scholarly journals Research on Distance Transform and Neural Network Lidar Information Sampling Classification-Based Semantic Segmentation of 2D Indoor Room Maps

Sensors ◽  
2021 ◽  
Vol 21 (4) ◽  
pp. 1365
Author(s):  
Tao Zheng ◽  
Zhizhao Duan ◽  
Jin Wang ◽  
Guodong Lu ◽  
Shengjie Li ◽  
...  
Keyword(s):  
Neural Network ◽  
High Speed ◽  
High Performance ◽  
High Efficiency ◽  
Semantic Segmentation ◽  
Raspberry Pi ◽  
Distance Transform ◽  
Testing Stage ◽  
Sampling Points ◽  
Information Sampling

Semantic segmentation of room maps is an essential issue in mobile robots’ execution of tasks. In this work, a new approach to obtain the semantic labels of 2D lidar room maps by combining distance transform watershed-based pre-segmentation and a skillfully designed neural network lidar information sampling classification is proposed. In order to label the room maps with high efficiency, high precision and high speed, we have designed a low-power and high-performance method, which can be deployed on low computing power Raspberry Pi devices. In the training stage, a lidar is simulated to collect the lidar detection line maps of each point in the manually labelled map, and then we use these line maps and the corresponding labels to train the designed neural network. In the testing stage, the new map is first pre-segmented into simple cells with the distance transformation watershed method, then we classify the lidar detection line maps with the trained neural network. The optimized areas of sparse sampling points are proposed by using the result of distance transform generated in the pre-segmentation process to prevent the sampling points selected in the boundary regions from influencing the results of semantic labeling. A prototype mobile robot was developed to verify the proposed method, the feasibility, validity, robustness and high efficiency were verified by a series of tests. The proposed method achieved higher scores in its recall, precision. Specifically, the mean recall is 0.965, and mean precision is 0.943.

scholarly journals Experimental research in automobile non-pneumatic tire force heterogeneity

2018 ◽  
Vol 224 ◽  
pp. 02019 ◽  
Author(s):  
Vladimir Mazur
Keyword(s):  
High Speed ◽  
High Performance ◽  
High Efficiency ◽  
Motor Vehicle ◽  
Heavy Traffic ◽  
Polymeric Materials ◽  
Air Pressure ◽  
Motor Vehicles ◽  
Tire Force ◽  
Excess Air

Simplicity and high efficiency of a wheeled mover as a mechanism for converting rotational motion into a translatory one have conditioned its wide application in overland machines including motor vehicles. However a wheel with a non-pneumatic tyre (NPT) has a sufficient drawback lying in termination of a wheeled machine movement at the excess air pressure loss. Moreover, the loss of excess air pressure in a pneumatic tyre of traditional design at high speed of movement of a motor vehicle can lead to a traffic accident with heavy consequences. The stop of a motor vehicle to change a wheel on a heavy traffic roadway or roadside also poses a threat. These reasons determine the necessity of both well-known design improvements and search for the new wheeled mover design solutions to enhance a motor vehicle safety, the use of wheels with non-pneumatic tyres of elastic polymeric materials being one of them. Safety enhancement by means of non-pneumatic tyre use along with keeping the high performance of wheeled machine operational properties, is an important scientific and technical task that determines the research urgency.

Advantages and Drawbacks of Popular Supercritical Fluid Chromatography / Mass Spectrometry Interfacing Approaches—A User's Perspective

2005 ◽  
Vol 11 (2) ◽  
pp. 189-197 ◽  
Author(s):  
J. David Pinkston
Keyword(s):  
Mass Spectrometry ◽  
Supercritical Fluid ◽  
Supercritical Fluid Chromatography ◽  
High Speed ◽  
High Performance ◽  
High Efficiency ◽  
User Friendliness ◽  
Chromatographic Separations ◽  
Bioanalytical Applications ◽  
Column Pressure

