Visibility Matrix Research Articles

Further development and application of a method for assessing radionuclide surface activity distribution and source location based on measurements of ambient dose equivalent rate

A method has been developed for solving the Fredholm equation in the barrier geometry for reconstructing the surface activity density (SAD) from the results of measuring the ambient dose equivalent rate (ADER). Inclusion of the barrier geometry means that the method takes into account the shielding effect of buildings and structures on the contaminated site. The method was based on the representation of the industrial site, buildings and radiation fields in the form of a raster and the use of the visibility matrix (VM) of raster cells to describe the barrier geometry. The developed method was applied to a hypothetical industrial site with a size of 200 × 200 conventional units for four types of SAD distribution over the surface of the industrial site: ‘fragmentation’, ‘diffuse’, ‘uniform’ and ‘random’. The method of Lorentz curves was applied to estimate the compactness of the distributions of SAD and the ADER for the considered radiation sources. It was shown that the difference between the Lorentz curve for SAD and ADER means that the determination of the spatial distribution of SAD over the industrial site by solving the integral equation is essentially useful for determining the location of radiation source locations on the industrial site. The accuracy of SAD reconstruction depends on the following parameters: resolution (fragmentation) of the raster, the height of the radiation detector above the scanned surface, and the angular aperture of the radiation detector. The measurement of ADER is simpler and quicker than the direct measurement of SAD and its distribution. This represents a significant advantage if SAD distribution needs to be determined in areas with high radiation dose-rate during limited time. The developed method is useful for supporting radiation monitoring and optimizing the remediation of nuclear legacies, as well as during the recovery phase after a major accident.

K-CTIAA: Automatic Analysis of Cyber Threat Intelligence Based on a Knowledge Graph

Cyber threat intelligence (CTI) sharing has gradually become an important means of dealing with security threats. Considering the growth of cyber threat intelligence, the quick analysis of threats has become a hot topic at present. Researchers have proposed some machine learning and deep learning models to automatically analyze these immense amounts of cyber threat intelligence. However, due to a large amount of network security terminology in CTI, these models based on open-domain corpus perform poorly in the CTI automatic analysis task. To address this problem, we propose an automatic CTI analysis method named K-CTIAA, which can extract threat actions from unstructured CTI by pre-trained models and knowledge graphs. First, the related knowledge in knowledge graphs will be supplemented to the corresponding position in CTI through knowledge query and knowledge insertion, which help the pre-trained model understand the semantics of network security terms and extract threat actions. Second, K-CTIAA reduces the adverse effects of knowledge insertion, usually called the knowledge noise problem, by introducing a visibility matrix and modifying the calculation formula of the self-attention. Third, K-CTIAA maps corresponding countermeasures by using digital artifacts, which can provide some feasible suggestions to prevent attacks. In the test data set, the F1 score of K-CTIAA reaches 0.941. The experimental results show that K-CTIAA can improve the performance of automatic threat intelligence analysis and it has certain significance for dealing with security threats.

Visibility Matrix: Efficient User Interface Modelling for Low-Code Development Platforms

In this paper, we introduce the idea of the ‘visibility matrix’ for automated data entry form generation in low-code development platforms. We then focus on the problem of software development productivity in the area of automated software generation as the main factor of the Industry 4.0 concept in the area of business information. In our study, two different approaches to user interface development in a business process management low-code platform were evaluated. The first, the multi-form model, assumes that input forms are prepared separately for each user task in the business process being automated. The second approach, the single-form model, assumes that there is one global input form for every task in the business process. Since users have access to different data in different process tasks, it is necessary to prepare the visibility matrix to define which data are relevant to which tasks. The experiments presented in this paper help to answer the following question: which approach yields better results in terms of productivity, which is measured as costs and time required to prepare the application? Several dozen real business processes were analysed to examine the properties of their visibility matrix. Additionally, the real project team members were evaluated to determine their productivity. Then, the productivity parameters were calculated for real business processes and real project teams. The results show which approach is better suited for real-world business process development.

