Hardware Interface with the Outside World

2021 ◽  
pp. 75-147
Keyword(s):  
Hardware Interface

Development of Dedicated Controller for HVAC

2012 ◽  
Vol 430-432 ◽  
pp. 1472-1476
Author(s):  
Jin Ming Yang ◽  
Yi Lin
Keyword(s):  
Fuzzy Control ◽  
Control Algorithm ◽  
Control Strategies ◽  
Control Software ◽  
Interface Circuits ◽  
Pid Algorithm ◽  
Hardware Interface ◽  
Hvac Control ◽  
Fuzzy Control Algorithm

This article describes the development of a dedicated controller for HVAC control, and introduces the hardware interface circuits about some main chip on controller. In addition, the article also explains composition and principle about control software applied to the controller, further more points out that the fuzzy control algorithm is more reasonable than the PID algorithm for most HVAC control and dedicated control strategies play an important role for HVAC control.

Developing program-hardware interface for polar codes characteristics studying

Trudy MAI ◽  
2021 ◽  
pp. 7-7
Author(s):  
Alexey Volkov ◽  
Alexey Solodkov ◽  
Denis Tsymlyakov
Keyword(s):  
Polar Codes ◽  
Hardware Interface

Software-defined data protection

2021 ◽  
Vol 14 (7) ◽  
pp. 1167-1174
Author(s):  
Zsolt István ◽  
Soujanya Ponnapalli ◽  
Vijay Chidambaram
Keyword(s):  
Data Processing ◽  
Data Protection ◽  
Distributed Storage ◽  
Hardware Design ◽  
Large Data ◽  
Hardware Interface ◽  
Future Data ◽  
Specialized Hardware

Most modern data processing pipelines run on top of a distributed storage layer, and securing the whole system, and the storage layer in particular, against accidental or malicious misuse is crucial to ensuring compliance to rules and regulations. Enforcing data protection and privacy rules, however, stands at odds with the requirement to achieve higher and higher access bandwidths and processing rates in large data processing pipelines. In this work we describe our proposal for the path forward that reconciles the two goals. We call our approach "Software-Defined Data Protection" (SDP). Its premise is simple, yet powerful: decoupling often changing policies from request-level enforcement allows distributed smart storage nodes to implement the latter at line-rate. Existing and future data protection frameworks can be translated to the same hardware interface which allows storage nodes to offload enforcement efficiently both for company-specific rules and regulations, such as GDPR or CCPA. While SDP is a promising approach, there are several remaining challenges to making this vision reality. As we explain in the paper, overcoming these will require collaboration across several domains, including security, databases and specialized hardware design.

Abstract P365: Blood Pressure Evaluation From Ppg Signal Analysis and Artificial Neural Network

Hypertension ◽  
2017 ◽  
Vol 70 (suppl_1) ◽  
Author(s):  
Francesco Lamonaca ◽  
Vitaliano Spagnuolo ◽  
Serena De Prisco ◽  
Domenico L Carnì ◽  
Domenico Grimaldi
Keyword(s):  
Neural Network ◽  
Blood Pressure ◽  
Artificial Neural Network ◽  
Audio Signal ◽  
Hardware Interface ◽  
Validation Procedure ◽  
Artificial Neural ◽  
Artificial Neural Network Ann ◽  
The Time Domain ◽  
And Storage

