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How do we judge others' behavior when they are bothThe online version contains supplementary material available at 10.1007/s11166-022-09396-7.

While online experimentation is becoming increasingly popular in psychology, implementing real-time interaction between participants in online studies remains uniquely challenging, as it requires researchers to have advanced programming skills, or to purchase expensive third-party services. These challenges prevent many psychologists and other social scientists from utilizing online methods when they wish to study a vast array of social behaviors and interpersonal decision-making. SMARTRIQS is a free and open-source application that fills in this crucial gap in contemporary experimental research methods. SMARTRIQS offers researchers the ability to design surveys that feature real-time interaction between participants—including live text chat—without requiring re-searchers to learn any programming language, install any software, or pay for any third-party services. This paper provides researchers a practical guide to SMARTRIQS and shows them howto turn regular (non-interactive) online surveys into fully interactive experiments. The paper not only provides a comprehensive guide to designing interactive studies in SMARTRIQS in general but also walks readers through the step-by-step instructions for setting up a particular study (Dictator Game with chat). The tutorial starts from the very basics, assuming no prior expertise in online experimentation, and is accessible to everyone, even those who are less—or not at all—familiar with Qualtrics.

Aerial surveys have always significantly contributed to the accurate mapping of certain geographical phenomena. Remote sensing opened up new perspectives in nature monitoring with state-of-the-art technical solutions using modern onboard recording equipment. We developed the technical background and the methodology that supports detailed and cost-effective monitoring of a network of natural areas, thereby detecting temporal changes in the spatial pattern of land cover, species, biodiversity, and other natural features. In this article, we share our experiences of the technical background, geometric accuracy and results of comparisons with selected Copernicus Land Monitoring products and an Ecosystem Map based on the testing of our methodology at 25 sites in Hungary. We combined a high-spatial-resolution aerial remote sensing service with field studies to support an efficient nature conservation monitoring network at 25 permanent sites. By analyzing annually (or more frequently) orthophotos taken with a range of 0.5–5 cm spatial resolution and 3D surface models of aerial surveys, it is possible to map the upper canopy of vegetation species. Furthermore, it allows us to accurately follow the changes in the dynamics at the forest edge and upper canopy, or the changes in species’ dominance in meadows. Additionally, spatial data obtained from aerial surveys and field studies can expand the knowledge base of the High-Resolution Aerial Monitoring Network (HRAMN) and support conservation and restoration management. A well-conducted high-resolution survey can reveal the impacts of land interventions and habitat regeneration. By building the HRAMN network, nature conservation could have an up-to-date database that could prompt legal processes, establish protection designation procedures and make environmental habitat management more cost-effective. Landscape protection could also utilize the services of HRAMN in planning and risk reduction interventions through more reliable inputs to environmental models.

International audience; There is a growing demand in the last years for farm-level sustainability data reflected in various initiatives from farmers, science and food industries. An alternative to creating new tools and indicator assessment frameworks is to further develop existing farm monitoring systems, such as the EU-wide Farm Accountancy Data Network (FADN), towards inclusion of sustainability-related data. This article reports on a study carried out within the EU-project FLINT comparing indicators for pesticide costs, application quantity and pesticide toxicity calculated for 416 farms in four EU countries (France, Germany, Hungary, Poland). The farm sample was a non-representative subsample of the national FADN samples in these countries. Major focus of the comparison was to analyse the suitability of the indicators for implementation in a large so-far primarily economic farm-level monitoring system, such as the FADN. The FADN currently includes farm-level expenditure for crop protection as the only indicator with reference to pesticides. We show that it is possible to extend the current FADN with reasonable effort towards indicators for pesticide application quantity (pesticide usage, treatment index) and pesticide toxicity (here exemplarily used: lethal dose 50 in rats), while the data demands of more elaborated indicators could not be met with the current system. The correlation between indicators, reflecting the extent to which indicators come to the same conclusion, was small between pesticide costs and pesticide usage or toxicity, thus the use of pesticide costs as an ecological indicator, as was done in other studies, cannot be recommended. A combined consideration in the FADN system of pesticide quantity and toxicity, which showed moderate correlation, could be a suitable approach instead.