AlgoSCR: an algorithm for solar contamination removal from radio interferometric data

ABSTRACT Hydrogen intensity mapping is a new field in astronomy that promises to make three-dimensional maps of the matter distribution of the Universe using the redshifted $21\, \textrm {cm}$ line of neutral hydrogen gas (HI). Several ongoing and upcoming radio interferometers, such as Tianlai, CHIME, HERA, HIRAX, etc., are using this technique. These instruments are designed to map large swaths of the sky by drift scanning over periods of many months. One of the challenges of the observations is that the daytime data are contaminated by strong radio signals from the Sun. In the case of Tianlai, this results in almost half of the measured data being unusable. We try to address this issue by developing an algorithm for solar contamination removal (AlgoSCR) from the radio data. The algorithm is based on an eigenvalue analysis of the visibility matrix and hence is applicable only to interferometers. We apply AlgoSCR to simulated visibilities, as well as real daytime data from the Tianlai dish array. The algorithm can reduce strong solar contamination by about 95 per cent without seriously affecting other weaker sky signals and thus makes the data usable for certain applications.

Connectivity Analysis of Mega-Constellation Satellite Networks With Optical Intersatellite Links

Recently, low earth orbit (LEO) satellite-based systems have attracted tremendous attention and various technologies have been developed for payload miniaturization and optical communications. In addition, mega-constellation architectures are expected to be deployed with LEO satellites for global broadband networks. In this article, we present a thorough analysis of mega-constellation architecture in terms of a change in the number of visible satellites and antenna steering capability to investigate the impact of increase in the constellation size and adoption of optical intersatellite links. The network architecture is evaluated with respect to satellite antenna steering capability and the satellite visibility considering the very narrow beam divergence of optical communications. We analyze the impact of a change in relative positions among the satellites due to continuous satellite movement in the constellation. The results offer guidelines for designing a novel visibility matrix using a time-varying satellite topology. This could defuse the problem of the conventional studies using fixed visibility matrices. The proposed time-varying visibility matrix achieves better performance than the previous preassigned links in terms of end-to-end link distance and hop count of LEO satellite networks.

Decision Routing Problems in A Wireless Sensor Network Based on A Neural Mechanism

This article proposes a solution for the routing problem in wireless sensor networks (WSN) based on a neural mechanism. The basic concepts of wireless sensor networks, artificial neural networks (ANNs), and WSN routing protocols are presented. The Kohonen ANN was selected to solve the problem of routing in wireless sensor networks based on a neural mechanism. A radio visibility matrix is proposed, which is a mathematical description of the connectivity of network nodes and the radio visibility of each node with respect to all other network nodes. Based on the Kohonen ANN trained by the constructive method, a method for WSN neural network clustering was developed. Two software-modeling environments are presented that were created to confirm the theory with respect to the logic of the developed methods for WSN clustering, their correction and the verification of their adequacy. Numerical results of modeling the solution of the routing problem in a wireless sensor network based on a neural mechanism by neural network clustering, the WSN matrix clustering method and the energy distance neural clustering protocol (EDNCP) are presented. It was found that the developed EDNCP protocol was 29% more efficient than known analogs.

Visibility Graph Power Geometric Aggregation Operator and Its Application in Water, Energy, and Food Efficiency Evaluation.

In the real decision-making process, there are so many time series values that need to be aggregated. In this paper, a visibility graph power geometric (VGPG) aggregation operator is developed, which is based on the complex network and power geometric operator. Time series data are converted into a visibility graph. A visibility matrix is developed to denote the links among different time series values. A new support function based on the distance of two values are proposed to measure the support degree of each other when the two time series values have visibility. The VGPG operator considers not only the relationship but also the similarity degree between two values. Meanwhile, some properties of the VGPG operator are also investigated. Finally, a case study for water, energy, and food coupling efficiency evaluation in China is illustrated to show the effectiveness of the proposed operator. Comparative analysis with the existing research is also offered to show the advantages of the proposed method.

Revisiting spectral clustering for near-convex decomposition of 2D shape

We present a novel 2D shape decomposition algorithm via a recursive partitioning process. Starting with the contour points of a shape, we repeatedly separate the points into two parts by spectral clustering, until the stopping condition is met. Motivated by the fact that the points in a convex part are mutually visible, we regard the visibility matrix of points as the affinity matrix of spectral clustering to obtain a near-convex decomposition. Additionally, we present an efficient stopping rule to avoid over-segmentation on the shape branches. The stopping criterion is based on a novel shape signature called visible protrusion strength which can be used to measure the segmentability of a sub-shape. Finally, we demonstrate the efficiency of our algorithm on a variety of publicly available shapes, and provide qualitative and quantitative comparisons with state-of-art approaches.

