scholarly journals Real-time reaction control for solar production of chemicals under fluctuating irradiance

2018 ◽  
Vol 20 (11) ◽  
pp. 2459-2464 ◽  
Author(s):  
Fang Zhao ◽  
Dario Cambié ◽  
Volker Hessel ◽  
Michael G. Debije ◽  
Timothy Noël

A simple and inexpensive reaction control system mitigates the impact of solar irradiance fluctuations on the conversion of a sunlight-powered photochemical reaction, affording constant product quality.

2019 ◽  
Vol 62 (2) ◽  
pp. 134-140 ◽  
Author(s):  
S. V. Knyazev ◽  
D. V. Skopich ◽  
E. A. Fat’yanova ◽  
A. A. Usol’tsev ◽  
A. I. Kutsenko

Introduction of the “Automated system for operational control of casts production (OCCP AS)” makes the basis of an integrated automated production control system (APCS). It performs three main tasks: control and recording (production, products, materials, etc.), improving quality of casts and operational management of technological processes. Solution of these tasks was accomplished through automating data collection in real time for all production operations, recording material flows, creating operational communication channels, as well as centralized collection, processing and representation of data by the process information server. The next step in building an effective automated control system is to stabilize product quality in changing external conditions, for example, quality of materials, and to optimize production (technology change in order to reduce costs for constant or higher product quality). The second stage is based on mathematical processing and analysis of data coming from OCCP AS, it allows to determine optimal ranges of parameters of technological processes  – “Automated system for optimization and analysis of production progress (OAPP AS)”. OAPP AS consists of two subsystems: quality analysis and technology management. The first solves the problem of data analysis and modeling, the second – calculation of real-time optimal process parameters and real time prediction. The stages tasks compete for access to different hardware resources. The most critical parameter for OCCP AS is performance of server disk arrays, for OAPP AS it is processor performance. In either case, system scaling is effectively solved by parallelizing operations across different servers, forming a cluster, and across different processors (cores) on the same server. To process defect images and to obtain cause-and-effect characteristics, you can use OpenCV software package, which is an open source computer vision library. In course of processing, Sobel operator, Gauss filter and binarization were used. They are based on processing pixels using matrices. Operations on pixels are independent and can be performed in parallel. The task of clustering is reduced to definition of an expert method or using various mathematical algorithms for defects belonging to a specific cluster (data block) through a set of values of dependent factors. Thus, data blocks are formed by the criterion of the defect cause. Calculation of a data block to which a product defect belongs can be very resource-intensive operation. To increase efficiency of image recognition systems and parallelization ofsearch operations, it makes sense to place data clusters on different servers. As a result, there is a need for a distributed database. This is a special class of DBMS, which requires appropriate software. Generation of OAPPAS based on a multi-node cluster with ApacheCassandra DBMS installed and using Nvidia video cards supporting CUDA technology on each node will be the cheapest and most effective solution. Video card is selected based on required number of graphics processors on the node.


2013 ◽  
Vol 712-715 ◽  
pp. 2234-2238
Author(s):  
Chao Dong ◽  
Jun Li

Power battery in the HEV normally has a high capacity. Therefore during the start-up procedure of HEV motor, pre-charge phase is essential in order to reduce the impact of high current. In this paper, we build a HEV motor pre-charge model then deploy it on cRIO embedded control system to simulate the whole process with high real time. Finally the paper tests some typical fault conditions which demonstrate great benefits.


Sensors ◽  
2021 ◽  
Vol 21 (24) ◽  
pp. 8365
Author(s):  
Xianfu Zhang ◽  
Yuping Hu ◽  
Ruimin Luo ◽  
Chao Li ◽  
Zhichuan Tang

