Exact Coordinates Research Articles

Carbon capture and storage from energy and industrial emission sources: A Europe-wide supply chain optimisation

Power, steel, cement and refining sectors are currently responsible for the largest shares of carbon dioxide emissions from stationary sources. Carbon capture and storage is envisioned as a key player for decarbonising the power and industry sectors. To achieve a significant penetration of carbon capture and storage technologies, supply chain optimisation has emerged as a crucial research task for designing such complex systems. A Europe-wide carbon capture and storage supply chain is here optimised via a mixed integer linear programming framework. The most significant carbon dioxide emitters (242 power plants, 25 steel mills, 111 cement plants and 59 refineries) are identified on exact geographic coordinates and included as candidates for capture. Capture plants are thoroughly represented in techno-economic terms, considering scale effects and different technological options. Transport and sequestration stages are implemented for either onshore or offshore operation. Different case studies are taken into account to assess carbon capture and storage policies and results determine optimal configurations in terms of costs, scale effects, technology options and network complexity. The minimum CO2 avoidance cost is 52 €/t, which increases by 9% if power plants are excluded from carbon sources. If offshore storage is preferred to onshore, cost raises by about 40%.

Fast and robust mesh arrangements using floating-point arithmetic

We introduce a novel algorithm to transform any generic set of triangles in 3D space into a well-formed simplicial complex. Intersecting elements in the input are correctly identified, subdivided, and connected to arrange a valid configuration, leading to a topologically sound partition of the space into piece-wise linear cells. Our approach does not require the exact coordinates of intersection points to calculate the resulting complex. We represent any intersection point as an unevaluated combination of input vertices. We then extend the recently introduced concept of indirect predicates [Attene 2020] to define all the necessary geometric tests that, by construction, are both exact and efficient since they fully exploit the floating-point hardware. This design makes our method robust and guaranteed correct, while being virtually as fast as non-robust floating-point based implementations. Compared with existing robust methods, our algorithm offers a number of advantages: it is much faster, has a better memory layout, scales well on extremely challenging models, and allows fully exploiting modern multi-core hardware with a parallel implementation. We thoroughly tested our method on thousands of meshes, concluding that it consistently outperforms prior art. We also demonstrate its usefulness in various applications, such as computing efficient mesh booleans, Minkowski sums, and volume meshes.

A benchmark case study for seismic event relative location

Summary ‘Precision seismology’ encompasses a set of methods which use differential measurements of time-delays to estimate the relative locations of earthquakes and explosions. Delay-times estimated from signal correlations often allow far more accurate estimates of one event location relative to another than is possible using classical hypocentre determination techniques. Many different algorithms and software implementations have been developed and different assumptions and procedures can often result in significant variability between different relative event location estimates. We present a Ground Truth (GT) dataset of 55 military surface explosions in northern Finland in 2007 that all took place within 300 m of each other. The explosions were recorded with a high signal-to-noise ratio to distances of about 2°, and the exceptional waveform similarity between the signals from the different explosions allows for accurate correlation-based time-delay measurements. With exact coordinates for the explosions, we are able to assess the fidelity of relative location estimates made using any location algorithm or implementation. Applying double-difference calculations using two different 1-D velocity models for the region results in hypocentre-to-hypocentre distances which are too short and it is clear that the wavefield leaving the source region is more complicated than predicted by the models. Using the GT event coordinates, we are able to measure the slowness vectors associated with each outgoing ray from the source region. We demonstrate that, had such corrections been available, a significant improvement in the relative location estimates would have resulted. In practice we would of course need to solve for event hypocentres and slowness corrections simultaneously, and significant work will be needed to upgrade relative location algorithms to accommodate uncertainty in the form of the outgoing wavefield. We present this data set, together with GT coordinates, raw waveforms for all events on six regional stations, and tables of time-delay measurements, as a reference benchmark by which relative location algorithms and software can be evaluated.

