scholarly journals Science & technology trends in cognitive radar concept

2021 ◽  
pp. 22-34
Author(s):  
А.С. Дудуш ◽  
І.І. Сачук ◽  
Сальман Оваід ◽  
А.К. Бідун
Keyword(s):  
High Performance ◽  
Pulse Repetition Frequency ◽  
Modulation Frequency ◽  
Pulse Length ◽  
Relevant Information ◽  
Human Cognition ◽  
Embedded Computing ◽  
Power Pulse ◽  
Human Operators ◽  
Arbitrary Waveform

Currently, human operators provide cognition in a radar system. However, advances in the “digitization” of radar front-ends, including digital arbitrary waveform generators (AWG) and advanced high performance embedded computing (HPEC) make it possible to vary all key radar parameters (power, pulse length, number of pulses, pulse repetition frequency (PRF), modulation, frequency, polarization) on a pulse-by-pulse basis within ns or ms and over a wide operating range. This timescale is much faster than the decision-making ability of a human operator. The cognitive-inspired techniques in radar, that are intensively developing last years, mimic elements of human cognition and the use of external knowledge to use the available system resources in an optimal way for the current goal and environment. Radar systems based on the perception-action cycle of cognition that senses the environment, learns relevant information from it about the target and the background and then adapts the radar to optimally satisfy the needs of the mission according to a desired goal are called cognitive radars. In the article, recent ideas and applications of cognitive radars were analyzed.

Sulphonamide: Distribution, Toxicology, Environmental Characteristics, and Analysis - A Review

2020 ◽  
Vol 16 ◽  
Author(s):  
Kirubanandam Grace Pavithra ◽  
Vasudevan Jaikumar ◽  
Ponnusamy Senthil Kumar ◽  
PanneerSelvam SundarRajan
Keyword(s):  
Aqueous Solution ◽  
High Performance Liquid Chromatography ◽  
Capillary Electrophoresis ◽  
Liquid Chromatography ◽  
High Performance ◽  
Uv Spectroscopy ◽  
Relevant Information ◽  
Fluorometric Determination ◽  
Distinctive Features ◽  
The World

Background: Many antibiotics were widely used as medication based on their distinctive features. Among them, sulphonamides were commonly used, however their recalcitrant nature makes them difficult to dispose. Hence, their interaction with environment and analytic technique requires considerable attention globally. Objective: Therefore, this review aimed to provide detailed discussion about environmental as well as human health behaviour and analytic techniques corresponding to sulphonamides. Methods: Various results and discussion were extracted from technical journals and books published by different researchers from all over the world. The cited bibliographic references were intentionally investigated in order to extract relevant information related to proposed work. Results: In this review, the determination techniques such as UV-spectroscopy, Enthalpimetry, Immunosensor, Chromatography, Chemiluminescence, Photoinduced fluorometric determination, Capillary electrophoresis for sulphonamide determination were discussed in detail. Among them, High performance liquid chromatography (HPLC) and UV-spectroscopy was effective and extensively used for screening sulphonamide. Conclusion: Knowing the quantification and behaviour of sulphonamide in aqueous solution is mandatory to opt the suitable wastewater treatment required. Hence, choosing appropriate high precision and feasible screening techniques is necessary, which can be attained with this review.

Evaluating the potential of graphics processors for high performance embedded computing

2011 ◽  
Author(s):  
Shuai Mu ◽  
Chenxi Wang ◽  
Ming Liu ◽  
Dongdong Li ◽  
Maohua Zhu ◽  
...  
Keyword(s):  
High Performance ◽  
Graphics Processors ◽  
Embedded Computing

An approach for document retrieval using cluster-based inverted indexing

2021 ◽  
pp. 016555152110184
Author(s):  
Gunjan Chandwani ◽  
Anil Ahlawat ◽  
Gaurav Dubey
Keyword(s):  
High Performance ◽  
Clustering Algorithm ◽  
Pearson Correlation ◽  
Relevant Information ◽  
Document Retrieval ◽  
Bhattacharyya Distance ◽  
Data Set ◽  
Query Matching ◽  
Inverted Indexing ◽  
Query Optimisation

Document retrieval plays an important role in knowledge management as it facilitates us to discover the relevant information from the existing data. This article proposes a cluster-based inverted indexing algorithm for document retrieval. First, the pre-processing is done to remove the unnecessary and redundant words from the documents. Then, the indexing of documents is done by the cluster-based inverted indexing algorithm, which is developed by integrating the piecewise fuzzy C-means (piFCM) clustering algorithm and inverted indexing. After providing the index to the documents, the query matching is performed for the user queries using the Bhattacharyya distance. Finally, the query optimisation is done by the Pearson correlation coefficient, and the relevant documents are retrieved. The performance of the proposed algorithm is analysed by the WebKB data set and Twenty Newsgroups data set. The analysis exposes that the proposed algorithm offers high performance with a precision of 1, recall of 0.70 and F-measure of 0.8235. The proposed document retrieval system retrieves the most relevant documents and speeds up the storing and retrieval of information.

