426 research outputs found
EXCESS MOLAR VOLUMES AND DEVIATIONS IN VISCOSITY OF THE BINARY MIXTURES OF 1-PENTANOL + AROMATIC HYDROCARBONS AT T = 298.15 K
The densities, ρ and viscosities, η of pure 1-Pentanol, toluene, ethylbenzene, propylbenzene, and those of their binary mixtures covering the whole composition range have been measured at 298.15 K under atmospheric pressure. Excess molar volumes, E Vm , partial molar volumes, Vi , deviations in viscosity, ∆η and excess free energies of activation, E G# ∆, have also been calculated from the ρ and η data. To obtain correlation coefficients and standard deviations E Vm , ∆η and E G# ∆were fitted to Redlich–Kister type function in terms of mole fraction. In the whole range of composition, E Vm were found to be positive for 1-pentanol + ethylbenzene and + propylbenzene, but 1-pentanol + toluene system showed negative E Vm in the alcohol-rich region for. The ∆η and E G# ∆ values were the negative for all the binary mixtures
EXCESS MOLAR VOLUMES AND DEVIATIONS IN VISCOSITY OF THE BINARY MIXTURES OF 1-PENTANOL + AROMATIC HYDROCARBONS AT T = 298.15 K
The densities, ρ and viscosities, η of pure 1-Pentanol, toluene, ethylbenzene, propylbenzene, and those of their binary mixtures covering the whole composition range have been measured at 298.15 K under atmospheric pressure. Excess molar volumes, E Vm , partial molar volumes, Vi , deviations in viscosity, ∆η and excess free energies of activation, E G# ∆, have also been calculated from the ρ and η data. To obtain correlation coefficients and standard deviations E Vm , ∆η and E G# ∆were fitted to Redlich–Kister type function in terms of mole fraction. In the whole range of composition, E Vm were found to be positive for 1-pentanol + ethylbenzene and + propylbenzene, but 1-pentanol + toluene system showed negative E Vm in the alcohol-rich region for. The ∆η and E G# ∆ values were the negative for all the binary mixtures
Internet of Things Cloud: Architecture and Implementation
The Internet of Things (IoT), which enables common objects to be intelligent
and interactive, is considered the next evolution of the Internet. Its
pervasiveness and abilities to collect and analyze data which can be converted
into information have motivated a plethora of IoT applications. For the
successful deployment and management of these applications, cloud computing
techniques are indispensable since they provide high computational capabilities
as well as large storage capacity. This paper aims at providing insights about
the architecture, implementation and performance of the IoT cloud. Several
potential application scenarios of IoT cloud are studied, and an architecture
is discussed regarding the functionality of each component. Moreover, the
implementation details of the IoT cloud are presented along with the services
that it offers. The main contributions of this paper lie in the combination of
the Hypertext Transfer Protocol (HTTP) and Message Queuing Telemetry Transport
(MQTT) servers to offer IoT services in the architecture of the IoT cloud with
various techniques to guarantee high performance. Finally, experimental results
are given in order to demonstrate the service capabilities of the IoT cloud
under certain conditions.Comment: 19pages, 4figures, IEEE Communications Magazin
Generative Model-Driven Synthetic Training Image Generation: An Approach to Cognition in Rail Defect Detection
Recent advancements in cognitive computing, with the integration of deep
learning techniques, have facilitated the development of intelligent cognitive
systems (ICS). This is particularly beneficial in the context of rail defect
detection, where the ICS would emulate human-like analysis of image data for
defect patterns. Despite the success of Convolutional Neural Networks (CNN) in
visual defect classification, the scarcity of large datasets for rail defect
detection remains a challenge due to infrequent accident events that would
result in defective parts and images. Contemporary researchers have addressed
this data scarcity challenge by exploring rule-based and generative data
augmentation models. Among these, Variational Autoencoder (VAE) models can
generate realistic data without extensive baseline datasets for noise modeling.
This study proposes a VAE-based synthetic image generation technique for rail
defects, incorporating weight decay regularization and image reconstruction
loss to prevent overfitting. The proposed method is applied to create a
synthetic dataset for the Canadian Pacific Railway (CPR) with just 50 real
samples across five classes. Remarkably, 500 synthetic samples are generated
with a minimal reconstruction loss of 0.021. A Visual Transformer (ViT) model
underwent fine-tuning using this synthetic CPR dataset, achieving high accuracy
rates (98%-99%) in classifying the five defect classes. This research offers a
promising solution to the data scarcity challenge in rail defect detection,
showcasing the potential for robust ICS development in this domain.Comment: 26 pages, 13 figures, Springer Journa
Performance Evaluation of Ad Hoc Network over Moving Vehicles in a City
A mobile ad hoc network (MANET) is a collection of wireless mobile nodes that can dynamically form a temporary network without the aid of any existing network infrastructure. Wireless connectivity on vehicles is an important mode of communication. It is more challenging to provide high-bandwidth networking over fast moving vehicles. Ad Hoc network can be formed on fast moving vehicles where the interior node acts as rely node. A dynamic routing protocol is needed for a node to exchange data with another. In this research work, we consider the traffic density of a typical district town where traffic density much lower than a metropolitan city and vehicle speed is regulated according to traffic law. We have studied two routing protocols AODV and DSR in city traffic. According to our study, AODV shows performance than DSR on city roa
The Effect of Web Reinforcement on the Shear Capacity of Brick Aggregate Concrete Beams
Shear capacity of reinforced brick aggregate concrete beams without any web
reinforcement and with varying ratio of web reinforcement was studied in this
investigation. Deflections of beams and cracks during the progress of loading
were recorded. Brick aggregate concrete beams with web reinforcement and
two layers of tensile reinforcement were found to have increased cracking shear
stress by a considerable amount. Equations for cracking and ultimate shear
stresses were suggested within the scope of this study. The experimental values
of ultimate shear strength of beams were compared with the values obtained by
equations proposed by ACI and other researchers. The equations proposed
herein were found to represent the test results better than those of other
researchers while remaining on the conservative side. It is hoped that the
equations developed herein will provide a rational and basic point of departure
from the prevailing concept and will help towards the formulation of a suitable
code to provide web reinforcement for brick aggregate concrete beams
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