Abstract: Human skull is shown to exhibit numerous sexually dimorphic traits. Estimation of sex is a challenging task especially when a part of skull is brought for medicolegal investigation. The present research was planned to evaluate the sexing potential of the dimensions of foramen magnum in forensic identification by craniometric analysis. Length and breadth of the foramen magnum was measured using Vernier calipers and the area of foramen magnum was calculated. The length, breadth, and area of foramen magnum were found to be larger in males than females. Sexual dimorphism index was calculated to estimate the sexing potential of each variable. The study observations are suggestive of the limited utility of the craniometric analysis of foramen magnum during the examination of skull and its parts in estimation of sex.
Abstract: Under the limitation of investment budget, a utility
company is required to maximize the utilization of their existing
assets during their life cycle satisfying both engineering and financial
requirements. However, utility does not have knowledge about the
status of each asset in the portfolio neither in terms of technical nor
financial values. This paper presents a knowledge based model for
the utility companies in order to make an optimal decision on power
transformer with their utilization. CommonKADS methodology, a
structured development for knowledge and expertise representation,
is utilized for designing and developing knowledge based model. A
case study of One MVA power transformer of Nepal Electricity
Authority is presented. The results show that the reusable knowledge
can be categorized, modeled and utilized within the utility company
using the proposed methodologies. Moreover, the results depict that
utility company can achieve both engineering and financial benefits
from its utilization.
Abstract: Many corporations are seriously concerned about
security of networks and therefore, their network supervisors are still
reluctant to install WLANs. In this regards, the IEEE802.11i standard
was developed to address the security problems, even though the
mistrust of the wireless LAN technology is still existing. The thought
was that the best security solutions could be found in open standards
based technologies that can be delivered by Virtual Private
Networking (VPN) being used for long time without addressing any
security holes for the past few years. This work, addresses this issue
and presents a simulated wireless LAN of IEEE802.11g protocol, and
analyzes impact of integrating Virtual Private Network technology to
secure the flow of traffic between the client and the server within the
LAN, using OPNET WLAN utility. Two Wireless LAN scenarios
have been introduced and simulated. These are based on normal
extension to a wired network and VPN over extension to a wired
network. The results of the two scenarios are compared and indicate
the impact of improving performance, measured by response time
and load, of Virtual Private Network over wireless LAN.
Abstract: This paper presents an efficient emission constrained
economic dispatch algorithm that deals with nonlinear cost function
and constraints. It is then incorporated into the dynamic
programming based hydrothermal coordination program. The
program has been tested on a practical utility system having 32
thermal and 12 hydro generating units. Test results show that a slight
increase in production cost causes a substantial reduction in
emission.
Abstract: One of the most important requirements for the
operation and planning activities of an electrical utility is the
prediction of load for the next hour to several days out, known as
short term load forecasting. This paper presents the development of
an artificial neural network based short-term load forecasting model.
The model can forecast daily load profiles with a load time of one
day for next 24 hours. In this method can divide days of year with
using average temperature. Groups make according linearity rate of
curve. Ultimate forecast for each group obtain with considering
weekday and weekend. This paper investigates effects of temperature
and humidity on consuming curve. For forecasting load curve of
holidays at first forecast pick and valley and then the neural network
forecast is re-shaped with the new data. The ANN-based load models
are trained using hourly historical. Load data and daily historical
max/min temperature and humidity data. The results of testing the
system on data from Yazd utility are reported.
Abstract: Mobile marketing through mobile messaging service
has highly impressive growth as it enables e-business firms to
communicate with their customers effectively. Educational
institutions hence start using this service to enhance communication
with their students. Previous studies, however, have limited
understanding of applying mobile messaging service in education.
This study proposes a theoretical model to understand the drivers of
students- intentions to use the university-s mobile messaging service.
The model indicates that social influence, perceived control and
attitudes affect students- intention to use the university-s mobile
messaging service. It also provides five antecedents of students-
attitudes–perceived utility (information utility, entertainment utility,
and social utility), innovativeness, information seeking, transaction
specificity (content specificity, sender specificity, and time
specificity) and privacy concern. The proposed model enables
universities to understand what students concern about the use of a
mobile messaging service in universities and handle the service more
effectively. The paper discusses the model development and
concludes with limitations and implications of the proposed model.
Abstract: Mammographic images and data analysis to
facilitate modelling or computer aided diagnostic (CAD) software development should best be done using a common database that can handle various mammographic image file
formats and relate these to other patient information.
This would optimize the use of the data as both primary
reporting and enhanced information extraction of research data could be performed from the single dataset. One desired
improvement is the integration of DICOM file header information into the database, as an efficient and reliable source of supplementary patient information intrinsically
available in the images.
The purpose of this paper was to design a suitable database to link and integrate different types of image files and gather common information that can be further used for research
purposes. An interface was developed for accessing, adding,
updating, modifying and extracting data from the common
database, enhancing the future possible application of the data in CAD processing.
