references using space-triangulation-based bundle adjustment techniques. The ground coordinates of the Landsat reference library, consisting of five million Ground Control Points (GCPs) were adjusted in a series of four simultaneous bundle block adjustments using thousands of Landsat-8 (L8) scenes anchored with more than 300,000 control points extracted from the GRI dataset. The net adjustments to each of the four blocks, namely, Australia, Americas, Eurasia, and Islands, varied anywhere from 1 to 13 m, depending on the accuracy of the GCPs in these blocks. The use of the GRI dataset in our bundle adjustment not only improved the absolute accuracy of the Landsat ground reference, but will also improve the co-registration between Sentinel-2 and Landsat terrain corrected products, as the European Space Agency plans to process the Sentinel-2 products using the GRI dataset. Independent validation of the Landsat products processed using harmonized GCPs with the GRI dataset indicated a global misregistration error of less than 8 m Circular Error Probable at 90 % (CE90), an improvement from the 25 m prior to harmonization. The improvements to the Landsat products using the harmonized GCPs are expected to be available to the public as part of Landsat Collection-2 processing by the end of 2020.

This paper proposes a novel method to reconstruct hierarchical 3D tree models from Mobile Laser Scanning (MLS) point clouds. Starting with a neighborhood graph from the tree point clouds, the method treats the root point of the tree as a source point and determines an initial tree skeleton by using the Dijkstra algorithm. The initial skeleton lines are then optimized by adjusting line connectivity and branch nodes based on morphological characteristics of the tree. Finally, combined with the tree point clouds, the radius of each branch skeleton node is estimated and flat cones are used to simulate tree branches. A local triangulation method is used to connect the gaps between two joint flat cones. Demonstrated by street trees of different sizes and point densities, the proposed method can extract street tree skeletons effectively, generate tree models with higher fidelity, and reconstruct trees with different details according to the skeleton level. It is found out the tree modeling error is related to the average point spacing, with a maximum error at the coarsest level 6 being about 0.61 times the average point spacing. The main source of the modeling error is the self-occlusion of trees branches. Such findings are both theoretically and practically useful for generating high-precision tree models from point clouds. The developed method can be an alternative to the current ones that struggle to balance modeling efficiency and modeling accuracy.

Geometry processing of surface meshes relies heavily on the discretization of differential operators such as gradient, Laplacian, and covariant derivative. While a variety of discrete operators over triangulated meshes have been developed and used for decades, a similar construction over polygonal meshes remains far less explored despite the prevalence of non-simplicial surfaces in geometric design and engineering applications. This paper introduces a principled construction of discrete differential operators on surface meshes formed by (possibly non-flat and non-convex) polygonal faces. Our approach is based on a novel mimetic discretization of the gradient operator that is linear-precise on arbitrary polygons. Equipped with this discrete gradient, we draw upon ideas from the Virtual Element Method in order to derive a series of discrete operators commonly used in graphics that are now valid over polygonal surfaces. We demonstrate the accuracy and robustness of our resulting operators through various numerical examples, before incorporating them into existing geometry processing algorithms.

[EN] Triangulation is a surveying method on which earlier maps made were based. Although the origins of the method can be traced back to the 16th century, it is still used today, with minor changes, to adjust networks observed with modern geodetic techniques. In this paper we present the geodetic survey work that was carried out for the primary triangulation network of the first 1:500 urban map of the city of València (Spain). It spanned from 1929 to 1944 and resulted in 421 maps covering about 174 square kilometres. We focus on four key elements to define the geometric framework of a map: (1) the geodetic network, (2) the cartographic projection, (3) the baseline measurements, and (4) the primary triangulation. The paper is based on the interpretation of original documents and field books recovered from the archives of the València City Council. In order to check the accuracy and consistency of the survey work, we recomputed all calculations directly from the field data, following the mathematical procedures of the time. We obtained a set of transformation parameters to convert the coordinates of 1929 to current coordinates based on the European Terrestrial Reference System of 1989 (ETRS89). Results showed that the 1929 primary triangulation angles and coordinates are accurate to 8 s of arc and 35 cm respectively, and that the coordinates transform well into the current reference system with average residuals of 26 cm across nine control points, demonstrating the high quality of the 1929 work.

Purpose: The article presents the usefulness issues of presented information on information and business internet services. The article presents a comparative analysis and an applicability analysis of information usefulness evaluation methods for textual and graphic forms of content presentation on the example of business internet services. Design/Methodology/Approach: The study describes the basic methodological assumptions, the research evaluation procedure of information usefulness and various forms of informational content presentation, and also the results of data analysis from the study conducted on a group of respondents. In order to determine the factors, that have the greatest impact on information usefulness evaluation of various forms of content presentation, the data obtained from the study using various methods such as online questionnaire, usability testing and heuristic analysis were compared and subjected using multi-criteria SAW method. Findings: Results of research presented in the article can be useful in creating assumptions for ways of content presentation and visualization on websites and continuous improvement of their functional quality and also consequently on the perception by customers, sellers and owners of these websites., peer-reviewed

In this paper, we study real-world performance of Sigfox, which is one of the most mature Low-Power Wide-Area Network (LPWAN) technologies that operate in unlicensed frequency bands. During an extensive measurement campaign conducted over three months in the city of Brno, Czech Republic, we assessed the communication performance and the radio channel properties in 311 different test locations. We observed that despite the challenging natural landscape and urban environment of the test area, more than 94% of the packets sent were received successfully, with at least one packet delivered from 297 out of 311 tested locations. Our results also reported experiment-based radio channel and signal-to-noise characterization as well as provided insights into the efficiency of two crucial mechanisms used by Sigfox to improve the packet delivery - packet repetition and multi-gateway reception. Finally, we employed our experimental data to understand the efficiency of two non-fingerprint localization methods based on received signal strength indicator in a practical Sigfox network. acceptedVersion

