scholarly journals A Multi-Scale Representation of Point-of-Interest (POI) Features in Indoor Map Visualization

2020 ◽  
Vol 9 (4) ◽  
pp. 239 ◽  
Author(s):  
Yi Xiao ◽  
Tinghua Ai ◽  
Min Yang ◽  
Xiang Zhang
Keyword(s):  
Age Groups ◽  
Adaptive Strategy ◽  
Adaptive Method ◽  
Building Structure ◽  
Multi Scale ◽  
Performance Requirements ◽  
Service Information ◽  
Developing Area ◽  
Map Scale ◽  
Functional Partitioning

As a result of the increasing popularity of indoor activities, many facilities and services are provided inside buildings; hence, there is a need to visualize points-of-interest (POIs) that can describe these indoor service facilities on indoor maps. Over the last few years, indoor mapping has been a rapidly developing area, with the emergence of many forms of indoor representation. In the design of indoor map applications, cartographical methodologies such as generalization and symbolization can make important contributions. In this study, a self-adaptive method is applied for the design of a multi-scale and personalized indoor map. Based on methods of map generalization and multi-scale representation, we adopt a scale-adaptive strategy to visualize the building structure and POI data on indoor maps. At smaller map scales, the general floor distribution and functional partitioning of each floor are represented, while the POI data are visualized by simple symbols. At larger map scales, the detailed room distribution is displayed, and the service information of the POIs is described by detailed symbols. Different strategies are used for the generalization of the background building structure and the foreground POI data to ensure that both can satisfy real-time performance requirements. In addition, for better personalization, different POI data, symbols or color schemes are shown to users in different age groups, with different genders or with different purposes for using the map. Because this indoor map is adaptive to both the scale and the user, each map scale can provide different map users with decision support from different perspectives.

On a Data and Requirements Driven Multi-Scale Framework Linking Performance to Materials

2010 ◽  
Author(s):  
John G. Michopoulos ◽  
Samuel G. Lambrakos ◽  
Athanasios Iliopoulos
Keyword(s):  
Experimental Data ◽  
Discrete Event ◽  
Equation System ◽  
Layered Architecture ◽  
Multi Scale ◽  
Performance Requirements ◽  
Physical Problems ◽  
Usability Requirements ◽  
And Performance ◽  
Behavior Characteristics

The initial progress towards the design and development of a framework for automating the process of integrating experimental data with stakeholder specifications describing usability requirements, along with multiscale models for tailoring material and structural behavior characteristics is reported in the present paper. The proposed framework consists of a layered architecture that is comprised of three main layers. The first layer involves the computational infrastructure that implements the low level computational container that encompasses the computational codes that enable the modeling of the forward problem for various physical problems at specific time and length scales. The second layer of the framework implements the cascaded and hierarchical implementation of the inverse problem in terms of a composition of discrete event system and differential equation system specifications. The third element of the proposed architecture utilizes Category theory abstractions and their computational implementations to provide the necessary infrastructure for automating the process of developing synthetic specifications driven from experimental data and performance requirements related to the design and use of material and structural systems.

On Scale Correction Model of Coastline and its Application for Coastline Remote Sensing Monitoring

2013 ◽  
Vol 303-306 ◽  
pp. 734-739
Author(s):  
Hua Guo Zhang ◽  
Dong Ling Li ◽  
Ai Qin Shi
Keyword(s):  
Remote Sensing ◽  
High Precision ◽  
Coastal Zone ◽  
Absolute Error ◽  
Correction Method ◽  
Remote Sensing Images ◽  
Correction Model ◽  
Remote Sensing Monitoring ◽  
Multi Scale ◽  
Map Scale

