Abstract: Tackling emergency situations is performed based on emergency scenarios. These scenarios do not have a uniform form in the Czech Republic. They are unstructured and developed primarily in the text form. This does not allow solving emergency situations efficiently. For this reason, the paper aims at defining a Process Oriented Architecture to support and thus to improve tackling emergency situations in the Czech Republic. The innovative Process Oriented Architecture is based on the Workflow Reference Model while taking into account the options of Business Process Management Suites for the implementation of process oriented emergency scenarios. To verify the proposed architecture the Proof of Concept has been used which covers the reception of an emergency event at the district emergency operations centre. Within the particular implementation of the proposed architecture the Bonita Open Solution has been used. The architecture created in this way is suitable not only for emergency management, but also for educational purposes.
Abstract: This paper addresses the problems encountered by conventional distance relays when protecting double-circuit transmission lines. The problems arise principally as a result of the mutual coupling between the two circuits under different fault conditions; this mutual coupling is highly nonlinear in nature. An adaptive protection scheme is proposed for such lines based on application of artificial neural network (ANN). ANN has the ability to classify the nonlinear relationship between measured signals by identifying different patterns of the associated signals. One of the key points of the present work is that only current signals measured at local end have been used to detect and classify the faults in the double circuit transmission line with double end infeed. The adaptive protection scheme is tested under a specific fault type, but varying fault location, fault resistance, fault inception angle and with remote end infeed. An improved performance is experienced once the neural network is trained adequately, which performs precisely when faced with different system parameters and conditions. The entire test results clearly show that the fault is detected and classified within a quarter cycle; thus the proposed adaptive protection technique is well suited for double circuit transmission line fault detection & classification. Results of performance studies show that the proposed neural network-based module can improve the performance of conventional fault selection algorithms.
Abstract: The analysis of Acoustic Emission (AE) signal
generated from metal cutting processes has often approached
statistically. This is due to the stochastic nature of the emission
signal as a result of factors effecting the signal from its generation
through transmission and sensing. Different techniques are applied in
this manner, each of which is suitable for certain processes. In metal
cutting where the emission generated by the deformation process is
rather continuous, an appropriate method for analysing the AE signal
based on the root mean square (RMS) of the signal is often used and
is suitable for use with the conventional signal processing systems.
The aim of this paper is to set a strategy in tool failure detection in
turning processes via the statistic analysis of the AE generated from
the cutting zone. The strategy is based on the investigation of the
distribution moments of the AE signal at predetermined sampling.
The skews and kurtosis of these distributions are the key elements in
the detection. A normal (Gaussian) distribution has first been
suggested then this was eliminated due to insufficiency. The so
called Beta distribution was then considered, this has been used with
an assumed β density function and has given promising results with
regard to chipping and tool breakage detection.
Abstract: In this paper, a new BiCMOS CCII and CCCII,
capable of operate at ±0.5V and having wide dynamic range with
achieved bandwidth of 480MHz and 430MHz respectively have been
proposed. The structures have been found to be insensitive to the
threshold voltage variations. The proposed circuits are suitable for
implementation using 0.25μm BiCMOS technology. Pspice
simulations confirm the performance of the proposed structures.
Abstract: Possible advantages of technology in educational
context required the defining boundaries of formal and informal
learning. Increasing opportunity to ubiquitous learning by
technological support has revealed a question of how to discover
the potential of individuals in the spontaneous environments such as
social networks. This seems to be related with the question of what
purposes in social networks have been being used? Social networks
provide various advantages in educational context as collaboration,
knowledge sharing, common interests, active participation and
reflective thinking. As a consequence of these, the purpose of this
study is composed of proposing a new model that could determine
factors which effect adoption of social network applications for usage
in educational context. While developing a model proposal, the
existing adoption and diffusion models have been reviewed and they
are thought to be suitable on handling an original perspective instead
of using completely other diffusion or acceptance models because of
different natures of education from other organizations. In the
proposed model; social factors, perceived ease of use, perceived
usefulness and innovativeness are determined four direct constructs
that effect adoption process. Facilitating conditions, image,
subjective norms and community identity are incorporated to model
as antecedents of these direct four constructs.