Mobile phases in supercritical fluid chromatography (SFC) have low viscosities and high diffusion coefficients with respect to those of traditional high-performance liquid chromatography (HPLC). These properties allow higher mobile phase flow rates and/or longer columns in SFC, resulting in rapid analyses and high efficiency separations. In addition, chiral SFC is becoming especially popular. Mass spectrometry (MS) is arguably the most popular “informative” detector for chromatographic separations. Most SFC/MS is performed with atmospheric pressure ionization (API) sources. Unlike LC/MS, the interface between the SFC column and the API source must allow control of the downstream (post-column) pressure while also providing good chromatographic fidelity. Here, we compare and contrast the popular interfacing approaches. Some are simple, such as direct effluent introduction with no active back pressure regulator (BPR) in high-speed bioanalytical applications. The pressure-regulating fluid interface is more versatile and provides excellent chromatographic fidelity, but is less user friendly. The pre-BPR-split interface and an interface which provides total flow introduction with a mechanical BPR are good compromises between user friendliness and performance and have become the most popular among practitioners. Applications of SFC/MS using these various interfaces are also discussed.

Sintering of Vitrified Bond CBN Grinding Tool

2007 ◽  
Vol 280-283 ◽  
pp. 1391-1394 ◽  
Author(s):  
Zhi Hong Li ◽  
Yong Hong Zhang ◽  
Y.M. Zhu ◽  
Zheng Fang Yang
Keyword(s):  
High Speed ◽  
High Performance ◽  
High Efficiency ◽  
Sintering Temperature ◽  
Cubic Boron Nitride ◽  
Heating Process ◽  
Initial Oxidation ◽  
Grinding Tool ◽  
Vitrified Bond ◽  
Lower Temperature

Cubic boron nitride(CBN) is a superhard materials with many advantages and many uses. Vitrified bond CBN grinding tool is a promising abrasive tool of high performance used for high speed, high efficiency, high precision grinding with lower grinding cost and less environment pollution. Sintering of vitrified bond CBN grinding tool was investigated in this paper. The results showed that practical sintering temperature of this tool was much lower than the initial oxidation temperature of CBN particle measured by comprehensive thermal analysis. The upper limit of sintering temperature should be determined by taking account of the thermal analyzing results, heating process of CBN and its change in strength and structure. Within the sintering temperature range of the vitrified bond, relatively higher sintering temperature was beneficial to the strength of bond bridge and the holding strength between bond and CBN abrasive particles. CBN tool sintered at relatively lower temperature tended to fracture through the bond bridge, while the one sintered at higher temperature tended to fracture along the boundary between CBN abrasive grain and vitrified bond.

scholarly journals High Speed Parallel SAD Architecture Implementation on FPGA for HEVC encoder

2019 ◽  
Vol 8 (6) ◽  
pp. 1235-1238
Keyword(s):  
Motion Estimation ◽  
Video Compression ◽  
High Speed ◽  
High Performance ◽  
High Efficiency ◽  
Block Size ◽  
Video Encoding ◽  
Computational Time ◽  
Absolute Difference ◽  
Asymmetric Mode

Video compression is a very complex and time consuming task which generally pursuit high performance. Motion Estimation (ME) process in any video encoder is responsible to primarily achieve the colossal performance which contributes to significant compression gain. Summation of Absolute Difference (SAD) is widely applied as distortion metric for ME process. With the increase in block size to 64×64 for real time applications along with the introduction of asymmetric mode motion partitioning(AMP) in High Efficiency Video Encoding (HEVC)causes variable block size motion estimation very convoluted. This results in increase in computational time and demands for significant requirement of hardware resources. In this paper parallel SAD hardware circuit for ME process in HEVC is propound where parallelism is used at various levels. The propound circuit has been implemented using Xilinx Virtex-5 FPGA for XC5VLX20T family. Synthesis results shows that the propound circuit provides significant reduction in delay and increase in frequency in comparison with results of other parallel architectures.

scholarly journals Silicon photonics for high data rate applications -INVITED

2020 ◽  
Vol 238 ◽  
pp. 01005
Author(s):  
David J. Thomson ◽  
Weiwei Zhang ◽  
Ke Li ◽  
Kapil Debnath ◽  
Shenghao Liu ◽  
...  
Keyword(s):  
Silicon Photonics ◽  
High Speed ◽  
High Performance ◽  
High Efficiency ◽  
Electrical Signal ◽  
Electronic Components ◽  
High Data ◽  
Electro Optic ◽  
Optical Domain ◽  
Linear Modulation

