Abstract: The mitigation of crop loss due to damaging freezes requires accurate air temperature prediction models. An improved model for temperature prediction in Georgia was developed by including information on seasonality and modifying parameters of an existing artificial neural network model. Alternative models were compared by instantiating and training multiple networks for each model. The inclusion of up to 24 hours of prior weather information and inputs reflecting the day of year were among improvements that reduced average four-hour prediction error by 0.18°C compared to the prior model. Results strongly suggest model developers should instantiate and train multiple networks with different initial weights to establish appropriate model parameters.
Abstract: This paper presents a video transmission system using
layered multiple description (coding (MDC) and multi-path transport
for reliable video communications in wireless ad-hoc networks.
The proposed MDC extends a quality-scalable H.264/AVC video
coding algorithm to generate two independent descriptions. The two
descriptions are transmitted over different paths to a receiver in order
to alleviate the effect of unstable channel conditions of wireless adhoc
networks. If one description is lost due to transmission erros,
then the correctly received description is used to estimate the lost
information of the corrupted description. The proposed MD coder
maintains an adequate video quality as long as both description are
not simultaneously lost. Simulation results show that the proposed
MD coding combined with multi-path transport system is largely
immune to packet losses, and therefore, can be a promising solution
for robust video communications over wireless ad-hoc networks.
Abstract: In this paper we present the information life cycle and analyze the importance of managing the corporate application portfolio across this life cycle. The approach presented here corresponds not just to the extension of the traditional information system development life cycle. This approach is based in the generic life cycle. In this paper it is proposed a model of an information system life cycle, supported in the assumption that a system has a limited life. But, this limited life may be extended. This model is also applied in several cases; being reported here two examples of the framework application in a construction enterprise and in a manufacturing enterprise.
Abstract: This work focuses on analysis of classical heat transfer equation regularized with Maxwell-Cattaneo transfer law. Computer simulations are performed in MATLAB environment. Numerical experiments are first developed on classical Fourier equation, then Maxwell-Cattaneo law is considered. Corresponding equation is regularized with a balancing diffusion term to stabilize discretizing scheme with adjusted time and space numerical steps. Several cases including a convective term in model equations are discussed, and results are given. It is shown that limiting conditions on regularizing parameters have to be satisfied in convective case for Maxwell-Cattaneo regularization to give physically acceptable solutions. In all valid cases, uniform convergence to solution of initial heat equation with Fourier law is observed, even in nonlinear case.
Abstract: This study analyzes on the Social Network Game
(SNG), ANIPANG, in order to discover its unique fun elements, so
that suggest new methodologies for development of SNGs. ANIPANG
is the most popular SNG in the South Korea on 2012. Recently, the
game industry is paying close attention to mobile-based SNGs due to
the rapid prevalence of smart-phones and social network services.
However, SNGs are not online games simply. Although the fun of
most online games is the victory through competition with other
players or the game system, the fun of SNG is the communication
through the collaboration with other players. Thus, features of users
and environments of game should be considered for the game industry
and for the fun of SNG to users.
Abstract: Many accidents were happened because of fast driving, habitual working overtime or tired spirit. This paper presents a solution of remote warning for vehicles collision avoidance using vehicular communication. The development system integrates dedicated short range communication (DSRC) and global position system (GPS) with embedded system into a powerful remote warning system. To transmit the vehicular information and broadcast vehicle position; DSRC communication technology is adopt as the bridge. The proposed system is divided into two parts of the positioning andvehicular units in a vehicle. The positioning unit is used to provide the position and heading information from GPS module, and furthermore the vehicular unit is used to receive the break, throttle, and othersignals via controller area network (CAN) interface connected to each mechanism. The mobile hardware are built with an embedded system using X86 processor in Linux system. A vehicle is communicated with other vehicles via DSRC in non-addressed protocol with wireless access in vehicular environments (WAVE) short message protocol. From the position data and vehicular information, this paper provided a conflict detection algorithm to do time separation and remote warning with error bubble consideration. And the warning information is on-line displayed in the screen. This system is able to enhance driver assistance service and realize critical safety by using vehicular information from the neighbor vehicles.KeywordsDedicated short range communication, GPS, Control area network, Collision avoidance warning system.