This paper focuses on the scale correction of coastline extracted from remote sensing images. Measurement of coastline is one of the basic and core work of coastal zone remote sensing monitoring projects. Based on analysis of coastline scale effect and multi-scale simulation of coastline, a scale correction method is presented for remote sensing coastline. This method can be used to correct remote sensing coastline to specified map scale, in order to obtain high-precision remote sensing monitoring results of coastline. The results of application example showed that the absolute error of coastline length is reduced to about one third of the original error after correction using the presented method. So the presented method can increase the accuracy of remote sensing coastline for specified scale substantially.

scholarly journals NSGA-II-Based Granularity-Adaptive Control-Flow Attestation

2021 ◽  
Vol 2021 ◽  
pp. 1-16
Author(s):  
Jing Zhan ◽  
Yongzhen Li ◽  
Yifan Liu ◽  
Hongchao Li ◽  
Shuai Zhang ◽  
...  
Keyword(s):  
Adaptive Control ◽  
Measurement Data ◽  
Adaptive Strategy ◽  
Control Flow ◽  
Coarse Grained ◽  
Embedded Devices ◽  
Nsga Ii ◽  
Performance Requirements ◽  
Control Flow Integrity ◽  
And Performance

Since the widespread adoption of edge computing and IoT technology, Control-Flow Hijacking (CFH) attacks targeting programs in resource-constrained embedded devices have become prevalent. While the Coarse-Grained Control-Flow integrity Attestation (CGCFA) lacks accuracy for the CFH attacks detection, the Fine-Grained Control-Flow integrity Attestation (FGCFA) detect the attacks more accurately but with high overheads, which can be a big burden (e.g., to industrial control system with strict performance requirements). In this paper, we propose a NSGA-II (Nondominated Sorting Genetic Algorithm-II) based Granularity-Adaptive Control-Flow Attestation (GACFA) for the programs in embedded devices. Specifically, we propose a Granularity-Adaptive Control-Flow representation model to reduce the complexity of programs’ control-flow graph and propose NSGA-II-based granularity-adaptive strategy generation algorithm to balance the security and performance requirements. Besides, runtime protection for the GACFA at the program end with SGX is proposed to protect the integrity and confidentiality of control-flow measurement data. The experiments show that our work can find out the best-so-far control-flow granularity with stability and provide secure program attestation for the verifier. In addition, the security/performance benefit of adopting our proposal over CGCFA is 13.7, 25.1, and 43.0 times that of adopting FGCFA over ours in different threat scenarios.

Highly Anti-Noise and Adaptive B-Spline Curve Reconstruction Based on ICT Slice Images

2013 ◽  
Vol 397-400 ◽  
pp. 1083-1087
Author(s):  
Guang Shuai Liu ◽  
Bai Lin Li
Keyword(s):  
Point Cloud ◽  
Adaptive Method ◽  
Point Cloud Data ◽  
Curve Reconstruction ◽  
B Spline ◽  
Cloud Data ◽  
Spline Curve ◽  
Multi Scale ◽  
Key Issues ◽  
Selection Of

Obtaining effective value points is one of key issues in cubic B-spline curve reconstruction. Since it is unfavorable for the selection of value points through curvature methods and the point cloud data acquired from ICT slice images is characterized with large volume of data, high noise and density, a baseline adaptive method is presented to get value points for curve reconstruction, baseline and scale threshold determined by wavelet multi-scale, in which the value points is obtained and curve is reconstructed automatically. Hausdorff distance is adopted to calculate the error of cubic B-spline curve reconstruction. Comparative analysis with existing methods proves that our method can effectively restrain noise and quickly reconstruct contour curves.

scholarly journals Adaptive implicit finite difference method for natural gas pipeline transient flow

2018 ◽  
Vol 73 ◽  
pp. 21 ◽  
Author(s):  
Peng Wang ◽  
Bo Yu ◽  
Dongxu Han ◽  
Jingfa Li ◽  
Dongliang Sun ◽  
...  
Keyword(s):  
Finite Difference ◽  
Finite Difference Method ◽  
Difference Method ◽  
Adaptive Strategy ◽  
Adaptive Method ◽  
Time Step ◽  
Simulation Process ◽  
Implicit Finite Difference ◽  
Spatial Grid ◽  
Implicit Finite Difference Method

