A field programmable gate array based modular motion control platform

The expectations from motion control systems have been rising day by day. As the systems become more complex, conventional motion control systems can not achieve to meet all the specifications with optimized results. This creates the necessity of fundamental changes in the infrastructure of the system. Field programmable gate array (FPGA) technology enables the reconfiguration of the digital hardware, thus dissolving the necessity of infrastructural changes for minor manipulations in the hardware even if the system is deployed. An FPGA based hardware system shrinks the size of the hardware hence the cost. FPGAs also provide better power ratings for the systems as well as a more reliable system with improved performance. As a trade off, the development is rather more difficult than software based systems, which also affects the research and development time of the overall system. In this paper a level of abstraction is introduced in order to diminish the requirement of advanced hardware description language (HDL) knowledge for implementing motion control systems thoroughly on an FPGA. The intellectual property library consists of synthesizable hardware modules specifically implemented for motion control purposes. Other parts of a motion control system, like user interface and trajectory generation, are implemented as software functions in order to protect the modularity of the system. There are also several external hardware designs for interfacing and driving various types of actuators

A field programmable gate array based motion control platform

The expectations from motion control systems have been rising day by day. As the system becomes more complex, conventional motion control systems can not achieve to meet all the specifications with optimized results. This creates the need of re-designing the control platform in order to meet the new specifications. Field programmable gate arrays (FPGA) offer reconfigurable hardware, which would result in overcoming this re-designing issue. The hardware structure of the system can be reconfigured, even though the hardware is deployed. As the functionality is provided by the hardware, the performance is enhanced. The dedicated hardware also improves the power consumption. The board size also shrinks, as the discrete components can be implemented in FPGA. The shrinkage of the board size also lowers the cost. As a trade-off, FPGA programming is more complicated than software programming. The aim of this thesis is to create a level of abstraction in order to diminish the requirement of advanced hardware description language knowledge for implementing motion control algorithms on FPGA's. The hardware library is introduced which is specifically implemented for motion control purposes. In order to have a thorough motion control platform, other parts of the system like, user interface, kinematics calculations and trajectory generation, have been implemented as a software library. The control algorithms are tested, and the system is verified by experimenting on a parallel mechanism

Clinical utility of serum cystatin C in predicting coronary artery disease

Background: There is limited data regarding the clinical utility of cystatin C in patients with stable coronary artery disease (CAD). The aim of this study was to determine the predictive value of cystatin C for the presence and severity of CAD and the association between this protein and other biochemical risk factors for atherosclerosis in patients with suspected CAD. Methods: Ninety-four patients with CAD, and 92 patients without CAD but with cardiovascular risk factors, were included in this study. Echocardiography and other pertinent laboratory examinations were performed. Subjects were divided into four groups according to their cystatin C quartile. Cystatin C groups were analyzed for the association with CAD characteristics. Results: The number of patients with CAD increased as the quartile of cystatin C increased, and there was a remarkable difference between quartiles (p < 0.001). Logistic regression analysis revealed independent predictors of incident CAD as cystatin C, hs-CRP, eGFR, HDL cholesterol and SBP (p = 0.005, p = 0.027, p = 0.017, p = 0.014 and p = 0.001, respectively). Moreover, cystatin C concentration was significantly correlated with CAD severity score (b = 0.258, p < 0.01). A cut-off value of 0.82 mg/L for cystatin C predicted incident CAD with a sensitivity and specificity of 75.5% and 75.0% respectively. Cystatin C concentration also correlated well with the atherosclerotic biochemical risk factors like homocysteine, creatinine and hs-CRP. Conclusions: Cystatin C could be a useful laboratory tool in predicting the presence and severity of CAD in daily practice. It also correlates significantly with biochemical risk factors for CAD, namely homocysteine, low HDL and CRP. (Cardiol J 2010; 17, 4: 374-380

Can we trust undervolting in FPGA-based deep learning designs at harsh conditions?