We have been looking for a safe and economical technique for making an Electronic Terrain and Obstacle Data collection (eTOD). We have developed a method and a quality assurance system which covers the complete process from making an aerial survey to data processing. In addition to presenting the method, the article focuses on the dependence of the aerial photogrammetric obstacle survey on spatial resolution. We have found that the most effective way of making an obstacle database is by making a passive aerial remote sensing, which is supported by a high-speed (200–600 km/h) fixed-wing aircraft. The high-speed aerial camera systems with vertical and oblique camera axis are more accurate and more aerial triangulation can be used with them than with classic single camera solutions. The carefully planned flights for fixed-wing platforms provide a stable camera position and the homogeneous shooting network more easily, and obstruct the air transport for less time. In most cases, a terrestrial survey in itself does not allow the creation of the eTOD within a reasonable time frame and with complete safety, because of hard-to-reach areas, subjectivity and slow traversal in the field.

SMARTRIQS is an open-source solution that allows researchers to design and implement interactive online experiments using the popular survey platform Qualtrics. Unlike other existing platforms that allow real-time interaction, SMARTRIQS does not require any programming skills or installing any software. SMARTRIQS is fully integrated into Qualtrics: researchers create and edit their interactive experiments in the standard survey editor after importing the generic SMARTRIQS survey template. Moreover, all data resulting from real-time interaction are saved in Qualtrics. The potential applications of SMARTRIQS in experimental economics and finance are very versatile, including but not limited to experiments featuring cooperation, coordination, competition, allocation, investment, auction, and other market interactions. Researchers working in related fields (organizational research, consumer research, decision science, social psychology, political science, etc.) might also benefit from using SMARTRIQS, as it offers a convenient and simple method of studying real-time social interaction, including communication, collaborative work, collective decision-making, and voting behavior.

A dose distribution map can be created using geographic information system (GIS) methods from sensor data that do not provide image information in a classical way. The results of discrete radiation measurements can be properly represented in a uniform raster above the surface. If the radiation measured at each site does not show a jump-like change, a dose distribution map can be prepared by interpolating the measured values. The coordinates of the measuring points can be used to calibrate the map. The calibrated and georeferenced map is suitable for locating hidden or lost radiation sources or for mapping active debris scattered during a possible reactor accident. The advantage of the developed method is the measurement can be performed with a small multicopter, cost-effectively, even without human intervention. The flight time of small multicopters is very limited, so it is especially important to increase the efficiency of the measurement. During the experiments, a practical comparison of several methods was made with regard to the measurement procedure. Similarly, based on the measurement experience, the detector system was further developed and tested in three main steps. A system was developed with a detector system with a total weight of 500 g, including a battery capable of operating the detector for at least 120 min. The device is capable of detecting an average of 30 events/min at of 0.01 μSv/h background radiation. Experiments have shown that the system is able to significantly detect a source with an activity of 300 μSv/h by scanning above 10 m ground level.

In this chapter we summarize how economists conceptualize beliefs. Moving both backward and forward in time, we review the way that mainstream economics currently deals with beliefs, as well as, briefly, the history of economists’ thinking about beliefs. Most importantly, we introduce the reader to a recent, transformational movement in economics that focuses on belief-based utility. This approach challenges the standard economic assumption that beliefs are only an input to decision making and examines implications of the intuitive idea that people derive pleasure and pain directly from their beliefs. We also address the question of when and why people care about what other people believe. We close with a discussion of the implications of these insights for contemporary social issues such as political polarization and fake news.

