Abstract: Microtomographic images and thin section (TS)
images were analyzed and compared against some parameters of
geological interest such as porosity and its distribution along the
samples. The results show that microtomography ( CT) analysis,
although limited by its resolution, have some interesting information
about the distribution of porosity (homogeneous or not) and can also
quantify the connected and non-connected pores, i.e., total porosity.
TS have no limitations concerning resolution, but are limited by the
experimental data available in regards to a few glass sheets for
analysis and also can give only information about the connected
pores, i.e., effective porosity. Those two methods have their own
virtues and flaws but when paired together they are able to
complement one another, making for a more reliable and complete
analysis.
Abstract: This is an applied research to propose the method for
price quotation for a contract electronics manufacturer. It has had a
precise price quoting method but such method could not quickly
provide a result as the customer required. This reduces the ability of
company to compete in this kind of business. In this case, the cause
of long time quotation process was analyzed. A lot of product
features have been demanded by customer. By checking routine
processes, it was found that high fraction of quoting time was used
for production time estimating which has effected to the
manufacturing or production cost. Then the historical data of
products including types, number of components, assembling
method, and their assembling time were used to analyze the key
components affecting to production time. The price quoting model
then was proposed. The implementation of proposed model was able
to remarkably reduce quoting time with an acceptable required
precision.
Abstract: Monitoring lightning electromagnetic pulses (sferics) and other terrestrial as well as extraterrestrial transient radiation signals is of considerable interest for practical and theoretical purposes in astro- and geophysics as well as meteorology. Managing a continuous flow of data, automation of the analysis and classification process is important. Features based on a combination of wavelet and statistical methods proved efficient for this task and serve as input into a radial basis function network that is trained to discriminate transient shapes from pulse like to wave like. We concentrate on signals in the Very Low Frequency (VLF, 3 -30 kHz) range in this paper, but the developed methods are independent of this specific choice.
Abstract: Landscape connectivity combines a description of the
physical structure of the landscape with special species- response to
that structure, which forms the theoretical background of applying
landscape connectivity principles in the practices of landscape
planning and design. In this study, a residential development project in
the southern United States was used to explore the meaning of
landscape connectivity and its application in town planning. The vast
rural landscape in the southern United States is conspicuously
characterized by the hedgerow trees or groves. The patchwork
landscape of fields surrounded by high hedgerows is a traditional and
familiar feature of the American countryside. Hedgerows are in effect
linear strips of trees, groves, or woodlands, which are often critical
habitats for wildlife and important for the visual quality of the
landscape. Based on geographic information system (GIS) and
statistical analysis (FRAGSTAT), this study attempts to quantify the
landscape connectivity characterized by hedgerows in south Alabama
where substantial areas of authentic hedgerow landscape are being
urbanized due to the ever expanding real estate industry and high
demand for new residential development. The results of this study
shed lights on how to balance the needs of new urban development and
biodiversity conservation by maintaining a higher level of landscape
connectivity, thus will inform the design intervention.
Abstract: In this paper, a two factor scheme is proposed to
generate cryptographic keys directly from biometric data, which
unlike passwords, are strongly bound to the user. Hash value of the
reference iris code is used as a cryptographic key and its length
depends only on the hash function, being independent of any other
parameter. The entropy of such keys is 94 bits, which is much higher
than any other comparable system. The most important and distinct
feature of this scheme is that it regenerates the reference iris code by
providing a genuine iris sample and the correct user password. Since
iris codes obtained from two images of the same eye are not exactly
the same, error correcting codes (Hadamard code and Reed-Solomon
code) are used to deal with the variability. The scheme proposed here
can be used to provide keys for a cryptographic system and/or for
user authentication. The performance of this system is evaluated on
two publicly available databases for iris biometrics namely CBS and
ICE databases. The operating point of the system (values of False
Acceptance Rate (FAR) and False Rejection Rate (FRR)) can be set
by properly selecting the error correction capacity (ts) of the Reed-
Solomon codes, e.g., on the ICE database, at ts = 15, FAR is 0.096%
and FRR is 0.76%.
Abstract: Automatic reading of handwritten cheque is a computationally
complex process and it plays an important role in financial
risk management. Machine vision and learning provide a viable
solution to this problem. Research effort has mostly been focused
on recognizing diverse pitches of cheques and demand drafts with an
identical outline. However most of these methods employ templatematching
to localize the pitches and such schemes could potentially
fail when applied to different types of outline maintained by the
bank. In this paper, the so-called outline problem is resolved by
a cheque information tree (CIT), which generalizes the localizing
method to extract active-region-of-entities. In addition, the weight
based density plot (WBDP) is performed to isolate text entities and
read complete pitches. Recognition is based on texture features using
neural classifiers. Legal amount is subsequently recognized by both
texture and perceptual features. A post-processing phase is invoked
to detect the incorrect readings by Type-2 grammar using the Turing
machine. The performance of the proposed system was evaluated
using cheque and demand drafts of 22 different banks. The test data
consists of a collection of 1540 leafs obtained from 10 different
account holders from each bank. Results show that this approach
can easily be deployed without significant design amendments.