We derive explicit closed-form matrix representations of Hamiltonians drawn from tensored algebras, such as quantum spin Hamiltonians. These formulas enable us to soft-code generic Hamiltonian systems and to systematize the input data for uniformly structured as well as for un-structured Hamiltonians. The result is an optimal computer code that can be used as a black box that takes in certain input files and returns spectral information about the Hamiltonian. The code is tested on Kitaev's toric code deployed on triangulated surfaces of genus 0 and 1. The input file corresponding to the minimal triangulation of genus 2 is also supplied., optimized code can be executed on a laptop

Currently, the submission guidelines for the Journal of Cheminformatics say it will “only publish research or software that is entirely reproducible by third parties.” They go on to specify that being reproducible means that anything essential to the conclusion of the paper be freely accessible and states that source code must be provided. I submit that this definition of reproducibility is too narrow—that a cheminformatics method can only truly be replicated by reimplementing it from a detailed, step-by-step high-level description to determine how reliably the algorithm per se does what it is intended to do.

Surface remeshing is widely required in modeling, animation, simulation, and many other computer graphics applications. Improving the elements’ quality is a challenging task in surface remeshing. Existing methods often fail to efficiently remove poor-quality elements especially in regions with sharp features. In this paper, we propose and use a robust segmentation method followed by remeshing the segmented mesh. Mesh segmentation is initiated using an existing Live-wire interaction approach and is further refined using local mesh operations. The refined segmented mesh is finally sent to the remeshing pipeline, in which each mesh segment is remeshed independently. An experimental study compares our mesh segmentation method as well as remeshing results with representative existing methods. We demonstrate that the proposed segmentation method is robust and suitable for remeshing.

For the purpose of coordinate transformation between two different horizontal geodetic data, the inherited one, the Croatian State Coordinate System (HDKS) and the new (official) one, Croatian Terrestrial Reference System 1996 (HTRS96) utilizing seven parameters coordinate transformation (Bursa–Wolf model) and distortion model, three methods of residual filtering were introduced in this paper, using our own developed algorithms. Each algorithm is based on a different ratio: the ratio of resultant residual and surface function of point’s environment, the ratio of difference and mutual distance of neighboring resultants in the area, and the ratio of difference and mutual distance of neighboring resultants in tangential plane. Thus, the concept of the theoretical residuals has been introduced, as well as the idea of semi–iterative procedure that is conducted through the automatization of filtering in spatial or just in plane sense and operates on the principle of a combination of classic Bursa–Wolf transformation and TIN tessellation under the terms of Delaunay’s triangulation and Voronoi’s polygons.

The developed subsystem of visual evaluation of triangulation models is presented. It is included in the system of technological planning of complex products manufacturing by additive technologies. This computer system allows to evaluate workability of industrial product and analyse the effectiveness of its production using additive technologies. It is proposed to perform an analysis of triangulated model of a complex product by colour visualizing of its representation on triangulated model of sphere and setting the colour scale of the correspondence to investigated characteristic of faces. The condition for mapping onto the sphere is the determination of inclination angles of faces vectors of the triangulation product model in the spherical coordinate system into the values range of a certain triangular face of the sphere model. Examples of workability evaluation based on analysis of spherical reflected of the original 3D model of product are considered. The proposed approach can significantly increase information capacity level in design development and visually determine possibility of rational product orientation in working space of layer-by-layer installation.

Background: Traditional evaluation methods are not keeping pace with rapid developments in mobile health. More flexible methodologies are needed to evaluate mHealth technologies, particularly simple, self-help tools. One approach is to combine a variety of methods and data to build a comprehensive picture of how a technology is used and its impact on users. Objective: This paper aims to demonstrate how analytical data and user feedback can be triangulated to provide a proportionate and practical approach to the evaluation of a mental wellbeing smartphone app (‘In Hand’). Methods: A three-part process was used to collect data: 1) app analytics; 2) an online user survey; and 3) interviews with users. Findings: Analytics showed that >50% of user sessions counted as ‘meaningful engagement’. User survey findings (N=108) revealed that In Hand was perceived to be helpful on several dimensions of mental wellbeing. Interviews (N=8) provided insight into how these self-reported positive effects were understood by users. Conclusions: This evaluation demonstrates how different methods can be combined to complete a real-world, naturalistic evaluation of a self-help digital tool and provide insights into how and why an app is used and its impact upon users’ wellbeing. Clinical implications: This triangulation approach to evaluation provides insight into how wellbeing apps are used and their perceived impact on users’ mental wellbeing. This approach is useful for mental healthcare professionals and commissioners who wish to recommend simple digital tools to their patients and evaluate their uptake, use and benefits.

We study a combinatorial game named “sankaku-tori” in Japanese, which means “triangle-taking” in English. It is an old pencil-and-paper game for two players played in Western Japan. The game is played on points on the plane in general position. In each turn, a player adds a line segment to join two points, and the game ends when a triangulation of the point set is completed. The player who completes more triangles than the other wins. In this paper, we formalize this game and investigate three restricted variants of this game. We first investigate a solitaire variant; for a given set of points and line segments with two integers t and k, the problem asks if you can obtain t triangles after k moves. We show that this variant is NP-complete in general. The second variant is the standard two player version, but the points are in convex position. In this case, the first player has a nontrivial winning strategy. The last variant is a natural extension of the second one; we have the points in convex position but one point inside. Then, it turns out that the first player has no winning strategy.