Going to the gym is likely to be judged more positively if it is known that the gym-goer is vaccinated against COVID-19 than unvaccinated. We investigate how people make sense of vaccination-contingent behaviors --- behaviors, such as going to the gym or a bar, which are judged differently depending on the target's vaccination status. We find that appropriateness and riskiness judgments deviate substantially from a normative benchmark in which judgments increase linearly with the probability of vaccination. Specifically, participants who are told nothing about the target judge these targets similarly to individuals known to be fully vaccinated. By contrast, informing participants that they do not know the target's vaccination status, leads to evaluations that are notably more disparaging.

Organizations strive to encourage curiosity, seeking employees who are open to asking questions and intrinsically motivated to find answers, i.e., who display curiosity traits. We argue that situational determinants are stronger predictors of information-seeking behaviors than traits. Situational curiosity is transient, and while people may be tempted by immediate answers, they may be less motivated when they need to wait for information. In a preregistered experiment (N = 1,245) featuring real effort and incentives, we find that a small change in the schedule of information provision—delaying performance feedback by 24–48 hours—reduces participants’ willingness to obtain this information by 24%. The effect of this short delay is at least three times stronger than a one-standard-deviation difference in trait openness. This reduction cannot be explained by standard models of time discounting or the goal gradient hypothesis, as an identical delay in monetary rewards reduces participants’ efforts by only 3%.

6 pags., 2 figs., Matrix product states and projected entangled pair states (PEPS) are powerful analytical and numerical tools to assess quantum many-body systems in one and higher dimensions, respectively. While matrix product states are comprehensively understood, in PEPS fundamental questions, relevant analytically as well as numerically, remain open, such as how to encode symmetries in full generality, or how to stabilize numerical methods using canonical forms. Here, we show that these key problems, as well as a number of related questions, are algorithmically undecidable, that is, they cannot be fully resolved in a systematic way. Our work thereby exposes fundamental limitations to a full and unbiased understanding of quantum many-body systems using PEPS., This project has received funding from the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation programme (Grants No. 648913 and No. 636201). S. I., D. P. G., and G. S. acknowledge financial support from MINECO (Grants No. MTM2014-54240-P and No. MTM2017- 88385-P), CAM research consortium QUITEMAD-CM (Grant No. P2018/TCS-4342), and Severo Ochoa Project No. SEV-2015-556. S. I. also acknowledges funding by the Ministerio de Ciencias, Innovacion y Universidades, PGC2018-095862-B-C22 (Spain) and by Quantum CAT (001-P-001644), Generalitat de Catalunya, and María de Maeztu Project No. CEX2019-000918-M (Spain). J. J. G. R. acknowledges financial support from MINECO Project No. FIS2015-70856-P, CAM research consortion QUITEMAD-CM Grant No. P2018/TCS-4342, MINECO research network FIS2016-81891-REDT. A. M., Y. G., and N. S. acknowledge support from the DFG (German Research Foundation) under Germany’s Excellence Strategy (EXC2111-390814868).

Soil carbon management practices are those that add and maintain organic carbon in the\ud soil. These agricultural practices can potentially both contribute to climate change\ud mitigation and increase the soil's resilience to physical and biological stresses. The paper\ud draws on research findings from five regions across Europe to identify regionally-specific\ud barriers to and opportunities for the adoption of soil carbon management practices. Data\ud were derived from 50 interviews with policy-makers and advisers and 5 stakeholder\ud workshops in Denmark, Italy, Hungary, Poland and Spain. Several barriers to the uptake of\ud soil carbon management practices were common across all regions, however, regional\ud variations were also identified highlighting the importance of understanding the context\ud into which these practices are introduced. Key barriers related to existing biophysical\ud conditions, lack of financial support, farmer knowledge and experience, and the quality of\ud the advisory service. Opportunities included providing economic incentives, harmonising\ud regulation, supporting long term thinking and planning for resilience and providing good\ud quality advice. We conclude that in addition to persuasive mechanisms for encouraging the\ud adoption of these practices, what is required is a more process-oriented approach that\ud focuses on a series of experiential changes and fosters farmer learning through interactive\ud models of communicative intervention.