As more Neural Networks on Field Programmable Gate Arrays (FPGAs) are used in a wider context, the importance of power efficiency increases. However, the focus on power should never compromise application accuracy. One technique to increase power efficiency is reducing the FPGAs' supply voltage ("undervolting"), which can cause accuracy problems. Therefore, careful design-time considerations are required for correct configuration without hindering the target accuracy. This fact becomes especially important for autonomous systems, edge-computing, or data-centers. This study reveals the impact of undervolting in harsh environmental conditions on the accuracy and power efficiency of the convolutional neural network benchmarks. We perform the comprehensive testing in a calibrated infrastructure at controlled temperatures (between -40C and 50C) and four distinct humidity levels (40%, 50%, 70%, 80%) for off-the-shelf FPGAs. We show the voltage guard-band shift with temperature is linear and propose new reliable undervolting designs providing a 65% increase in power efficiency (GOPS/W).Peer ReviewedPostprint (author's final draft

An Experimental Study of Reduced-Voltage Operation in Modern FPGAs for Neural Network Acceleration

We empirically evaluate an undervolting technique, i.e., underscaling the circuit supply voltage below the nominal level, to improve the power-efficiency of Convolutional Neural Network (CNN) accelerators mapped to Field Programmable Gate Arrays (FPGAs). Undervolting below a safe voltage level can lead to timing faults due to excessive circuit latency increase. We evaluate the reliability-power trade-off for such accelerators. Specifically, we experimentally study the reduced-voltage operation of multiple components of real FPGAs, characterize the corresponding reliability behavior of CNN accelerators, propose techniques to minimize the drawbacks of reduced-voltage operation, and combine undervolting with architectural CNN optimization techniques, i.e., quantization and pruning. We investigate the effect of environmental temperature on the reliability-power trade-off of such accelerators. We perform experiments on three identical samples of modern Xilinx ZCU102 FPGA platforms with five state-of-the-art image classification CNN benchmarks. This approach allows us to study the effects of our undervolting technique for both software and hardware variability. We achieve more than 3X power-efficiency (GOPs/W) gain via undervolting. 2.6X of this gain is the result of eliminating the voltage guardband region, i.e., the safe voltage region below the nominal level that is set by FPGA vendor to ensure correct functionality in worst-case environmental and circuit conditions. 43% of the power-efficiency gain is due to further undervolting below the guardband, which comes at the cost of accuracy loss in the CNN accelerator. We evaluate an effective frequency underscaling technique that prevents this accuracy loss, and find that it reduces the power-efficiency gain from 43% to 25%.Comment: To appear at the DSN 2020 conferenc

