Abstract: In syntactic pattern recognition a pattern can be
represented by a graph. Given an unknown pattern represented by
a graph g, the problem of recognition is to determine if the graph g
belongs to a language L(G) generated by a graph grammar G. The
so-called IE graphs have been defined in [1] for a description of
patterns. The IE graphs are generated by so-called ETPL(k) graph
grammars defined in [1]. An efficient, parsing algorithm for ETPL(k)
graph grammars for syntactic recognition of patterns represented by
IE graphs has been presented in [1]. In practice, structural
descriptions may contain pattern distortions, so that the assignment
of a graph g, representing an unknown pattern, to
a graph language L(G) generated by an ETPL(k) graph grammar G is
rejected by the ETPL(k) type parsing. Therefore, there is a need for
constructing effective parsing algorithms for recognition of distorted
patterns. The purpose of this paper is to present a new approach to
syntactic recognition of distorted patterns. To take into account all
variations of a distorted pattern under study, a probabilistic
description of the pattern is needed. A random IE graph approach is
proposed here for such a description ([2]).
Abstract: In this paper we propose a novel Run Time Interface
(RTI) technique to provide an efficient environment for MPI jobs on
the heterogeneous architecture of PARAM Padma. It suggests an
innovative, unified framework for the job management interface
system in parallel and distributed computing. This approach employs
proxy scheme. The implementation shows that the proposed RTI is
highly scalable and stable. Moreover RTI provides the storage access
for the MPI jobs in various operating system platforms and improve
the data access performance through high performance C-DAC
Parallel File System (C-PFS). The performance of the RTI is
evaluated by using the standard HPC benchmark suites and the
simulation results show that the proposed RTI gives good
performance on large scale supercomputing system.
Abstract: This paper presents a wavelet transform and Support
Vector Machine (SVM) based algorithm for estimating fault location
on transmission lines. The Discrete wavelet transform (DWT) is used
for data pre-processing and this data are used for training and testing
SVM. Five types of mother wavelet are used for signal processing to
identify a suitable wavelet family that is more appropriate for use in
estimating fault location. The results demonstrated the ability of SVM
to generalize the situation from the provided patterns and to
accurately estimate the location of faults with varying fault resistance.
Abstract: Modeling of complex dynamic systems, which are
very complicated to establish mathematical models, requires new and
modern methodologies that will exploit the existing expert
knowledge, human experience and historical data. Fuzzy cognitive
maps are very suitable, simple, and powerful tools for simulation and
analysis of these kinds of dynamic systems. However, human experts
are subjective and can handle only relatively simple fuzzy cognitive
maps; therefore, there is a need of developing new approaches for an
automated generation of fuzzy cognitive maps using historical data.
In this study, a new learning algorithm, which is called Big Bang-Big
Crunch, is proposed for the first time in literature for an automated
generation of fuzzy cognitive maps from data. Two real-world
examples; namely a process control system and radiation therapy
process, and one synthetic model are used to emphasize the
effectiveness and usefulness of the proposed methodology.
Abstract: This paper presents a distributed intrusion
detection system IDS, based on the concept of specialized
distributed agents community representing agents with the
same purpose for detecting distributed attacks. The semantic of
intrusion events occurring in a predetermined network has been
defined. The correlation rules referring the process which our
proposed IDS combines the captured events that is distributed
both spatially and temporally. And then the proposed IDS tries
to extract significant and broad patterns for set of well-known
attacks. The primary goal of our work is to provide intrusion
detection and real-time prevention capability against insider
attacks in distributed and fully automated environments.
Abstract: Efficient modulo 2n+1 adders are important for
several applications including residue number system, digital signal
processors and cryptography algorithms. In this paper we present a
novel modulo 2n+1 addition algorithm for a recently represented
number system. The proposed approach is introduced for the
reduction of the power dissipated. In a conventional modulo 2n+1
adder, all operands have (n+1)-bit length. To avoid using (n+1)-bit
circuits, the diminished-1 and carry save diminished-1 number
systems can be effectively used in applications. In the paper, we also
derive two new architectures for designing modulo 2n+1 adder, based
on n-bit ripple-carry adder. The first architecture is a faster design
whereas the second one uses less hardware. In the proposed method,
the special treatment required for zero operands in Diminished-1
number system is removed. In the fastest modulo 2n+1 adders in
normal binary system, there are 3-operand adders. This problem is
also resolved in this paper. The proposed architectures are compared
with some efficient adders based on ripple-carry adder and highspeed
adder. It is shown that the hardware overhead and power
consumption will be reduced. As well as power reduction, in some
cases, power-delay product will be also reduced.
