Plastic Limit, Liquid Limit and Undrained Shear Strength of Soil—Reappraisal

The concept that plasticity index of soils can be defined as a range of water contents producing a 100-fold variation in undrained shear strength has been experimentally verified with the help of a large number of tests on soils of diverse nature. This has led to the redefinition of the plastic limit as the water content at which undrained shear strength is around 170 kN/m2. Undrained shear strength of a soil at the liquid limit can be considered to be around 1.7 kN/m2. Accordingly, both the liquid limit and the plastic limit have been determined in the present work by a single consistent method, i.e., the Swedish fall cone method. The undrained shear strength-water content relationship has been found to be log-linear for a wide range of water contents beginning from lower than the plastic limit to higher than the liquid limit. This resulted in the formulation of an expression for predicting undrained shear strength of a remolded soil at any water content based solely on its liquid limit and plastic limit.     

Approximate variational inference based on a finite sample of Gaussian latent variables

Variational methods are employed in situations where exact Bayesian inference becomes intractable due to the difficulty in performing certain integrals. Typically, variational methods postulate a tractable posterior and formulate a lower bound on the desired integral to be approximated, e.g. marginal likelihood. The lower bound is then optimised with respect to its free parameters, the so-called variational parameters. However, this is not always possible as for certain integrals it is very challenging (or tedious) to come up with a suitable lower bound. Here, we propose a simple scheme that overcomes some of the awkward cases where the usual variational treatment becomes difficult. The scheme relies on a rewriting of the lower bound on the model log-likelihood. We demonstrate the proposed scheme on a number of synthetic and real examples, as well as on a real geophysical model for which the standard variational approaches are inapplicable.     

SWGMM: a semi-wrapped Gaussian mixture model for clustering of circular–linear data

Finite mixture models are widely used to perform model-based clustering of multivariate data sets. Most of the existing mixture models work with linear data; whereas, real-life applications may involve multivariate data having both circular and linear characteristics. No existing mixture models can accommodate such correlated circular–linear data. In this paper, we consider designing a mixture model for multivariate data having one circular variable. In order to construct a circular–linear joint distribution with proper inclusion of correlation terms, we use the semi-wrapped Gaussian distribution. Further, we construct a mixture model (termed SWGMM) of such joint distributions. This mixture model is capable of approximating the distribution of multi-modal circular–linear data. An unsupervised learning of the mixture parameters is proposed based on expectation maximization method. Clustering is performed using maximum a posteriori criterion. To evaluate the performance of SWGMM, we choose the task of color image segmentation in LCH space. We present comprehensive results and compare SWGMM with existing methods. Our study reveals that the proposed mixture model outperforms the other methods in most cases.     

Design and Uncertainty Evaluation of a Strain Measurement System

Strain measurement is very important in various industrial applications as well as different disciplines of science and technology for direct and indirect observations of certain parameters. Designing signal conditioning circuit is always a challenging and important task for satisfactory and reliable performance of a sensor as well as the system. The design and implementation details of a signal conditioning circuit of resistive sensor (strain gauge) for strain measurement are presented in this paper. Also the important aspects in designing a signal conditioning circuit for resistive sensor are presented and a novel method for the measurement of strain is discussed. Quarter bridge configuration with AC voltage excitation is used for the measurement along with the necessary circuitry to get a suitable and measurable output DC voltage. The measurement system is calibrated using a cantilever of stainless steel and the details of calibration are presented in the paper. The uncertainty associated with the measurement system is evaluated.     

EMERS: a tree matching–based performance evaluation of mathematical expression recognition systems

Performance evaluation of mathematical expression recognition systems is attempted. The proposed method assumes expressions (input as well as recognition output) are coded following MathML or T_EX/LaT_EX (which also gets converted into MathML) format. Since any MathML representation follows a tree structure, evaluation of performance has been modeled as a tree-matching problem. The tree corresponding to the expression generated by the recognizer is compared with the groundtruthed one by comparing the corresponding Euler strings. The changes required to convert the tree corresponding to the expression generated by the recognizer into the groundtruthed one are noted. The number of changes required to make such a conversion is basically the distance between the trees. This distance gives the performance measure for the system under testing. The proposed algorithm also pinpoints the positions of the changes in the output MathML file. Testing of the proposed evaluation method considers a set of example groundtruthed expressions and their corresponding recognized results produced by an expression recognition system.     

Innovations in Individual Feature History Management—The Significance of Feature-based Temporal Model

A feature relies on three dimensions (space, theme, and time) for its representation. Even though spatiotemporal models have been proposed, they have principally focused on the spatial changes of a feature. In this paper, a feature-based temporal model is proposed to represent the changes of both space and theme independently. The proposed model modifies the ISO’s temporal schema and adds new explicit temporal relationship structure that stores temporal topological relationship with the ISO’s temporal primitives of a feature in order to keep track feature history. The explicit temporal relationship can enhance query performance on feature history by removing topological comparison during query process. Further, a prototype system has been developed to test a proposed feature-based temporal model by querying land parcel history in Athens, Georgia. The result of temporal query on individual feature history shows the efficiency of the explicit temporal relationship structure.

A tetrode based fast pulsed microwave source for electron cyclotron resonance breakdown experiments

To study electron cylotron resonance (ECR) breakdown and afterglow plasma in an experimental linear plasma system, a pulsed microwave source with rapid rise and fall of microwave power is desired. A pulsed microwave source with fast rise and fall capability for ECR breakdown experiments has been designed and tested for performance in the system. A tetrode, controlled by a modulator card, is used as a fast switch to initiate microwave power from a conventional magnetron operating at 2.45 GHz. The typical rise time of microwave power is approximately 3 micros and a fall time of approximately 10 micros. Using this scheme in a realistic pulsed microwave source at 800 W power, ECR breakdown of neutral gas is achieved and the plasma delay and fall time are observed from the plasma density measurements using a Langmuir probe. The design details of the fast rise pulsed microwave source are presented in this article with initial experimental results.