Abstract: Green and renewable energy is getting extraordinary
consideration today, because of ecological concerns made by blazing
of fossil powers. Photovoltaic and wind power generation are the
basic decisions for delivering power in this respects. Producing
power by the sun based photovoltaic systems is known to the world,
yet control makers may get confounded to pick between on-grid and
off-grid systems. In this exploration work, an endeavor is made to
compare the off-grid (stand-alone) and on-grid (grid-connected)
frameworks. The work presents relative examination, between two
distinctive PV frameworks situated at V.V.P. Engineering College,
Rajkot. The first framework is 100 kW remain solitary and the
second is 60 kW network joined. The real-time parameters compared
are; output voltage, load current, power in-flow, power output,
performance ratio, yield factor, and capacity factor. The voltage
changes and the power variances in both frameworks are given
exceptional consideration and the examination is made between the
two frameworks to judge the focal points and confinements of both
the frameworks.
Abstract: Small-size and low-power sensors with sensing, signal
processing and wireless communication capabilities is suitable for the
wireless sensor networks. Due to the limited resources and battery
constraints, complex routing algorithms used for the ad-hoc networks
cannot be employed in sensor networks. In this paper, we propose
node-disjoint multi-path hexagon-based routing algorithms in wireless
sensor networks. We suggest the details of the algorithm and compare
it with other works. Simulation results show that the proposed scheme
achieves better performance in terms of efficiency and message
delivery ratio.
Abstract: Wavelength Division Multiplexing (WDM)
technology is the most promising technology for the proper
utilization of huge raw bandwidth provided by an optical fiber. One
of the key problems in implementing the all-optical WDM network is
the packet contention. This problem can be solved by several
different techniques. In time domain approach the packet contention
can be reduced by incorporating Fiber Delay Lines (FDLs) as optical
buffer in the switch architecture. Different types of buffering
architectures are reported in literatures. In the present paper a
comparative performance analysis of three most popular FDL
architectures are presented in order to obtain the best contention
resolution performance. The analysis is further extended to consider
the effect of different fiber non-linearities on the network
performance.
Abstract: This paper describes the development of new class of
epoxy based rice husk filled jute reinforced composites. Rice husk
flour is added in 0%, 1%, 3%, 5% by weight. Epoxy resin and
triethylenetetramine (T.E.T.A) is used as matrix and hardener
respectively. It investigates the mechanical properties of the
composites and a comparison is done for monolithic jute composite
and the filled ones. The specimens are prepared according to the
ASTM standards and experimentation is carried out using INSTRON
8801. The result shows that with the increase of filler percentage the
tensile properties increases but compressive and flexural properties
decreases.
Abstract: Brushless DC motors (BLDC) are widely used in
industrial areas. The BLDC motors are driven either by indirect ACAC
converters or by direct AC-AC converters. Direct AC-AC
converters i.e. matrix converters are used in this paper to drive the
three phase BLDC motor and it eliminates the bulky DC link energy
storage element. A matrix converter converts the AC power supply to
an AC voltage of variable amplitude and variable frequency. A
control technique is designed to generate the switching pulses for the
three phase matrix converter. For the control of speed of the BLDC
motor a separate PI controller and Fuzzy Logic Controller (FLC) are
designed and a hysteresis current controller is also designed for the
control of motor torque. The control schemes are designed and tested
separately. The simulation results of both the schemes are compared
and contrasted in this paper. The results show that the fuzzy logic
control scheme outperforms the PI control scheme in terms of
dynamic performance of the BLDC motor. Simulation results are
validated with the experimental results.
