Abstract: This paper presents a fault-tolerant implementation for
adder schemes using the dual duplication code. To prove the
efficiency of the proposed method, the circuit is simulated in double
pass transistor CMOS 32nm technology and some transient faults are
voluntary injected in the Layout of the circuit. This fully differential
implementation requires only 20 transistors which mean that the
proposed design involves 28.57% saving in transistor count
compared to standard CMOS technology.
Abstract: Energy has a prominent role for development of
nations. Countries which have energy resources also have strategic
power in the international trade of energy since it is essential for all
stages of production in the economy. Thus, it is important for
countries to analyze the weaknesses and strength of the system. On
the other side, international trade is one of the fields that are analyzed
as a complex network via network analysis. Complex network is one
of the tools to analyze complex systems with heterogeneous agents
and interaction between them. A complex network consists of nodes
and the interactions between these nodes. Total properties which
emerge as a result of these interactions are distinct from the sum of
small parts (more or less) in complex systems. Thus, standard
approaches to international trade are superficial to analyze these
systems. Network analysis provides a new approach to analyze
international trade as a network. In this network, countries constitute
nodes and trade relations (export or import) constitute edges. It
becomes possible to analyze international trade network in terms of
high degree indicators which are specific to complex networks such
as connectivity, clustering, assortativity/disassortativity, centrality,
etc. In this analysis, international trade of crude oil and coal which
are types of fossil fuel has been analyzed from 2005 to 2014 via
network analysis. First, it has been analyzed in terms of some
topological parameters such as density, transitivity, clustering etc.
Afterwards, fitness to Pareto distribution has been analyzed via
Kolmogorov-Smirnov test. Finally, weighted HITS algorithm has
been applied to the data as a centrality measure to determine the real
prominence of countries in these trade networks. Weighted HITS
algorithm is a strong tool to analyze the network by ranking countries
with regards to prominence of their trade partners. We have
calculated both an export centrality and an import centrality by
applying w-HITS algorithm to the data. As a result, impacts of the
trading countries have been presented in terms of high-degree
indicators.
Abstract: In order to retrieve images efficiently from a large
database, a unique method integrating color and texture features
using genetic programming has been proposed. Opponent color
histogram which gives shadow, shade, and light intensity invariant
property is employed in the proposed framework for extracting color
features. For texture feature extraction, fast discrete curvelet
transform which captures more orientation information at different
scales is incorporated to represent curved like edges. The recent
scenario in the issues of image retrieval is to reduce the semantic gap
between user’s preference and low level features. To address this
concern, genetic algorithm combined with relevance feedback is
embedded to reduce semantic gap and retrieve user’s preference
images. Extensive and comparative experiments have been conducted
to evaluate proposed framework for content based image retrieval on
two databases, i.e., COIL-100 and Corel-1000. Experimental results
clearly show that the proposed system surpassed other existing
systems in terms of precision and recall. The proposed work achieves
highest performance with average precision of 88.2% on COIL-100
and 76.3% on Corel, the average recall of 69.9% on COIL and 76.3%
on Corel. Thus, the experimental results confirm that the proposed
content based image retrieval system architecture attains better
solution for image retrieval.
Abstract: The introduction of a multitude of new and interactive
e-commerce information technology (IT) artifacts has impacted
adoption research. Rather than solely functioning as productivity
tools, new IT artifacts assume the roles of interaction mediators and
social actors. This paper describes the varying roles assumed by IT
artifacts, and proposes and distinguishes between four distinct foci of
how the artifacts are evaluated. It further proposes a theoretical
model that maps the different views of IT artifacts to four distinct
types of evaluations.
Abstract: In this paper, a modified Wilkinson power divider for
GSM application is presented. The quarter–wavelength microstrip
lines in the conventional Wilkinson power divider (WPD) are
replaced by one-eighth wavelength transmission line. Wilkinson
power divider is designed using λ/4 and λ/8 transmission line. It has
the operating frequency of 915 MHz which is used in the GSM
standard. The proposed Wilkinson Power Divider is designed using
the simulation tool Advanced Design System. The results of λ/8
transmission line are very close to the results of λ/4 transmission line.