Abstract: Commercial hydroxyapatite (HA) was reinforced by
adding 2, 5, and 10 wt % of 28.5%CaO-28.5%P2O5-38%Na2 O-
5%CaF2 based glass and then sintered. Although HA shows good
biocompatibility with the human body, its applications are limited to
non load-bearing areas and coatings due to its poor mechanical
properties. These mechanical properties can be improved
substantially with addition of glass ceramics by sintering. In this
study, the effects of sintering hydroxyapatite with above specified
phosphate glass additions are quantified. Each composition was
sintered over a range of temperatures. Scanning electron microscopy
and x-ray diffraction were used to characterize the microstructure and
phases of the composites. The density, microhardness, and
compressive strength were measured using Archimedes Principle,
Vickers Microhardness Tester (at 0.98 N), and Instron Universal
Testing Machine (cross speed of 0.5 mm/min) respectively. These
results were used to indicate which composition provided suitable
material for use in hard tissue replacement. Composites containing 10
wt % glass additions formed dense HA/TCP (tricalcium phosphate)
composite materials possessing good compressive strength and
hardness than HA. In-vitro bioactivity was assessed by evaluating
changes in pH and Ca2+ ion concentration of SBF-simulated body
fluid on immersion of these composites in it for two weeks.
Abstract: Pairwise testing, which requires that every
combination of valid values of each pair of system factors be covered
by at lease one test case, plays an important role in software testing
since many faults are caused by unexpected 2-way interactions among
system factors. Although meta-heuristic strategies like simulated
annealing can generally discover smaller pairwise test suite, they may
cost more time to perform search, compared with greedy algorithms.
We propose a new method, improved Extremal Optimization (EO)
based on the Bak-Sneppen (BS) model of biological evolution, for
constructing pairwise test suites and define fitness function according
to the requirement of improved EO. Experimental results show that
improved EO gives similar size of resulting pairwise test suite and
yields an 85% reduction in solution time over SA.
Abstract: Continuous-time delta-sigma analog digital converter (ADC) for radio frequency identification (RFID) complementary metal oxide semiconductor (CMOS) biosensor has been reported. This delta-sigma ADC is suitable for digital conversion of biosensor signal because of small process variation, and variable input range. As the input range of continuous-time switched current delta-sigma ADC (Dynamic range : 50 dB) can be limited by using current reference, amplification of biosensor signal is unnecessary. The input range is switched to wide input range mode or narrow input range mode by command of current reference. When the narrow input range mode, the input range becomes ± 0.8 V. The measured power consumption is 5 mW and chip area is 0.31 mm^2 using 1.2 um standard CMOS process. Additionally, automatic input range detecting system is proposed because of RFID biosensor applications.
Abstract: Gas turbine air inlet cooling is a useful method for
increasing output for regions where significant power demand and
highest electricity prices occur during the warm months. Inlet air
cooling increases the power output by taking advantage of the gas
turbine-s feature of higher mass flow rate when the compressor inlet
temperature decreases. Different methods are available for reducing
gas turbine inlet temperature. There are two basic systems currently
available for inlet cooling. The first and most cost-effective system is
evaporative cooling. Evaporative coolers make use of the evaporation
of water to reduce the gas turbine-s inlet air temperature. The second
system employs various ways to chill the inlet air. In this method, the
cooling medium flows through a heat exchanger located in the inlet
duct to remove heat from the inlet air. However, the evaporative
cooling is limited by wet-bulb temperature while the chilling can cool
the inlet air to temperatures that are lower than the wet bulb
temperature. In the present work, a thermodynamic model of a gas
turbine is built to calculate heat rate, power output and thermal
efficiency at different inlet air temperature conditions. Computational
results are compared with ISO conditions herein called "base-case".
Therefore, the two cooling methods are implemented and solved for
different inlet conditions (inlet temperature and relative humidity).