Surface electromyogram (sEMG) signals are widely employed as a neural control source for lower-limb exoskeletons, in which gait recognition based on sEMG is particularly important. Many scholars have taken measures to improve the accuracy of gait recognition, but several real-time limitations affect its applicability, of which variation in the load styles is obvious. The purposes of this study are to (1) investigate the impact of different load styles on gait recognition; (2) study whether good gait recognition performance can be obtained when a convolutional neural network (CNN) is used to deal with the sEMG image from sparse multichannel sEMG (SMC-sEMG); and (3) explore whether the control system of the lower-limb exoskeleton trained by sEMG from part of the load styles still works efficiently in a real-time environment where multiload styles are required. In addition, we discuss an effective method to improve gait recognition at the levels of the load styles. In our experiment, fifteen able-bodied male graduate students with load (20% of body weight) and using three load styles (SBP = backpack, SCS = cross shoulder, SSS = straight shoulder) were asked to walk uniformly on a treadmill. Each subject performed 50 continuous gait cycles under three speeds (V3 = 3 km/h, V5 = 5 km/h, and V7 = 7 km/h). A CNN was employed to deal with sEMG images from sEMG signals for gait recognition, and back propagation neural networks (BPNNs) and support vector machines (SVMs) were used for comparison by dealing with the same sEMG signal. The results indicated that (1) different load styles had remarkable impact on the gait recognition at three speeds under three load styles (p < 0.001); (2) the performance of gait recognition from the CNN was better than that from the SVM and BPNN at each speed (84.83%, 81.63%, and 83.76% at V3; 93.40%, 88.48%, and 92.36% at V5; and 90.1%, 86.32%, and 85.42% at V7, respectively); and (3) when all the data from three load styles were pooled as testing sets at each speed, more load styles were included in the training set, better performance was obtained, and the statistical analysis suggested that the kinds of load styles included in training set had a significant effect on gait recognition (p = 0.002), from which it can be concluded that the control system of a lower-limb exoskeleton trained by sEMG using only some load styles is not sufficient in a real-time environment.


Author(s):  
Ruxandra Calapod Ioana ◽  
Irina Bojoga ◽  
Duta Simona Gabriela ◽  
Ana-Maria Stancu ◽  
Amalia Arhire ◽  
...  

2019 ◽  
Vol 2019 ◽  
pp. 790-791
Author(s):  
Cunhyeong Ci ◽  
◽  
Hyo-Gyoo Kim ◽  
Seungbae Park ◽  
Heebok Lee
Keyword(s):  

Diabetes ◽  
2020 ◽  
Vol 69 (Supplement 1) ◽  
pp. 778-P
Author(s):  
ZIYU LIU ◽  
CHAOFAN WANG ◽  
XUEYING ZHENG ◽  
SIHUI LUO ◽  
DAIZHI YANG ◽  
...  

2007 ◽  
Vol 30 (4) ◽  
pp. 51 ◽  
Author(s):  
A. Baranchuk ◽  
G. Dagnone ◽  
P. Fowler ◽  
M. N. Harrison ◽  
L. Lisnevskaia ◽  
...  

Electrocardiography (ECG) interpretation is an essential skill for physicians as well as for many other health care professionals. Continuing education is necessary to maintain these skills. The process of teaching and learning ECG interpretation is complex and involves both deductive mechanisms and recognition of patterns for different clinical situations (“pattern recognition”). The successful methodologies of interactive sessions and real time problem based learning have never been evaluated with a long distance education model. To evaluate the efficacy of broadcasting ECG rounds to different hospitals in the Southeastern Ontario region; to perform qualitative research to determine the impact of this methodology in developing and maintaining skills in ECG interpretation. ECG rounds are held weekly at Kingston General Hospital and will be transmitted live to Napanee, Belleville, Oshawa, Peterborough and Brockville. The teaching methodology is based on real ECG cases. The audience is invited to analyze the ECG case and the coordinator will introduce comments to guide the case through the proper algorithm. Final interpretation will be achieved emphasizing the deductive process and the relevance of each case. An evaluation will be filled out by each participant at the end of each session. Videoconferencing works through a vast array of internet LANs, WANs, ISDN phone lines, routers, switches, firewalls and Codecs (Coder/Decoder) and bridges. A videoconference Codec takes the analog audio and video signal codes and compresses it into a digital signal and transmits that digital signal to another Codec where the signal is decompressed and retranslated back into analog video and audio. This compression and decompression allows large amounts of data to be transferred across a network at close to real time (384 kbps with 30 frames of video per second). Videoconferencing communication works on voice activation so whichever site is speaking has the floor and is seen by all the participating sites. A continuous presence mode allows each site to have the same visual and audio involvement as the host site. A bridged multipoint can connect between 8 and 12 sites simultaneously. This innovative methodology for teaching ECG will facilitate access to developing and maintaining skills in ECG interpretation for a large number of health care providers. Bertsch TF, Callas PW, Rubin A. Effectiveness of lectures attended via interactive video conferencing versus in-person in preparing third-year internal medicine clerkship students for clinical practice examinations. Teach Learn Med 2007; 19(1):4-8. Yellowlees PM, Hogarth M, Hilty DM. The importance of distributed broadband networks to academic biomedical research and education programs. Acad Psychaitry 2006;30:451-455


1992 ◽  
Author(s):  
PAUL BORCHERS ◽  
ERNESTO MORALEZ, III ◽  
VERNON MERRICK ◽  
MICHAEL STORTZ ◽  
DAVID EAMES

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