Abstract: This article considers the main features of party
construction in the course of political modernization of Kazakhstan.
Along with consideration of party construction author analyzed how
the transformation of the party system was fulfilled in Kazakhstan.
Besides the basic stages in the course of party construction were
explained by the author. The statistical data is cited.
Abstract: The goal of this research is discovering the
determinants of the success or failure of external cooperation in small
and medium enterprises (SMEs). For this, a survey was given to 190
SMEs that experienced external cooperation within the last 3 years. A
logistic regression model was used to derive organizational or strategic
characteristics that significantly influence whether external
collaboration of domestic SMEs is successful or not. Results suggest
that research and development (R&D) features in general
characteristics (both idea creation and discovering market
opportunities) that focused on and emphasized indirected-market
stakeholders (such as complementary companies and affiliates) and
strategies in innovative strategic characteristics raise the probability of
successful external cooperation. This can be used meaningfully to
build a policy or strategy for inducing successful external cooperation
or to understand the innovation of SMEs.
Abstract: Feature selection study is gaining importance due to its contribution to save classification cost in terms of time and computation load. In search of essential features, one of the methods to search the features is via the decision tree. Decision tree act as an intermediate feature space inducer in order to choose essential features. In decision tree-based feature selection, some studies used decision tree as a feature ranker with a direct threshold measure, while others remain the decision tree but utilized pruning condition that act as a threshold mechanism to choose features. This paper proposed threshold measure using Manhattan Hierarchical Cluster distance to be utilized in feature ranking in order to choose relevant features as part of the feature selection process. The result is promising, and this method can be improved in the future by including test cases of a higher number of attributes.
Abstract: Personal computers draw non-sinusoidal current
with odd harmonics more significantly. Power Quality of
distribution networks is severely affected due to the flow of these
generated harmonics during the operation of electronic loads. In
this paper, mathematical modeling of odd harmonics in current like
3rd, 5th, 7th and 9th influencing the power quality has been presented.
Live signals have been captured with the help of power quality
analyzer for analysis purpose. The interesting feature is that Total
Harmonic Distortion (THD) in current decreases with the increase
of nonlinear loads has been verified theoretically. The results
obtained using mathematical expressions have been compared with
the practical results and exciting results have been found.
Abstract: In this paper, we propose a reversible watermarking
scheme based on histogram shifting (HS) to embed watermark bits
into the H.264/AVC standard videos by modifying the last nonzero
level in the context adaptive variable length coding (CAVLC) domain.
The proposed method collects all of the last nonzero coefficients (or
called last level coefficient) of 4×4 sub-macro blocks in a macro
block and utilizes predictions for the current last level from the
neighbor block-s last levels to embed watermark bits. The feature of
the proposed method is low computational and has the ability of
reversible recovery. The experimental results have demonstrated that
our proposed scheme has acceptable degradation on video quality and
output bit-rate for most test videos.
Abstract: Classification of video sequences based on their contents is a vital process for adaptation techniques. It helps decide which adaptation technique best fits the resource reduction requested by the client. In this paper we used the principal feature analysis algorithm to select a reduced subset of video features. The main idea is to select only one feature from each class based on the similarities between the features within that class. Our results showed that using this feature reduction technique the source video features can be completely omitted from future classification of video sequences.
Abstract: The use of machine vision to inspect the outcome of
surgical tasks is investigated, with the aim of incorporating this
approach in robotic surgery systems. Machine vision is a non-contact
form of inspection i.e. no part of the vision system is in direct contact
with the patient, and is therefore well suited for surgery where
sterility is an important consideration,. As a proof-of-concept, three
primary surgical tasks for a common neurosurgical procedure were
inspected using machine vision. Experiments were performed on
cadaveric pig heads to simulate the two possible outcomes i.e.
satisfactory or unsatisfactory, for tasks involved in making a burr
hole, namely incision, retraction, and drilling. We identify low level
image features to distinguish the two outcomes, as well as report on
results that validate our proposed approach. The potential of using
machine vision in a surgical environment, and the challenges that
must be addressed, are identified and discussed.
Abstract: Advent enhancements in the field of computing have
increased massive use of web based electronic documents. Current
Copyright protection laws are inadequate to prove the ownership for
electronic documents and do not provide strong features against
copying and manipulating information from the web. This has
opened many channels for securing information and significant
evolutions have been made in the area of information security.
Digital Watermarking has developed into a very dynamic area of
research and has addressed challenging issues for digital content.
Watermarking can be visible (logos or signatures) and invisible
(encoding and decoding). Many visible watermarking techniques
have been studied for text documents but there are very few for web
based text. XML files are used to trade information on the internet
and contain important information. In this paper, two invisible
watermarking techniques using Synonyms and Acronyms are
proposed for XML files to prove the intellectual ownership and to
achieve the security. Analysis is made for different attacks and
amount of capacity to be embedded in the XML file is also noticed.
A comparative analysis for capacity is also made for both methods.
The system has been implemented using C# language and all tests are
made practically to get the results.
Abstract: One major source of performance decline in speaker
recognition system is channel mismatch between training and testing.
