Abstract: This article presents the results using a parametric approach and a Wavelet Transform in analysing signals emitting from the sperm whale. The extraction of intrinsic characteristics of these unique signals emitted by marine mammals is still at present a difficult exercise for various reasons: firstly, it concerns non-stationary signals, and secondly, these signals are obstructed by interfering background noise. In this article, we compare the advantages and disadvantages of both methods: Auto Regressive models and Wavelet Transform. These approaches serve as an alternative to the commonly used estimators which are based on the Fourier Transform for which the hypotheses necessary for its application are in certain cases, not sufficiently proven. These modern approaches provide effective results particularly for the periodic tracking of the signal's characteristics and notably when the signal-to-noise ratio negatively effects signal tracking. Our objectives are twofold. Our first goal is to identify the animal through its acoustic signature. This includes recognition of the marine mammal species and ultimately of the individual animal (within the species). The second is much more ambitious and directly involves the intervention of cetologists to study the sounds emitted by marine mammals in an effort to characterize their behaviour. We are working on an approach based on the recordings of marine mammal signals and the findings from this data result from the Wavelet Transform. This article will explore the reasons for using this approach. In addition, thanks to the use of new processors, these algorithms once heavy in calculation time can be integrated in a real-time system.
Abstract: Developing a supply chain management (SCM) system is costly, but important. However, because of its complicated nature, not many of such projects are considered successful. Few research publications directly relate to key success factors (KSFs) for implementing a SCM system. Motivated by the above, this research proposes a hierarchy of KSFs for SCM system implementation in the semiconductor industry by using a two-step approach. First, the literature review indicates the initial hierarchy. The second step includes a focus group approach to finalize the proposed KSF hierarchy by extracting valuable experiences from executives and managers that actively participated in a project, which successfully establish a seamless SCM integration between the world's largest semiconductor foundry manufacturing company and the world's largest assembly and testing company. Future project executives may refer the resulting KSF hierarchy as a checklist for SCM system implementation in semiconductor or related industries.
Abstract: It has been always observed that the effectiveness of
MIS as a support tool for management decisions degenerate after
time of implementation, despite the substantial investments being
made. This is true for organizations at the initial stages of MIS
implementations, manual or computerized. A survey of a sample of
middle to top managers in business and government institutions was
made. A large ratio indicates that the MIS has lost its impact on the
day-to-day operations, and even the response lag time expands
sometimes indefinitely. The data indicates an infant mortality
phenomenon of the bathtub model. Reasons may be monotonous
nature of MIS delivery, irrelevance, irreverence, timeliness, and lack
of adequate detail. All those reasons collaborate to create a degree of
degeneracy. We investigate and model as a bathtub model the
phenomenon of MIS degeneracy that inflicts the MIS systems and
renders it ineffective. A degeneracy index is developed to identify
the status of the MIS system and possible remedies to prevent the
onset of total collapse of the system to the point of being useless.
Abstract: A nonlinear optimal controller with a fuzzy gain
scheduler has been designed and applied to a Line-Of-Sight (LOS)
stabilization system. Use of Linear Quadratic Regulator (LQR)
theory is an optimal and simple manner of solving many control
engineering problems. However, this method cannot be utilized
directly for multigimbal LOS systems since they are nonlinear in
nature. To adapt LQ controllers to nonlinear systems at least a
linearization of the model plant is required. When the linearized
model is only valid within the vicinity of an operating point a gain
scheduler is required. Therefore, a Takagi-Sugeno Fuzzy Inference
System gain scheduler has been implemented, which keeps the
asymptotic stability performance provided by the optimal feedback
gain approach. The simulation results illustrate that the proposed
controller is capable of overcoming disturbances and maintaining a
satisfactory tracking performance.
Abstract: all of religions free towards society in Kazakhstan. Considering that Islam is more widespread religion in the region, Islamic industry is developing sector of Economy. There are some new sectors of Halal (Islamic) industry, which have importance for state developing on the whole. One of the youngest sectors of Halal industry is Islamic tourism, which became an object of disputes and led to dilemma, such as Islamic tourism is a result of a Religious revival and Islamic tourism is a new trend of Tourism. The paper was written under the research project “Islam in modern Kazakhstan: the nature and outcome of the religious revival".
Abstract: Despite the relatively large number of studies that
have examined the use of appeals in advertisements, research on the
use of appeals in green advertisements is still underdeveloped and
needs to be investigated further, as it is definitely a tool for marketers
to create illustrious ads. In this study, content analysis was employed
to examine the nature of green advertising appeals and to match the
appeals with the green advertisements. Two different types of green
print advertisings, product orientation and organizational image
orientation were used. Thirty highly educated participants with
different backgrounds were asked individually to ascertain three
appeals out of thirty-four given appeals found among forty real green
advertisements. To analyze participant responses and to group them
based on common appeals, two-step K-mean clustering is used. The
clustering solution indicates that eye-catching graphics and
imaginative appeals are highly notable in both types of green ads.
Depressed, meaningful and sad appeals are found to be highly used in
organizational image orientation ads, whereas, corporate image,
informative and natural appeals are found to be essential for product
orientation ads.