Evaporative cooler and absorption chiller systems results show that
when the ambient temperature is extremely high with low relative
humidity (requiring a large temperature reduction) the chiller is the
more suitable cooling solution. The net increment in the power output
as a function of the temperature decrease for each cooling method is
also obtained.
Abstract: The literature reports a large number of approaches for
measuring the similarity between protein sequences. Most of these
approaches estimate this similarity using alignment-based techniques
that do not necessarily yield biologically plausible results, for two
reasons.
First, for the case of non-alignable (i.e., not yet definitively aligned
and biologically approved) sequences such as multi-domain, circular
permutation and tandem repeat protein sequences, alignment-based
approaches do not succeed in producing biologically plausible results.
This is due to the nature of the alignment, which is based on the
matching of subsequences in equivalent positions, while non-alignable
proteins often have similar and conserved domains in non-equivalent
positions.
Second, the alignment-based approaches lead to similarity measures
that depend heavily on the parameters set by the user for the alignment
(e.g., gap penalties and substitution matrices). For easily alignable
protein sequences, it's possible to supply a suitable combination of
input parameters that allows such an approach to yield biologically
plausible results. However, for difficult-to-align protein sequences,
supplying different combinations of input parameters yields different
results. Such variable results create ambiguities and complicate the
similarity measurement task.
To overcome these drawbacks, this paper describes a novel and
effective approach for measuring the similarity between protein
sequences, called SAF for Substitution and Alignment Free. Without
resorting either to the alignment of protein sequences or to substitution
relations between amino acids, SAF is able to efficiently detect the
significant subsequences that best represent the intrinsic properties of
protein sequences, those underlying the chronological dependencies of
structural features and biochemical activities of protein sequences.
Moreover, by using a new efficient subsequence matching scheme,
SAF more efficiently handles protein sequences that contain similar
structural features with significant meaning in chronologically
non-equivalent positions. To show the effectiveness of SAF, extensive
experiments were performed on protein datasets from different
databases, and the results were compared with those obtained by
several mainstream algorithms.
Abstract: Despite of many scholars and practitioners recognize
the knowledge management implementation in an organizations but
insufficient attention has been paid by researchers to select suitable
knowledge portal system (KPS) selection. This study develops a
Multi Criteria Decision making model based on the fuzzy VIKOR
approach to help organizations in selecting KPS. The suitable portal
is the critical influential factors on the success of knowledge
management (KM) implementation in an organization.
Abstract: Kepsut-Dursunbey volcanic field (KDVF) is located
in NW Turkey and contains various products of the post-collisional
Neogene magmatic activity. Two distinct volcanic suites have been
recognized; the Kepsut volcanic suite (KVS) and the Dursunbey
volcanic suite (DVS). The KVS includes basaltic trachyandesitebasaltic
andesite-andesite lavas and associated pyroclastic rocks. The
DVS consists of dacite-rhyodacite lavas and extensive pumice-ash
fall and flow deposits. Petrographical features (i.e. existence of
xenocrysts, glomerocrysts, and mixing-compatible textures) and
mineral chemistry of phenocryst assemblages of both suites provide
evidence for magma mixing/AFC. Calculated crystallization
pressures and temperatures give values of 5.7–7.0 kbar and 927–982
°C for the KVS and 3.7–5.3 kbar and 783-787°C for the DVS,
indicating separate magma reservoirs and crystallization in magma
chambers at deep and mid crustal levels, respectively. These
observations support the establishment and evolution of KDVF
magma system promoted by episodic basaltic inputs which may
generate and mix with crustal melts.