Antifungalna aktivnost propolisa u četiri vrste voćnih sokova

Fruit juices and soft drinks are targets for spoilage yeasts, moulds and bacteria. The aim of this study is to examine the antifungal effect of ethanolic extract of Turkish propolis (EETP) treatments in four nonpasteurized fruit juices including apple, orange, white grape and mandarin against 6 different yeasts isolated from the corresponding spoiled juices. These isolated yeasts include: Candida famata, C. glabrata, C. kefyr, C. pelliculosa, C. parapsilosis and Pichia ohmeri. Minimum Inhibitory Concentration (MIC) ranges were determined responding to the National Committee for Clinical Laboratory Standards (NCCLS) M27-A that were slightly modified with broth microdilution method. In this study, the presence of propolis in apple (pH=3.9), orange (pH=3.7), white grape (pH=3.8) and mandarin (pH=3.4) juices ranging from 0.01 to 0.375 mg/mL inhibited the growth of all spoilage yeasts at 25 °C. MIC ranges of propolis were 0.02–0.375, 0.04–0.375, 0.01–0.185, 0.02–0.185 and 0.04–0.375 mg/mL in mandarin, apple, orange, white grape juices and RPMI medium, respectively. MIC ranges of Na benzoate, which was used as positive control, were 80–320, 80–320, 40–640, 40–80 and 320–1280 μg/mL in mandarin, apple, orange, white grape and RPMI medium as blank control, respectively. In terms of MIC ranges, propolis showed greater antifungal activity than Na benzoate. As a result, propolis had significant antimicrobial activity against the yeast isolates from spoiled fruit juices. It was concluded that propolis is worthy to study further as a natural preservative for foods prone to fungal spoilage.Voćni sokovi i negazirana pića podložni su kvarenju u prisutnosti kvasaca, plijesni i bakterija. Svrha je ovog istraživanja ispitati antifungalni učinak etanolnog ekstrakta turskog propolisa (ETTP) u nepasteriziranom soku jabuke, naranče, bijeloga grožđa i mandarine na 6 različitih sojeva kvasca izoliranih iz pokvarenih sokova. Izolirani su sojevi kvasca Candida famata, C. glabrata, C. kefyr, C. pelliculosa, C. parapsilosis i Pichia omeri. Minimalna inhibicijska koncentracija (MIC) određena je prema standardima nacionalnog odbora za kliničke laboratorije (NCCLS) M27-A, neznatno modificiranih metodom mikrodilucije bujona. Prisutnost propolisa u soku jabuke (pH=3,9), naranče (pH=3,7), bijeloga grožđa (pH=3,8) i mandarine (pH=3,4) u rasponu od 0,01 do 0,375 mg/mL inhibirala je rast svih sojeva kvasca na temperaturi od 25 °C. MIC propolisa u soku mandarine iznosila je 0,02-0,375, u soku jabuke 0,04-0,375, u soku naranče 0,01-0,185, u soku bijeloga grožđa 0,02-0,185 te u RPMI mediju 0,04-0,375 mg/mL. MIC natrijeva benzoata, primijenjenog kao pozitivna kontrola, iznosila je 80-320 u soku mandarine, 80-320 u soku jabuke, 40-640 u soku naranče, 40-80 u soku bijeloga grožđa i 320-1280 μg/mL u RPMI mediju korištenom za slijepu probu. Propolis je imao značajnu antimikrobnu aktivnost na sojeve kvasca izoliranih iz pokvarenih voćnih sokova. Predloženo je daljnje istraživanje propolisa kao prirodnog konzervansa hrane podložne kvarenju u prisutnosti kvasaca

An experimental study of reduced-voltage operation in modern FPGAs for neural network acceleration

We empirically evaluate an undervolting technique, i.e., underscaling the circuit supply voltage below the nominal level, to improve the power-efficiency of Convolutional Neural Network (CNN) accelerators mapped to Field Programmable Gate Arrays (FPGAs). Undervolting below a safe voltage level can lead to timing faults due to excessive circuit latency increase. We evaluate the reliability-power trade-off for such accelerators. Specifically, we experimentally study the reduced-voltage operation of multiple components of real FPGAs, characterize the corresponding reliability behavior of CNN accelerators, propose techniques to minimize the drawbacks of reduced-voltage operation, and combine undervolting with architectural CNN optimization techniques, i.e., quantization and pruning. We investigate the effect ofenvironmental temperature on the reliability-power trade-off of such accelerators. We perform experiments on three identical samples of modern Xilinx ZCU102 FPGA platforms with five state-of-the-art image classification CNN benchmarks. This approach allows us to study the effects of our undervolting technique for both software and hardware variability. We achieve more than 3X power-efficiency (GOPs/W ) gain via undervolting. 2.6X of this gain is the result of eliminating the voltage guardband region, i.e., the safe voltage region below the nominal level that is set by FPGA vendor to ensure correct functionality in worst-case environmental and circuit conditions. 43% of the power-efficiency gain is due to further undervolting below the guardband, which comes at the cost of accuracy loss in the CNN accelerator. We evaluate an effective frequency underscaling technique that prevents this accuracy loss, and find that it reduces the power-efficiency gain from 43% to 25%.The work done for this paper was partially supported by a HiPEAC Collaboration Grant funded by the H2020 HiPEAC Project under grant agreement No. 779656. The research leading to these results has received funding from the European Union’s Horizon 2020 Programme under the LEGaTO Project (www.legato-project.eu), grant agreement No. 780681.Peer ReviewedPostprint (author's final draft