Mathematical Modeling of Non-Stationary Modes of a Helium Liquefier

Dynamic models of a heat exchanger, a turboexpander, a helium phase separator, and a dynamic model of the entire helium liquefaction installation were created. This model is necessary for modeling unsteady operating conditions of a helium liquefier. When creating models for heat exchangers, laws of conservation of energy of flows, heat transfer walls, the core and body of heat exchangers were used along with laws of conservation of energy and mass for the helium phase separator. The system of equations for unknown values in exact coordinates and time is solved by the finite difference method. The obtained results adequately describe the unsteady processes taking place in the installation.

실시간 렌더링 환경에서의 3D 텍스처를 활용한 GPU 기반 동적 포인트 라이트 파티클 구현

This study proposes a real-time rendering algorithm for lighting when each of more than 100,000 moving particles exists as a light source. Two 3D textures are used to dynamically determine the range of influence of each light, and the first 3D texture has light color and the second 3D texture has light direction information. Each frame goes through two steps. The first step is to update the particle information required for 3D texture initialization and rendering based on the Compute shader. Convert the particle position to the sampling coordinates of the 3D texture, and based on this coordinate, update the colour sum of the particle lights affecting the corresponding voxels for the first 3D texture and the sum of the directional vectors from the corresponding voxels to the particle lights for the second 3D texture. The second stage operates on a general rendering pipeline. Based on the polygon world position to be rendered first, the exact sampling coordinates of the 3D texture updated in the first step are calculated. Since the sample coordinates correspond 1:1 to the size of the 3D texture and the size of the game world, use the world coordinates of the pixel as the sampling coordinates. Lighting process is carried out based on the color of the sampled pixel and the direction vector of the light. The 3D texture corresponds 1:1 to the actual game world and assumes a minimum unit of 1m, but in areas smaller than 1m, problems such as stairs caused by resolution restrictions occur. Interpolation and super sampling are performed during texture sampling to improve these problems. Measurements of the time taken to render a frame showed that 146 ms was spent on the forward lighting pipeline, 46 ms on the defered lighting pipeline when the number of particles was 262144, and 214 ms on the forward lighting pipeline and 104 ms on the deferred lighting pipeline when the number of particle lights was 1,024766.

Modelling Taxi Drivers’ Behaviour for the Next Destination Prediction

In this paper, we study how to model taxi drivers’ behavior and geographical information for an interesting and challenging task: the next destination prediction in a taxi journey. Predicting the next location is a well-studied problem in human mobility, which finds several applications in real-world scenarios, from optimizing the efficiency of electronic dispatching systems to predicting and reducing the traffic jam. This task is normally modeled as a multiclass classification problem, where the goal is to select, among a set of already known locations, the next taxi destination. We present a Recurrent Neural Network (RNN) approach that models the taxi drivers’ behavior and encodes the semantics of visited locations by using geographical information from Location-Based Social Networks (LBSNs). In particular, the RNNs are trained to predict the exact coordinates of the next destination, overcoming the problem of producing, in output, a limited set of locations, seen during the training phase. The proposed approach was tested on the ECML/PKDD Discovery Challenge 2015 dataset—based on the city of Porto—, obtaining better results with respect to the competition winner, whilst using less information, and on Manhattan and San Francisco datasets.

Smart Traffic Accident Monitoring System

A system which detects the occurrence of accidents and informs the respective units responsible is designed. When a vehicle meets an accident then the sensors installed in the vehicle detect the accident and inform the medical unit, police control as well as family members by sending an alert message to the fire station (in case if the vehicle catches fire during the accident). To avoid accidents due to collision in winters because of FOG, ultrasonic sensors to detect the nearby objects and produce sound if it gets too close are used. Vibration sensor installed will detect the changes in vibration and if it is above threshold which means an accident occurred and it will notify the respective units. The alert message contains accident location coordinates obtained by the GPS module which was sent to respective units through the GSM module. Designed system is fully automated therefore it would get the exact location coordinates of the accident spot.