An Eigenvector-Based Method of Radio Array Calibration and Its Application to the Tianlai Cylinder Pathfinder

Abstract We propose an eigenvector-based formalism for the calibration of radio interferometer arrays. In the presence of a strong dominant point source, the complex gains of the array can be obtained by taking the first eigenvector of the visibility matrix. We use the stable principle component analysis method to help separate outliers and noise from the calibrator signal to improve the performance of the method. This method can be applied with poorly known beam model of the antenna, is insensitive to outliers or imperfections in the data, and has low computational complexity. It thus is particularly suitable for the initial calibration of the array, which can serve as the initial point for more accurate calibrations. We demonstrate this method by applying it to the cylinder pathfinder of the Tianlai experiment, which aims to measure the dark energy equation of state using the baryon acoustic oscillation features in the large-scale structure by making intensity mapping observation of the redshifted 21 cm emission of the neutral hydrogen (H i). The complex gain of the array elements and the beam profile in the east–west direction (short axis of the cylinder) are successfully obtained by applying this method to the transit data of bright radio sources.

Measurement of large-scale BGP events: Definition, detection, and analysis

Measurement on the Border Gateway Protocol (BGP) system is important for understanding the Internet. Many attempts have been made to detect anomalous Internet events through dissecting BGP updates and tables. We notice that most works in this field either deploy/use few monitors or analyze aggregated statistics. Such practices may result in overestimating the impact of monitor-local events, which can be viewed by only a small area.We propose Large-scale BGP Event (LBE), which affects many IP prefixes (high impact) and is widely observable (non-local). To detect LBE, we propose the Update Visibility Matrix (UVM) to record the prefix and monitor related to each update. We formulate the problem of identifying LBE in UVM, which is NP-hard. Then we propose a heuristic algorithm to solve it. We apply the scheme to 2.18 TB of BGP updates and find that the identified LBEs are highly correlated with many well-known disruptive incidents. Besides, we identify 101 LBEs that have never been investigated before. By conducting case studies, we find that the LBEs have high impact and are caused by various reasons. Our work can assist in network/Internet management tasks such as problem prevention, diagnosis, and recovery.

VOE: A new sparsity-based camera network placement framework

In this paper, we propose a stepwise sparsity-based framework for camera network placement. Unlike most previous methods which are developed for specific tasks, our approach is universal and can generalize well for different application scenarios. There are three steps in our approach: visibility analysis, optimization and evaluation (VOE), which are employed sequentially and iteratively. First, we use a cascaded visibility filter model to construct a visibility matrix, where each column describes the appearance representation of the surveillance area. Then, we formulate camera network layout as a sparse representation problem, and employ an l1-optimization algorithm to obtain a feasible solution. Our framework is general enough and applicable to various objectives in practical applications. Experiment results are presented to show the effectiveness and efficiency of the proposed framework.

A structure-based approach for optimizing distributed reconstruction in Motion Capture systems

Abstract The diffusion of visual sensor networks, and in particular of smart camera networks, is motivating an increasing interest on the research of distributed solutions for several vision problems. Specifically, in this paper we propose a distributed solution to the problem of reconstructing target positions in large Motion Capture (MoCap) systems. Real time reconstruction by means of centralized procedures is practically unfeasible for very large systems, while the use of distributed computation allows to significantly reduce the computational time required for reconstruction, thus allowing the development of real time solutions. Then the proposed distributed reconstruction procedure is optimized by exploiting information about the structure of the system: the visibility matrix states which objects in the scene are somehow measurable by a sensor (sensor-object matrix). Often, the typical localization of data from real application scenarios induces an underlying structure on the visibility matrix, that can be exploited to improve the performance of the system in understanding the surrounding environment. Unfortunately, usually these data are not properly organized in the visibility matrix: for instance, listing the sensors in a pseudo-random order can hide the underlying structure of the matrix. This paper considers the problem of recovering such underlying structure directly from the visibility matrix and designs an algorithm to perform this task. Our simulations show that the distributed reconstruction algorithm optimized by means of the estimation of the structure of the visibility matrix achieves an important computational time reduction with respect to the standard (centralized) reconstruction algorithm.