Abstract: Employees commonly encounter unpredictable and
unavoidable work related stressors. Exposure to such stressors can
evoke negative appraisals and associated adverse mental, physical,
and behavioral responses. Because Acceptance and Commitment
Therapy (ACT) emphasizes acceptance of unavoidable stressors and
diffusion from negative appraisals, it may be particularly beneficial
for work stress. Forty-five workers were randomly assigned to an
ACT intervention for work stress (n = 21) or a waitlist control group
(n = 24). The intervention consisted of two 3-hour sessions spaced
one week apart. An examination of group process and outcomes was
conducted using the Revised Sessions Rating Scale. Results indicated
that the ACT participants reported that they perceived the
intervention to be supportive, task focused, and without adverse
therapist behaviors (e.g., feelings of being criticized or discounted).
Additionally, the second session (values clarification and
commitment to action) was perceived to be more supportive and task
focused than the first session (mindfulness, defusion). Process ratings
were correlated with outcomes. Results indicated that perceptions of
therapy supportiveness and task focus were associated with reduced
psychological distress and improved perceived physical health.
Abstract: The wireless adhoc network is comprised of wireless
node which can move freely and are connected among themselves
without central infrastructure. Due to the limited transmission range
of wireless interfaces, in most cases communication has to be relayed
over intermediate nodes. Thus, in such multihop network each node
(also called router) is independent, self-reliant and capable to route
the messages over the dynamic network topology. Various protocols
are reported in this field and it is very difficult to decide the best one.
A key issue in deciding which type of routing protocol is best for
adhoc networks is the communication overhead incurred by the
protocol. In this paper STAR a table driven and DSR on demand
protocols based on IEEE 802.11 are analyzed for their performance
on different performance measuring metrics versus varying traffic
CBR load using QualNet 5.0.2 network simulator.
Abstract: Burnishing is a method of finishing and hardening
machined parts by plastic deformation of the surface. Experimental
work based on central composite second order rotatable design has
been carried out on a lathe machine to establish the effects of ball
burnishing parameters on the surface roughness of brass material.
Analysis of the results by the analysis of variance technique and the
F-test show that the parameters considered, have significant effects
on the surface roughness.
Abstract: In spite of all advancement in software testing,
debugging remains a labor-intensive, manual, time consuming, and
error prone process. A candidate solution to enhance debugging
process is to fuse it with testing process. To achieve this integration,
a possible solution may be categorizing common software tests and
errors followed by the effort on fixing the errors through general
solutions for each test/error pair. Our approach to address this issue is
based on Christopher Alexander-s pattern and pattern language
concepts. The patterns in this language are grouped into three major
sections and connect the three concepts of test, error, and debug.
These patterns and their hierarchical relationship shape a pattern
language that introduces a solution to solve software errors in a
known testing context.
Finally, we will introduce our developed framework ADE as a
sample implementation to support a pattern of proposed language,
which aims to automate the whole process of evolving software
design via evolutionary methods.
Abstract: Individually Network reconfiguration or Capacitor control
perform well in minimizing power loss and improving voltage
profile of the distribution system. But for heavy reactive power loads
network reconfiguration and for heavy active power loads capacitor
placement can not effectively reduce power loss and enhance
voltage profiles in the system. In this paper, an hybrid approach
that combine network reconfiguration and capacitor placement using
Harmony Search Algorithm (HSA) is proposed to minimize power
loss reduction and improve voltage profile. The proposed approach
is tested on standard IEEE 33 and 16 bus systems. Computational
results show that the proposed hybrid approach can minimize losses
more efficiently than Network reconfiguration or Capacitor control.
The results of proposed method are also compared with results
obtained by Simulated Annealing (SA). The proposed method has
outperformed in terms of the quality of solution compared to SA.