Abstract: The aim of the present study was to analyze and
distinguish playing pattern between winning and losing field hockey
team in Delhi 2012 tournament. The playing pattern is focus to the D
penetration (right, center, left.) and to distinguish D penetration
linking to end shot made from it. The data was recorded and analyzed
using Sportscode elite computer software. 12 matches were analyzed
from the tournament. Two groups of performance indicators are used
to analyze, that is D penetration right, center, and left. The type of
shot chosen is hit, push, flick, drag, drag flick, deflect sweep, deflect
push, scoop, sweep, and reverse hit. This is to distinguish the pattern
of play between winning and losing, only 2 performance indicator
showed high significant differences from right (Z=-2.87, p=.004,
p
Abstract: Text similarity measurement is a fundamental issue in
many textual applications such as document clustering, classification,
summarization and question answering. However, prevailing approaches
based on Vector Space Model (VSM) more or less suffer
from the limitation of Bag of Words (BOW), which ignores the semantic
relationship among words. Enriching document representation
with background knowledge from Wikipedia is proven to be an effective
way to solve this problem, but most existing methods still
cannot avoid similar flaws of BOW in a new vector space. In this
paper, we propose a novel text similarity measurement which goes
beyond VSM and can find semantic affinity between documents.
Specifically, it is a unified graph model that exploits Wikipedia as
background knowledge and synthesizes both document representation
and similarity computation. The experimental results on two different
datasets show that our approach significantly improves VSM-based
methods in both text clustering and classification.
Abstract: Customer-supplier collaboration enables firms to
achieve greater success than acting independently. Nevertheless, not
many firms have fully utilized the potential of collaboration. This
paper presents organizational and human related success factors for
collaboration in manufacturing supply chains in casting industry. Our
research approach was a case study including multiple cases. Data
was gathered by interviews and group discussions in two different
research projects. In the first research project we studied seven firms
and in the second five. It was found that the success factors are
interrelated, in other words, organizational and human factors
together enable success but not any of them alone. Some of the found
success factors are a culture of following agreements, and a speed of
informing the partner about changes affecting to the product or the
delivery chain.
Abstract: This paper examines economic and Information and Communication Technology (ICT) development influence on recently increasing Internet purchases by individuals for European Union member states. After a growing trend for Internet purchases in EU27 was noticed, all possible regression analysis was applied using nine independent variables in 2011. Finally, two linear regression models were studied in detail. Conducted simple linear regression analysis confirmed the research hypothesis that the Internet purchases in analyzed EU countries is positively correlated with statistically significant variable Gross Domestic Product per capita (GDPpc). Also, analyzed multiple linear regression model with four regressors, showing ICT development level, indicates that ICT development is crucial for explaining the Internet purchases by individuals, confirming the research hypothesis.
Abstract: A variety of new technology-based services have
emerged with the development of Information and Communication
Technologies (ICTs). Since technology-based services have technology-driven characteristics, the identification of relationships
between technology-based services and ICTs would give meaningful implications. Thus, this paper proposes an approach for identifying the
relationships between technology-based services and ICTs by
analyzing patent documents. First, business model (BM) patents are
classified into relevant service categories. Second, patent citation
analysis is conducted to investigate the technological linkage and impacts between technology-based services and ICTs at macro level.
Third, as a micro level analysis, patent co-classification analysis is
employed to identify the technological linkage and coverage. The
proposed approach could guide and help managers and designers of
technology-based services to discover the opportunity of the development of new technology-based services in emerging service sectors.
Abstract: One of the biggest problems of SMEs is their tendencies to financial distress because of insufficient finance background. In this study, an Early Warning System (EWS) model based on data mining for financial risk detection is presented. CHAID algorithm has been used for development of the EWS. Developed EWS can be served like a tailor made financial advisor in decision making process of the firms with its automated nature to the ones who have inadequate financial background. Besides, an application of the model implemented which covered 7,853 SMEs based on Turkish Central Bank (TCB) 2007 data. By using EWS model, 31 risk profiles, 15 risk indicators, 2 early warning signals, and 4 financial road maps has been determined for financial risk mitigation.
Abstract: Cryo-electron microscopy (CEM) in combination with
single particle analysis (SPA) is a widely used technique for
elucidating structural details of macromolecular assemblies at closeto-
atomic resolutions. However, development of automated software
for SPA processing is still vital since thousands to millions of
individual particle images need to be processed. Here, we present our
workflow for automated particle picking. Our approach integrates
peak shape analysis to the classical correlation and an iterative
approach to separate macromolecules and background by
classification. This particle selection workflow furthermore provides
a robust means for SPA with little user interaction. Processing
simulated and experimental data assesses performance of the
presented tools.