This paper introduces a solution to stand-alone system based, real-time object-detection, can efficiently facilitate the search for missing persons with an unmanned aerial vehicle. The challenge is the real-time implementation of the systems and training the given deep neural network for the desired task. The paper describes the methods and procedures currently in use, as well as the possible tools. Subsequently, the autonomous aircraft system, which carries a real-time detection system, is introduced. In the section about real-time detection, we will introduce the TensorFlow lite-based application, building on SSD topology, in detail, which was implemented on mobile phones. We will also introduce the dataset used for training, testing and the results achieved. In summary, the recall achieved is 65.4% and precision is 96.4%, besides the fact that the android-based application, using the phone’s camera, performs image analysis at a rate of 11 to 17 FPS in real-time, while continuously providing

In this paper, we go around two completely different levels of program design of a biomechanical program. First, the broadest level is the data level, where we show that we can use the whole world’s data. This is covered by the System of Systems engineering. The second and most particular level is the algorithm level. Our goal is to achieve the fastest program run we can. For this, we overview the possibilities and show an example of how a parallel paradigm accelerates our program.

High altitude aerial surveys have the potential to improve disturbance-free data collection in wildlife research, but previously, bird species were not recognizable in high-altitude orthophotos. This method of aerial surveying is effective and can be repeated frequently due to its low cost, it also has the additional advantage of being able to monitor the status of protected areas. In the case of waterbirds, due to the low vegetation coverage, aerial remote sensing is an exceptionally effective technique for surveying populations and detecting nests. Aerial surveys made at low altitudes can cause serious stress for birds. The method we developed and employed is unlikely to be detected by either ground-based or nesting birds but is far more reliable compared to the low-resolution imaging methods and to the evaluation of non-georeferenced photo series. The modern sensors and photogrammetric procedures enable the use of the present method worldwide, furthermore, the large-scale ortho image-derived information has become obtainable more frequently. Direct georeferencing makes the field geodetic survey unnecessary. Orthophotos with a 0.7 cm spatial resolution allow us to reliably identify even the individuals of smaller species, and by the use of oblique images, they can be tracked from two or four different directions.

These days a lot can be heard about special weapons which accelerate the projectile not based on the traditional, chemical energy release, but providing the muzzle velocity with the help of electromagnets. In English terminology, many descriptions can be read about these devices, referred to as “coilgun”. There are so many hobbyist and amateurs who make these devices [1,2] and publish their results on the internet [3,4]. The purpose of the project is dual. On one hand, features, advantages, disadvantages and the limits of the electromagnetically accelerated weapons can be found by building an experimental tool. On the other hand, it was intended to point out the fact that anybody can build such a tool using commercially available commercial components. Although the muzzle energy of the device presented in this paper is not more than 6.8J, but it can cause serious injury. The paper also points out that in a similar way, still not using special components, a weapon can be made with a larger (10-20J) muzzle energy.

In the last decade, the rate of the industrial usage of fixed-wing and blended wing aircraft has increased. A 1–2-km2 area can be surveyed by such a drone within 30 to 60 minutes, without any special infrastructure, and this can be repeated at any time. This provides an opportunity to conduct automatized surveys and time series data testing, which can be used as a basis to decide specific processes. The state and the development of the plants can be monitored as well as the spread of pests and the efficiency of the procedures that protect against them. During the surveys, thousands of images are taken of the area, which can be converted to a georeferenced large-sized map within 20 to 40 hours, including post-production and a resolution varying from 0.01 to 0.1 cm/pixel. The paper provides a solution to the industrial post-production of these high-quantity data, in which a deep learning-based automated process using Matlab is presented, including a comparison of the results to the GIS data.

In the last decade modern agriculture used significant resources for automated evaluation. Game damage and crop evaluation and prediction are the main focus of the precision agriculture. At John von Neumann Faculty of Informatics, Óbuda University, Hungary, researchers together with agricultural experts are developing automated evaluation methods for high-resolution survey data. With the locally developed unmanned aerial vehicles (UAVs) the agricultural survey can be easily done for 1-2km2 area from a single flight. The paper presents the detailed method of the early steps of the automated evaluation using Matlab and the comparison of results to the GIS data.

