Sensitivity Analysis of Calibration Methods and Factors Effecting the Statistical Nature of Radiation Measurement

The scintillator detectors are recalibrated against the datasheet given by the manufacturer. Optimal and mutual dependent values of (a) high voltage at PMT (Photomultiplier Tube), (b) amplifier gain, (c) average time to count the radiation particles (set by operator), and (d) number of instances/sample number are estimated. Total 5: two versions of Central Limit Theorem (CLT), (3) industry preferred Pulse Width Saturation, (4) calibration based on MPPC coupled Gamma-ray detector, and (5) gross method are used. It is shown that the CLT method is the most optimal method to calibrate the detector and its respective electronics couple. An inverse modeling-based Computerized Tomography method is used for verification. It is shown that statistically averaging results are more accurate and precise data than mode and median if the data is not skewed and a random number of samples are used during the calibration process. It is also shown that the average time to count the radiation particle is the most important parameter affecting the optimal calibration setting for precision and accurate measurements of gamma radiation.

     

Effect of electric field on the hydrodynamics of fluidized nanoparticles

The effect of electric field on the hydrodynamics of nanoparticles was studied in a fluidized rectangular bed, with electrodes attached to two parallel walls. It was shown that the electric field of the order of 3 times the gravity markedly decreased the bed expansion and increased the solids volume fraction of nanoparticles fluidized by air. In these experiments, a light diode assembly was utilized to infer the local solids volume fractions within a rectangular bed of 10 nm silica particles. These experimental measurements yielded a two dimensional solids volume fraction distribution within the rectangular bed. The experimental results provided some new insights into the distribution of solids within the bed. The agglomerate diameters were computed using a momentum balance with the drag given by the Ergun equation and the empirical Richardson-Zaki method. Both methods yielded agglomerate diameters of the order of 100 μm and showed dependence on the strength of the electric field. The electric field decreased the granular temperature of the nanoparticles.     

Acoustic modeling problem for automatic speech recognition system: conventional methods (Part I)

In automatic speech recognition (ASR) systems, the speech signal is captured and parameterized at front end and evaluated at back end using the statistical framework of hidden Markov model (HMM). The performance of these systems depend critically on both the type of models used and the methods adopted for signal analysis. Researchers have proposed a variety of modifications and extensions for HMM based acoustic models to overcome their limitations. In this review, we summarize most of the research work related to HMM-ASR which has been carried out during the last three decades. We present all these approaches under three categories, namely conventional methods, refinements and advancements of HMM. The review is presented in two parts (papers): (i) An overview of conventional methods for acoustic phonetic modeling, (ii) Refinements and advancements of acoustic models. Part I explores the architecture and working of the standard HMM with its limitations. It also covers different modeling units, language models and decoders. Part II presents a review on the advances and refinements of the conventional HMM techniques along with the current challenges and performance issues related to ASR.     

Periodic subgraph mining in dynamic networks

In systems of interacting entities such as social networks, interactions that occur regularly typically correspond to significant, yet often infrequent and hard to detect, interaction patterns. To identify such regular behavior in streams of dynamic interaction data, we propose a new mining problem of finding a minimal set of periodically recurring subgraphs to capture all periodic behavior in a dynamic network. We analyze the computational complexity of the problem and show that it is polynomial, unlike many related subgraph or itemset mining problems. We propose an efficient and scalable algorithm to mine all periodic subgraphs in a dynamic network. The algorithm makes a single pass over the data and is also capable of accommodating imperfect periodicity. We demonstrate the applicability of our approach on several real-world networks and extract interesting and insightful periodic interaction patterns. We also show that periodic subgraphs can be an effective way to uncover and characterize the natural periodicities in a system.     