Abstract: Efficient storage, transmission and use of video information are key requirements in many multimedia applications currently being addressed by MPEG-4. To fulfill these requirements, a new approach for representing video information which relies on an object-based representation, has been adopted. Therefore, objectbased watermarking schemes are needed for copyright protection. This paper proposes a novel blind object watermarking scheme for images and video using the in place lifting shape adaptive-discrete wavelet transform (SA-DWT). In order to make the watermark robust and transparent, the watermark is embedded in the average of wavelet blocks using the visual model based on the human visual system. Wavelet coefficients n least significant bits (LSBs) are adjusted in concert with the average. Simulation results shows that the proposed watermarking scheme is perceptually invisible and robust against many attacks such as lossy image/video compression (e.g. JPEG, JPEG2000 and MPEG-4), scaling, adding noise, filtering, etc.
Abstract: Mobile agents are a powerful approach to develop distributed systems since they migrate to hosts on which they have the resources to execute individual tasks. In a dynamic environment like a peer-to-peer network, Agents have to be generated frequently and dispatched to the network. Thus they will certainly consume a certain amount of bandwidth of each link in the network if there are too many agents migration through one or several links at the same time, they will introduce too much transferring overhead to the links eventually, these links will be busy and indirectly block the network traffic, therefore, there is a need of developing routing algorithms that consider about traffic load. In this paper we seek to create cooperation between a probabilistic manner according to the quality measure of the network traffic situation and the agent's migration decision making to the next hop based on decision tree learning algorithms.
Abstract: Does a communication modality matter in delivering e-learning information? With the recent growth of broadcasting systems, media technologies and e-learning contents, various systems with different communication modalities have been introduced. In accordance with these trends, this study examines the effects of the information delivery modality on psychology of students. Findings from an experiment indicated that the delivering information which includes a video modality elicited higher degrees of credibility, quality, representativeness of content, and perceived suitability for delivering information than those of auditory information. However, there is no difference between content liking and attitude. The Implications of the findings and the limitations are discussed.
Abstract: Genome profiling (GP), a genotype based technology, which exploits random PCR and temperature gradient gel electrophoresis, has been successful in identification/classification of organisms. In this technology, spiddos (Species identification dots) and PaSS (Pattern similarity score) were employed for measuring the closeness (or distance) between genomes. Based on the closeness (PaSS), we can buildup phylogenetic trees of the organisms. We noticed that the topology of the tree is rather robust against the experimental fluctuation conveyed by spiddos. This fact was confirmed quantitatively in this study by computer-simulation, providing the limit of the reliability of this highly powerful methodology. As a result, we could demonstrate the effectiveness of the GP approach for identification/classification of organisms.
Abstract: Power system stabilizers (PSS) must be capable of providing appropriate stabilization signals over a broad range of
operating conditions and disturbance. Traditional PSS rely on robust
linear design method in an attempt to cover a wider range of operating
condition. Expert or rule-based controllers have also been proposed.
Recently fuzzy logic (FL) as a novel robust control
design method has shown promising results. The emphasis in fuzzy
control design center is around uncertainties in the system parameters
& operating conditions. In this paper a novel Robust Fuzzy Logic Power
System Stabilizer (RFLPSS) design is proposed The RFLPSS
basically utilizes only one measurable Δω signal as input
(generator shaft speed).
The speed signal is discretized resulting in three inputs to the
RFLPSS. There are six rules for the fuzzification and two rules for
defuzzification. To provide robustness, additional signal namely,
speed are used as inputs to RFLPSS enabling appropriate gain
adjustments for the three RFLPSS inputs. Simulation studies
show the superior performance of the RFLPSS compared
with an optimally designed conventional PSS and discrete mode FLPSS.
Abstract: Digital Video Terrestrial Broadcasting (DVB-T)
allows combining broadcasting, telephone and data services in one
network. It has facilitated mobile TV broadcasting. Mobile TV
broadcasting is dominated by fragmentation of standards in use in
different continents. In Asia T-DMB and ISDB-T are used while
Europe uses mainly DVB-H and in USA it is MediaFLO. Issues of
royalty for developers of these different incompatible technologies,
investments made and differing local conditions shall make it
difficult to agree on a unified standard in a very near future. Despite
this shortcoming, mobile TV has shown very good market potential.
There are a number of challenges that still exist for regulators,
investors and technology developers but the future looks bright.
There is need for mobile telephone operators to cooperate with
content providers and those operating terrestrial digital broadcasting
infrastructure for mutual benefit.
Abstract: By systematically applying different engineering
methods, difficult financial problems become approachable. Using a
combination of theory and techniques such as wavelet transform,
time series data mining, Markov chain based discrete stochastic
optimization, and evolutionary algorithms, this work formulated a
strategy to characterize and forecast non-linear time series. It
attempted to extract typical features from the volatility data sets of
S&P100 and S&P500 indices that include abrupt drops, jumps and
other non-linearity. As a result, accuracy of forecasting has reached
an average of over 75% surpassing any other publicly available
results on the forecast of any financial index.