Matrix Product States form the basis of powerful simulation methods for ground state problems in one dimension. Their power stems from the fact that they faithfully approximate states with a low amount of entanglement, the "area law". In this work, we establish the mixed state analogue of this result: We show that one-dimensional mixed states with a low amount of entanglement, quantified by the entanglement of purification, can be efficiently approximated by Matrix Product Density Operators (MPDOs). In combination with results establishing area laws for thermal states, this helps to put the use of MPDOs in the simulation of thermal states on a formal footing.

While temperature is well understood as an intensive quantity in standard thermodynamics, it is less clear whether the same holds in the presence of strong correlations, especially in the case of quantum systems, which may even display correlations with no classical analogue. The problem lies in the fact that, under the presence of strong correlations, subsystems of a system in thermal equilibrium are, in general, not described by a thermal state at the same temperature as the global system and thus one cannot simply assign a local temperature to them. However, there have been identified situations in which correlations in thermal states decay sufficiently fast so that the state of their subsystems can be very well approximated by the reduced states of equilibrium systems that are only slightly bigger than the subsystems themselves, hence allowing for a valid local definition of temperature. In this work, we address the question of whether temperature is locally well defined for a bosonic system with local interactions that undergoes a phase transition at non-zero temperature. We consider a three-dimensional bosonic model in the grand canonical state and verify that a certain form of locality of temperature holds regardless of the temperature, and despite the presence of infinite-range correlations at and below the critical temperature of the phase transition.

Nowadays, 3D digitization techniques, such as laser scanning and photogrammetry, are the most widespread and frequently used methods for recording and documenting Cultural Heritage monuments. Despite the time and resource consuming data processing, several reasons explain their success, especially the speed of the data acquisition, the high degree of accuracy, and the precision and quality of the output 3D model. In this paper, the 3D documentation of the external facings of the Reformed church of Kližska Nema located in southern Slovakia is discussed. The church was measured using various methods: terrestrial laser scanning, UAV Structurefrom-Motion photogrammetry and GNSS measurements.

We propose an alternative account to the conventional theory of belief homophily--that people have an intrinsic distaste for encountering differences in beliefs. We argue that when people face others who hold beliefs different from their own, they do not find these encounters disturbing because others hold different beliefs per se, but because they are convinced that others hold false beliefs. In five pre-registered studies (N = 2,835, MTurk) featuring self-recalled personal experiences and vignette scenarios, we demonstrate that participants express stronger negative feelings when others hold false beliefs, compared to when others' beliefs are merely different from their own. We also show that higher confidence that others hold false beliefs--but not different beliefs--evokes stronger negative emotions and triggers avoidance behaviors. Finally, we highlight that people are primarily disturbed by others holding false beliefs when the negative consequences of these beliefs might affect someone who they care about.

Nowadays, high resolution aerial or satellite photos can be taken, which can be appropriate for further analyses. Photos can be taken using a satellite, aircraft, a robot drone or even a multicopter. However, generally speaking, every solution results in similarly high-resolution images. Analyses can be conducted on the resulting aerial photos in the light of various criteria, which conditions can be determined by the customer. One such task can be the enumeration of pools built in areas with detached houses, which can constitute the basis for specific data. One of the most obvious automated procedures for the detection of objects is to use neural networks, which utilizing properly chosen teaching samples is subsequently able to decide about individual image parts whether they contain the desired object or not. In spite of a large number of teaching samples, a neural network may give a false-positive or a false-negative result in the image passed over for analysis. These mistakes can occur from the fact that the teaching samples and the photos of the areas examined were not taken in the same season, in the same time of day or that they do not show pools having the same maintenance level. Instead of the further teaching of the network, the mentioned mistakes can be eliminated using classical image analysis methods in a way that the results of individual procedures are fusioned. Such methods may be color coding analysis or Fuzzy-logic analysis based on some property in the image. Fuzzy-logic can be used to detect visual objects if there is a definite, distinctive property, like color range or color depth.