Deployment of Li-Fi in indoor positioning systems

The number of connected devices is rapidly increasing and the radio spectrum is not enough, but the visible light spectrum is broad enough to accommodate all the devices. Radio waves cause signal distortion which harms the efficiency of the system, but light rays are less prone to signal distortion. The purpose of this research is to establish efficient Li-Fi one-way communication and to derive a mathematical formula for finding exact coordinates of the object by utilizing some 3D geometrical concepts. The proposed model in this paper is responsible for finding the exact coordinates of the object irrespective of the physical architecture of the indoor area. This research uses only 10 bytes of data packet size for accurate positioning in an area that can accommodate more than 1000 transmitters. The accuracy received in indoor positioning using the mathematical formulas prescribed here is up to 6 cm, which is a benchmark in the field of indoor positioning.

Efficient method for detecting a zero-phase point in off-axis circular fringe projection profilometry

Off-axis circular fringe projection profilometry (OCFPP) is a kind of recently proposed three-dimensional (3D) measurement technique. Coordinates of the zero-phase point is an indispensable parameter for the application of OCFPP. As the zero-phase point is virtual, calculation of its coordinates is a key problem to be solved. To efficiently and accurately calculate the coordinates of the zero-phase point, a compound method is put forward in this paper. Firstly, a method is proposed to detect the coarse coordinates of the zero-phase point with the aid of the property of the phase distribution; then, a fast searching strategy is presented to efficiently detect the exact coordinates. The coarse coordinates provide a reasonable center for the following fast searching. The foundation of the fast searching strategy is laid with the aid of a constructed mathematical model and computer simulation. Benefits of the compound method are twofold: firstly, it makes it possible to locate the searching center without usage of an additional ruler; secondly, it significantly improves the efficiency of detecting the zero-phase point while keeping the accuracy. Experiments confirm the advantages of the proposed method.

Dynamic Inefficiency and Spatial Spillovers in Dutch Dairy Farming

AbstractThis article examines the presence of spatial spillovers in farms’ dynamic technical inefficiency scores using Data Envelopment Analysis and a second‐stage spatial truncated bootstrap regression model. Dynamic inefficiency is measured in terms of variable input contraction and gross investment expansion, while the second‐stage model allows an individual’s dynamic inefficiency to be influenced by both own and neighbours’ characteristics. The empirical application focuses on the panel data of specialised Dutch dairy farms observed over the period 2009–2016 and for which exact geographical coordinates of latitude and longitude are available. The results confirm the existence of spatial spillovers in farmers’ dynamic technical inefficiency levels. Although changes in neighbours’ subsidies do not significantly influence an individual’s inefficiency, an increase in neighbours’ age reduces an individual’s performance, while an increase in neighbours’ levels of intensification improves an individual’s dynamic efficiency.

Robust Segmentation of Building Planar Features From Unorganized Point Cloud

This paper presents a novel method for segmentation of planar feature from unorganized point cloud based on 2D Hough Transform and octree. Given the input point cloud, three steps are performed to segment planar features. Firstly, the original point cloud is sampled and projected to the X-Y plane, and an extended 2D Hough transform algorithm is employed to extract the line segments. The selecting weight iteration method is used to calculate line equations and endpoint coordinates of those line segments. The space geometric equations of the vertical planes are then determined. Secondly, the octree structure of the original point cloud is established, and then the exact endpoint coordinates of the line segment are used to design a cube perpendicular to the X-Y plane and all points held by the cube are extracted. The distance from each of the extracted points inside the cube to its corresponding facade is calculated, if the distance is less than the predefined threshold, the point is regarded as a point inside the facade. Finally, all the facade points are removed from the original point cloud, and remaining point cloud is sampled and projected to the X-Z plane. The above process is repeated to extract horizontal planes. Evaluation experiments are performed by analyzing the performance of our method in four different scenes. The experimental results indicate that the proposed algorithm is suitable for segmentation of building planar features in different scenes. A comparison with competing techniques shows that our approach is considerably faster and scales significantly better than previous ones.