This paper focuses on improving channel robustness of speaker
recognition system in two aspects of channel compensation technique
and channel robust features. The system is text-independent speaker
identification system based on two-stage recognition. In the aspect of
channel compensation technique, this paper applies MAP (Maximum
A Posterior Probability) channel compensation technique, which was
used in speech recognition, to speaker recognition system. In the
aspect of channel robust features, this paper introduces
pitch-dependent features and pitch-dependent speaker model for the
second stage recognition. Based on the first stage recognition to
testing speech using GMM (Gaussian Mixture Model), the system
uses GMM scores to decide if it needs to be recognized again. If it
needs to, the system selects a few speakers from all of the speakers
who participate in the first stage recognition for the second stage
recognition. For each selected speaker, the system obtains 3
pitch-dependent results from his pitch-dependent speaker model, and
then uses ANN (Artificial Neural Network) to unite the 3
pitch-dependent results and 1 GMM score for getting a fused result.
The system makes the second stage recognition based on these fused
results. The experiments show that the correct rate of two-stage
recognition system based on MAP channel compensation technique
and pitch-dependent features is 41.7% better than the baseline system
for closed-set test.
Abstract: The purpose of planned islanding is to construct a
power island during system disturbances which are commonly
formed for maintenance purpose. However, in most of the cases
island mode operation is not allowed. Therefore distributed
generators (DGs) must sense the unplanned disconnection from the
main grid. Passive technique is the most commonly used method for
this purpose. However, it needs improvement in order to identify the
islanding condition. In this paper an effective method for
identification of islanding condition based on phase space and neural
network techniques has been developed. The captured voltage
waveforms at the coupling points of DGs are processed to extract the
required features. For this purposed a method known as the phase
space techniques is used. Based on extracted features, two neural
network configuration namely radial basis function and probabilistic
neural networks are trained to recognize the waveform class.
According to the test result, the investigated technique can provide
satisfactory identification of the islanding condition in the
distribution system.
Abstract: This paper presents a new classification algorithm using colour and texture for obstacle detection. Colour information is computationally cheap to learn and process. However in many cases, colour alone does not provide enough information for classification. Texture information can improve classification performance but usually comes at an expensive cost. Our algorithm uses both colour and texture features but texture is only needed when colour is unreliable. During the training stage, texture features are learned specifically to improve the performance of a colour classifier. The algorithm learns a set of simple texture features and only the most effective features are used in the classification stage. Therefore our algorithm has a very good classification rate while is still fast enough to run on a limited computer platform. The proposed algorithm was tested with a challenging outdoor image set. Test result shows the algorithm achieves a much better trade-off between classification performance and efficiency than a typical colour classifier.
Abstract: Aspect of visual perception occupies a central position
in shaping the physical structure of a city. This paper discusses the
visual characteristics of utopian cities and their impact on the shaping
of real urban structures. Utopian examples of cities will not be
discussed in terms of social and sociological conditions, but rather
the emphasis is on urban utopias and ideal cities that have achieved
or have had potential impact on the shape of the physical structure of
Nikšić. It is a Renaissance-Baroque period with a touch of classicism.
The paper’s emphasis is on the physical dimension, not excluding the
importance of social equilibrium, studies of which are dating back to
Aristotle, Plato, Thomas More, Robert Owen, Tommaso Campanella
and others. The emphasis is on urban utopias and their impact on the
development of sustainable physical structure of a real city in the
context of visual perception. In the case of Nikšić, this paper
identifies the common features of a real city and a utopian city, as
well as criteria for sustainable urban development in the context of
visual achievement.
Abstract: Aerial and satellite images are information rich. They are also complex to analyze. For GIS systems, many features require fast and reliable extraction of roads and intersections. In this paper, we study efficient and reliable automatic extraction algorithms to address some difficult issues that are commonly seen in high resolution aerial and satellite images, nonetheless not well addressed in existing solutions, such as blurring, broken or missing road boundaries, lack of road profiles, heavy shadows, and interfering surrounding objects. The new scheme is based on a new method, namely reference circle, to properly identify the pixels that belong to the same road and use this information to recover the whole road network. This feature is invariable to the shape and direction of roads and tolerates heavy noise and disturbances. Road extraction based on reference circles is much more noise tolerant and flexible than the previous edge-detection based algorithms. The scheme is able to extract roads reliably from images with complex contents and heavy obstructions, such as the high resolution aerial/satellite images available from Google maps.
Abstract: Currently electronic slide (e-slide) is one of the most common styles in educational presentation. Unfortunately, the utilization of e-slide for the visually impaired is uncommon since they are unable to see the content of such e-slides which are usually composed of text, images and animation. This paper proposes a model for presenting e-slide in multimodal presentation i.e. using conventional slide concurrent with voicing, in both languages Malay and English. At the design level, live multimedia presentation concept is used, while at the implementation level several components are used. The text content of each slide is extracted using COM component, Microsoft Speech API for voicing the text in English language and the text in Malay language is voiced using dictionary approach. To support the accessibility, an auditory user interface is provided as an additional feature. A prototype of such model named as VSlide has been developed and introduced.