The isolation loss of λ/8 transmission line is improved by introducing
a capacitor between the output ports. The proposed Wilkinson power
divider has the best return loss of greater than -10 dB and isolation
loss of -15.25 dB. The λ/8 transmission line Wilkinson power divider
has the reduced size of 53.9 percentages than λ/4 transmission line
WPD. The proposed design has simple structure, better isolation loss
and good insertion loss.
Abstract: Scripts are one of the basic text resources to understand
broadcasting contents. Topic modeling is the method to get the
summary of the broadcasting contents from its scripts. Generally,
scripts represent contents descriptively with directions and speeches,
and provide scene segments that can be seen as semantic units.
Therefore, a script can be topic modeled by treating a scene segment
as a document. Because scene segments consist of speeches mainly,
however, relatively small co-occurrences among words in the scene
segments are observed. This causes inevitably the bad quality of
topics by statistical learning method. To tackle this problem, we
propose a method to improve topic quality with additional word
co-occurrence information obtained using scene similarities. The
main idea of improving topic quality is that the information that
two or more texts are topically related can be useful to learn high
quality of topics. In addition, more accurate topical representations
lead to get information more accurate whether two texts are related
or not. In this paper, we regard two scene segments are related
if their topical similarity is high enough. We also consider that
words are co-occurred if they are in topically related scene segments
together. By iteratively inferring topics and determining semantically
neighborhood scene segments, we draw a topic space represents
broadcasting contents well. In the experiments, we showed the
proposed method generates a higher quality of topics from Korean
drama scripts than the baselines.
Abstract: This paper proposes an APPLE scheme that aims at providing absolute and proportional throughput guarantees, and maximizing system throughput simultaneously for wireless LANs with homogeneous and heterogenous traffic. We formulate our objectives as an optimization problem, present its exact and approximate solutions, and prove the existence and uniqueness of the approximate solution. Simulations validate that APPLE scheme is accurate, and the approximate solution can well achieve the desired objectives already.
Abstract: In this research, we propose to conduct diagnostic and
predictive analysis about the key factors and consequences of urban
population relocation. To achieve this goal, urban simulation models
extract the urban development trends as land use change patterns from
a variety of data sources. The results are treated as part of urban big
data with other information such as population change and economic
conditions. Multiple data mining methods are deployed on this data to
analyze nonlinear relationships between parameters. The result
determines the driving force of population relocation with respect to
urban sprawl and urban sustainability and their related parameters.
This work sets the stage for developing a comprehensive urban
simulation model for catering to specific questions by targeted users. It
contributes towards achieving sustainability as a whole.
Abstract: In this paper, an Infinite Impulse Response (IIR) filter
has been designed and simulated on an Field Programmable Gate
Arrays (FPGA). The implementation is based on Multiply Add and
Accumulate (MAC) algorithm which uses multiply operations for
design implementation. Parallel Pipelined structure is used to
implement the proposed IIR Filter taking optimal advantage of the
look up table of target device. The designed filter has been
synthesized on Digital Signal Processor (DSP) slice based FPGA to
perform multiplier function of MAC unit. The DSP slices are useful
to enhance the speed performance. The proposed design is simulated
with Matlab, synthesized with Xilinx Synthesis Tool, and
implemented on FPGA devices. The Virtex 5 FPGA based design can
operate at an estimated frequency of 81.5 MHz as compared to 40.5
MHz in case of Spartan 3 ADSP based design. The Virtex 5 based
implementation also consumes less slices and slice flip flops of target
FPGA in comparison to Spartan 3 ADSP based implementation to
provide cost effective solution for signal processing applications.
Abstract: In this paper, an approach for the liver tumor detection
in computed tomography (CT) images is represented. The detection
process is based on classifying the features of target liver cell to
either tumor or non-tumor. Fractional differential (FD) is applied for
enhancement of Liver CT images, with the aim of enhancing texture
and edge features. Later on, a fusion method is applied to merge
between the various enhanced images and produce a variety of
feature improvement, which will increase the accuracy of
classification. Each image is divided into NxN non-overlapping
blocks, to extract the desired features. Support vector machines
(SVM) classifier is trained later on a supplied dataset different from
the tested one. Finally, the block cells are identified whether they are
classified as tumor or not. Our approach is validated on a group of
patients’ CT liver tumor datasets. The experiment results
demonstrated the efficiency of detection in the proposed technique.