Abstract: This paper proposes a novel system for monitoring the
health of underground pipelines. Some of these pipelines transport
dangerous contents and any damage incurred might have catastrophic
consequences. However, most of these damage are unintentional and
usually a result of surrounding construction activities. In order to
prevent these potential damages, monitoring systems are
indispensable. This paper focuses on acoustically recognizing road
cutters since they prelude most construction activities in modern
cities. Acoustic recognition can be easily achieved by installing a
distributed computing sensor network along the pipelines and using
smart sensors to “listen" for potential threat; if there is a real threat,
raise some form of alarm. For efficient pipeline monitoring, a novel
monitoring approach is proposed. Principal Component Analysis
(PCA) was studied and applied. Eigenvalues were regarded as the
special signature that could characterize a sound sample, and were
thus used for the feature vector for sound recognition. The denoising
ability of PCA could make it robust to noise interference. One class
SVM was used for classifier. On-site experiment results show that the
proposed PCA and SVM based acoustic recognition system will be
very effective with a low tendency for raising false alarms.
Abstract: TELMES project aims to develop a securized
multimedia system devoted to medical consultation teleservices. It
will be finalized with a pilot system for a regional telecenters
network that connects local telecenters, having as support
multimedia platforms. This network will enable the implementation
of complex medical teleservices (teleconsulations, telemonitoring,
homecare, urgency medicine, etc.) for a broader range of patients
and medical professionals, mainly for family doctors and those
people living in rural or isolated regions. Thus, a multimedia,
scalable network, based on modern IT&C paradigms, will result. It
will gather two inter-connected regional telecenters, in Iaşi and
Piteşti, Romania, each of them also permitting local connections of
hospitals, diagnostic and treatment centers, as well as local networks
of family doctors, patients, even educational entities. As
communications infrastructure, we aim to develop a combined fixmobile-
internet (broadband) links. Other possible communication
environments will be GSM/GPRS/3G and radio waves. The
electrocardiogram (ECG) acquisition, internet transmission and
local analysis, using embedded technologies, was already
successfully done for patients- telemonitoring.
Abstract: In this paper, the robust exponential stability problem of discrete-time uncertain stochastic neural networks with timevarying delays is investigated. By introducing a new augmented Lyapunov function, some delay-dependent stable results are obtained in terms of linear matrix inequality (LMI) technique. Compared with some existing results in the literature, the conservatism of the new criteria is reduced notably. Three numerical examples are provided to demonstrate the less conservatism and effectiveness of the proposed method.
Abstract: This paper presented a new approach for centralized
monitoring and self-protected against fiber fault in fiber-to-the-home
(FTTH) access network by using Smart Access Network Testing,
Analyzing and Database (SANTAD). SANTAD will be installed
with optical line terminal (OLT) at central office (CO) for in-service
transmission surveillance and fiber fault localization within FTTH
with point-to-multipoint (P2MP) configuration downwardly from CO
towards customer residential locations based on the graphical user
interface (GUI) processing capabilities of MATLAB software.
SANTAD is able to detect any fiber fault as well as identify the
failure location in the network system. SANTAD enable the status of
each optical network unit (ONU) connected line is displayed onto
one screen with capability to configure the attenuation and detect the
failure simultaneously. The analysis results and information will be
delivered to the field engineer for promptly actions, meanwhile the
failure line will be diverted to protection line to ensure the traffic
flow continuously. This approach has a bright prospect to improve
the survivability and reliability as well as increase the efficiency and
monitoring capabilities in FTTH.
Abstract: Most of the commonly used blind equalization algorithms are based on the minimization of a nonconvex and nonlinear cost function and a neural network gives smaller residual error as compared to a linear structure. The efficacy of complex valued feedforward neural networks for blind equalization of linear and nonlinear communication channels has been confirmed by many studies. In this paper we present two neural network models for blind equalization of time-varying channels, for M-ary QAM and PSK signals. The complex valued activation functions, suitable for these signal constellations in time-varying environment, are introduced and the learning algorithms based on the CMA cost function are derived. The improved performance of the proposed models is confirmed through computer simulations.
