Analytic expressions for the sizes of logically minimized truth tables for binary addition and subtraction

1990 ◽  
Vol 29 (23) ◽  
pp. 3339 ◽  
Author(s):  
Mir Mirsalehi ◽  
Thomas K. Gaylord
Keyword(s):  
Analytic Expressions ◽  
Addition And Subtraction ◽  
Binary Addition ◽  
Truth Tables

A new approach of binary addition and subtraction by non-linear material based switching technique

Pramana ◽  
2005 ◽  
Vol 64 (2) ◽  
pp. 239-247 ◽  
Author(s):  
Archan Kumar Das ◽  
Partha Pratima Das ◽  
Sourangshu Mukhopadhyay
Keyword(s):  
New Approach ◽  
Non Linear ◽  
Linear Material ◽  
Addition And Subtraction ◽  
Binary Addition

Binary Addition and Subtraction

2020 ◽  
pp. 153-184
Author(s):  
Dale Patrick ◽  
Stephen Fardo ◽  
Vigyan ‘Vigs’ Chandra
Keyword(s):  
Addition And Subtraction ◽  
Binary Addition

Security of Cyber-Physical Systems: A Generalized Algorithm for Intrusion Detection and Determining Security Robustness of Cyber Physical Systems using Logical Truth Tables

2013 ◽  
Vol 9 ◽  
Author(s):  
Curtis G. Northcutt
Keyword(s):  
Intrusion Detection ◽  
Cyber Security ◽  
Logical Truth ◽  
Cyber Physical Systems ◽  
Security Model ◽  
Security Measures ◽  
Physical Systems ◽  
Multiple Signal ◽  
Security Attack ◽  
Truth Tables

The recent proliferation of embedded cyber components in modern physical systems [1] has generated a variety of new security risks which threaten not only cyberspace, but our physical environment as well. Whereas earlier security threats resided primarily in cyberspace, the increasing marriage of digital technology with mechanical systems in cyber-physical systems (CPS), suggests the need for more advanced generalized CPS security measures. To address this problem, in this paper we consider the first step toward an improved security model: detecting the security attack. Using logical truth tables, we have developed a generalized algorithm for intrusion detection in CPS for systems which can be defined over discrete set of valued states. Additionally, a robustness algorithm is given which determines the level of security of a discrete-valued CPS against varying combinations of multiple signal alterations. These algorithms, when coupled with encryption keys which disallow multiple signal alteration, provide for a generalized security methodology for both cyber-security and cyber-physical systems.

CNN performance dependence on linear image processing

2020 ◽  
Vol 2020 (10) ◽  
pp. 310-1-310-7
Author(s):  
Khalid Omer ◽  
Luca Caucci ◽  
Meredith Kupinski
Keyword(s):  
Image Processing ◽  
Texture Classification ◽  
Full Rank ◽  
Detection Performance ◽  
Ideal Observer ◽  
Training Data ◽  
Image Texture ◽  
Training Images ◽  
Analytic Expressions ◽  
Linear Compression

This work reports on convolutional neural network (CNN) performance on an image texture classification task as a function of linear image processing and number of training images. Detection performance of single and multi-layer CNNs (sCNN/mCNN) are compared to optimal observers. Performance is quantified by the area under the receiver operating characteristic (ROC) curve, also known as the AUC. For perfect detection AUC = 1.0 and AUC = 0.5 for guessing. The Ideal Observer (IO) maximizes AUC but is prohibitive in practice because it depends on high-dimensional image likelihoods. The IO performance is invariant to any fullrank, invertible linear image processing. This work demonstrates the existence of full-rank, invertible linear transforms that can degrade both sCNN and mCNN even in the limit of large quantities of training data. A subsequent invertible linear transform changes the images’ correlation structure again and can improve this AUC. Stationary textures sampled from zero mean and unequal covariance Gaussian distributions allow closed-form analytic expressions for the IO and optimal linear compression. Linear compression is a mitigation technique for high-dimension low sample size (HDLSS) applications. By definition, compression strictly decreases or maintains IO detection performance. For small quantities of training data, linear image compression prior to the sCNN architecture can increase AUC from 0.56 to 0.93. Results indicate an optimal compression ratio for CNN based on task difficulty, compression method, and number of training images.

Thinking in Action and Beyond

2018 ◽  
Author(s):  
Terezinha Nunes
Keyword(s):  
Hard Of Hearing ◽  
Inverse Relation ◽  
Teaching Approaches ◽  
Multiplicative Reasoning ◽  
Mathematical Concepts ◽  
Logical Organization ◽  
The World ◽  
Mathematical Problems ◽  
Addition And Subtraction ◽  
Learning By Imitation

Before children learn to use language, they learn about the world in action and by imitation. This learning provides the basis for language acquisition. Learning by imitation and thinking in action continue to be significant throughout life. Mathematical concepts are grounded in children’s schemas of action, which are action patterns that represent a logical organization that can be applied to different objects. This chapter describes some of the conditions that allow deaf or hard-of-hearing (DHH) children to learn by imitation and use schemas of action successfully to solve mathematical problems. Three examples of concepts that can be taught by observation and thinking in action are presented: the inverse relation between addition and subtraction, the concepts necessary for learning to write numbers, and multiplicative reasoning. There is sufficient knowledge for the use of teaching approaches that can prevent DHH children from falling behind before they start school.

scholarly journals Phase Stability under Thermal Drifts in Photodiode-Conditioning Transimpedance Amplifiers for Distance Metrology

Sensors ◽  
2021 ◽  
Vol 21 (10) ◽  
pp. 3455
Author(s):  
Francisco Javier Meca Meca ◽  
Ernesto Martín-Gorostiza ◽  
Miguel Ángel García-Garrido ◽  
David Salido-Monzú
Keyword(s):  
Delay Time ◽  
Measurement Errors ◽  
Continuous Wave ◽  
Signal To Noise Ratio ◽  
Circuit Board ◽  
Transimpedance Amplifiers ◽  
Optical Distance ◽  
High Measurement ◽  
Analytic Expressions ◽  
Measured Distance

Transimpedance amplifiers (TIA) are widely used for front-end signal conditioning in many optical distance measuring applications in which high accuracy is often required. Small effects due to the real characteristics of the components and the parasitic elements in the circuit board may cause the error to rise to unacceptable levels. In this work we study these effects on the TIA delay time error and deduce analytic expressions, taking into account the trade-off between the uncertainties caused by the delay time instability and by the signal-to-noise ratio. A specific continuous-wave phase-shift case study is shown to illustrate the analysis, and further compared with real measurements. General strategies and conclusions, useful for designers of this kind of system, are extracted too. The study and results show that the delay time thermal stability is a key determinant factor in the measured distance accuracy and, without an adequate design, moderate temperature variations of the TIA can cause extremely high measurement errors.

scholarly journals Elasticity of connected semiflexible quadrilaterals

Soft Matter ◽  
2021 ◽  
Vol 17 (1) ◽  
pp. 102-112
Author(s):  
Mohammadhosein Razbin ◽  
Alireza Mashaghi
Keyword(s):  
Thermal Fluctuations ◽  
Analytic Expressions ◽  
Probability Densities

The analytic expressions for the probability densities associated with the thermal fluctuations and the elasticity of the structure are obtained.

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