ФОРМИРОВАНИЕ СМЫСЛА ДРАМАТУРГИЧЕСКОЙ РЕЧИ

Specific ways of forming the meaning of a dramaturgic phrase lie in its basic characteristics, its ontology. There are three stages of the formation of its meaning. The first stage is the text of the play, which in many ways determines the semantic basis of the future performance as a whole and of each single phrase in particular. The second stage is the work of a Director who, based on the text of the play, forms the overall aesthetic concept of the future performance and about the performance as a multicode entity, defines the principles of work for the specialists in such semiotic systems, as the material/object world of the stage, scenery, light, color, music, noise. The Director forms the concept of the chronotope of the virtual world of the performance and the general concept of each character for the performer. The third stage is the work of the actor, who is the key instance in shaping the meaning of the play as a whole and each of its phrases separately. The key communicative role of an actor is not described in the traditional multicode understanding, but in the aspect of space-and-time correlation of the virtual world of the performance presented on the stage, and and the social space-and-time space of the viewer. The viewer identifies himself with a particular character and simultaneously exists in two worlds: a virtual world of the play and the world of his own life. One can get acquainted with the performance in different ways, but one can watch the performance only where and when it takes place. In the system of the chronotope categories and in the system of social space the semantics of the same verb is described differently. The mandatory connection of the performance with the exact coordinates of the social space-time inevitably adds a socio-political aspect; it makes the play part of people’s life, making the theater one of the main components of the communicative environment of society, and functionally bringing it closer to traditional media.

Analysis of saline land and determination of the level of salinity of irrigated lands with use of the geographic information system technologies

In Uzbekistan, more than half of population lives in rural area, their well-being depends on quality of land and water resources availability. Quality of land is determined by ameliorative indicators: ground water depth level, ground water salt amount and salinity of soil. These factors do not appear naturally but rather due to the human activity. Inefficient irrigation and excessive consumption of irrigation water on irrigated land in Boyavut District of Syrdarya region of Uzbekistan within several decades have led to a salinization of soil. The primary objective of this article is determination of the level of salinity of soil for modelling spatial distribution of soil salinity throughout an irrigated land by using GIS technology. This technology is focused on automation of development and creation of ameliorative maps, while totally eliminating manual operations. Nowadays, ameliorative expedition specialists still create cadastral map using tracing paper over the marginal areas within irrigated lands based on their ameliorative conditions and by selecting from the three thematic maps and then selecting the poorest conditions of ameliorative indicators. The suggested technology is designed for professionals of cadastral subdivisions of regional ameliorative expeditions, who use the GIS-based software, such as ArcView 3.2. or ArcGIS 10x; their duties include creating of thematic maps based on salinity levels of irrigated lands. Exact coordinates of collection sites of soils samples (collected in 2018-2019) were determined using GPS. The Inverse Distance Weighting (IDW) interpolation method was applied to use that data to create ameliorative maps categorized by the salinity levels (non-saline, slightly saline, saline area and highly saline areas). Those maps were then analysed to develop procedures on how to improve ameliorative conditions of irrigated areas.

Localization of Mobile Submerged Sensors using Lambert-W Function and Cayley-Menger Determinant

This paper demonstrates a new mechanism to localize mobile submerged sensors using only a single beacon node. In range-based localization, fast and accurate distance measurement is vital in underwater wireless sensor networks (UWSN). The knowledge of exact coordinates of the sensors is as important as the actuated data in underwater wireless sensor networks. Mostly bouncing technique is used to determine the distance between the beacon and the sensors. Moreover, to determine the coordinates, trilateration and multilateration technique is used; where using multiple beacons (usually three or more) is the most common approach. Nevertheless, because of many factors, this method gives less accurate results in distance measurements, which finally leads to determine erroneous coordinates. As TDOA is very ponderous to achieve in underwater environment because of time synchronization; again, using AOA is extremely difficult and challenging; TOA is the most common approach and is widely employed. However, it still needs precise synchronization. So, to determine the distances between beacon and sensor nodes, we have used a method based on Lambert-W function in this study, which is an approach based on RSS, and it avoids any synchronization. Besides, coordinates of the mobile sensors are calculated using Cayley-Menger determinant. In this paper, the method is derived and the accuracy is verified by simulation results.

