scholarly journals Hardware Acceleration of Convolution Neural Network for AI-Enabled Realtime Biomedical System

2021 ◽  
Vol 102 ◽  
pp. 04019
Author(s):  
Okada Yuuki ◽  
Jiangkun Wang ◽  
Ogbodo Mark Ikechukwu ◽  
Abderazek Ben Abdallah
Keyword(s):  
Circuit Design ◽  
Data Transfer ◽  
Hardware Acceleration ◽  
Single Image ◽  
Speed Up ◽  
Chest X Ray ◽  
Software And Hardware ◽  
Biomedical System ◽  
Diagnostic Measurement ◽  
Network Software

COVID-19 is currently on the rage all over the world and has become a pandemic. To efficiently handle it, accurate diagnosis and prompt reporting are essential. The AI-Enabled Real-time Biomedical System (AIRBiS) research project aims to develop a system that handles diagnosis using chest X-ray images. The project is divided into UI, network, software and hardware. This work focuses on the hardware, which uses CNN technology to create a model that determines the presence of pneumonia. This CNN model is designed on an FPGA to speed up diagnostic results. The FPGA increases the flexibility of circuit design, allowing us to optimize the computational processing during data transfer and CNN implementation, reducing the diagnostic measurement time for a single image.

A COMPREHENSIVE AUTOMATED SOLUTION TO THE PROBLEM OF AIR ENVIRONMENT MONITORING

2021 ◽  
Author(s):  
В.А. ОСАНОВ ◽  
С.М. КОНДРАТЬЕВ ◽  
О.С. КОНЯЕВА
Keyword(s):  
Unmanned Aerial Vehicles ◽  
Communication Channel ◽  
Data Transfer ◽  
Automated System ◽  
Environment Monitoring ◽  
Practical Application ◽  
Air Masses ◽  
System Functioning ◽  
Direction Of Movement ◽  
Software And Hardware

Рассмотрена автоматизированная система мониторинга воздушной среды с использованием технологий беспилотных летательных аппаратов, оснащенных датчиками для выявления вредных веществ. Представлены алгоритм функционирования системы и программно-аппаратная часть решения. Показано, что канал связи на основе методов шифрования обеспечивает безопасную передачу данных с беспилотного аппарата на сервер. Результаты исследования найдут практическое применение в мониторинге уровня загрязнения воздуха в городах. An automated system for monitoring the air environment using technologies of unmanned aerial vehicles equipped with sensors for detecting harmful substances is considered. The algorithm of the system functioning and the software and hardware part of the solution are presented. It is shown that a communication channel based on encryption methods ensures secure data transfer from an unmanned vehicle to a server. The results of the study will find practical application in monitoring the level of air pollution in cities and in predicting the direction of movement of polluting air masses.

The Design for High-Power Maglev Blower Controller

2013 ◽  
Vol 712-715 ◽  
pp. 2747-2752
Author(s):  
Wen Tao Yu ◽  
Hong Wei Li ◽  
Shu Qin Liu ◽  
Yun Peng Zhang
Keyword(s):  
High Power ◽  
Data Transfer ◽  
Sewage Treatment ◽  
Magnetic Bearing ◽  
Plain Bearing ◽  
Current Signal ◽  
Speed Up ◽  
Bandstop Filter ◽  
Dual Core

The maglev blower used in sewage treatment, which power is 115kW, speed up to 20000rpm, for plain bearing blower speed 6-8 times, volume is only 1/4 of the plain bearing and the noise is less than 80dB. The controller uses a DSP and FPGA dual-core controller to complete. DSP process the rotor suspension signal with digital bandstop filter program and improved PID program, FPGA complete the current signal amplification.Two chip via custom protocol to complete the data transfer. It is successful application of the controller that used in the magnetic bearing blower.

scholarly journals Hardware Acceleration of Sparse Support Vector Machines for Edge Computing

2020 ◽  
Vol 26 (3) ◽  
pp. 42-53
Author(s):  
Vuk Vranjkovic ◽  
Rastislav Struharik
Keyword(s):  
Support Vector Machines ◽  
Hardware Acceleration ◽  
Edge Computing ◽  
Support Vector ◽  
Vector Machines ◽  
Field Programmable ◽  
Programmable Gate Arrays ◽  
Speed Up ◽  
Memory Reduction ◽  
Systems With Memory