Abstract: In a competitive energy market, system reliability
should be maintained at all times. Power system operation being of
online in nature, the energy balance requirements must be satisfied to
ensure reliable operation the system. To achieve this, information
regarding the expected status of the system, the scheduled
transactions and the relevant inputs necessary to make either a
transaction contract or a transmission contract operational, have to be
made available in real time. The real time procedure proposed,
facilitates this. This paper proposes a quadratic curve learning
procedure, which enables a generator-s contribution to the retailer
demand, power loss of transaction in a line at the retail end and its
associated losses for an oncoming operating scenario to be predicted.
Matlab program was used to test in on a 24-bus IEE Reliability Test
System, and the results are found to be acceptable.
Abstract: A design flow of multi-standard down-conversion
CMOS mixers for three modern standards: Global System Mobile,
Digital Enhanced Cordless Telephone and Universal Mobile
Telecommunication Systems is presented. Three active mixer-s
structures are studied. The first is based on the Gilbert cell which
gives a tolerable noise figure and linearity with a low conversion
gain. The second and third structures use the current bleeding and
charge injection techniques in order to increase the conversion gain.
An improvement of about 2 dB of the conversion gain is achieved
without a considerable degradation of the other characteristics. The
models used for noise figure, conversion gain and IIP3 used are
studied. This study describes the nature of trade-offs inherent in such
structures and gives insights that help in identifying which structure
is better for given conditions.
Abstract: The leisure boatbuilding industry has tight profit margins that demand that boats are created to a high quality but with low cost. This requirement means reduced design times combined with increased use of design for production can lead to large benefits. The evolutionary nature of the boatbuilding industry can lead to a large usage of previous vessels in new designs. With the increase in automated tools for concurrent engineering within structural design it is important that these tools can reuse this information while subsequently feeding this to designers. The ability to accurately gather this materials and parts data is also a key component to these tools. This paper therefore aims to develop an architecture made up of neural networks and databases to feed information effectively to the designers based on previous design experience.
Abstract: In this paper we developed the Improved Runge-Kutta Nystrom (IRKN) method for solving second order ordinary differential equations. The methods are two step in nature and require lower number of function evaluations per step compared with the existing Runge-Kutta Nystrom (RKN) methods. Therefore, the methods are computationally more efficient at achieving the higher order of local accuracy. Algebraic order conditions of the method are obtained and the third and fourth order method are derived with two and three stages respectively. The numerical results are given to illustrate the efficiency of the proposed method compared to the existing RKN methods.
Abstract: In this study, we introduced a communication system
where human body was used as medium through which data were
transferred. Multiple biosignal sensing units were attached to a subject
and wireless personal area network was formed. Data of the sensing
units were shared among them. We used wideband pulse
communication that was simple, low-power consuming and high data
rated. Each unit functioned as independent communication device or
node. A method of channel search and communication among the
modes was developed. A protocol of carrier sense multiple
access/collision detect was implemented in order to avoid data
collision or interferences. Biosignal sensing units should be located at
different locations due to the nature of biosignal origin. Our research
provided a flexibility of collecting data without using electrical wires.
More non-constrained measurement was accomplished which was
more suitable for u-Health monitoring.
Abstract: With the widespread growth of applications of
Wireless Sensor Networks (WSNs), the need for reliable security
mechanisms these networks has increased manifold. Many security
solutions have been proposed in the domain of WSN so far. These
solutions are usually based on well-known cryptographic
algorithms.
In this paper, we have made an effort to survey well known
security issues in WSNs and study the behavior of WSN nodes that
perform public key cryptographic operations. We evaluate time
and power consumption of public key cryptography algorithm for
signature and key management by simulation.
Abstract: Computer worm detection is commonly performed by
antivirus software tools that rely on prior explicit knowledge of the
worm-s code (detection based on code signatures). We present an
approach for detection of the presence of computer worms based on
Artificial Neural Networks (ANN) using the computer's behavioral
measures. Identification of significant features, which describe the
activity of a worm within a host, is commonly acquired from security
experts. We suggest acquiring these features by applying feature
selection methods. We compare three different feature selection
techniques for the dimensionality reduction and identification of the
most prominent features to capture efficiently the computer behavior
in the context of worm activity. Additionally, we explore three
different temporal representation techniques for the most prominent
features. In order to evaluate the different techniques, several
computers were infected with five different worms and 323 different
features of the infected computers were measured. We evaluated
each technique by preprocessing the dataset according to each one
and training the ANN model with the preprocessed data. We then
evaluated the ability of the model to detect the presence of a new
computer worm, in particular, during heavy user activity on the
infected computers.
Abstract: A dynamic risk management framework for software
projects is presented. Currently available software risk management
frameworks and risk assessment models are static in nature and lacks
feedback capability. Such risk management frameworks are not
capable of providing the risk assessment of futuristic changes in risk
events. A dynamic risk management framework for software project
is needed that provides futuristic assessment of risk events.
