Error catch and analysis for semiconductor memories using March tests

With improved speech understanding technology, many successful working systems have been developed. However, the high degree of complexity and wide variety of design methodology make the performance evaluation and error analysis for such systems very difficult. The different metrics for individual modules such as the word accuracy, spotting rate, language model coverage and slot accuracy are very often helpful, but it is always difficult to select or tune each of the individual modules or determine which module contributed to how much percentage of understanding errors based on such metrics. A new framework for performance evaluation and error analysis for speech understanding systems is proposed based on the comparison with the 'best-matched' references obtained from the word graphs with the target words and tags given. In this framework, all test utterances can be classified based on the error types, and various understanding metrics can be obtained accordingly. Error analysis approaches based on an error plane are then proposed, with which the sources for understanding errors (e.g., poor acoustic recognition, language model, search error, etc.) can be identified for each utterance. Such a framework will be very helpful for design and analysis of speech understanding systems.

An orthogonal system of interferometry baselines aboard a geostationary satellite is considered primarily as a global positioning and navigation system. The mathematical model based on the relationship between the measured phase differences, the known transmitter positions, and other systematic error model parameters is derived. A generalized Least‐Squares estimation procedure is used for the solution of the unknown transmitter positions. Study of the effects of the various system and error model parameters on the position accuracy reveals that this accuracy is critically dependent on the baseline length and the magnitude of the random component of the measuring errors. With a 50‐m baseline, the obtainable accuracy at a frequency of 1.5 GHz is comparable to that of the NAVSTAR/ GPS system. Considering the interest and needs of the potential users for a multicapability system, this interferometry system is considered a major improvement over existing and planned navigation systems.

Efficient march test for 3-coupling faults in random access memories

The vast majority of the occurrences of condition numbers in the study of linear systems of equations involve the normwise condition number κ(A). Almost invariably, the use of κ(A) is enough to provide a satisfying explanation of the phenomena observed in practice.The case of triangular systems of linear equations provides, in contrast, an example in which κ(A) turns out to be inadequate. Practitioners long observed that triangular systems of equations are generally solved to high accuracy in spite of being, in general, ill-conditioned. Thus, for instance, J.H. Wilkinson wrote: “In practice one almost invariably finds that if L is ill-conditioned, so that ∥L∥∥L −1∥≫1, then the computed solution of Lx=b (or the computed inverse) is far more accurate than [what forward stability analysis] would suggest.”A first goal in this chapter is to give a precise meaning to the feeling that triangular matrices are, in general, ill-conditioned. We prove that if \(L\in \mathbb {R}^{n\times n}\) is a lower-triangular matrix whose entries are independent standard Gaussian random variables, then \(\mathbb {E}(\log \kappa(L))=\varOmega(n)\). This yields an expected loss of precision satisfying $$\mathbb {E}\bigl(\mathsf {LoP}\bigl(L^{-1}b\bigr)\bigr)= \mathcal {O}(n). $$ Were the loss of precision in the solution of triangular systems to conform to this bound, we would not be able to accurately find these solutions. The reason we actually do find them can be briefly stated. The error analysis of triangular systems reveals that we may use a componentwise condition number Cw(L,b) instead of the normwise condition number. The second goal of this chapter is to prove that when L and \(b\in \mathbb {R}^{n}\) are drawn from standard Gaussian distributions, then we have \(\mathbb {E}(\log \mathsf {Cw}(L,b))=\mathcal {O}(\log n)\). This bound, together with some backward error analysis, yields bounds for \(\mathbb {E}(\mathsf {LoP}(L^{-1}b))\) that are much smaller than the one above, as well as closer to the loss of precision observed in practice.KeywordsTriangular Linear SystemNormwise Condition NumberComponentwise ConditionIndependent Standard Gaussian Random VariablesBackward Error AnalysisThese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

"Zero waste" is the eternal pursuit of goals of global manufacturing. But the 2D error analysis has not yet comprehensive and accurate analysis and prediction of product quality information. Comprehensive 3D error analysis and judgments can be obtained through the high-precision 3D data acquisition on part and standard error of alignment for 3D data. According to the error information, the deformation of the part can be measured, traced and predicted, thus to reduce waste generation. 3D error analysis and deformation prediction system is proposed in this article, it has higher reliability and a certain role for the correct evaluation of processing conditions and comprehensive understanding of the process of evaluating the whole production process.