Technically, future developments envisaged include the creation of an advanced search function to selects image files
based on descriptor combinations. Results can be further used for specific CAD processing and other research. Design of a
user friendly configuration utility for importing of the required fields from the DICOM files must be done.
Abstract: Wireless sensor networks (WSNs) consist of number
of tiny, low cost and low power sensor nodes to monitor some physical phenomenon. The major limitation in these networks is the use of non-rechargeable battery having limited power supply. The
main cause of energy consumption in such networks is
communication subsystem. This paper presents an energy efficient
Cluster Cooperative Caching at Sensor (C3S) based upon grid type clustering. Sensor nodes belonging to the same cluster/grid form a
cooperative cache system for the node since the cost for
communication with them is low both in terms of energy
consumption and message exchanges. The proposed scheme uses
cache admission control and utility based data replacement policy to
ensure that more useful data is retained in the local cache of a node.
Simulation results demonstrate that C3S scheme performs better in
various performance metrics than NICoCa which is existing
cooperative caching protocol for WSNs.
Abstract: Recently, as the scale of construction projects has
increases, more ground excavation for foundations is carried out than ever before. Consequently, damage to underground ducts (gas, water/sewage or oil pipelines, communication cables or power cable ducts) or superannuated pipelines frequently cause serious accidents
resulting in damage to life and property. (In Korea, the total length of city water pipelines was approximately 2,000 km as of the end of 2009.) In addition, large amounts of damage caused by fractures, water
and gas leakage caused by superannuation or damage to underground
ducts in construction has been reported. Therefore, a system is required to precisely detect defects and deterioration in underground
pipelines and the locations of such defects, for timely and accurate
maintenance or replacement of the ducts. In this study, a system was
developed which can locate underground structures (gas and water
pipelines, power cable ducts, etc.) in 3D-coordinates and monitor the
degree and position of defects using an Inertial Measurement Unit
(IMU) sensing technique. The system can prevent damage to underground ducts and superannuated pipelines during construction,
and provide reliable data for maintenance. The utility of the IMU sensing technique used in aircraft and ships in civil applications was
verified.
Abstract: In North America, Most power distribution systems
employ a four-wire multi-grounded neutral (MGN) design. This paper has explained the inherent characteristics of multi-grounded three-phase four-wire distribution systems under unbalanced
situations. As a result, the mechanism of voltage swell and voltage sag in MGN feeders becomes difficult to understand. The simulation
tool that has been used in this paper is MATLAB under Windows software. In this paper the equivalent model of a full-scale multigrounded
distribution system implemented by MATLAB is
introduced. The results are expected to help utility engineers to understand the impact of MGN on distribution system operations.
Abstract: Cognitive models allow predicting some aspects of utility
and usability of human machine interfaces (HMI), and simulating
the interaction with these interfaces. The action of predicting is based
on a task analysis, which investigates what a user is required to do
in terms of actions and cognitive processes to achieve a task. Task
analysis facilitates the understanding of the system-s functionalities.
Cognitive models are part of the analytical approaches, that do not
associate the users during the development process of the interface.
This article presents a study about the evaluation of a human
machine interaction with a contextual assistant-s interface using ACTR
and GOMS cognitive models. The present work shows how these
techniques may be applied in the evaluation of HMI, design and
research by emphasizing firstly the task analysis and secondly the
time execution of the task. In order to validate and support our
results, an experimental study of user performance is conducted at
the DOMUS laboratory, during the interaction with the contextual
assistant-s interface. The results of our models show that the GOMS
and ACT-R models give good and excellent predictions respectively
of users performance at the task level, as well as the object level.
Therefore, the simulated results are very close to the results obtained
in the experimental study.
Abstract: The value of overall oxygen transfer Coefficient
(KLa), which is the best measure of oxygen transfer in water through
aeration, is obtained by a simple approach, which sufficiently
explains the utility of the method to eliminate the discrepancies due
to inaccurate assumption of saturation dissolved oxygen
concentration. The rate of oxygen transfer depends on number of
factors like intensity of turbulence, which in turns depends on the
speed of rotation, size, and number of blades, diameter and
immersion depth of the rotor, and size and shape of aeration tank, as
well as on physical, chemical, and biological characteristic of water.
An attempt is made in this paper to correlate the overall oxygen
transfer Coefficient (KLa), as an independent parameter with other
influencing parameters mentioned above. It has been estimated that
the simulation equation developed predicts the values of KLa and
power with an average standard error of estimation of 0.0164 and
7.66 respectively and with R2 values of 0.979 and 0.989 respectively,
when compared with experimentally determined values. The
comparison of this model is done with the model generated using
Computational fluid dynamics (CFD) and both the models were
found to be in good agreement with each other.