scholarly journals Embedded GPU Implementation for High-Performance Ultrasound Imaging

Electronics ◽  
2021 ◽  
Vol 10 (8) ◽  
pp. 884
Author(s):  
Stefano Rossi ◽  
Enrico Boni
Keyword(s):  
High Performance ◽  
Graphics Processing Unit ◽  
Digital Signal ◽  
Processing Unit ◽  
Embedded Computing ◽  
Field Programmable ◽  
Peripheral Component Interconnect ◽  
Programmable Gate Arrays ◽  
Graphics Processing ◽  
Signal Processors

Methods of increasing complexity are currently being proposed for ultrasound (US) echographic signal processing. Graphics Processing Unit (GPU) resources allowing massive exploitation of parallel computing are ideal candidates for these tasks. Many high-performance US instruments, including open scanners like ULA-OP 256, have an architecture based only on Field-Programmable Gate Arrays (FPGAs) and/or Digital Signal Processors (DSPs). This paper proposes the implementation of the embedded NVIDIA Jetson Xavier AGX module on board ULA-OP 256. The system architecture was revised to allow the introduction of a new Peripheral Component Interconnect Express (PCIe) communication channel, while maintaining backward compatibility with all other embedded computing resources already on board. Moreover, the Input/Output (I/O) peripherals of the module make the ultrasound system independent, freeing the user from the need to use an external controlling PC.

On Construction of a Diskless Cluster Computing Environment in a Computer Classroom

2012 ◽  
Vol 4 (4) ◽  
pp. 68-88
Author(s):  
Chao-Tung Yang ◽  
Wen-Feng Hsieh
Keyword(s):  
High Performance ◽  
Cluster Computing ◽  
Relevant Information ◽  
Computing Environment ◽  
Cluster Architecture ◽  
Computer Classroom ◽  
Computation Node ◽  
Cluster Environment ◽  
Computing Performance ◽  
Performance Computing

This paper’s objective is to implement and evaluate a high-performance computing environment by clustering idle PCs (personal computers) with diskless slave nodes on campuses to obtain the effectiveness of the largest computer potency. Two sets of Cluster platforms, BCCD and DRBL, are used to compare computing performance. It’s to prove that DRBL has better performance than BCCD in this experiment. Originally, DRBL was created to facilitate instructions for a Free Software Teaching platform. In order to achieve the purpose, DRBL is applied to the computer classroom with 32 PCs so to enable PCs to be switched manually or automatically among different OS (operating systems). The bioinformatics program, mpiBLAST, is executed smoothly in the Cluster architecture as well. From management’s view, the state of each Computation Node in Clusters is monitored by “Ganglia”, an existing Open Source. The authors gather the relevant information of CPU, Memory, and Network Load for each Computation Node in every network section. Through comparing aspects of performance, including performance of Swap and different network environment, they attempted to find out the best Cluster environment in a computer classroom at the school. Finally, HPL of HPCC is used to demonstrate cluster performance.

scholarly journals Microprocessors KOMDIV for High Performance Embedded Systems

2021 ◽  
Vol 7 (3) ◽  
Author(s):  
S.G. Bobkov
Keyword(s):  
Embedded Systems ◽  
Power Consumption ◽  
High Performance ◽  
Clock Cycle ◽  
Embedded Computing ◽  
Computing Systems ◽  
Processor Performance

The problems of creating of high-performance embedded computing systems based on microprocessors KOMDIV is considered. Processor performance is dependent upon three characteristics: clock cycle, clock cycles per instruction, and instruction count. These characteristics for microprocessors KOMDIV are optimized using parameter performance/power consumption and requirements of embedded systems.

scholarly journals A High-Speed Elliptic Curve Cryptography Processor for Teleoperated Systems Security

2021 ◽  
Vol 2021 ◽  
pp. 1-8
Author(s):  
Yong Xiao ◽  
Weibin Lin ◽  
Yun Zhao ◽  
Chao Cui ◽  
Ziwen Cai
Keyword(s):  
Elliptic Curve ◽  
Elliptic Curve Cryptography ◽  
High Speed ◽  
High Performance ◽  
Prime Field ◽  
Practical Applications ◽  
Cell Library ◽  
Cryptographic Algorithm ◽  
Human Operators ◽  
Key Length

Teleoperated robotic systems are those in which human operators control remote robots through a communication network. The deployment and integration of teleoperated robot’s systems in the medical operation have been hampered by many issues, such as safety concerns. Elliptic curve cryptography (ECC), an asymmetric cryptographic algorithm, is widely applied to practical applications because its far significantly reduced key length has the same level of security as RSA. The efficiency of ECC on GF (p) is dictated by two critical factors, namely, modular multiplication (MM) and point multiplication (PM) scheduling. In this paper, the high-performance ECC architecture of SM2 is presented. MM is composed of multiplication and modular reduction (MR) in the prime field. A two-stage modular reduction (TSMR) algorithm in the SCA-256 prime field is introduced to achieve low latency, which avoids more iterative subtraction operations than traditional algorithms. To cut down the run time, a schedule is put forward when exploiting the parallelism of multiplication and MR inside PM. Synthesized with a 0.13 um CMOS standard cell library, the proposed processor consumes 341.98k gate areas, and each PM takes 0.092 ms.

