Abstract: The paper deals with the development of portable aerosol concentrator and its application for the determination of nitrites and nitrates. The device enables the continuous trapping of pollutants in the air. An extensive literature search has been elaborated which aims at the development of samplers and the possibilities of their application in the continuous determination of volatile organic compounds. The practical part of the paper is focused on the development of the portable aerosol concentrator. The device using the Aerosol Enrichment Unit has been experimentally verified and subsequently realized. It operates on the principle of equilibrium accumulation of pollutants from the gaseous phase using absorption liquid polydisperse aerosol. The device has been applied for monitoring nitrites and nitrates in the air. The chemiluminescence detector was used for detection; the achieved detection limit for nitrites was 28 ng/m3 and for nitrates 78 ng/m3.
Abstract: In this paper we introduce an effective ECG compression algorithm based on two dimensional multiwavelet transform. Multiwavelets offer simultaneous orthogonality, symmetry and short support, which is not possible with scalar two-channel wavelet systems. These features are known to be important in signal processing. Thus multiwavelet offers the possibility of superior performance for image processing applications. The SPIHT algorithm has achieved notable success in still image coding. We suggested applying SPIHT algorithm to 2-D multiwavelet transform of2-D arranged ECG signals. Experiments on selected records of ECG from MIT-BIH arrhythmia database revealed that the proposed algorithm is significantly more efficient in comparison with previously proposed ECG compression schemes.
Abstract: This paper presents a new Quality-Controlled, wavelet based, compression method for electrocardiogram (ECG) signals. Initially, an ECG signal is decomposed using the wavelet transform. Then, the resulting coefficients are iteratively thresholded to guarantee that a predefined goal percent root mean square difference (GPRD) is matched within tolerable boundaries. The quantization strategy of extracted non-zero wavelet coefficients (NZWC), according to the combination of RLE, HUFFMAN and arithmetic encoding of the NZWC and a resulting look up table, allow the accomplishment of high compression ratios with good quality reconstructed signals.
Abstract: The current-voltage characteristics of a PtSi/p-Si
Schottky barrier diode was measured at the temperature of 85 K and
from the forward bias region of the I-V curve, the electrical
parameters of the diode were measured by three methods. The results
obtained from the two methods which considered the series resistance
were in close agreement with each other and from them barrier height
(), ideality factor (n) and series resistance () were found to be
0.2045 eV, 2.877 and 14.556 K respectively. By measuring the I-V
characteristics in the temperature range of 85-136 K the electrical
parameters were observed to have strong dependency on temperature.
The increase of barrier height and decrease of ideality factor with
increasing temperature is attributed to the existence of barrier height
inhomogeneities in the silicide-semiconductor structure.
Abstract: In this work, the influence of temperature on the
different parameters of solar cells based on organic semiconductors
are studied. The short circuit current Isc increases so monotonous
with temperature and then saturates to a maximum value before
decreasing at high temperatures. The open circuit voltage Vco
decreases linearly with temperature. The fill factor FF and efficiency,
which are directly related with Isc and Vco follow the variations of
the letters. The phenomena are explained by the behaviour of the
mobility which is a temperature activated process.
Abstract: Text categorization is the problem of classifying text
documents into a set of predefined classes. After a preprocessing
step, the documents are typically represented as large sparse vectors.
When training classifiers on large collections of documents, both the
time and memory restrictions can be quite prohibitive. This justifies
the application of feature selection methods to reduce the
dimensionality of the document-representation vector. In this paper,
we present three feature selection methods: Information Gain,
Support Vector Machine feature selection called (SVM_FS) and
Genetic Algorithm with SVM (called GA_SVM). We show that the
best results were obtained with GA_SVM method for a relatively
small dimension of the feature vector.