In many cases, there is a need for local authorities to carry out a territorial survey of municipalities. The purpose of surveys may be to refine the data or to verify the information that forms the basis of local taxes. Such data include the possession of private outdoor swimming pools belonging to family houses. The knowledge of the number of pools is important in many ways. Drainage load will increase significantly when pools are drained for which the channel operator needs to prepare. In the same way, filling also has a significant water demand for which the water supplier needs to be prepared. For all these reasons, it is understandable if the local government requests an extra contribution from the pool owners in the form of a tax. Up-to-date and accurate data are important for municipalities. Aerial photography can be used to recognize outdoor pools with ease. With drones, the process is fast and cost-effective. At the same time, the numerical quantification of pools from a large amount of data produced during the photo shoot (high-resolution orthophoto covering the area) is a time-consuming task. The method we have developed can automatically detect basins and to quantify them by using a neural network on orthophotos.

Making the right choice sometimes involves selecting the “lesser of two evils,” and only seeing the chosen option can lead others to misunderstand the decision maker’s intentions. Are decision-makers intrinsically driven to fix this misjudgment by revealing the choice set? If so, why, and what is the effect on the audience? Previous studies could not examine this desire to be understood because the research designs did not isolate the decision to reveal information from the original choice. In two experiments (N=448 pairs), we show that people are willing to pay ex post to reveal their choice set to the recipient, even after a one-shot anonymous interaction with no reputational consequences, and in some cases even when doing so reveals their selfish intentions. We find that this revealing behavior is effective at improving recipients’ rating of their outcome when it signals generous intentions, but not when it signals selfish intentions. The choice to reveal is driven by concern for the beliefs of strangers, but only when revealing signals generous intentions; those who reveal a choice that appears selfish report doing so out of a desire to be or appear honest. And though some people leave a misunderstanding in place when it is self-enhancing to do so, almost no one is willing to create a misunderstanding (by hiding the other option), even when it could conceal selfish behavior.

During their flight, small-sized drones use satelite navigation (the most widespread is GPS). This means that frequent coordinate information can be recorded in the entire duration of the flight with varying frequency according to the type. Several aerial photography applications utilize these data. If the drone is equipped with a sensitive gamma detector the flight coordinates can be assigned to gamma measurement data. These groups of data provide an opportunity during the gamma detector-based scan of an area to determine its radiation distribution. The method can provide help to explore and localize patterns, stored or transported illegally, which exhaust gamma radiation. This paper introduces a system based on practical experiments which makes the localization of small-dose patterns possible as well as the creation of a qualitative gamma radiation map in a given area. The method can be primarily used in terrain circumstances, first and foremost to detect low-activity gamma radiators.

Due to their efficient flight control systems and their camera of high quality modern drones can fly precisely and take aerial photos of high resolution. Although these multi-rotor devices are not able to fly long distances yet, they are very efficient instruments for taking aerial photographs of their proximate environment. As they are able to float and rotate along their vertical axis to a discretionary direction, they can be used for monitoring and taking pictures of a building from several directions. If pictures are taken of a building from all directions with significant overlap (of at least 50%) the 3D reconstruction of the building in a photogrammetric way becomes possible. The reconstructed models do not only contain the spatial forms but also the visualinformation based on the snapshots. As a result of the entire reconstruction a virtual object is gained in the virtual space that can freely be accessed and visible from all directions by enlarging or reducing the size. A virtual collection can be established for monuments, historical buildings or other spectacular objects worth recording. The objects of the collection (buildings) are lifelike and can be perceived and studied by anyone. The 3D models, of course, cannot substitute the photographs of high resolution but they can complement them in the collection.