The high speed conversion of signals between the optical and electrical domains is crucial for many key applications of silicon photonics. Electro-optic modulators integrated with electronic drive amplifiers are typically used to convert an electrical signal to the optical domain. Design of these individual elements is important to achieve high performance, however a true optimisation requires careful co-design of the photonic and electronic components considering the properties of each other. Here we present our recent results in this area together with a MOSCAP type modulator with the potential for high speed, high efficiency and highly linear modulation.

scholarly journals METHODS OF METOPROLOL ANALYSIS IN DRUGS AND BIOLOGICAL FLUIDS: REVIEW AND SUGGESTIONS

2020 ◽  
Vol 5 (2) ◽  
pp. 88-97
Author(s):  
M. M. Horyn ◽  
L. S. Logoyda
Keyword(s):  
Analytical Method ◽  
High Speed ◽  
High Performance ◽  
Method Development ◽  
High Efficiency ◽  
Biological Fluids ◽  
Dosage Forms ◽  
Pharmaceutical Chemistry ◽  
Components Separation ◽  
Analysis Methods

Background. Analytical method is increasingly implemented into fundamental pharmaceutical chemistry and analysis, considering their high sensitivity, accuracy, specificity and expressiveness. Objective. Metoprolol’s analytical method development was the research goal. Methods. The sources were world recognized journals (1990-2019) and key words used as filter were “metoprolol”, “spectrophotometry” “high-performance liquid chromatography, HPLC”, “quantitative analysis”, “validation”. Results. Chromatographic methods of analysis have the highest specificity and objectivity and allow qualitative and quantitative determination of Active Pharmaceutic Ingredient (API) in combined dosage forms and biological fluids without prior components separation. The main disadvantage of the described API analysis methods is long terms from the beginning of chromatography to API release and specific solvents used as the mobile phase in HPLC. New methods development and selection such chromatographic conditions that provide high speed and high efficiency at lower pressure of the system are essential. Also, the reduction of analysis time is achieved by simplifying the conditions for sample preparation. Conclusions. Analysts are constantly working on developing new analysis methods and their optimization in order to save time and consumables, which also ensures the efficiency of the developed method. There is no monograph on the substance or dosage forms of metoprolol in SPhU. Therefore, some of the developed methods should be suggested for the SPhU monograph, which is important for ensuring pharmacopoeial quality control of medicines in Ukraine.

scholarly journals Semantic Segmentation of Building Roof in Dense Urban Environment with Deep Convolutional Neural Network: A Case Study Using GF2 VHR Imagery in China

Sensors ◽  
2019 ◽  
Vol 19 (5) ◽  
pp. 1164 ◽  
Author(s):  
Yuchu Qin ◽  
Yunchao Wu ◽  
Bin Li ◽  
Shuai Gao ◽  
Miao Liu ◽  
...  
Keyword(s):  
Neural Network ◽  
High Performance ◽  
Semantic Segmentation ◽  
Urban Environments ◽  
Building Roof ◽  
Metropolitan Regions ◽  
Novel Approach ◽  
Development Goals ◽  
Model Training ◽  
Dense Urban Environment

This paper presents a novel approach for semantic segmentation of building roofs in dense urban environments with a Deep Convolution Neural Network (DCNN) using Chinese Very High Resolution (VHR) satellite (i.e., GF2) imagery. To provide an operational end-to-end approach for accurately mapping build roofs with feature extraction and image segmentation, a fully convolutional DCNN with both convolutional and deconvolutional layers is designed to perform building roof segmentation. We selected typical cities with dense and diverse urban environments in different metropolitan regions of China as study areas, and sample images were collected over cities. High performance GPU-mounted workstations are employed to perform the model training and optimization. With the building roof samples collected over different cities, the predictive model with convolution layers is developed for building roof segmentation. The validation shows that the overall accuracy (OA) and the mean Intersection Over Union (mIOU) of DCNN-based semantic segmentation results are 94.67% and 0.85, respectively, and the CRF-refined segmentation results achieved OA of 94.69% and mIOU of 0.83. The results suggest that the proposed approach is a promising solution for building roof mapping with VHR images over large areas in dense urban environments with different building patterns. With the operational acquisition of GF2 VHR imagery, it is expected to develop an automated pipeline of operational built-up area monitoring, and the timely update of building roof map could be applied in urban management and assessment of human settlement-related sustainable development goals over large areas.