Abstract: The question of legal liability over injury arising out
of the import and the introduction of GM food emerges as a crucial
issue confronting to promote GM food and its derivatives. There is a
greater possibility of commercialized GM food from the exporting
country to enter importing country where status of approval shall not
be same. This necessitates the importance of fixing a liability
mechanism to discuss the damage, if any, occurs at the level of
transboundary movement or at the market. There was a widespread consensus to develop the Cartagena
Protocol on Biosafety and to give for a dedicated regime on liability
and redress in the form of Nagoya Kuala Lumpur Supplementary
Protocol on the Liability and Redress (‘N-KL Protocol’) at the
international context. The national legal frameworks based on this
protocol are not adequately established in the prevailing food
legislations of the developing countries. The developing economy
like India is willing to import GM food and its derivatives after the
successful commercialization of Bt Cotton in 2002. As a party to the
N-KL Protocol, it is indispensable for India to formulate a legal
framework and to discuss safety, liability, and regulatory issues
surrounding GM foods in conformity to the provisions of the
Protocol. The liability mechanism is also important in the case where
the risk assessment and risk management is still in implementing
stage. Moreover, the country is facing GM infiltration issues with its
neighbors Bangladesh. As a precautionary approach, there is a need
to formulate rules and procedure of legal liability to discuss any kind
of damage occurs at transboundary trade. In this context, the
proposed work will attempt to analyze the liability regime in the
existing Food Safety and Standards Act, 2006 from the applicability
and domestic compliance and to suggest legal and policy options for
regulatory authorities.
Abstract: Average temperatures worldwide are expected to
continue to rise. At the same time, major cities in developing
countries are becoming increasingly populated and polluted.
Governments are tasked with the problem of overheating and air
quality in residential buildings. This paper presents the development
of a model, which is able to estimate the occupant exposure
to extreme temperatures and high air pollution within domestic
buildings. Building physics simulations were performed using the
EnergyPlus building physics software. An accurate metamodel is
then formed by randomly sampling building input parameters and
training on the outputs of EnergyPlus simulations. Metamodels are
used to vastly reduce the amount of computation time required when
performing optimisation and sensitivity analyses. Neural Networks
(NNs) have been compared to a Radial Basis Function (RBF)
algorithm when forming a metamodel. These techniques were
implemented using the PyBrain and scikit-learn python libraries,
respectively. NNs are shown to perform around 15% better than RBFs
when estimating overheating and air pollution metrics modelled by
EnergyPlus.
Abstract: Social networking sites such as Twitter and Facebook
attracts over 500 million users across the world, for those users, their
social life, even their practical life, has become interrelated. Their
interaction with social networking has affected their life forever.
Accordingly, social networking sites have become among the main
channels that are responsible for vast dissemination of different kinds
of information during real time events. This popularity in Social
networking has led to different problems including the possibility of
exposing incorrect information to their users through fake accounts
which results to the spread of malicious content during life events.
This situation can result to a huge damage in the real world to the
society in general including citizens, business entities, and others. In this paper, we present a classification method for detecting the
fake accounts on Twitter. The study determines the minimized set of
the main factors that influence the detection of the fake accounts on
Twitter, and then the determined factors are applied using different
classification techniques. A comparison of the results of these
techniques has been performed and the most accurate algorithm is
selected according to the accuracy of the results. The study has been
compared with different recent researches in the same area; this
comparison has proved the accuracy of the proposed study. We claim
that this study can be continuously applied on Twitter social network
to automatically detect the fake accounts; moreover, the study can be
applied on different social network sites such as Facebook with minor
changes according to the nature of the social network which are
discussed in this paper.
Abstract: A broadband wire monopole antenna loaded by inhomogeneous stack of annular dielectric ring resonators (DRRs) is proposed. The proposed antenna exhibits a broad impedance bandwidth from 3 to 30 GHz. This is achieved by adding an external step matching network at the antenna feed point. The matching network is comprised of three annular DRRs possessing different permittivity values and sharing the same axial over a finite ground plane. The antenna performance is characterized using full-wave EM simulation. Compared to previous-reported wire antennas with improved bandwidth achieved by DRRs, the proposed topology provides relatively compact realization and superior broadband performance.
Abstract: The Internet of Things (IoT) field has been applied in
industries with different purposes. Sensing Enterprise (SE) is an
attribute of an enterprise or a network that allows it to react to
business stimuli originating on the Internet. These fields have come
into focus recently on the enterprises, and there is some evidence of
the use and implications in supply chain management, while
finding it as an interesting aspect to work on. This paper presents a
revision and proposals of IoT applications in supply chain
management.
