scholarly journals Statistical Prediction of Circuit Aging under Process Variations

10.5772/6875 ◽  
2010 ◽  
Author(s):  
Wenping Wang ◽  
Vijay Reddy ◽  
Varsha Balakrishnan ◽  
Srikanth Krishnan ◽  
Yu Cao
Keyword(s):  
Process Variations ◽  
Statistical Prediction ◽  
Circuit Aging

scholarly journals Statistical prediction of circuit aging under process variations

2008 ◽  
Author(s):  
Wenping Wang ◽  
Vijay Reddy ◽  
Bo Yang ◽  
Varsha Balakrishnan ◽  
Srikanth Krishnan ◽  
...  
Keyword(s):  
Process Variations ◽  
Statistical Prediction ◽  
Circuit Aging

An evaluation of DSM-5 Section III Personality Disorder Criterion A (Impairment) in accounting for psychopathology

2018 ◽  
Author(s):  
Chelsea Sleep ◽  
Donald Lynam ◽  
Thomas A. Widiger ◽  
Michael L Crowe ◽  
Josh Miller
Keyword(s):  
Personality Disorders ◽  
Discriminant Validity ◽  
Factor Model ◽  
Incremental Validity ◽  
Self Report ◽  
Statistical Prediction ◽  
Dsm 5 ◽  
Criterion A ◽  
Personality Dysfunction ◽  
Axis I

An alternative diagnostic model of personality disorders (AMPD) was introduced in DSM-5 that diagnoses PDs based on the presence of personality impairment (Criterion A) and pathological personality traits (Criterion B). Research examining Criterion A has been limited to date, due to the lack of a specific measure to assess it; this changed, however, with the recent publication of a self-report assessment of personality dysfunction as defined by Criterion A (Levels of Personality Functioning Scale – Self-report; LPFS-SR; Morey, 2017). The aim of the current study was to test several key propositions regarding the role of Criterion A in the AMPD including the underlying factor structure of the LPFS-SR, the discriminant validity of the hypothesized factors, whether Criterion A distinguishes personality psychopathology from Axis I symptoms, the overlap between Criterion A and B, and the incremental predictive utility of Criterion A and B in the statistical prediction of traditional PD symptom counts. Neither a single factor model nor an a priori four-factor model of dysfunction fit the data well. The LPFS-SR dimensions were highly interrelated and manifested little evidence of discriminant validity. In addition, the impairment dimensions manifested robust correlations with measures of both Axis I and II constructs, challenging the notion that personality dysfunction is unique to PDs. Finally, multivariate regression analyses suggested that the traits account for substantially more unique variance in DSM-5 Section II PDs than does personality impairment. These results provide important information as to the functioning of the two main components of the DSM-5 AMPD and raise questions about whether the model may need revision moving forward.Keywords: dysfunction, impairment, personality disorders, Section III, incremental validity Public Significance: The alternative model of personality disorders included in Section III of the 5th addition of the Diagnostic and Statistical Manual of Mental Disorders (DSM-5) includes two primary components: personality dysfunction and maladaptive traits. The current results raise questions about how a new, DSM-5 aligned measure of personality dysfunction operates with regard its factor structure, discriminant validity, ability to differentiate between personality and non-personality based forms of psychopathology, and incremental validity in the statistical prediction of traditional DSM personality disorders.

Pseudo-Dynamic Fault Isolation Technique Using Backside Emission Microscopy – Case Study, Where All Other Methods Fail

2002 ◽  
Author(s):  
Yoav Weizman ◽  
Ezra Baruch ◽  
Michael Zimin
Keyword(s):  
Failure Analysis ◽  
Process Variations ◽  
Fault Isolation ◽  
Operating Conditions ◽  
Detection Sensitivity ◽  
Isolation Technique ◽  
Root Cause ◽  
Emission Microscopy ◽  
Failure Location ◽  
Noisy Background

Abstract Emission microscopy is usually implemented for static operating conditions of the DUT. Under dynamic operation it is nearly impossible to identify a failure out of the noisy background. In this paper we describe a simple technique that could be used in cases where the temporal location of the failure was identified however the physical location is not known or partially known. The technique was originally introduced to investigate IDDq failures (1) in order to investigate timing related issues with automated tester equipment. Ishii et al (2) improved the technique and coupled an emission microscope to the tester for functional failure analysis of DRAMs and logic LSIs. Using consecutive step-by-step tester halting coupled to a sensitive emission microscope, one is able detect the failure while it occurs. We will describe a failure analysis case in which marginal design and process variations combined to create contention at certain logic states. Since the failure occurred arbitrarily, the use of the traditional LVP, that requires a stable failure, misled the analysts. Furthermore, even if we used advanced tools as PICA, which was actually designed to locate such failures, we believe that there would have been little chance of observing the failure since the failure appeared only below 1.3V where the PICA tool has diminished photon detection sensitivity. For this case the step-by-step halting technique helped to isolate the failure location after a short round of measurements. With the use of logic simulations, the root cause of the failure was clear once the failing gate was known.

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