The power supply of quadcopters is provided for by a battery. Flight time depends on total weight and on battery capacity. The most widespread one is the lithium polymer (LiPo) battery. Its advantage is that it has a high electricity transmission ability and a very good mass-capacity ratio. In case of a critical capacity level it is important for the quadcopter to land as soon as possible. Landing speed however is limited. The so-called vortex wave state (vortex ring state) appears at landing. The vortex ring state was first observed at helicopters. The reason for the phenomenon is that at descent the air flow speed arriving from below at a vertical descent approximates the speed of the air currents generated by the rotors. In this moment, the air flowing through the rotors creates a closed vortex wave and a low-pressure spot is created. In this case, the perfomance of the rotors drops, the quadrocopter might become instable and uncontrollable. This phenomenon can be avoided by limiting descent speed. In the article, I tested how to increase descent speed to be able to land safely as fast as possible, using the least possible energy.

Air pollution in settlements constitutes a rapidly increasing problem. As long as the size and consistence of the pollution in a given settlement are quantitatively unknown, effective counter-measures can not be taken. Air pollution is not static, in other words, it may greatly vary over time. Using this experimental method, the spatial and temporal distribution of a settlement's air pollutants, including their composition, can be exhibited. The components of the pollutants show the type of pollutant emission in a given area. As industrial emission or residential heating may be the source of pollutant emmision, or possibly pollutant emission by vehicles, measures to be taken ensuring protection or the decrease of the quantity of pollutants may vary depending on the nature of the sources. If the components of pollutants refer to features resulting from residential heating, then the solution must be found in the regulation of the materials used for heating. It is typical of very many -mainly economically underdeveloped-settlements that waste prohibited for residential heating, PET bottles, tires, rags, etc, are used. Demonstrating this fact quantitatively may serve as a basis for legal measures. In case of the signs of industrial pollution, naturally, enforcement or tightening technological parameters of the polluting factory will provide a result. As these actions pose a significant financial burden considering the given factory, their enforcement is only possible in possession of well-founded measurement results. Limiting vehicle traffic also has a socially acceptable result only if, based on the type of the pollution, the source can be clearly verified. The developed measurement process is capable of conducting accurate spatial and temporal measurements in possession of various polluting components. During the experiment, typically CO, CO2, NO, NO2, O2 and O3 measurements have been conducted. A spatial coordinate and a time stamp belongs to every measurement point. The results were processed offline following the surveys. The method is capable of archiving the pollution of a given period, as a result, it is possible to make statements concerning the given period and to possibly hold people accountable.

With new methods of 3D model creation, the examination of real objects and natural or artificial formations in virtual space become possible. A precondition is that the models be created along the principles of photogrammetry. The bases of the method introduced in the paper are the precise flight ability of small-sized machines piloted by a robot and a mounted camera with distortion-free optics. Surveys conducted by such devices can be faster and more economical than the usage of conventional aircraft requiring human personnel. As long as all the parameters of the devices are known, it is possible to create a kind of 3D model on which volume calculation can be conducted referring to the real object. In this present paper, we introduce the algorithmic and automatized version of the previous analysis method demanding manual engineering work. The solution can be appropriate for the complete substitution of geodetic field work; it produces faster and more accurate results.

With the spread of photogrammetry processes, photo-based 2D/3D reconstruction became general, in research as well as in the industry. Source images are taken using either a handheld camera or an automated camera fixed to the carrier, a UAV, then they are matched during post-processing. The price of digital microbolometer-based high-resolution (1 megapixel) thermal cameras is currently very high, but these, compared to RGB cameras (16–20 megapixel), are still considered to have very low-resolution, in this way employing photogrammetry in this present case is not feasible. In the article, a novel method developed by us is introduced which by using a low thermal resolution camera (FLIR DUO R), based on which a 3D thermal image can be produced with the help of a camera capable of dual imaging (RGB and Thermal). The work is illustrated using measurements, and post-production was conducted using the MATLAB software. The process is adequate for producing 3D thermal images taken using UAV devices.