Abstract: Drinking water is one of the most valuable resources
available to mankind. The presence of pathogens in drinking water is
highly undesirable. Because of the Lateritic soil, the iron
concentrations were high in ground water. High concentration of iron
and other trace elements could restrict bacterial growth and modify
their metabolic pattern as well. The bacterial growth rate reduced in
the presence of iron in water. This paper presents the results of a
controlled laboratory study conducted to assess the inhibition of
micro-organism (pathogen) in well waters in the presence of
dissolved iron concentrations. Synthetic samples were studied in the
laboratory and the results compared with field samples. Predictive
model for microbial inhibition in the presence of iron is presented. It
was seen that the bore wells, open wells and the field results varied,
probably due to the nature of micro-organism utilizing the iron in
well waters.
Abstract: Diffuse viral encephalitis may lack fever and other cardinal signs of infection and hence its distinction from other acute encephalopathic illnesses is challenging. Often, the EEG changes seen routinely are nonspecific and reflect diffuse encephalopathic changes only. The aim of this study was to use nonlinear dynamic mathematical techniques for analyzing the EEG data in order to look for any characteristic diagnostic patterns in diffuse forms of encephalitis.It was diagnosed on clinical, imaging and cerebrospinal fluid criteria in three young male patients. Metabolic and toxic encephalopathies were ruled out through appropriate investigations. Digital EEGs were done on the 3rd to 5th day of onset. The digital EEGs of 5 male and 5 female age and sex matched healthy volunteers served as controls.Two sample t-test indicated that there was no statistically significant difference between the average values in amplitude between the two groups. However, the standard deviation (or variance) of the EEG signals at FP1-F7 and FP2-F8 are significantly higher for the patients than the normal subjects. The regularisation dimension is significantly less for the patients (average between 1.24-1.43) when compared to the normal persons (average between 1.41-1.63) for the EEG signals from all locations except for the Fz-Cz signal. Similarly the wavelet dimension is significantly less (P = 0.05*) for the patients (1.122) when compared to the normal person (1.458). EEGs are subdued in the case of the patients with presence of uniform patterns, manifested in the values of regularisation and wavelet dimensions, when compared to the normal person, indicating a decrease in chaotic nature.
Abstract: The Major Depressive Disorder has been a burden of
medical expense in Taiwan as well as the situation around the world.
Major Depressive Disorder can be defined into different categories by
previous human activities. According to machine learning, we can
classify emotion in correct textual language in advance. It can help
medical diagnosis to recognize the variance in Major Depressive
Disorder automatically. Association language incremental is the
characteristic and relationship that can discovery words in sentence.
There is an overlapping-category problem for classification. In this
paper, we would like to improve the performance in classification in
principle of no overlapping-category problems. We present an
approach that to discovery words in sentence and it can find in high
frequency in the same time and can-t overlap in each category, called
Association Language Features by its Category (ALFC).
Experimental results show that ALFC distinguish well in Major
Depressive Disorder and have better performance. We also compare
the approach with baseline and mutual information that use single
words alone or correlation measure.
Abstract: There are two common methodologies to verify
signatures: the functional approach and the parametric approach. This
paper presents a new approach for dynamic handwritten signature
verification (HSV) using the Neural Network with verification by the
Conjugate Gradient Neural Network (NN). It is yet another avenue in
the approach to HSV that is found to produce excellent results when
compared with other methods of dynamic. Experimental results show
the system is insensitive to the order of base-classifiers and gets a
high verification ratio.
Abstract: Crime is a major societal problem for most of the
world's nations. Consequently, the police need to develop new
methods to improve their efficiency in dealing with these ever increasing crime rates. Two of the common difficulties that the police
face in crime control are crime investigation and the provision of crime information to the general public to help them protect themselves. Crime control in police operations involves the use of
spatial data, crime data and the related crime data from different organizations (depending on the nature of the analysis to be made).
These types of data are collected from several heterogeneous sources
in different formats and from different platforms, resulting in a lack of standardization. Moreover, there is no standard framework for
crime data collection, integration and dissemination through mobile
devices. An investigation into the current situation in crime control was carried out to identify the needs to resolve these issues. This
paper proposes and investigates the use of service oriented
architecture (SOA) and the mobile spatial information service in crime control. SOA plays an important role in crime control as an
appropriate way to support data exchange and model sharing from
heterogeneous sources. Crime control also needs to facilitate mobile
spatial information services in order to exchange, receive, share and release information based on location to mobile users anytime and
anywhere.
Abstract: The data exchanged on the Web are of different nature
from those treated by the classical database management systems;
these data are called semi-structured data since they do not have a
regular and static structure like data found in a relational database;
their schema is dynamic and may contain missing data or types.
Therefore, the needs for developing further techniques and
algorithms to exploit and integrate such data, and extract relevant
information for the user have been raised. In this paper we present
the system OSIX (Osiris based System for Integration of XML
Sources). This system has a Data Warehouse model designed for the
integration of semi-structured data and more precisely for the
integration of XML documents. The architecture of OSIX relies on
the Osiris system, a DL-based model designed for the representation
and management of databases and knowledge bases. Osiris is a viewbased
data model whose indexing system supports semantic query
optimization. We show that the problem of query processing on a
XML source is optimized by the indexing approach proposed by
Osiris.