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.     

BIIR: A Beacon Information Independent VANET Routing Algorithm with Low Broadcast Overhead

Most of the existing VANET routing protocols rely on information collected from beacons for making routing decisions such as next neighbor selection. Beacons are very small size hello messages that each vehicle broadcasts periodically. Owing to very small payload size of beacons as compared to the payload size of a data message, they can easily pass through even very weak links, through which a data message could never pass. Therefore, the use of beacon information for making routing decisions in a highly dynamic scenario such as VANETs may cause selection of routes through which data message can never be sent. Several researchers have given solutions that do not use beacon information for making routing decisions. But most of these solutions incorporate a large number of broadcasts to forward the data packets, causing wastage of bandwidth. In this paper, we present a beacon information independent geographic routing algorithm called BIIR, which reduces the number of broadcasts to forward the data packets by making intelligent use of information collected by the vehicle during previous route discovery attempts for a destination. Our simulation results have shown that the proposed algorithm outperforms the existing beacon less routing protocols in terms of the average number of broadcasts per data packet forwarding, packet delivery ratio and end to end delay experienced by the data messages.     

Low Cost Low Power Smart Helmet for Real-Time Remote Underground Mine Environment Monitoring

Underground mining production process is vulnerable and highly dynamic in nature. Among the various causes of accidents in underground mine, major one is presence of flammable and noxious gases. Though many existing safety gadgets are there but they could not work reliably because of the typical nature of mines structure and production variability. Wireless data and communication network is also not successful because wireless communication in underground mine is significantly more challenging than through air. This work introduces the application of mobile wireless sensor network in order to monitor a variety of parameters in underground mines which have life threatening effects towards them. Each node of the network placed over the safety gear (helmet wore statutorily by every miner) comprises of various sensors depending on the requirement with microcontroller unit and other low power accessories. The proposed work has a unique feature that it will make the personnel aware about the situation of the gases present and surrounding by automatically generating different alarms and different light indicators. Other function of this device will be to transmit the data sensed by the sensors in the device to the control room wirelessly so that the responsible person would be aware of the situation. This work is focused on the design of such a prototype model for the underground mines with the aforementioned specification.     

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.

     

Formal modeling and verification of software‐defined networks: A survey

Unlike traditional networking devices, control and management plane are decoupled from data plane in software‐defined networks (SDN). The logically centralized control and management plane facilitate dynamic orchestration of network resources, services, and policies by writing software programs. This provides much needed flexibility and programmability where networking rules and policies can be modified dynamically depending upon the application context. As the operation of network services entirely depends on a program, a small fault may induce several issues which can adversely affect the expected behavior of the network. Formal modeling and verification help in catching inconsistencies and existence of errors prior to the deployment of the programs that control the behavior of a network. In this paper, we provide a comprehensive survey of tools and techniques available in the literature for formal modeling and verification of SDN. These tools and techniques are classified based on their types, the components of SDN where they can be applied, and the design and development phase when they are utilized. In particular, their respective benefits and limitations are discussed in terms of ease of use, interfaces, and the ability to capture and verify intended network properties.     

Effect of functionalization on dispersion of POSS‐silicone rubber nanocomposites

The nanocomposite of PDMS using functionalized fumed silica and nonreactive POSS as fillers were prepared by blend method in a planetary mixer. Fumed silica was functionalized by aliphatic and aromatic groups to study the filler–filler interactions with the aliphatic and aromatic POSS fillers and consequently their influence on the properties in the PDMS matrix. Transmission electron microscope (TEM) showed a good dispersion in the systems having the silica and POSS fillers with similar modifications. However, aliphatic and aromatic filler combinations showed more aggregated structures. Moreover, aliphatic POSS despite of good dispersion at higher loadings, act as lubricant, which is attributed to the disturbance in the PDMS‐ silica filler interaction and also the filler–filler interaction within fumed silica. There is a decrease in complex viscosity with the functionalization of fumed silica and with the aromatic/aliphatic POSS fillers. The thermal stability of aromatic functionalized fillers improves owing to the thermally stable phenyl groups. © 2013 Wiley Periodicals, Inc. J. Appl. Polym. Sci., 2013     

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.     

Thermally aware performance analysis of single-walled carbon nanotube bundle as VLSI interconnects

A comparative performance analysis in terms of delay, power dissipation, power delay product (PDP), and crosstalk noise between SWCNT bundle interconnects with resistance estimated using conventionally (temperature independent model), and thermally aware model is investigated. The results are also compared with those of currently used copper interconnects at 22 nm technology node. It is observed that, with rise in temperature from 300 to 500 K, SWCNT bundles have a lower delay than that of copper interconnect at different lengths from 100 to \(1000\,\upmu \hbox {m}\) whereas reverse is true for power dissipation. The SPICE simulation results further reveal that for temperature variations ranging from 300 to 500 K, compared to conventional metal (copper) conductors, crosstalk noise voltage levels (positive peaks) in capacitively coupled SWCNT bundle, at the far end of victim line, are significantly low. Moreover, a relative average improvement in delay, power, and PDP using a thermally aware model in comparison with a temperature independent model is about 22.44, 7.59 and 31.96 %, respectively, with length variations from 100 to \(1000\,\upmu \hbox {m}\), whereas for varied tube diameter is about 16.6, 5.6 and 19.72 %, respectively. The average relative improvement in the time duration reduction of victim output, for varied tube diameters, is about 21.7 % by using a thermally-aware model instead of a temperature-independent model of an SWCNT bundle resistance.     

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.