Creating Superior Knowledge Discovery Solutions

2011 ◽  
pp. 795-799 ◽  
Author(s):  
Nilmini Wickramasinghe
Keyword(s):  
Decision Making ◽  
Knowledge Management ◽  
Decision Support ◽  
Knowledge Discovery ◽  
High Performance ◽  
New Technologies ◽  
Relevant Information ◽  
Customer Relationship ◽  
Business Strategies ◽  
Competitive Edge

The information age has made information communication technology (ICT) a necessity for conducting business. This in turn has led to the exponential increase in the electronic capture of data and its storage in vast data warehouses. In order to respond quickly to fast changing markets, organizations must maximize these raw data and information resources. Specifically, they need to transform them into germane knowledge to aid superior decision-making (Wickramasinghe & von Lubitz, 2006). To do this effectively not only involves the analysis of the data and information but also requires the use of sophisticated tools to enable such analyses to occur. Knowledge discovery technologies represent a spectrum of new technologies that facilitate the analysis of data to find relationships from the data to finding reasons behind observable patterns (i.e., transform the data into relevant information and germane knowledge). Such new discoveries can have a profound impact on decision making in general and the designing of business strategies. With the massive increase in data being collected and the demands of a new breed of intelligent applications like customer relationship management, demand planning, and predictive forecasting, these knowledge discovery technologies are becoming competitive necessities for providing a high performance and feature rich intelligent application servers for intelligent enterprises. Knowledge management (KM) tools and technologies are the systems that integrate various legacy systems, databases, ERP systems, and data warehouse to help facilitate an organization’s knowledge discovery process. Integrating all of these with advanced decision support and online real time events enables an organization to understand customers better and devise business strategies accordingly. Creating a competitive edge is the goal of all organizations employing knowledge discovery for decision support (Thorne & Smith, 2000). The following provides a synopsis of the major tools and critical considerations required to enable an organization to successfully effect appropriate knowledge sharing, knowledge distribution, knowledge creation, as well as knowledge capture and codification processes and hence embrace effective knowledge management (KM) techniques and advanced knowledge discovery.

scholarly journals Phase-coded pulse aperiodic transmitter coding

2009 ◽  
Vol 27 (7) ◽  
pp. 2799-2811 ◽  
Author(s):  
I. I. Virtanen ◽  
J. Vierinen ◽  
M. S. Lehtinen
Keyword(s):  
Correlation Time ◽  
Pulse Repetition Frequency ◽  
Pulse Length ◽  
Simulated Data ◽  
Qualitative Evaluation ◽  
Weather Radar ◽  
Estimation Accuracy ◽  
Time Lags ◽  
F Region ◽  
D Region

Abstract. Both ionospheric and weather radar communities have already adopted the method of transmitting radar pulses in an aperiodic manner when measuring moderately overspread targets. Among the users of the ionospheric radars, this method is called Aperiodic Transmitter Coding (ATC), whereas the weather radar users have adopted the term Simultaneous Multiple Pulse-Repetition Frequency (SMPRF). When probing the ionosphere at the carrier frequencies of the EISCAT Incoherent Scatter Radar facilities, the range extent of the detectable target is typically of the order of one thousand kilometers – about seven milliseconds – whereas the characteristic correlation time of the scattered signal varies from a few milliseconds in the D-region to only tens of microseconds in the F-region. If one is interested in estimating the scattering autocorrelation function (ACF) at time lags shorter than the F-region correlation time, the D-region must be considered as a moderately overspread target, whereas the F-region is a severely overspread one. Given the technical restrictions of the radar hardware, a combination of ATC and phase-coded long pulses is advantageous for this kind of target. We evaluate such an experiment under infinitely low signal-to-noise ratio (SNR) conditions using lag profile inversion. In addition, a qualitative evaluation under high-SNR conditions is performed by analysing simulated data. The results show that an acceptable estimation accuracy and a very good lag resolution in the D-region can be achieved with a pulse length long enough for simultaneous E- and F-region measurements with a reasonable lag extent. The new experiment design is tested with the EISCAT Tromsø VHF (224 MHz) radar. An example of a full D/E/F-region ACF from the test run is shown at the end of the paper.

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