Abstract: In the recent past Learning Classifier Systems have
been successfully used for data mining. Learning Classifier System
(LCS) is basically a machine learning technique which combines
evolutionary computing, reinforcement learning, supervised or
unsupervised learning and heuristics to produce adaptive systems. A
LCS learns by interacting with an environment from which it
receives feedback in the form of numerical reward. Learning is
achieved by trying to maximize the amount of reward received. All
LCSs models more or less, comprise four main components; a finite
population of condition–action rules, called classifiers; the
performance component, which governs the interaction with the
environment; the credit assignment component, which distributes the
reward received from the environment to the classifiers accountable
for the rewards obtained; the discovery component, which is
responsible for discovering better rules and improving existing ones
through a genetic algorithm. The concatenate of the production rules
in the LCS form the genotype, and therefore the GA should operate
on a population of classifier systems. This approach is known as the
'Pittsburgh' Classifier Systems. Other LCS that perform their GA at
the rule level within a population are known as 'Mitchigan' Classifier
Systems. The most predominant representation of the discovered
knowledge is the standard production rules (PRs) in the form of IF P
THEN D. The PRs, however, are unable to handle exceptions and do
not exhibit variable precision. The Censored Production Rules
(CPRs), an extension of PRs, were proposed by Michalski and
Winston that exhibit variable precision and supports an efficient
mechanism for handling exceptions. A CPR is an augmented
production rule of the form: IF P THEN D UNLESS C, where
Censor C is an exception to the rule. Such rules are employed in
situations, in which conditional statement IF P THEN D holds
frequently and the assertion C holds rarely. By using a rule of this
type we are free to ignore the exception conditions, when the
resources needed to establish its presence are tight or there is simply
no information available as to whether it holds or not. Thus, the IF P
THEN D part of CPR expresses important information, while the
UNLESS C part acts only as a switch and changes the polarity of D
to ~D. In this paper Pittsburgh style LCSs approach is used for
automated discovery of CPRs. An appropriate encoding scheme is
suggested to represent a chromosome consisting of fixed size set of
CPRs. Suitable genetic operators are designed for the set of CPRs
and individual CPRs and also appropriate fitness function is proposed
that incorporates basic constraints on CPR. Experimental results are
presented to demonstrate the performance of the proposed learning
classifier system.
Abstract: Link reliability and transmitted power are two important design constraints in wireless network design. Error control coding (ECC) is a classic approach used to increase link reliability and to lower the required transmitted power. It provides coding gain, resulting in transmitter energy savings at the cost of added decoder power consumption. But the choice of ECC is very critical in the case of wireless sensor network (WSN). Since the WSNs are energy constraint in nature, both the BER and power consumption has to be taken into count. This paper develops a step by step approach in finding suitable error control codes for WSNs. Several simulations are taken considering different error control codes and the result shows that the RS(31,21) fits both in BER and power consumption criteria.
Abstract: In recent years, scanning probe atomic force
microscopy SPM AFM has gained acceptance over a wide spectrum
of research and science applications. Most fields focuses on physical,
chemical, biological while less attention is devoted to manufacturing
and machining aspects. The purpose of the current study is to assess
the possible implementation of the SPM AFM features and its
NanoScope software in general machining applications with special
attention to the tribological aspects of cutting tool. The surface
morphology of coated and uncoated as-received carbide inserts is
examined, analyzed, and characterized through the determination of
the appropriate scanning setting, the suitable data type imaging
techniques and the most representative data analysis parameters
using the MultiMode SPM AFM in contact mode. The NanoScope
operating software is used to capture realtime three data types
images: “Height", “Deflection" and “Friction". Three scan sizes are
independently performed: 2, 6, and 12 μm with a 2.5 μm vertical
range (Z). Offline mode analysis includes the determination of three
functional topographical parameters: surface “Roughness", power
spectral density “PSD" and “Section". The 12 μm scan size in
association with “Height" imaging is found efficient to capture every
tiny features and tribological aspects of the examined surface. Also,
“Friction" analysis is found to produce a comprehensive explanation
about the lateral characteristics of the scanned surface. Configuration
of many surface defects and drawbacks has been precisely detected
and analyzed.
Abstract: In this paper, the modified optimal sliding mode control with a proposed method to design a sliding surface is presented. Because of the inability of the previous approach of the sliding mode method to design a bounded and suitable input, the new variation is proposed in the sliding manifold to obviate problems in a structural system. Although the sliding mode control is a powerful method to reject disturbances and noises, the chattering problem is not good for actuators. To decrease the chattering phenomena, the optimal control is added to the sliding mode control. Not only the proposed method can decline the intense variations in the inputs of the system but also it can produce the efficient responses respect to the sliding mode control and optimal control that are shown by performing some numerical simulations.