Corrective feedback and error correction are important tasks for ESL/EFL (English as a Second Language/English as a Foreign Language) writing instruction. Research findings showed that students' major difficulty in error correction lies in their failure to detect errors. Also, researchers proposed that error analysis can be reinvented in the form of computer-aided error analysis, a new type of computer corpus annotation. Annotations on digital documents can be easily shared among groups of people, making them valuable for a wide variety of tasks, including providing feedback. This study developed a web-based online corrective feedback and error analysis system called WRITE (Writing Revision Instrument for Teaching English). With this system, teachers can make error corrections on digitized documents, on the general web browser such as Microsoft Internet Explorer, with online annotations in the same way as the traditional paper-based correction approach. The WRITE system can feedback correct answers, teachers' comments, and the grammatical error type for each error to students. In addition, this system can provide users the annotation marks subject to different query conditions so that the problem of cognitive overload can be avoided. For error analysis purposes, this system can access the database and analyzes students' errors and displays the results as requested. Students use WRITE will be able to effectively identify more errors. Moreover, the ways that the corrective feedback delivered through the online annotation system can be used by students to develop his/her corrective strategies.

BackgroundCREs are feared pathogens with resistance occurring through the production of carbapenemases. Identification of carbapenemase-producing (CP) organisms assists with proper antimicrobial selection of commonly used agents, such as ceftazidime/avibactam (CA), meropenem/vaborbactam (MV), and tigecycline (TG). AdventHealth Orlando implemented a CRE screening method based on meropenem (MER) and a confirmatory CRE PCR testing in March 2018. Prior to implementing this test, patients were deemed to have CRE infections (CREI) if the organism demonstrated resistance to any carbapenem. The objective of this study was to evaluate the impact of this testing on the utilization of anti-CRE antibiotics.MethodsThis was a retrospective pre (March 2017–February 2018)- and post (March 2018–February 2019)-implementation study examining the impact of CRE PCR testing. Outcomes included the number of antibiotic days saved, average duration of therapy (DOT), median length of stay (LOS), and change in CP-CRE prevalence. The intervention consisted of the implementation of CRE PCR testing and included inpatients > 18 years old who received either CA, MV, or TG for the treatment of a CREI.ResultsPost-implementation, 30 unique patients were identified as having a positive K. pneumoniae carbapenemase gene by PCR, indicating a CP-CRE and received CA, MV, or TG; whereas, 42 patients in the pre-implementation group had a CREI and received CA, MV, or TG. Testing to identify CP-CREs led to a 50% reduction in the number of antibiotic days for CA, MV, and TG (575 vs. 287 days, P < 0.0001). Additionally, the average DOT decreased by 2.5 days in the post-implementation group (10.5 days vs. 8 days, P = 0.18) along with a 3.5-day shorter median LOS (15 days vs. 11.5 days, P = 0.48). The CRE prevalence based on resistance only to MER is 0.27%, compared with the previously reported rate of 2.5% that included resistance to ertapenem or MER.ConclusionImplementing CRE PCR testing to identify CP-CRE organisms resulted in a significant reduction in utilization of anti-CRE agents for CREIs. Additionally, the testing algorithm allowed for accurate reporting of our local CRE prevalence. By avoiding CA, MV, or TG in patients without CP-CREs, this has the potential to optimize therapy while reducing collateral damage associated with broad-spectrum agents.DisclosuresAll authors: No reported disclosures.

In the captive testing of conventional solid rocket motors, a large number of fundamental physical measurements are normally implemented. These include the determination of instantaneous motor force, pressure, temperature, deflection, acceleration and electrical power data associated with the particular motor configuration. In the majority of applications, however, the motor performance indicators of most general interest are not measured directly, but are calculated from these basic data. Thus, for example, motor specific impulse is computed from given instantaneous values of measured thrust, pressure and weight parameters. All physical measurements are subject to inaccuracies, i.e., even the most sophisticated data acquisition system will necessarily inject discrepancies into the measured data. Hence, the mechanisms through which errors inherent in the measured quantities affect the accuracy of the calculated ballistic parameters are of extreme practical importance and must be quantitatively defined. At the Aerojet-General Corporation, an intensive and continuing analysis of overall measurement system errors (through rigorous analytical and experimental techniques) has permitted the statistical characterization of the error parameters within the framewcrk of each current large scale motor development program. Based upon these data and for a specific ballistic parameter computational routine, an extensive error analysis is required to deduce the errors associated with the computed performance parameters. Because of the nonlinearities and interactions inherent within the ballistic computations, a Monte Carlo technique is invoked.