Abstract: A novel behavioral detection framework is proposed
to detect zero day buffer overflow vulnerabilities (based on network
behavioral signatures) using zero-day exploits, instead of the
signature-based or anomaly-based detection solutions currently
available for IDPS techniques. At first we present the detection
model that uses shadow honeypot. Our system is used for the online
processing of network attacks and generating a behavior detection
profile. The detection profile represents the dataset of 112 types of
metrics describing the exact behavior of malware in the network. In
this paper we present the examples of generating behavioral
signatures for two attacks – a buffer overflow exploit on FTP server
and well known Conficker worm. We demonstrated the visualization
of important aspects by showing the differences between valid
behavior and the attacks. Based on these metrics we can detect
attacks with a very high probability of success, the process of
detection is however very expensive.
Abstract: We evaluate the average energy consumption per bit
in Optical Packet Switches equipped with BENES switching fabric
realized in Semiconductor Optical Amplifier (SOA) technology. We
also study the impact that the Amplifier Spontaneous Emission
(ASE) noise generated by a transmission system has on the power
consumption of the BENES switches due to the gain saturation of the
SOAs used to realize the switching fabric. As a matter of example for
32×32 switches supporting 64 wavelengths and offered traffic equal
to 0,8, the average energy consumption per bit is 2, 34 · 10-1 nJ/bit
and increases if ASE noise introduced by the transmission systems
is increased.
Abstract: Defect prevention is the most vital but habitually
neglected facet of software quality assurance in any project. If
functional at all stages of software development, it can condense the
time, overheads and wherewithal entailed to engineer a high quality
product. The key challenge of an IT industry is to engineer a
software product with minimum post deployment defects.
This effort is an analysis based on data obtained for five selected
projects from leading software companies of varying software
production competence. The main aim of this paper is to provide
information on various methods and practices supporting defect
detection and prevention leading to thriving software generation. The
defect prevention technique unearths 99% of defects. Inspection is
found to be an essential technique in generating ideal software
generation in factories through enhanced methodologies of abetted
and unaided inspection schedules. On an average 13 % to 15% of
inspection and 25% - 30% of testing out of whole project effort time
is required for 99% - 99.75% of defect elimination.
A comparison of the end results for the five selected projects
between the companies is also brought about throwing light on the
possibility of a particular company to position itself with an
appropriate complementary ratio of inspection testing.
Abstract: Preparation of hydrogel based on carrageenan
extracted from Kappaphycus alvarezii was conducted with film
immersion in glutaraldehyde solution (GA 4%w/w) for 2min and
then followed by thermal curing at 110°C for 25min. The method of
carrageenan recovery strongly determines the properties of
crosslinked carrageenan. Hydrogel obtained from alkali treated
carrageenan showed higher swelling ability compared to hydrogel
from nonalkali treated carrageenan. Hydrogel from alkali treated
showed the ability of sensitive to pH media.
Abstract: In the present study the efficiency of Big Bang-Big
Crunch (BB-BC) algorithm is investigated in discrete structural
design optimization. It is shown that a standard version of the BB-BC
algorithm is sometimes unable to produce reasonable solutions to
problems from discrete structural design optimization. Two
reformulations of the algorithm, which are referred to as modified
BB-BC (MBB-BC) and exponential BB-BC (EBB-BC), are
introduced to enhance the capability of the standard algorithm in
locating good solutions for steel truss and frame type structures,
respectively. The performances of the proposed algorithms are
experimented and compared to its standard version as well as some
other algorithms over several practical design examples. In these
examples, steel structures are sized for minimum weight subject to
stress, stability and displacement limitations according to the
provisions of AISC-ASD.