The preoperative serum CA125 can predict the lymph node metastasis in endometrioid-type endometrial cancer

Objectives: To evaluate the predictive value of preoperative CA125 in extra-uterine disease and its association with poorprognostic factors in endometrioid-type endometrial cancer (EC).Material and methods: A total of 423 patients with pathologically proven endometrioid-type EC were included in thestudy. The association between preoperative CA125 level and surgical–pathological factors was evaluated. The conventional cut-off value was defined as 35 IU/mL.Results: A high CA125 level ( &gt; 35 IU/mL) was significantly associated with all of the studied poor prognostic factors,except grade. The risk of lymph node metastasis (LNM) increased from 15.9% to 45.7% when CA125 level was &gt; 35 IU/mL (p &lt; 0.05). The optimal cut-off value for the prediction of LNM in patients aged &gt; 50 years was determined to be 16 IU/mL (sensitivity, specificity, positive predictive value, and negative predictive value were 71%, 60%, 35%, and 87%, respectively.)Conclusions: Preoperative CA125 level was significantly related with the extent of the disease and LNM. The age-dependent cut-off level of CA125 can improve the prediction of LNM in endometrioid-type EC. For older patients, CA125 level of &gt; 16 IU/ml could be used to predict LNM. However, further studies are needed to evaluate the appropriate cut-off level of CA125 for younger patients

The evaluation of doxorubicin-induced cardiotoxicity: Comparison of Doppler and tissue Doppler-derived myocardial performance index

Background: Doxorubicin is a chemotherapeutic agent used in a wide spectrum of cancers. However, cardiotoxic effects have limited its clinical use. The early detection of doxorubicin-induced cardiotoxicity is crucial. The purpose of our study was to assess values of Doppler and tissue Doppler imaging (TDI)-derived myocardial performance index (MPI) in adult cancer patients receiving doxorubicin treatment. Methods: A total of 45 patients underwent echocardiographic examinations before any doxorubicin had been administered and then after doxorubicin. Doppler and TDI-derived MPI of left ventricular (LV) were determined in the evaluation of cardiotoxicity. Additionally, TDI-derived MPI of right ventricular (RV) was determined. Results: All patients underwent control echocardiographic examination after mean 5 &#177; 1.7 months. The LV MPI obtained by both Doppler and TDI were increased after doxorubicin treatment (0.56 &#177; 0.11, 0.61 &#177; 0.10, p = 0,005 vs 0.51 &#177; 0.09, 0.59 &#177; 0.09, p = 0.001, respectively). There was no correlation between Doppler-derived MPI and cumulative doxorubicin dose (coefficient of correlation 0.11, p = 0.6). TDI-derived MPI was correlated with cumulative doxorubicin dose (coefficient of correlation 0.35, p = 0.015), but this correlation is weak (r = 0.38). The study population was divided into two groups according to doxorubicin dose (below and above 300 mg level). There was a moderate correlation between TDI-derived MPI and less than 300 mg of doxorubicin dose (coefficient of correlation 0.51, p = 0.028). However, Doppler-derived MPI was not correlated with less than 300 mg of doxorubicin dose (coefficient of correlation 0.38, p = 0.123). Also, there was no significant change in the TDI-derived RV-MPI (0.49 &#177; 0.14, 0.50 &#177; 0.12, p = 0.56). Conclusions: TDI-derived MPI is a useful parameter and an early indicator compared with Doppler-derived MPI in the detection of cardiotoxicity during the early stages. Also, doxorubicin administration does not affect RV function