Abstract: Customer’ needs, quality, and value creation while
reducing costs through supply chain management provides challenges
and opportunities for companies and researchers. In the light of these
challenges, modern ideas must contribute to counter these challenges
and exploit opportunities. Therefore, this paper discusses the impact
of the quality cost on revenue sharing as a most important incentive
to configure business networks. This paper develops the quality cost approach to align with the
modern era. It develops a model to measure quality costs which
might enable firms to manage revenue sharing in a supply chain. The
developed model includes five categories; besides the well-known
four categories (namely prevention costs, appraisal costs, internal
failure costs, and external failure costs), a new category has been
developed in this research as a new vision of the relationship between
quality costs and innovations in industry. This new category is
Recycle Cost. This paper also examines whether such quality costs in
supply chains influence the revenue sharing between partners. Using the author's quality cost model, the relationship between
quality costs and revenue sharing among partners is examined using a
case study in an Egyptian manufacturing company which is a part of
a supply chain. This paper argues that the revenue-sharing proportion
allocated to supplier increases as the recycle cost of supplier
increases, and the revenue-sharing proportion allocated to
manufacturer increases as the prevention and appraisal costs increase,
as well as the failure costs, the recycle costs of manufacturer, and the
recycle costs of suppliers decrease. However, the results present
surprising findings. The purposes of this study are developing quality cost approach
and understanding the relationships between quality costs and
revenue sharing in supply chains. Therefore, the present study
contributes to theory and practice by explaining how the cost of
recycling can be combined in quality cost model to better
understanding the revenue sharing among partners in supply chains.
Abstract: Since the advances in digital imaging technologies have led to
development of high quality digital devices, there are a lot of illegal copies
of copyrighted video content on the Internet. Also, unauthorized editing is
occurred frequently. Thus, we propose an editing prevention technique for
high-quality (HQ) video that can prevent these illegally edited copies from
spreading out. The proposed technique is applied spatial and temporal gradient
methods to improve the fidelity and detection performance. Also, the scheme
duplicates the embedding signal temporally to alleviate the signal reduction
caused by geometric and signal-processing distortions. Experimental results
show that the proposed scheme achieves better performance than previously
proposed schemes and it has high fidelity. The proposed scheme can be used
in unauthorized access prevention method of visual communication or traitor
tracking applications which need fast detection process to prevent illegally
edited video content from spreading out.
Abstract: In this paper, a learning algorithm using neuronal networks to improve the roll stability and prevent the rollover in a single unit heavy vehicle is proposed. First, LQR control to keep balanced normalized rollovers, between front and rear axles, below the unity, then a data collected from this controller is used as a training basis of a neuronal regulator. The ANN controller is thereafter applied for the nonlinear side force model, and gives satisfactory results than the LQR one.
Abstract: The study of implicature which is one of the
discussions of pragmatics is such an interesting and challenging topic
to discuss. Implicature is such a meaning which is implied in such an
utterance which is not the same as its literal meaning. The rapid
development of information technology results social networks as
media to broadcast messages. The broadcast messages may be in the
form of jokes which contain implicature. The research applies the
pragmatic equivalent method to analyze the topics of jokes based on
the implicatures contained in them. Furthermore, the method is also
applied to reveal the purpose of creating implicature in jokes. The
findings include the kinds of implicature found in jokes which are
classified into conventional implicature and conversational
implicature. Then, in detailed analysis, implicature in jokes is divided
into implicature related to gender, culture, and social phenomena.
Furthermore, implicature in jokes may not only be used to give
entertainment but also to soften criticisms or satire so that it does not
sound rude and harsh.
Abstract: As one of the convenient and noninvasive sensing
approaches, the automatic limb girth measurement has been applied
to detect intention behind human motion from muscle deformation.
The sensing validity has been elaborated by preliminary researches
but still need more fundamental studies, especially on kinetic
contraction modes. Based on the novel fabric strain sensors, a soft
and smart limb girth measurement system was developed by the
authors’ group, which can measure the limb girth in-motion.
Experiments were carried out on elbow isometric flexion and elbow
isokinetic flexion (biceps’ isokinetic contractions) of 90°/s, 60°/s, and
120°/s for 10 subjects (2 canoeists and 8 ordinary people). After
removal of natural circumferential increments due to elbow position,
the joint torque is found not uniformly sensitive to the limb
circumferential strains, but declining as elbow joint angle rises,
regardless of the angular speed. Moreover, the maximum joint torque
was found as an exponential function of the joint’s angular speed.
This research highly contributes to the application of the automatic
limb girth measuring during kinetic contractions, and it is useful to
predict the contraction level of voluntary skeletal muscles.