Cell Balancing (CB) is a crucial aspect of the Battery Management System (BMS), which is used to increase the batteries operate time as well as operational life. The most widely used method is Passive Cell Balancing (PCB) since it is inexpensive and simple to use. This work proposes an algorithm using Deep Learning (DL) that selects the balancing resistor effectively with respect to increasing temperature, C-rate, level of cell imbalance, and balancing duration. Convolution Neural Network (CNN), hybrid method of Convolution Neural Network (CNN)-Long short-term memory (LSTM) (CNN-LSTM) and Convolution Bidirectional LSTM (CNN-BiLSTM) are used to assess the performance of the suggested system. In order to optimize the balancing parameters, the balancing system's error analysis is carried out, and performance indices like Mean Square Error (MSE), Root Mean Square Error (RMSE), and Mean Absolute Error (MAE) are used to compare the suggested algorithms. The hybrid CNN-BiLSTM obtained MAE of 0.0453, MSE of 0.0062 and RMSE value of 0.0671 which is better than other models.

Appears in: EDULEARN19 Proceedings Publication year: 2019Pages: 1562-1568ISBN: 978-84-09-12031-4ISSN: 2340-1117doi: 10.21125/edulearn.2019.0463Conference name: 11th International Conference on Education and New Learning TechnologiesDates: 1-3 July, 2019Location: Palma, Spain

As the Internet refreshes every day, a large scale of images are generated online which present a challenge to image classification problems. Firstly, the classifier once trained by the old training set is not able to describe all the characteristics of a class when new samples appear. Secondly, to train a classifier using all the upcoming samples can take a long time so that the speed of updating the classifier is much slower than the speed of new data generation. Thirdly, the newly generated images may be duplicate or similar to current training samples with minor variance, hence training by these minor informative images will waste lots of time and resources, Samples being continuously misclassified by the updated classifiers should be laid with more weight in future update process than other easily classified samples. In this paper, we propose an Incremental learning method using Error and Sensitivity Analysis (IESA) of Multiple Classifier System (MCS) for upcoming images. Radial Basis Function Neural Network (RBFNN) is used to classify upcoming images firstly and misclassified images with large sensitivity are selected for the following updating process. Experimental results on a large scale image dataset convince the efficiency of the IESA strategy.

The additional deformation of the quartz crystal under the vibration stress disturbance greatly affects the measurement accuracy of the fiber optic voltage sensor. In this paper, the influence of different vibration directions on quartz crystal deformation is analyzed by the finite element method based on the analysis and derivation of the system error mathematical model of the quasi-reciprocal reflected fiber optic voltage sensor. Furthermore, the effect of additional quartz crystal deformation on the output precision of the system is calculated. The results show that the vibration stress along the axial direction mainly causes the quartz crystal to deform in height, and the vibration stress along the radial direction mainly causes the quartz crystal to deform the circumference. Among them, the deformation of the crystal radial circumference is the main reason to influence the system output accuracy. In addition, the size and deformation parameters of the quartz crystal are related to the output error of the sensor system. This paper provides the parameter optimization and design guidance for improving the anti-mechanical vibration performance of the sensor head of the fiber optic voltage sensor and provides a theoretical basis for the suppression method of the system error.

Battleground Zero: A Review of Best Practice Recommendations for Clostridioides (Clostridium) difficile Testing

Objective. To analyze adverse outcomes of surgical treatment of radicular compression syndrome and to present an algorithm for diagnosis and differential treatment of radicular and pseudoraducular brachialgias. Material and Methods. The catamneses of 60 patients hospitalized for adverse outcome of previous surgery for cervical radicular compression syndrome were studied. Analysis of errors and developed algorithm for diagnosis and differential treatment of upper limb pain syndromes facilitated the prospective study of 350 patients with pseudoradicular brachialgia caused by pathological impulses from the affected intervertebral discs and facet joints. Results. Stable regression of pseudoradicular arm pain was achieved in 94 % of patients. Disc puncture reproduction of patient’s specific arm pain and its elimination by means of chemical denervation confirmed the dependence of this pain mainly on degenerative disc disease in 33.8 % of cases, on spondylarthrosis in 6.7 %, and equally on degenerative disc disease and spondylarthrosis in 59.5 %. Conclusion. The developed algorithm for diagnosis and differentiated treatment of upper limb pain syndromes depending on the combination of different pathomorphological substrates and syndromes can improve the results of treatment in patients with brachialgia and achieve stable regression of pseudoradicular pain.

A calibration system was designed to evaluate the accuracy of linear optical encoders at the micron level in a fast and economical manner. The system uses a commercial interferometer and motor stage as the calibrator and moving platform. Error analysis is necessary to prove the effectiveness and identify areas for optimization. A fixture was designed for the scale and interferometer target to meet the Abbe principle. A five-degree-of-freedom manual stage was utilized to adjust the reading head in optimal or suboptimal working conditions, such as working distance, offset, and angular misalignment. The results indicate that the calibration system has an accuracy of ±2.2 μm. The geometric errors of the calibration system, including mounting errors and non-ideal motions, are analyzed in detail. The system could be an inexpensive solution for encoder manufacturers and customers to calibrate a linear optical encoder or test its performance.