Rsadp - Road Saftey Accident Detection and Prevention in Vehicular Adhoc Network

Vehicular Ad-Hoc Networks (VANETs) is evolving into highly developed systems that improve driver experience in terms of security and offer much-needed tranquility on the roads as well. VANET makes it possible for a vehicle to communicate, (vehicle to vehicle communication) V2V, beyond its visual coverage region for an advance alert. Vehicle accident alert depends on data received from sensors, cameras, onboard units, wireless communication, global positioning systems, and Roadside Units (RSU) placed on equidistance along the roads. It collects data from all entities, i.e., RSUs or OBU, and processes it, leading decisions subsequently. In V2V communication, vehicles support different services such as declaring an accident with their exact coordinates and traffic status updates. In this paper, a protocol is discussed and reviewed and studied about on-vehicle wireless communication capabilities in terms of handling accident alerts for road safety applications. Accident detection in an early stage can help in saving life on the road and enhance medical support probability. Providing the accurate time of accident and locality to the approaching vehicles to reduce down further mishaps on the road. This proposed protocol is flexible enough to adapt real-time environmental adjustments, including road density and speed, traffic state, and network dynamics.

An Implementation of Substantial and Structure Algorithm on Brain MRI Image Datasets for Tumor Detection

Big data mining is one of the upgrowing technology to represent the greater number of data into a single repository and within the Ad-hoc repository to main the high-level abstraction as per the intended request. The Big data is used in the various sectors for the nature of the usability, the medical sectors uses the big data concept to store more patients records for the intended need. Performing a Mining operation in the big data is not a challenging task as we have much more protocols available to extract the intended data set to be mined from the big data repository. In this paper we find the solution for the detection of Brain Tumor with the MRI Image Datasets which is being created and stored in the repository. The Similar Datasets is being created from the various other MRI Images and being stored in the Big Data MRI Repository. The Patient MRI is being compared with Existing patterns with two types of mining operation namely Substantial Mining and Structure Mining which gives the exact location coordinates of the existence of the tumor in the records. This method uses two variant algorithms to cross verify all the axis in the 360o rotation for the verification of the data sets which adjoins with the finding of the existence of tumor in the MRI Image. We Propose Unified Structural Architecture which comprises of two main algorithms namely Partially Augmented Direct Mean Analytics Algorithm for the Substantial Mining and Vertically Augmented Tensor-Heap Interface Algorithm for the Structure Mining in the defined repository to efficiently mine in the information for verifiable usage. The Performance of the algorithm is being compared with the other existing Substantial Mining and Structure for the accuracy mean value. The Simulated Result has provided the evidence for the high dimensional efficiency and throughput of the proposed system

Technology GEONOD: Status and Prospects of Automation and Control

Seismic prospecting is one of the crucial components for an effective use of oil and gas fields on offshore. Since the costs of drilling a well on the shelf is hundreds of times more expensive than drilling a well on land, preliminary marine seismic exploration can help avoid unnecessary costs. High quality data of marine seismic surveys can only be obtained from bottom technologies: special bottom stations are lowered into the investigated area of the seabed. These bottom stations collecting direct and reflected acoustic signals (generated on the surface by an acoustic radiator) from the seabed. After all data is recorded, bottom stations are lifted to the surface, the recorded data is downloaded for subsequent interpretation. As a result, based on the obtained data, a 2D or 3D detailed map of the potential oil and gas deposits is complied. The resulting maps are used to determine the exact coordinates of the installation of drilling stations. The most common technology of marine seismic exploration is the use of bottom stations on a halyard rope. First development of this technology began in the 1970s and did not assume the means of automation work with bottom stations. All operations of removal and attachment of rope to station, diving and lifting stations, as well as a number of other operations were performed manually. Nowadays, there has not been any automation in working with stations on the halyard rope. In addition, the use of halyard rope has a number of disadvantages such as: Hooking of halyard rope for obstacles on the sea bottom; The breakage of the halyard rope; The need to have additional space on the vessel to store the halyard rope and all accessories, which leads to the use of larger vessels that can not operate at shallow depths; The halyard rope that is connected to the bottom stations generates a seismic noise, which degrades the quality of the received data; Impossible to conduct seismic prospecting in places with high shipping traffic. Developed over the past few years, a new Russian technology of marine seismic exploration GEONOD allows us easily solve many of mentioned problems. Many of these problems do not rise at all, since the GEONODE technology does not use halyards, and the work is carried out by the autonomous self-popup bottom stations (ASDS). In this paper a number of problems on applied mechanics and control in connection with technology GEONOD are considering.