Abstract: In this corporate world, the technology of Web
services has grown rapidly and its significance for the development
of web based applications gradually rises over time. The success of
Business to Business integration rely on finding novel partners and
their services in a global business environment. However, the
selection of the most suitable Web service from the list of services
with the identical functionality is more vital. The satisfaction level of
the customer and the provider’s reputation of the Web service are
primarily depending on the range it reaches the customer’s
requirements. In most cases, the customer of the Web service feels
that he is spending for the service which is undelivered. This is
because the customer always thinks that the real functionality of the
web service is not reached. This will lead to change of the service
frequently. In this paper, a framework is proposed to evaluate the
Quality of Service (QoS) and its cost that makes the optimal
correlation between each other. In addition, this research work
proposes some management decision against the functional deviancy
of the web service that is guaranteed at time of selection.
Abstract: Weak damping of low frequency oscillations is a frequent phenomenon in electrical power systems. These frequencies can be damped by power system stabilizers. Unified power flow controller (UPFC), as one of the most important FACTS devices, can be applied to increase the damping of power system oscillations and the more effect of this controller on increasing the damping of oscillations depends on its proper placement in power systems. In this paper, a technique based on controllability is proposed to select proper location of UPFC and the best input control signal in order to enhance damping of power oscillations. The effectiveness of the proposed technique is demonstrated in IEEE 9 bus power system.
Abstract: In this work, by replacing the traditional solid spokes with colloidal spokes, a vehicle wheel with a built-in suspension structure is proposed. Following the background and description of the wheel system, firstly, a vibration model of the wheel equipped with colloidal spokes is proposed, and based on such model the equivalent damping coefficients and spring constants are identified. Then, a modified model of a quarter-vehicle moving on a rough pavement is proposed in order to estimate the transmissibility of vibration from the road roughness to vehicle body. In the end, the optimal design of the colloidal spokes and the optimum number of colloidal spokes are decided in order to minimize the transmissibility of vibration, i.e., to maximize the ride comfort of the vehicle.
Abstract: This paper presents the effects of mixing procedures
on mechanical properties of flyash-based geopolymer matrices
containing nanosilica (NS) at 0.5%, 1.0%, 2.0%, and 3.0% by weight.
Comparison is made with conventional mechanical dry-mixing of NS
with flyash and wet-mixing of NS in alkaline solutions. Physical and
mechanical properties are investigated using X-Ray Diffraction
(XRD) and Scanning Electron Microscope (SEM). Results show that
generally the addition of NS particles enhanced the microstructure
and improved flexural and compressive strengths of geopolymer
nanocomposites. However, samples, prepared using dry-mixing
approach, demonstrate better physical and mechanical properties
comparing to wet-mixing samples.
Abstract: This paper aims to analysis the behavior of DC corona
discharge in wire-to-plate electrostatic precipitators (ESP). Currentvoltage
curves are particularly analyzed. Experimental results show
that discharge current is strongly affected by the applied voltage. The proposed method of current identification is to use the method
of least squares. Least squares problems that of into two categories:
linear or ordinary least squares and non-linear least squares,
depending on whether or not the residuals are linear in all unknowns.
The linear least-squares problem occurs in statistical regression
analysis; it has a closed-form solution. A closed-form solution (or
closed form expression) is any formula that can be evaluated in a
finite number of standard operations. The non-linear problem has no
closed-form solution and is usually solved by iterative.
Abstract: Low density polyethylene (LDPE) nanocomposites
with 3, 5 and 7 wt. % cobalt ferrite (CoFe2O4) nanopowder fabricated
with extrusion mixing and followed up by hot press to reach compact
samples. The transmission/reflection measurements were carried out
with a network analyzer in the frequency range of 8-12 GHz. By
increasing the percent of CoFe2O4 nanopowder, reflection loss (S11)
increases, while transferring loss (S21) decreases. Reflectivity (R)
calculations made using S11 and S21. Increase in percent of CoFe2O4
nanopowder up to 7 wt. % in composite leaded to higher reflectivity
amount, and revealed that increasing the percent of CoFe2O4
nanopowder up to 7 wt. % leads to further microwave absorption in
8-12 GHz range.