The implicit finite difference method is one of the most widely applied methods for transient natural gas simulation. However, this implicit method is associated with high computational cost. To improve the simulation efficiency of implicit finite difference method, an adaptive strategy is introduced into the simulation process. The proposed adaptive strategy consists of the adaptive time step strategy and the adaptive spatial grid strategy. And these two parts are implemented based on the local error technique and the multilevel grid technique respectively. The results illustrate that the proposed adaptive method can automatically and independently adjust the time step and the spatial grid system according to the gas flow state in the simulation process, and demonstrates a significant advantage in terms of computational accuracy and efficiency compared with the non-adaptive method.

scholarly journals Multi-scale Adaptive Differential Abundance Analysis in Microbial Compositional Data

2021 ◽  
Author(s):  
Shulei Wang
Keyword(s):  
Compositional Data ◽  
Adaptive Strategy ◽  
Data Sets ◽  
Data Set ◽  
Differential Abundance ◽  
Multi Scale ◽  
Experimental Bias ◽  
The Difference ◽  
Microbiome Data ◽  
Differential Abundance Analysis

Differential abundance analysis is an essential and commonly used tool to characterize the difference between microbial communities. However, identifying differentially abundant microbes remains a challenging problem because the observed microbiome data is inherently compositional, excessive sparse, and distorted by experimental bias. Besides these major challenges, the results of differential abundance analysis also depend largely on the choice of analysis unit, adding another practical complexity to this already complicated problem. In this work, we introduce a new differential abundance test called the MsRDB test, which embeds the sequences into a metric space and integrates a multi-scale adaptive strategy for utilizing spatial structure to identify differentially abundant microbes. Compared with existing methods, the MsRDB test can detect differentially abundant microbes at the finest resolution offered by data and provide adequate detection power while being robust to zero counts, compositional effect, and experimental bias in the microbial compositional data set. Applications to both simulated and real microbial compositional data sets demonstrate the usefulness of the MsRDB test.

On prognostic connection between hard cosmic ray flux decrease and leaps of cardiovascular diseases in 2008–2009 in Vilnius

2011 ◽  
Vol 18 (3) ◽  
pp. 132-137
Author(s):  
Dmitrijus STYRA ◽  
Algirdas JUOZULYNAS ◽  
Ana USOVAITĖ ◽  
Jonas GASPARIŪNAS
Keyword(s):  
Cardiovascular Diseases ◽  
Human Factor ◽  
Age Groups ◽  
Ground Surface ◽  
Cosmic Ray ◽  
Average Value ◽  
Service Information ◽  
Surface Data ◽  
Hard Cosmic Ray Flux ◽  
Cosmic Ray Flux

Data on a prognostic relationship between the hard cosmic ray flux (HCRF) and the leaps of cardiovascular diseases (CVD) in Vilnius in 2008–2009 are presented. A gamma spectrometer with a scintillation detector were used to register the HCRF near the ground surface. Data on CVD over a period of 24 months (2008–2009) were obtained from the Vilnius Ambulance Service. Information on CVD was selected for all age groups in accordance with the international codes for identification of diseases (ICD). The present study was restricted to time periods when the cosmophysical and medical data could be compared. For the processing of experimental results, empirical criteria in the analysis of HCRF and CVD were used. The criterion in HCRF change is a decrease of HCRF values by 200 impulses and more during a period of 4 hours. The CVD number exceeding the monthly average value by 10, 15, 20% was analysed. A correlation between the above parameters was studied in the range of 1–3-day period. The efficiency of the prognosis of CVD leaps by HCRF decrease in 1–2 days in 2008 was 74–82% and in 2009 65–70%, and for 2–3 days in 2008 54–60% and in 2009 63–65%. The human factor was analysed, too. Keywords: hard cosmic ray flux, cardiovascular diseases, connection, human factor

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