VisibilityCluster: Average Directional Visibility for Many-Light Rendering

This paper proposes the VisibilityCluster algorithm for efficient visibility approximation and representation in many-light rendering. By carefully clustering lights and shading points, we can construct a visibility matrix that exhibits good local structures due to visibility coherence of nearby lights and shading points. Average visibility can be efficiently estimated by exploiting the sparse structure of the matrix and shooting only few shadow rays between clusters. Moreover, we can use the estimated average visibility as a quality measure for visibility estimation, enabling us to locally refine VisibilityClusters with large visibility variance for improving accuracy. We demonstrate that, with the proposed method, visibility can be incorporated into importance sampling at a reasonable cost for the many-light problem, significantly reducing variance in Monte Carlo rendering. In addition, the proposed method can be used to increase realism of local shading by adding directional occlusion effects. Experiments show that the proposed technique outperforms state-of-the-art importance sampling algorithms, and successfully enhances the preview quality for lighting design.

화랑 문제의 최소 정점 경비원 수 알고리즘

This paper suggests the minimum number of vertex guards algorithm. Given n rooms, the exact number of minimum vertex guards is proposed. However, only approximation algorithms are presented about the maximum number of vertex guards for polygon and orthogonal polygon without or with holes. Fisk suggests the maximum number of vertex guards for polygon with n vertices as follows. Firstly, you can triangulate with n-2 triangles. Secondly, 3-chromatic vertex coloring of every triangulation of a polygon. Thirdly, place guards at the vertices which have the minority color. This paper presents the minimum number of vertex guards using dominating set. Firstly, you can obtain the visibility graph which is connected all edges if two vertices can be visible each other. Secondly, you can obtain dominating set from visibility graph or visibility matrix. This algorithm applies various art galley problems. As a results, the proposed algorithm is simple and can be obtain the minimum number of vertex guards.

Object shape virtualization in impedance tomography

PurposeThe purpose of this paper is to introduce a method for increasing imaging quality in impedance tomography. The paper presents an optical method of shape virtualization, processing algorithm draft and results of virtualization for sample objects.Design/methodology/approachIn impedance tomography the image reconstruction algorithms must yield accurate images of impedance changes. One of the keys to producing an accurate reconstructed image is the inclusion of prior information regarding the physical geometry of the object. When the object under investigation is filled with transparent medium, optical methods can provide information about its interior and estimate the shape of non‐transparent interjections. Computer graphics methods (e.g. ray tracing) can be used to simulate propagation of the light transmitted along straight lines within the object, and thus yield geometric data to better imaging. The process of setting up boundary conditions is then supplied with additional information about interior of the object, which can significantly improve solution of the forward problem in impedance tomography.FindingsThe visibility matrix includes information about the interior of the object. However, the information is incomplete since the scanning is done along one axis. In order to obtain all remaining data, scanning along three axes is required. On the basis of the visibility matrix, the shape and volume of the non‐transparent interjections are recovered and then estimated.Originality/valueThe biggest novelty is indeed the combination of methods used in optical tomography with those in impedance tomography.

A modular classification model for received signal strength based location systems

Estimating location of mobile devices based on received signal strength (RSS) patterns is an attractive method to realize indoor positioning systems. Accuracy of RSS based location estimation, particularly in large target sites, is effected by several environmental factors. Especially the temporal or permanent absence of radio signals introduces null values rendering sparsity and redundancy in feature space. We present a visibility matrix based modular classification model which systematically caters for unavailable signals. This model is practically realized using two eminent classification methods: (1) multi-layer perceptron and (2) LVQ. In order to confirm robustness and applicability of this model, we developed two location systems at different sites. Experimental results in real-world environments demonstrate that modular classification model consistently achieves superior location accuracy.

THE SIMULATION OF AN INFANTRY ATTACK USING GEOGRAPHICAL INFORMATION SYSTEMS

An infantry attack over a specific terrain is modeled. A stochastic method described in our previous study is used. In this model, the position of each soldier during the attack is approximately defined by a square [10 × 10 m] on the battlefield. Making use of the possibilities inherent in a three‐dimensional digital map, a visibility matrix is made up, i. e. the indication whether the enemy sees the soldier in a specific case is given.