The analysis of the PPG signal in the time domain for the evaluation of the blood pressure (BP) is proposed. Some features extracted from the PPG signal are used to train an Artificial Neural Network (ANN) to determine the function that fit the target systolic and diastolic BP. The data related to the PPG signals and BP used in the analysis are provided by the Multi-parameter Intelligent Monitoring in Intensive Care (MIMIC II) database. The pre-analysis of the signal to remove inconsistent data is also proposed. A set of 1750 valid pulse is considered. The 80% of the input samples is used for the training of the network. Instead, the 10% of the input data are used for the validation of the network and 10% for final test of this last. The results show as the error for both the systolic and diastolic BP evaluation is included in the range of ±3 mmHg. Tab.1 shows the results for 20 PPG pulses randomly selected analyzed together with the systolic and diastolic blood pressure furnished by MIMC and evaluated by the trained ANN. Tab.1 experimental results comparing MIMIC and the ANN results. Moreover, a suitable hardware to validate the ANN with the sphygmomanometer is designed and realized. This hardware allows clinicians to collect data according to the requirements of the validation procedure. With the sphygmomanometer the systolic and diastolic values are referred to two different PPG pulses. As a consequence, it is proposed a new hardware interface allowing the synchronized acquisition and storage of the PPG signal and clinician voice. For the validation, the clinician: (i) evaluates the BP on both the arms and assesses that no significant differences occur; (ii) plugs the PPG sensor on the finger of one arm; (iii) starts the recording of both the PPG signal and the audio signal; (iv) evaluates the BP on the other arm with sphygmomanometer and says the systolic and diastolic values when detected. Through suitable post processing algorithm, the Systolic and Diastolic values are associated to the corresponding PPG Pulses. Following this procedure, the dataset to further validate the ANN according the standard is obtained. Once the ANN is validated it will be implemented on smartphone to have always in the pocket a reliable measurement system for Blood Pressure, oximetry and heart rate.

Design of CAN Central Control Modular Based on USB

2012 ◽  
Vol 490-495 ◽  
pp. 990-993
Author(s):  
Xiao Yan Zhang ◽  
Guo Liang Fan
Keyword(s):  
Real Time ◽  
High Speed ◽  
Can Bus ◽  
High Reliability ◽  
Central Control ◽  
Single Chip ◽  
Interface Circuits ◽  
Hardware Interface ◽  
Level Data ◽  
Communication Devices

The central control modular of liquid level data acquisition and transmission system based on CAN bus was introduced. The modular was controlled by PC for transmitting and receiving data to CAN units through the USB port by the USB2.0-CAN High Speed adapter card designed by CP2102 and SJAl000, and the CAN bus controller SJA1000 and CP2102 was controlled by single chip computer (SCC) AT89C51. The hardware interface circuits was introduced, and the software flowchart and PC application program was also designed. The result shows that the system has the advantages of strong real-time, high speed, high reliability, easily extending communication devices, Plug and Play supporting, and automatic configuration. Its communications quality is better than the traditional ones, such as RS232, RS485 et al., and it can be used as real-time monitor in industrial multiple devices.

Four DOF pneumatic robot design and hardware interface

2017 ◽  
Author(s):  
Jose-Eduardo Gaspar-Badillo ◽  
Juan-Manuel Ramos-Arreguin ◽  
Gonzalo Macias-Bobadilla ◽  
Dimas Talavera-Velazquez ◽  
Edgar-Alejandro Rivas-Araiza ◽  
...  
Keyword(s):  
Robot Design ◽  
Hardware Interface

The Design of WinCE Driver of WSN Nodes Based on ARM

2014 ◽  
Vol 556-562 ◽  
pp. 6058-6062 ◽  
Author(s):  
Jin Wu Ju
Keyword(s):  
Wireless Sensor Networks ◽  
Wireless Sensor Network ◽  
Sensor Network ◽  
Basic Structure ◽  
Network Routing ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Network Node ◽  
Intelligent Sensor ◽  
Hardware Interface

Wireless sensor network (WSN) is the network which is composed of a large number of intelligent sensor nodes, it has the ability of self-organizing network routing, therefore, it has been widely used. Building wireless sensor networks is the key to WSN nodes. This paper introduces the basic structure of wireless sensor network node based on ARM, and it delivers a detailed analysis on the operating features and the CC2480 hardware interface of the ZigBee processor, what’s more, it specifically talks about the implementation of the Wince driver of WSN nodes.

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