An opinion on imaging challenges in phenotyping field crops

Almost all the world’s food is grown in open fields, where plant phenotypes can be very different from those observed in greenhouses. Geneticists and agronomists studying food crops routinely detect, measure, and classify a wide variety of phenotypes in fields that contain many visually distinct types of a single crop. Augmenting humans in these tasks by automatically interpreting images raises some important and nontrivial challenges for research in computer vision. Nonetheless, the rewards for overcoming these obstacles could be exceptionally high for today’s 7 billion people, let alone the 9.6 billion projected by 2050 (United Nations Department of Economic and Social Affairs, Population Division, World Population Prospects: The 2012 Revision). To stimulate dialog between researchers in computer vision and those in genetics and agronomy, we offer our views on three computational challenges that are central to many phenotyping tasks. These are disambiguating one plant from another; assigning an individual plant’s organs to it; and identifying field phenotypes from those shown in archival images. We illustrate these challenges with annotated photographs of maize highlighting the regions of interest. We also describe some of the experimental, logistical, and photographic constraints on image collection and processing. While collecting the data sets needed for algorithmic experiments requires sustained collaboration and funding, the images we show and have posted should allow one to consider the problems, think of possible approaches, and decide on the next steps.     

Structural and Luminescence Studies on Barium Sodium Borosilicate Glasses Containing Uranium Oxides

Barium sodium borosilicate glasses containing different amounts of uranium oxides were prepared by conventional melt quench method and investigated for their structural aspects by ²⁹Si and ¹¹B MAS NMR technique combined with steady‐state luminescence and lifetime measurements. Based on MAS NMR studies, it is confirmed that uranium ions act as network modifier up to 15 wt% and beyond which a separate uranium containing phase is formed. From the luminescence studies, it is inferred that uranyl species is in a highly distorted environment. For more than 15 wt% uranium oxide incorporation, weaker U–O–U linkages are formed at the expense stronger U–O–Si/B linkages, as suggested by the excited state lifetime value of the uranyl species as well as red shift in emission peak maximum. For glass samples containing more than 25 wt% uranium oxides, crystalline barium uranium silicate gets phase separated from glass matrix as confirmed by XRD studies.     

A unified graphical formulation for synthesis of basic and subcolumn distillation sequences

In contrast to the different approaches currently adopted for generating basic and side-split subcolumn distillation sequence for separating zeotropic multicomponent feed mixture, we present a unified graphical method applicable towards both basic and side-split subcolumn distillation sequence. For a given number of components in the feed mixture, we enforce constraints on a base graph to eliminate violations of conservation principles and to preclude distillation sequences that demand higher heat duty in all appraised practical scenarios. A compact set of algebraic constraints is transfixed using the graph counterpart for generating basic-only distillation configurations. These algebraic constraints utilize binary variables to quantify existence of submixture streams and this considerably reduces the number of variables in generating distillation sequences. We also suggest extension of the formulation to enable the exploration of thermally coupled configurations.     

Quantification of carbon nanotube dispersion and its correlation with mechanical and thermal properties of epoxy nanocomposites

An experimental study is carried out to quantitatively assess the dispersion quality of carbon nanotubes (CNTs) in epoxy matrix as a function of CNT variant and weight fraction. To this end, two weight fractions (0.05% and 0.25%) of as-grown, oxidized, and functionalized CNTs are used to process CNT/epoxy nanocomposites. Scanning electron microscopy, X-ray diffraction, and Fourier transform infrared analysis of different variants of CNTs are used to establish the efficiency of purification route. While the relative change in mechanical properties is investigated through tensile and micro-hardness testing, thermal conductivity of different nanocomposites is measured to characterize the effect of CNT addition on the average thermal properties of epoxy. Later on, a quantitative analysis is carried out to establish the relationship between the observed improvements in average composite properties with the dispersion quality of CNTs in epoxy. It is shown that carboxylic (-COOH) functionalization reduces the average CNT agglomerate size and thus ensures better dispersion of CNTs in epoxy even at higher CNT weight fraction. The improved dispersion leads to enhanced interfacial interaction at the CNT/epoxy interface and hence provides higher relative improvement in nanocomposite properties compared to the samples prepared using as-grown and oxidized CNTs. © 2019 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2020 , 137, 48879.     

Study of pyro-carbon coated alumina kernel using mixed contrast transfer based X-ray phase retrieval technique

We have used the contrast transfer function based X-ray phase retrieval technique for phase retrieval studies on a two-component system. Pyro-carbon coated alumina matrix was chosen as a two-component system for these studies. Simulations as well as experimental results are presented. This paper shows that X-ray phase contrast along with phase retrieval can become an alternative tool for non-destructive characterization of these materials. We have also attempted to retrieve the spatial distribution of the projected thickness map of the two different elements.