In this paper, a hardware accelerator for sparse support vector machines (SVM) is proposed. We believe that the proposed accelerator is the first accelerator of this kind. The accelerator is designed for use in field programmable gate arrays (FPGA) systems. Additionally, a novel algorithm for the pruning of SVM models is developed. The pruned SVM model has a smaller memory footprint and can be processed faster compared to dense SVM models. In the systems with memory throughput, compute or power constraints, such as edge computing, this can be a big advantage. The experiments on several standard datasets are conducted, which aim is to compare the efficiency of the proposed architecture and the developed algorithm to the existing solutions. The results of the experiments reveal that the proposed hardware architecture and SVM pruning algorithm has superior characteristics in comparison to the previous work in the field. A memory reduction from 3 % to 85 % is achieved, with a speed-up in a range from 1.17 to 7.92.

scholarly journals Chest X-ray image analysis and classification for COVID-19 pneumonia detection using Deep CNN

2020 ◽  
Author(s):  
Terry Gao ◽  
Grace Wang
Keyword(s):  
Training Dataset ◽  
X Rays ◽  
X Ray ◽  
Speed Up ◽  
Chest X Ray ◽  
Coronavirus Infection ◽  
Deep Cnn ◽  
Detection And Diagnosis ◽  
The Individual ◽  
New Diagnosis

Abstract To speed up the discovery of COVID-19 disease mechanisms, this research developed a new diagnosis platform using a deep convolutional neural network (CNN) that is able to assist radiologists with diagnosis by distinguishing COVID-19 pneumonia from non-COVID-19 pneumonia in patients at Middlemore Hospital based on chest X-ray classification and analysis. Such a tool can save time in interpreting chest X-rays and increase the accuracy and thereby enhance our medical capacity for the detection and diagnosis of COVID-19. The research idea is that a set of X-ray medical lung images (which include normal, infected by bacteria, infected by virus including COVID-19) were used to train a deep CNN that can distinguish between the noise and the useful information and then uses this training to interpret new images by recognizing patterns that indicate certain diseases such as coronavirus infection in the individual images. The supervised learning method is used as the process of learning from the training dataset and can be thought of as a doctor supervising the learning process. It becomes more accurate as the number of analyzed images grows. In this way, it imitates the training for a doctor, but the theory is that since it is capable of learning from a far larger set of images than any human, it can have the potential of being more accurate.

scholarly journals Software and Hardware Requirements and Trade-Offs in Operating Systems for Wearables: A Tool to Improve Devices’ Performance

Sensors ◽  
2019 ◽  
Vol 19 (8) ◽  
pp. 1904 ◽  
Author(s):  
Vicente J. P. Amorim ◽  
Mateus C. Silva ◽  
Ricardo A. R. Oliveira
Keyword(s):  
Operating Systems ◽  
Software Tool ◽  
Wearable Devices ◽  
End User ◽  
Performance Impact ◽  
Performance Improvements ◽  
Trade Offs ◽  
Speed Up ◽  
Software And Hardware ◽  
Hard Real Time

Wearable device requirements currently vary from soft to hard real-time constraints. Frequently, hardware improvements are a way to speed-up the global performance of a solution. However, changing some parts or the whole hardware may increase device complexity, raising the costs and leading to development delays of products or research prototypes. This paper focuses on software improvements, presenting a tool designed to create different versions of operating systems (OSs) fitting the specifications of wearable devices projects. Authors have developed a software tool allowing the end-user to craft a new OS in just a few steps. In order to validate the generated OS, an original wearable prototype for mining environments is outlined. Resulting data presented here allows for measuring the actual impact an OS has in different variables of a solution. Finally, the analysis also allows for evaluating the performance impact associated with each hardware part. Results suggest the viability of using the proposed solution when searching for performance improvements on wearables.

SECURITY ANALYSIS OF SOFTWARE AND HARDWARE COMPONENTS IN WIRELESS SENSOR NETWORKS

Telecom IT ◽  
2019 ◽  
Vol 7 (1) ◽  
pp. 75-83
Author(s):  
V. Desnitsky ◽  
A. Meleshko
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
System Analysis ◽  
Data Transfer ◽  
Security Analysis ◽  
Wireless Sensor ◽  
Practical Significance ◽  
Analysis Method ◽  
The Subject ◽  
Software And Hardware

The paper comprises a review of approaches to security analysis of software and hardware components in wireless sensor networks. Research subject. The subject of the research is existing approaches to security analysis. Method. The methods of system analysis are applied in the work. Core results. A detailed analysis of existing threats and attacks on wireless sensor networks as well as an analysis of vulnerabilities and data transfer protocols between nodes of such systems has been performed. The main directions to ensure security of the wireless sensor networks are identified. Practical significance. The results obtained in this paper can be used to improve the means of protecting the wireless sensor networks from various cyber-physical attacks.