Abstract: The proposed system identifies the species of the wood
using the textural features present in its barks. Each species of a wood
has its own unique patterns in its bark, which enabled the proposed
system to identify it accurately. Automatic wood recognition system
has not yet been well established mainly due to lack of research in this
area and the difficulty in obtaining the wood database. In our work, a
wood recognition system has been designed based on pre-processing
techniques, feature extraction and by correlating the features of those
wood species for their classification. Texture classification is a problem
that has been studied and tested using different methods due to its
valuable usage in various pattern recognition problems, such as wood
recognition, rock classification. The most popular technique used
for the textural classification is Gray-level Co-occurrence Matrices
(GLCM). The features from the enhanced images are thus extracted
using the GLCM is correlated, which determines the classification
between the various wood species. The result thus obtained shows a
high rate of recognition accuracy proving that the techniques used in
suitable to be implemented for commercial purposes.
Abstract: Personal name matching system is the core of
essential task in national citizen database, text and web mining,
information retrieval, online library system, e-commerce and record
linkage system. It has necessitated to the all embracing research in
the vicinity of name matching. Traditional name matching methods
are suitable for English and other Latin based language. Asian
languages which have no word boundary such as Myanmar language
still requires sounds alike matching system in Unicode based
application. Hence we proposed matching algorithm to get analogous
sounds alike (phonetic) pattern that is convenient for Myanmar
character spelling. According to the nature of Myanmar character, we
consider for word boundary fragmentation, collation of character.
Thus we use pattern conversion algorithm which fabricates words in
pattern with fragmented and collated. We create the Myanmar sounds
alike phonetic group to help in the phonetic matching. The
experimental results show that fragmentation accuracy in 99.32% and
processing time in 1.72 ms.
Abstract: The hydraulic actuated excavator, being a non-linear
mobile machine, encounters many uncertainties. There are
uncertainties in the hydraulic system in addition to the uncertain
nature of the load. The simulation results obtained in this study show
that there is a need for intelligent control of such machines and in
particular interval type-2 fuzzy controller is most suitable for
minimizing the position error of a typical excavator-s bucket under
load variations. We consider the model parameter uncertainties such
as hydraulic fluid leakage and friction. These are uncertainties which
also depend up on the temperature and alter bulk modulus and
viscosity of the hydraulic fluid. Such uncertainties together with the
load variations cause chattering of the bucket position. The interval
type-2 fuzzy controller effectively eliminates the chattering and
manages to control the end-effecter (bucket) position with positional
error in the order of few millimeters.
Abstract: In this paper, a new approach for target recognition based on the Empirical mode decomposition (EMD) algorithm of Huang etal. [11] and the energy tracking operator of Teager [13]-[14] is introduced. The conjunction of these two methods is called Teager-Huang analysis. This approach is well suited for nonstationary signals analysis. The impulse response (IR) of target is first band pass filtered into subsignals (components) called Intrinsic mode functions (IMFs) with well defined Instantaneous frequency (IF) and Instantaneous amplitude (IA). Each IMF is a zero-mean AM-FM component. In second step, the energy of each IMF is tracked using the Teager energy operator (TEO). IF and IA, useful to describe the time-varying characteristics of the signal, are estimated using the Energy separation algorithm (ESA) algorithm of Maragos et al .[16]-[17]. In third step, a set of features such as skewness and kurtosis are extracted from the IF, IA and IMF energy functions. The Teager-Huang analysis is tested on set of synthetic IRs of Sonar targets with different physical characteristics (density, velocity, shape,? ). PCA is first applied to features to discriminate between manufactured and natural targets. The manufactured patterns are classified into spheres and cylinders. One hundred percent of correct recognition is achieved with twenty three echoes where sixteen IRs, used for training, are free noise and seven IRs, used for testing phase, are corrupted with white Gaussian noise.