High-speed electron beam data verification system using high-performance neural network accelerator board

1996 ◽  
Author(s):  
Toshiyuki Tamura ◽  
Dominique Bouchon ◽  
Pierre Fournier ◽  
Koichi Moriizumi ◽  
Ken-ichi Tanaka ◽  
...  
Keyword(s):  
Neural Network ◽  
Electron Beam ◽  
High Speed ◽  
High Performance ◽  
Data Verification ◽  
Verification System

scholarly journals Fast Calculation of Computer Generated Holograms for 3D Photostimulation through Compressive-Sensing Gerchberg–Saxton Algorithm

2018 ◽  
Vol 2 (1) ◽  
pp. 2 ◽  
Author(s):  
Paolo Pozzi ◽  
Laura Maddalena ◽  
Nicolò Ceffa ◽  
Oleg Soloviev ◽  
Gleb Vdovin ◽  
...  
Keyword(s):  
Compressive Sensing ◽  
High Speed ◽  
High Performance ◽  
High Efficiency ◽  
Three Dimensions ◽  
Spatial Light Modulators ◽  
Multiple Diffraction ◽  
Excitation Light ◽  
Computer Generated Holograms

The use of spatial light modulators to project computer generated holograms is a common strategy for optogenetic stimulation of multiple structures of interest within a three-dimensional volume. A common requirement when addressing multiple targets sparsely distributed in three dimensions is the generation of a points cloud, focusing excitation light in multiple diffraction-limited locations throughout the sample. Calculation of this type of holograms is most commonly performed with either the high-speed, low-performance random superposition algorithm, or the low-speed, high performance Gerchberg–Saxton algorithm. This paper presents a variation of the Gerchberg–Saxton algorithm that, by only performing iterations on a subset of the data, according to compressive sensing principles, is rendered significantly faster while maintaining high quality outputs. The algorithm is presented in high-efficiency and high-uniformity variants. All source code for the method implementation is available as Supplementary Materials and as open-source software. The method was tested computationally against existing algorithms, and the results were confirmed experimentally on a custom setup for in-vivo multiphoton optogenetics. The results clearly show that the proposed method can achieve computational speed performances close to the random superposition algorithm, while retaining the high performance of the Gerchberg–Saxton algorithm, with a minimal hologram quality loss.

scholarly journals Forward Kinematics and Workspace Determination of a Novel Redundantly Actuated Parallel Manipulator

2019 ◽  
Vol 2019 ◽  
pp. 1-14 ◽  
Author(s):  
Haiqiang Zhang ◽  
Hairong Fang ◽  
Dan Zhang ◽  
Xueling Luo ◽  
Qi Zou
Keyword(s):  
Neural Network ◽  
Bp Neural Network ◽  
Parallel Manipulator ◽  
High Speed ◽  
High Efficiency ◽  
Screw Theory ◽  
Back Propagation ◽  
Forward Kinematics ◽  
Redundantly Actuated ◽  
Five Axis

This paper presents a novel redundantly actuated 2RPU-2SPR parallel manipulator that can be employed to form a five-axis hybrid kinematic machine tool for large heterogeneous complex structural component machining in aerospace field. On the contrary to series manipulators, the parallel manipulator has the potential merits of high stiffness, high speed, excellent dynamic performance, and complicated surface processing capability. First, by resorting to the screw theory, the degree of freedom of the proposed parallel manipulator is briefly addressed with general configuration and verified by Grübler-Kutzbach (G-K) criteria as well. Next, the inverse kinematics solution for such manipulator is deduced in detail; however, the forward kinematics is mathematically intractable. To deal with such problem, the forward kinematics is solved by means of three back propagation (BP) neural network optimization strategies. The remarkable simulation results of the parallel manipulator demonstrate that the BP neural network with position compensation is an appropriate method for solving the forward kinematics because of its various advantages, such as high efficiency and high convergence ratios. Simultaneously, workspaces, including joint space and workspace of the proposed parallel manipulator, are graphically depicted based on the previous research, which illustrate that the proposed manipulator is a good candidate for engineering practical application.

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