Abstract: Advances in spatial and spectral resolution of satellite
images have led to tremendous growth in large image databases. The
data we acquire through satellites, radars, and sensors consists of
important geographical information that can be used for remote
sensing applications such as region planning, disaster management.
Spatial data classification and object recognition are important tasks
for many applications. However, classifying objects and identifying
them manually from images is a difficult task. Object recognition is
often considered as a classification problem, this task can be
performed using machine-learning techniques. Despite of many
machine-learning algorithms, the classification is done using
supervised classifiers such as Support Vector Machines (SVM) as the
area of interest is known. We proposed a classification method,
which considers neighboring pixels in a region for feature extraction
and it evaluates classifications precisely according to neighboring
classes for semantic interpretation of region of interest (ROI). A
dataset has been created for training and testing purpose; we
generated the attributes by considering pixel intensity values and
mean values of reflectance. We demonstrated the benefits of using
knowledge discovery and data-mining techniques, which can be on
image data for accurate information extraction and classification from
high spatial resolution remote sensing imagery.
Abstract: The acceptance of sustainable products by the final
consumer is still one of the challenges of the industry, which
constantly seeks alternative approaches to successfully be accepted in
the global market. A large set of methods and approaches have been
discussed and analysed throughout the literature. Considering the current need for sustainable development and the
current pace of consumption, the need for a combined solution
towards the development of new products became clear, forcing
researchers in product development to propose alternatives to the
previous standard product development models. This paper presents, through a systemic analysis of the literature
on product development, eco-design and consumer involvement, a set
of alternatives regarding consumer involvement towards the
development of sustainable products and how these approaches could
help improve the sustainable industry’s establishment in the general
market. Still being developed in the course of the author’s PhD, the initial
findings of the research show that the understanding of the benefits of
sustainable behaviour lead to a more conscious acquisition and
eventually to the implementation of sustainable change in the
consumer. Thus this paper is the initial approach towards the
development of new sustainable products using the fashion industry
as an example of practical implementation and acceptance by the
consumers. By comparing the existing literature and critically analysing it, this
paper concluded that the consumer involvement is strategic to
improve the general understanding of sustainability and its features.
The use of consumers and communities has been studied since the
early 90s in order to exemplify uses and to guarantee a fast
comprehension. The analysis done also includes the importance of
this approach for the increase of innovation and ground breaking
developments, thus requiring further research and practical
implementation in order to better understand the implications and
limitations of this methodology.
Abstract: Segmentation of left ventricle (LV) from cardiac
ultrasound images provides a quantitative functional analysis of the
heart to diagnose disease. Active Shape Model (ASM) is widely used
for LV segmentation, but it suffers from the drawback that
initialization of the shape model is not sufficiently close to the target,
especially when dealing with abnormal shapes in disease. In this work,
a two-step framework is improved to achieve a fast and efficient LV
segmentation. First, a robust and efficient detection based on Hough
forest localizes cardiac feature points. Such feature points are used to
predict the initial fitting of the LV shape model. Second, ASM is
applied to further fit the LV shape model to the cardiac ultrasound
image. With the robust initialization, ASM is able to achieve more
accurate segmentation. The performance of the proposed method is
evaluated on a dataset of 810 cardiac ultrasound images that are mostly
abnormal shapes. This proposed method is compared with several
combinations of ASM and existing initialization methods. Our
experiment results demonstrate that accuracy of the proposed method
for feature point detection for initialization was 40% higher than the
existing methods. Moreover, the proposed method significantly
reduces the number of necessary ASM fitting loops and thus speeds up
the whole segmentation process. Therefore, the proposed method is
able to achieve more accurate and efficient segmentation results and is
applicable to unusual shapes of heart with cardiac diseases, such as left
atrial enlargement.
Abstract: Game-based learning can enhance the learning
motivation of students and provide a means for them to learn through
playing games. This study used augmented reality technology to
develop an interactive card game as a game-based teaching aid for
delivering elementary school science course content with the aim of
enhancing student learning processes and outcomes. Through playing
the proposed card game, students can familiarize themselves with
appearance, features, and foraging behaviors of insects. The system
records the actions of students, enabling teachers to determine their
students’ learning progress. In this study, 37 students participated in an
assessment experiment and provided feedback through questionnaires.
Their responses indicated that they were significantly more motivated
to learn after playing the game, and their feedback was mostly
positive.