ANALYZER OF DATA STRUCTURES AT APPLICATION LEVEL OF INTERACTION BASED ON AUTOMATED EXTRACTION OF KNOWLEDGE (INFORMATION) FROM SOURCES

2018 ◽  
pp. 45-49
Author(s):  
A. S. Aksenov
Keyword(s):  
Data Transfer ◽  
Software Tool ◽  
Data Representation ◽  
Network Activity ◽  
Software Suite ◽  
Network Interaction ◽  
Information Interaction ◽  
Source Data ◽  
Software And Hardware ◽  
Further Development

This paper considers the issue of creating a software tool that provides the performing of the analysis of data received via various data transfer interfaces. The performing of the analysis helps to check the correctness of formation of the structure of informational and controlling messages of various components of a system under development, as well as the correctness of the network interaction and testing debugging and adjustment of software and hardware in terms of their information interaction at the level of information compatibility. A comparison with the existing network activity analysis tools is presented and several approaches to solving the issue of data analysis at the application level are compared. The article provides the validity of the choice of a unified format of srcML source data representation. Also it specifies the directions for further development of the analyzing program within present project solution. The expediency of the development of this software tool and the results of its application in the development of special‑purpose hardware and software suite are given in the conclusion.

Quantum-based algorithm and circuit design for bounded Knapsack optimization problem

2020 ◽  
Vol 20 (9&10) ◽  
pp. 766-786
Author(s):  
Wenjun Hou ◽  
Marek Perkowski
Keyword(s):  
Circuit Design ◽  
Knapsack Problem ◽  
Decision Problem ◽  
Optimization Problem ◽  
Quantum Algorithm ◽  
Quantum Circuits ◽  
Local Quantum ◽  
Speed Up ◽  
Grover Search ◽  
Quantum Simulator

The Knapsack Problem is a prominent problem that is used in resource allocation and cryptography. This paper presents an oracle and a circuit design that verifies solutions to the decision problem form of the Bounded Knapsack Problem. This oracle can be used by Grover Search to solve the optimization problem form of the Bounded Knapsack Problem. This algorithm leverages the quadratic speed-up offered by Grover Search to achieve a quantum algorithm for the Knapsack Problem that shows improvement with regard to classical algorithms. The quantum circuits were designed using the Microsoft Q# Programming Language and verified on its local quantum simulator. The paper also provides analyses of the complexity and gate cost of the proposed oracle. The work in this paper is the first such proposed method for the Knapsack Optimization Problem.

A Data Transfer Integrate System by Using Single Camera

2013 ◽  
Vol 373-375 ◽  
pp. 960-964
Author(s):  
Shyang Lih Chang ◽  
Shih Jia Wang ◽  
Ming Chih Lu ◽  
Cheng Pei Tsai
Keyword(s):  
Data Transfer ◽  
Digital Signal ◽  
Landslide Monitoring ◽  
Single Image ◽  
Integration System ◽  
The Matrix ◽  
Monitoring Camera ◽  
Sensor Signals ◽  
Mountain Terrains ◽  
Monitoring Area

there is a novel data transfer integration system by using single image proposed in this paper. There are many sensors use to monitoring the landslide occurred or not, but the monitoring results have different transmit protocol such as: Wi-Fi, transmit line, 2.4 GHz and ZigBee. This system is a data transfer integration system for all sensors, and it can achieve a real time monitoring system. The system integrate many sensor signals to microprocessor, and convert analog signal to digital signal by using A/D converter, i2c and UART, and the measuring results of sensors and display on a 8*8 matrix LED board. The system use the existing landslide-monitoring camera, and the matrix LED board install in the monitoring area. The result of sensors can be transmit to monitoring center by using single image, the data will not affect by environment, weather and mountain terrains.

Sign in / Sign up

Export Citation Format

Share Document