Abstract: Opportunistic Routing (OR) increases the
transmission reliability and network throughput. Traditional routing
protocols preselects one or more predetermined nodes before
transmission starts and uses a predetermined neighbor to forward a
packet in each hop. The opportunistic routing overcomes the
drawback of unreliable wireless transmission by broadcasting one
transmission can be overheard by manifold neighbors. The first
cooperation-optimal protocol for Multirate OR (COMO) used to
achieve social efficiency and prevent the selfish behavior of the
nodes. The novel link-correlation-aware OR improves the
performance by exploiting the miscellaneous low correlated forward
links. Context aware Adaptive OR (CAOR) uses active suppression
mechanism to reduce packet duplication. The Context-aware OR
(COR) can provide efficient routing in mobile networks. By using
Cooperative Opportunistic Routing in Mobile Ad hoc Networks
(CORMAN), the problem of opportunistic data transfer can be
tackled. While comparing to all the protocols, COMO is the best as it
achieves social efficiency and prevents the selfish behavior of the
nodes.
Abstract: Rivers have transient storage or dead zones where
injected pollutants or solutes are entrapped for considerable period of
time, known as residence time, before being released into the main
flowing zones of rivers. In this study, a new empirical expression for
residence time, implementing genetic programming on published
dispersion data, has been derived. The proposed expression uses few
hydraulic and geometric characteristics of rivers which are normally
known to the authorities. When compared with some reported
expressions, based on various statistical indices, it can be concluded
that the proposed expression predicts the residence time of pollutants
in natural rivers more accurately.
Abstract: The change of conditions for production companies in
high-wage countries is characterized by the globalization of
competition and the transition of a supplier´s to a buyer´s market. The
companies need to face the challenges of reacting flexibly to these
changes. Due to the significant and increasing degree of automation,
assembly has become the most expensive production process.
Regarding the reduction of production cost, assembly consequently
offers a considerable rationalizing potential. Therefore, an
aerodynamic feeding system has been developed at the Institute of
Production Systems and Logistics (IFA), Leibniz Universitaet
Hannover. This system has been enabled to adjust itself by using a
genetic algorithm. The longer this genetic algorithm is executed the
better is the feeding quality. In this paper, the relation between the
system´s setting time and the feeding quality is observed and a
function which enables the user to achieve the minimum of the total
feeding time is presented.
Abstract: Both steady and unsteady turbulent mixed convection
heat transfer in a 3D lid-driven enclosure, which has constant heat
flux on the middle of bottom wall and with isothermal moving
sidewalls, is reported in this paper for working fluid with Prandtl
number Pr = 0.71. The other walls are adiabatic and stationary. The
dimensionless parameters used in this research are Reynolds number,
Re = 5000, 10000 and 15000, and Richardson number, Ri = 1 and 10.
The simulations have been done by using different turbulent methods
such as RANS, URANS, and LES. The effects of using different k-ε
models such as standard, RNG and Realizable k-ε model are
investigated. Interesting behaviours of the thermal and flow fields
with changing the Re or Ri numbers are observed. Isotherm and
turbulent kinetic energy distributions and variation of local Nusselt
number at the hot bottom wall are studied as well. The local Nusselt
number is found increasing with increasing either Re or Ri number.
In addition, the turbulent kinetic energy is discernibly affected by
increasing Re number. Moreover, the LES results have shown good
ability of this method in predicting more detailed flow structures in
the cavity.
Abstract: One of the global combinatorial optimization
problems in machine learning is feature selection. It concerned with
removing the irrelevant, noisy, and redundant data, along with
keeping the original meaning of the original data. Attribute reduction
in rough set theory is an important feature selection method. Since
attribute reduction is an NP-hard problem, it is necessary to
investigate fast and effective approximate algorithms. In this paper,
we proposed two feature selection mechanisms based on memetic
algorithms (MAs) which combine the genetic algorithm with a fuzzy
record to record travel algorithm and a fuzzy controlled great deluge
algorithm, to identify a good balance between local search and
genetic search. In order to verify the proposed approaches, numerical
experiments are carried out on thirteen datasets. The results show that
the MAs approaches are efficient in solving attribute reduction
problems when compared with other meta-heuristic approaches.