Inference in the spatial autoregressive efficiency model with an application to Dutch dairy farms

This article extends the conventional spatial autoregressive efficiency model by including firm characteristics that may impact efficiency. This extension allows performing the typical inference in spatial autoregressive models that involves the derivation of direct and indirect marginal effects, with the latter revealing the nature and magnitude of spatial spillovers. Furthermore, this study accounts for the endogeneity of the spatial autoregressive efficiency model using a lag spatial lag efficiency component, which makes inference to be performed in a long-run framework. The case study concerns specialized Dutch dairy farms observed over the period 2009–2016 and for which exact geographical coordinates of latitude and longitude are available. The results reveal that the efficiency scores are spatially dependent. The derived marginal effects further suggest that farmers’ long-run efficiency is driven by changes in both their own and their neighbors’ characteristics, highlighting the existence of motivation and learning domino effects between neighboring producers.

BioSwitch: a tool for the detection of bistability and multi-steady state behaviour in signalling and gene regulatory networks.

Multi-steady state behaviour, and in particular multi-stability, provides biological systems with the capacity to take reliable decisions (such as cell fate determination). A problem arising frequently in systems biology is to elucidate whether a signal transduction mechanism or a gene regulatory network has the capacity for multi-steady state behaviour, and consequently for a switch-like response to stimuli. Bifurcation diagrams are a powerful instrument in non-linear analysis to study the qualitative and quantitative behaviour of equilibria including bifurcation into different equilibrium branches and bistability. However, in the context of signalling pathways, the inherent large parametric uncertainty hampers the (direct) use of standard bifurcation tools. We present BioSwitch, a toolbox to detect multi-steady state behaviour in signalling pathways and gene regulatory networks. The tool combines results from chemical reaction network theory with global optimization to efficiently detect whether a signalling pathway has the capacity to undergo a saddle node bifurcation, and in case of multi-stationarity, provides the exact coordinates of the bifurcation where to start a numerical continuation analysis with standard bifurcation tools, leading to two different branches of equilibria. Bistability detection in the G1/S transition pathway of Saccharomyces cerevisiae is included as an illustrative example. BioSwitch runs under the popular MATLAB computational environment, and is available at https://sites.google.com/view/bioswitch.

Wireless sensor node deployment strategy for hilly terrains – a surface approximation based approach

Sensor deployment in a wireless sensor network (WSN) is a challenging task due to the high chance of occurrence of the error in the deployment process, which makes the network inefficient. Particularly in three-dimensional (3D) WSN, the ideal positioning of sensor nodes over the ground with precise coverage and connectivity is a very significant consideration in the deployment of sensors. Various models for 2D sensor deployment have been proposed to date, but in real-world scenarios, the target field (field of interest) is not always 2D flat surface and therefore a 2D deployment model cannot address the issue of deploying sensor nodes on uneven surfaces such as hilly terrains. In this paper, we presented a surface approximation-based sensor deployment using truncated octahedron (SASD-TO) to solve the problems of sensor deployment on an irregular surface. Using the B-Spline, a 3D model of the target surface is approximated and then a Truncated Octahedron is used to estimate the exact coordinates of a sensor node. A very decent coverage area as high as 98% on average, whereas at lowest 2% of the uncovered area and 8% of the superimposed area were observed.