Abstract: The paper investigates the potential of support vector
machines and Gaussian process based regression approaches to
model the oxygen–transfer capacity from experimental data of
multiple plunging jets oxygenation systems. The results suggest the
utility of both the modeling techniques in the prediction of the
overall volumetric oxygen transfer coefficient (KLa) from operational
parameters of multiple plunging jets oxygenation system. The
correlation coefficient root mean square error and coefficient of
determination values of 0.971, 0.002 and 0.945 respectively were
achieved by support vector machine in comparison to values of
0.960, 0.002 and 0.920 respectively achieved by Gaussian process
regression. Further, the performances of both these regression
approaches in predicting the overall volumetric oxygen transfer
coefficient was compared with the empirical relationship for multiple
plunging jets. A comparison of results suggests that support vector
machines approach works well in comparison to both empirical
relationship and Gaussian process approaches, and could successfully
be employed in modeling oxygen-transfer.
Abstract: This paper presents an interval-based multi-attribute
decision making (MADM) approach in support of the decision
process with imprecise information. The proposed decision
methodology is based on the model of linear additive utility function
but extends the problem formulation with the measure of composite
utility variance. A sample study concerning with the evaluation of
electric generation expansion strategies is provided showing how the
imprecise data may affect the choice toward the best solution and
how a set of alternatives, acceptable to the decision maker (DM),
may be identified with certain confidence.
Abstract: Cyber physical system (CPS) for target tracking, military surveillance, human health monitoring, and vehicle detection all require maximizing the utility and saving the energy. Sensor selection is one of the most important parts of CPS. Sensor selection problem (SSP) is concentrating to balance the tradeoff between the number of sensors which we used and the utility which we will get. In this paper, we propose a performance constrained slide windows (PCSW) based algorithm for SSP in CPS. we present results of extensive simulations that we have carried out to test and validate the PCSW algorithms when we track a target, Experiment shows that the PCSW based algorithm improved the performance including selecting time and communication times for selecting.
Abstract: In this paper variation of spot price and total profits of
the generating companies- through wholesale electricity trading are
discussed with and without Central Generating Stations (CGS) share
and seasonal variations are also considered. It demonstrates how
proper analysis of generators- efficiencies and capabilities, types of
generators owned, fuel costs, transmission losses and settling price
variation using the solutions of Optimal Power Flow (OPF), can
allow companies to maximize overall revenue. It illustrates how
solutions of OPF can be used to maximize companies- revenue under
different scenarios. And is also extended to computation of Available
Transfer Capability (ATC) is very important to the transmission
system security and market forecasting. From these results it is
observed that how crucial it is for companies to plan their daily
operations and is certainly useful in an online environment of
deregulated power system. In this paper above tasks are demonstrated
on 124 bus real-life Indian utility power system of Andhra Pradesh
State Grid and results have been presented and analyzed.
Abstract: We consider the problem of bandwidth allocation in a
substrate network as an optimization problem for the aggregate utility
of multiple applications with diverse requirements and describe a
simulation scheme for dynamically adaptive bandwidth allocation
protocols. The proposed simulation model based on Coloured Petri
Nets (CPN) is realized using CPN Tools.
Abstract: This paper describes the design and development of pico-hydro generation system using consuming water distributed to houses. Water flow in the domestic pipes has kinetic energy that potential to generate electricity for energy storage purposes in addition to the routine activities such as laundry, cook and bathe. The inherent water pressure and flow inside the pipe from utility-s main tank that used for those usual activities is also used to rotate small scale hydro turbine to drive a generator for electrical power generation. Hence, this project is conducted to develop a small scale hydro generation system using consuming water distributed to houses as an alternative electrical energy source for residential use.
Abstract: Due to the increasing penetration of wind energy, it is
necessary to possess design tools that are able to simulate the impact
of these installations in utility grids. In order to provide a net
contribution to this issue a detailed wind park model has been
developed and is briefly presented. However, the computational costs
associated with the performance of such a detailed model in
describing the behavior of a wind park composed by a considerable
number of units may render its practical application very difficult. To
overcome this problem integral manifolds theory has been applied to
reduce the order of the detailed wind park model, and therefore
create the conditions for the development of a dynamic equivalent
which is able to retain the relevant dynamics with respect to the
existing a.c. system. In this paper integral manifold method has been
introduced for order reduction. Simulation results of the proposed
method represents that integral manifold method results fit the
detailed model results with a higher precision than singular
perturbation method.
Abstract: The measurement of anesthetic depth is necessary in
anesthesiology. NN10 is very simple method among the RR intervals
analysis methods. NN10 parameter means the numbers of above the 10
ms intervals of the normal to normal RR intervals.
Bispectrum analysis is defined as 2D FFT. EEG signal reflected the
non-linear peristalsis phenomena according to the change brain
function. After analyzing the bispectrum of the 2 dimension, the most
significant power spectrum density peaks appeared abundantly at the
specific area in awakening and anesthesia state. These points are
utilized to create the new index since many peaks appeared at the
specific area in the frequency coordinate. The measured range of an
index was 0-100. An index is 20-50 at an anesthesia, while the index is
90-60 at the awake.
In this paper, the relation between NN10 parameter using ECG and
bisepctrum index using EEG is observed to estimate the depth of
anesthesia during anesthesia and then we estimated the utility of the
anesthetic.