Abstract: Random Access Memory (RAM) is an important
device in computer system. It can represent the snapshot on how the
computer has been used by the user. With the growth of its
importance, the computer memory has been an issue that has been
discussed in digital forensics. A number of tools have been developed
to retrieve the information from the memory. However, most of the
tools have their limitation in the ability of retrieving the important
information from the computer memory. Hence, this paper is aimed
to discuss the limitation and the setback for two main techniques such
as process signature search and process enumeration. Then, a new
hybrid approach will be presented to minimize the setback in both
individual techniques. This new approach combines both techniques
with the purpose to retrieve the information from the process block
and other objects in the computer memory. Nevertheless, the basic
theory in address translation for x86 platforms will be demonstrated
in this paper.
Abstract: In this paper, a novel method for a biometric system based on the ECG signal is proposed, using spectral coefficients computed through linear predictive coding (LPC). ECG biometric systems have traditionally incorporated characteristics of fiducial points of the ECG signal as the feature set. These systems have been shown to contain loopholes and thus a non-fiducial system allows for tighter security. In the proposed system, incorporating non-fiducial features from the LPC spectrum produced a segment and subject recognition rate of 99.52% and 100% respectively. The recognition rates outperformed the biometric system that is based on the wavelet packet decomposition (WPD) algorithm in terms of recognition rates and computation time. This allows for LPC to be used in a practical ECG biometric system that requires fast, stringent and accurate recognition.
Abstract: Quantitative methods of economic decision-making as
the methodological base of the so called operational research
represent an important set of tools for managing complex economic
systems,both at the microeconomic level and on the macroeconomic
scale. Mathematical models of controlled and controlling processes
allow, by means of artificial experiments, obtaining information
foroptimalor optimum approaching managerial decision-making.The
quantitative methods of economic decision-making usually include a
methodology known as structural analysis -an analysisof
interdisciplinary production-consumption relations.
Abstract: Heart sound is an acoustic signal and many techniques
used nowadays for human recognition tasks borrow speech recognition
techniques. One popular choice for feature extraction of accoustic
signals is the Mel Frequency Cepstral Coefficients (MFCC) which
maps the signal onto a non-linear Mel-Scale that mimics the human
hearing. However the Mel-Scale is almost linear in the frequency
region of heart sounds and thus should produce similar results with
the standard cepstral coefficients (CC). In this paper, MFCC is
investigated to see if it produces superior results for PCG based
human identification system compared to CC. Results show that the
MFCC system is still superior to CC despite linear filter-banks in
the lower frequency range, giving up to 95% correct recognition rate
for MFCC and 90% for CC. Further experiments show that the high
recognition rate is due to the implementation of filter-banks and not
from Mel-Scaling.
Abstract: Method of determining of moisture diffusivity on two types of autoclaved aerated concretes with different bulk density is represented in the paper. On the specimens were measured one dimensional water transport only on liquid phase. Ever evaluation was done from moisture profiles measured in specific times by capacitance moisture meter. All values from capacitance meter were recalculated to moisture content by mass. Moisture diffusivity was determined in dependence on both moisture and temperature. The experiment temperatures were set at values 55, 65, 75 and 85°C.
Abstract: This study is concerned with the investigation of the
suitability of several empirical and semi-empirical drying models
available in the literature to define drying behavior of viscose yarn
bobbins. For this purpose, firstly, experimental drying behaviour of
viscose bobbins was determined on an experimental dryer setup
which was designed and manufactured based on hot-air bobbin
dryers used in textile industry. Afterwards, drying models considered
were fitted to the experimentally obtained moisture ratios. Drying
parameters were drying temperature and bobbin diameter. The fit
was performed by selecting the values for constants in the models in
such a way that these values make the sum of the squared differences
between the experimental and the model results for moisture ratio
minimum. Suitability of fitting was specified as comparing the
correlation coefficient, standard error and mean square deviation.
The results show that the most appropriate model in describing the
drying curves of viscose bobbins is the Page model.
Abstract: In this paper, we use an M/G/C/C state dependent
queuing model within a complex network topology to determine the
different performance measures for pedestrian traffic flow. The
occupants in this network topology need to go through some source
corridors, from which they can choose their suitable exiting
corridors. The performance measures were calculated using arrival
rates that maximize the throughputs of source corridors. In order to
increase the throughput of the network, the result indicates that the
flow direction of pedestrian through the corridors has to be restricted
and the arrival rates to the source corridor need to be controlled.