Small-sized drones, either having classical fixed-wing design or the so rapidly widespread rotorcraft design, are now revolutionizing the complete work process of aerial surveys. In the paper, we will discuss the possibilities of the quality characteristics of large-scale point cloud processing, already introduced in our previous work, and primarily the reduction of the execution time of the large-point cloud processing presented in our previous work. Based on the work process developed by us, we survey the work area, typically a quarry, using UAVs, and then we create a high resolution 3D point cloud out of the pictures. Then, the time series photos are fitted to each other using the ICP algorithm and we conduct the volume analysis. In the present case, the ICP algorithm and volume calculation were very time-consuming operations, as every 3D model was made up of ~20 million points. The two leading graphics processing unit producers of the market have made the resources of the hardware available for general-purpose calculations. In this way, we can see good opportunity in the implementation of these time-consuming calculations into the target hardware.

The creation of high-resolution thermal images, which cover great areas and which are suitable for area measurements, proves to be a serious challenge. The native resolution of thermal cameras is significantly lower than of cameras operating within the visible light spectrum. Conventional methods, which are capable of producing large, so-called orthophotos from several pictures, cannot be applied for thermal images. However, if specific requirements are met, it is possible to produce an orthophoto from overlapping thermal image mosaics, which contains a larger area. The advantage of the thermal orthophoto is that it displays thermal radiation within the spectrum 7–14 μm, that is invisible to the naked eye, in such manner that the area deemed interesting can be substantially enlarged and distance and area calculation can be conducted on the picture. The developed procedure can be automatized, in this way, this means a process difficulty nearly identical to the creation of orthophotos within the visible light range. During the experiments, an extremely low-resolution (160 * 120 pixel), 35 Megapixel thermal image was created using the data of the thermal sensor, which met other requirements for the orthophoto.

Photogrammetry based 3D model creation provides a new opportunty to survey and to evaluate natural and arificial surface formations. The photos needed for 3D model building can be taken using fixed wing aircraft or multicopters. These machines are more economical and are capable of more precise route tracking than big machines operated by human personnel. Depending on the size of the area (0.5 to 10km2), the survey can be finished within an hour. The volume calculation method is introduced in the paper through the example of an actual, operating mine. Previous, mainly manual but competent analytical tasks, which demand engineering work, can be partly replaced agorithmically. The method may provide more accurate volume results than a conventional geodetic survey, as it builds a model with 10 cm resolution of any examined area or object. Another advantage is that the results are ready within a few hours after beginning the survey, it is not necessary to wait days for accurate volume data.

Tensor networks are generated by a set of small rank tensors and define many-body quantum states in a succinct form. The corresponding map is not one-to-one: different sets of tensors may generate the very same state. A fundamental question in the study of tensor networks naturally arises: what is then the relation between those sets? The answer to this question in one dimensional setups has found several applications, like the characterization of local and global symmetries, the classification of phases of matter and unitary evolutions, or the determination of the fixed points of renormalization procedures. Here we answer this question for projected entangled-pair states (PEPS) in any dimension and lattice geometry, as long as the tensors generating the states are normal, which constitute an important and generic class.

Volume analysis with remote sensing in open cast mines opens up new possibilities as regards the condition survey of mines. This method, not fully replacing conventional geodetic surveys, enables economical and quickly reproducible surveys. By employing this method frequent monitoring of mine production becomes possible. 3D models created by aerial remote sensing may be archived and using them the time-proportional volume change of the mine is analyzable during operation. Using drones (multicopters or fixed wing drones) aerial photos can be made, from which a georeferenced orthophoto and a 3D surface model can be produced based on photogrammetric procedure. The survey takes little time. Being size-dependent, it takes 10 to 40 minutes per 0.5 to 10km2. In this discourse, volume computing is presented with the help of a specific, operating mine. During the experiment, besides determining the current volume of the mine, annual production was also determined. As result of the method, besides the quantitative determination of the production, the exact area of extraction has also been determined. The developed method is an effective supplement to conventional surveying.