Abstract: Noise has adverse effect on human health and
comfort. Noise not only cause hearing impairment, but it also acts as
a causal factor for stress and raising systolic pressure. Additionally it
can be a causal factor in work accidents, both by marking hazards
and warning signals and by impeding concentration. Industry
workers also suffer psychological and physical stress as well as
hearing loss due to industrial noise. This paper proposes an approach
to enable engineers to point out quantitatively the noisiest source for
modification, while multiple machines are operating simultaneously.
The model with the point source and spherical radiation in a free field
was adopted to formulate the problem. The procedure works very
well in ideal cases (point source and free field). However, most of the
industrial noise problems are complicated by the fact that the noise is
confined in a room. Reflections from the walls, floor, ceiling, and
equipment in a room create a reverberant sound field that alters the
sound wave characteristics from those for the free field. So the model
was validated for relatively low absorption room at NIT Kurukshetra
Central Workshop. The results of validation pointed out that the
estimated sound power of noise sources under simultaneous
conditions were on lower side, within the error limits 3.56 - 6.35 %.
Thus suggesting the use of this methodology for practical
implementation in industry. To demonstrate the application of the
above analytical procedure for estimating the sound power of noise
sources under simultaneous operating conditions, a manufacturing
facility (Railway Workshop at Yamunanagar, India) having five
sound sources (machines) on its workshop floor is considered in this
study. The findings of the case study had identified the two most
effective candidates (noise sources) for noise control in the Railway
Workshop Yamunanagar, India. The study suggests that the
modification in the design and/or replacement of these two identified
noisiest sources (machine) would be necessary so as to achieve an
effective reduction in noise levels. Further, the estimated data allows
engineers to better understand the noise situations of the workplace
and to revise the map when changes occur in noise level due to a
workplace re-layout.
Abstract: Flight management system (FMS) is a specialized
computer system that automates a wide variety of in-flight tasks,
reducing the workload on the flight crew to the point that modern
aircraft no longer carry flight engineers or navigators. The primary
function of FMS is to perform the in-flight management of the flight
plan using various sensors (such as GPS and INS often backed up by
radio navigation) to determine the aircraft's position. From the
cockpit FMS is normally controlled through a Control Display Unit
(CDU) which incorporates a small screen and keyboard or touch
screen. This paper investigates the performance of GPS/ INS
integration techniques in which the data fusion process is done using
Kalman filtering. This will include the importance of sensors
calibration as well as the alignment of the strap down inertial
navigation system. The limitations of the inertial navigation systems
are investigated in order to understand why INS sometimes is
integrated with other navigation aids and not just operating in standalone
mode. Finally, both the loosely coupled and tightly coupled
configurations are analyzed for several types of situations and
operational conditions.
Abstract: An artificial neural network (ANN) model is
presented for the prediction of kinematic viscosity of binary mixtures
of poly (ethylene glycol) (PEG) in water as a function of temperature,
number-average molecular weight and mass fraction. Kinematic
viscosities data of aqueous solutions for PEG (0.55419×10-6 –
9.875×10-6 m2/s) were obtained from the literature for a wide range
of temperatures (277.15 - 338.15 K), number-average molecular
weight (200 -10000), and mass fraction (0.0 – 1.0). A three layer
feed-forward artificial neural network was employed. This model
predicts the kinematic viscosity with a mean square error (MSE) of
0.281 and the coefficient of determination (R2) of 0.983. The results
show that the kinematic viscosity of binary mixture of PEG in water
could be successfully predicted using an artificial neural network
model.
Abstract: The data is available in abundance in any business
organization. It includes the records for finance, maintenance,
inventory, progress reports etc. As the time progresses, the data keep
on accumulating and the challenge is to extract the information from
this data bank. Knowledge discovery from these large and complex
databases is the key problem of this era. Data mining and machine
learning techniques are needed which can scale to the size of the
problems and can be customized to the application of business. For
the development of accurate and required information for particular
problem, business analyst needs to develop multidimensional models
which give the reliable information so that they can take right
decision for particular problem. If the multidimensional model does
not possess the advance features, the accuracy cannot be expected.
The present work involves the development of a Multidimensional
data model incorporating advance features. The criterion of
computation is based on the data precision and to include slowly
change time dimension. The final results are displayed in graphical
form.