Abstract: Quantitative precipitation forecast (QPF) from
atmospheric model as input to hydrological model in an integrated
hydro-meteorological flood forecasting system has been operational
in many countries worldwide. High-resolution numerical weather
prediction (NWP) models with grid cell sizes between 2 and 14 km
have great potential in contributing towards reasonably accurate QPF.
In this study the potential of two NWP models to forecast
precipitation for a flood-prone area in a tropical region is examined.
The precipitation forecasts produced from the Fifth Generation Penn
State/NCAR Mesoscale (MM5) and Weather Research and
Forecasting (WRF) models are statistically verified with the observed
rain in Kelantan River Basin, Malaysia. The statistical verification
indicates that the models have performed quite satisfactorily for low
and moderate rainfall but not very satisfactory for heavy rainfall.
Abstract: In this paper, some problem formulations of dynamic object parameters recovery described by non-autonomous system of ordinary differential equations with multipoint unshared edge conditions are investigated. Depending on the number of additional conditions the problem is reduced to an algebraic equations system or to a problem of quadratic programming. With this purpose the paper offers a new scheme of the edge conditions transfer method called by conditions shift. The method permits to get rid from differential links and multipoint unshared initially-edge conditions. The advantage of the proposed approach is concluded by capabilities of reduction of a parametric identification problem to essential simple problems of the solution of an algebraic system or quadratic programming.
Abstract: Salary risk and demographic risk have been identified
as main risks in analyzing pension expenditure particularly in
Defined Benefit pension plan. Therefore, public pension plan in
Malaysia is studied to analyze pension expenditure due to salary and
demographic risk. Through the literature review and interview session
with several officers in public sector, factors affecting pension
expenditure are determined. Then, the inter-relationships between
these factors are analyzed through causal loop diagram. The System
Dynamics model is later developed using iThink software to show how
demographic and salary changes affect the pension expenditure. Then, by
using actual data, the impact of different policy scenarios on pension
expenditure is analyzed. It is shown that dynamics simulation model of
pension expenditure is useful to evaluate the impact of changes and
policy decisions on risk particularly involving demographic and salary risk.
Abstract: A mathematical model of the surface roughness
has been developed by using response surface methodology
(RSM) in grinding of AISI D2 cold work tool steels. Analysis
of variance (ANOVA) was used to check the validity of the
model. Low and high value for work speed and feed rate are
decided from design of experiment. The influences of all
machining parameters on surface roughness have been
analyzed based on the developed mathematical model. The
developed prediction equation shows that both the feed rate
and work speed are the most important factor that influences
the surface roughness. The surface roughness was found to be
the lowers with the used of low feed rate and low work speed.
Accuracy of the best model was proved with the testing data.
Abstract: As one result of the project “Reactive Construction
Project Scheduling using Real Time Construction Logistic Data and
Simulation”, a procedure for using data about uncertain resource
availability assumptions in reactive scheduling processes has been
developed. Prediction data about resource availability is generated in
a formalized way using real-time monitoring data e.g. from auto-ID
systems on the construction site and in the supply chains. The paper
focusses on the formalization of the procedure for monitoring
construction logistic processes, for the detection of disturbance and
for generating of new and uncertain scheduling assumptions for the
reactive resource constrained simulation procedure that is and will be
further described in other papers.
Abstract: This paper discusses the effectiveness of the EEG signal
for human identification using four or less of channels of two different
types of EEG recordings. Studies have shown that the EEG signal
has biometric potential because signal varies from person to person
and impossible to replicate and steal. Data were collected from 10
male subjects while resting with eyes open and eyes closed in 5
separate sessions conducted over a course of two weeks. Features
were extracted using the wavelet packet decomposition and analyzed
to obtain the feature vectors. Subsequently, the neural networks
algorithm was used to classify the feature vectors. Results show that,
whether or not the subjects- eyes were open are insignificant for a 4–
channel biometrics system with a classification rate of 81%. However,
for a 2–channel system, the P4 channel should not be included if data
is acquired with the subjects- eyes open. It was observed that for 2–
channel system using only the C3 and C4 channels, a classification
rate of 71% was achieved.
Abstract: In this study, a software has been developed to predict
the optimum conditions for drying of cotton based yarn bobbins in a
hot air dryer. For this purpose, firstly, a suitable drying model has
been specified using experimental drying behavior for different
values of drying parameters. Drying parameters in the experiments
were drying temperature, drying pressure, and volumetric flow rate of
drying air. After obtaining a suitable drying model, additional curve
fittings have been performed to obtain equations for drying time and
energy consumption taking into account the effects of drying
parameters. Then, a software has been developed using Visual Basic
programming language to predict the optimum drying conditions for
drying time and energy consumption.