Abstract: Fine-grained data replication over the Internet allows duplication of frequently accessed data objects, as opposed to entire sites, to certain locations so as to improve the performance of largescale content distribution systems. In a distributed system, agents representing their sites try to maximize their own benefit since they are driven by different goals such as to minimize their communication costs, latency, etc. In this paper, we will use game theoretical techniques and in particular auctions to identify a bidding mechanism that encapsulates the selfishness of the agents, while having a controlling hand over them. In essence, the proposed game theory based mechanism is the study of what happens when independent agents act selfishly and how to control them to maximize the overall performance. A bidding mechanism asks how one can design systems so that agents- selfish behavior results in the desired system-wide goals. Experimental results reveal that this mechanism provides excellent solution quality, while maintaining fast execution time. The comparisons are recorded against some well known techniques such as greedy, branch and bound, game theoretical auctions and genetic algorithms.
Abstract: An adaptive dynamic cerebellar model articulation
controller (DCMAC) neural network used for solving the prediction
and identification problem is proposed in this paper. The proposed
DCMAC has superior capability to the conventional cerebellar model
articulation controller (CMAC) neural network in efficient learning
mechanism, guaranteed system stability and dynamic response. The
recurrent network is embedded in the DCMAC by adding feedback
connections in the association memory space so that the DCMAC
captures the dynamic response, where the feedback units act as
memory elements. The dynamic gradient descent method is adopted to
adjust DCMAC parameters on-line. Moreover, the analytical method
based on a Lyapunov function is proposed to determine the
learning-rates of DCMAC so that the variable optimal learning-rates
are derived to achieve most rapid convergence of identifying error.
Finally, the adaptive DCMAC is applied in two computer simulations.
Simulation results show that accurate identifying response and
superior dynamic performance can be obtained because of the
powerful on-line learning capability of the proposed DCMAC.
Abstract: This paper presents an algorithm for reconstructing phase and magnitude responses of the impulse response when only the output data are available. The system is driven by a zero-mean independent identically distributed (i.i.d) non-Gaussian sequence that is not observed. The additive noise is assumed to be Gaussian. This is an important and essential problem in many practical applications of various science and engineering areas such as biomedical, seismic, and speech processing signals. The method is based on evaluating the bicepstrum of the third-order statistics of the observed output data. Simulations results are presented that demonstrate the performance of this method.
Abstract: The purpose of suspension system in automobiles is to
improve the ride comfort and road handling. In this research the ride
and handling performance of a specific automobile with passive
suspension system is compared to a proposed fuzzy logic semi active
suspension system designed for that automobile. The bodysuspension-
wheel system is modeled as a two degree of freedom
quarter car model. MATLAB/SIMULINK [1] was used for
simulation and controller design. The fuzzy logic controller is based
on two inputs namely suspension velocity and body velocity. The
output of the fuzzy controller is the damping coefficient of the
variable damper. The result shows improvement over passive
suspension method.
Abstract: An electric utility-s main concern is to plan, design, operate and maintain its power supply to provide an acceptable level of reliability to its users. This clearly requires that standards of reliability be specified and used in all three sectors of the power system, i.e., generation, transmission and distribution. That is why reliability of a power system is always a major concern to power system planners. This paper presents the reliability analysis of Bangladesh Power System (BPS). Reliability index, loss of load probability (LOLP) of BPS is evaluated using recursive algorithm and considering no de-rated states of generators. BPS has sixty one generators and a total installed capacity of 5275 MW. The maximum demand of BPS is about 5000 MW. The relevant data of the generators and hourly load profiles are collected from the National Load Dispatch Center (NLDC) of Bangladesh and reliability index 'LOLP' is assessed for the period of last ten years.
Abstract: We investigate sonic cues for binaural sound localization within classrooms and present a structural model for the same. Two of the primary cues for localization, interaural time difference (ITD) and interaural level difference (ILD) created between the two ears by sounds from a particular point in space, are used. Although these cues do not lend any information about the elevation of a sound source, the torso, head, and outer ear carry out elevation dependent spectral filtering of sounds before they reach the inner ear. This effect is commonly captured in head related transfer function (HRTF) which aids in resolving the ambiguity from the ITDs and ILDs alone and helps localize sounds in free space. The proposed structural model of HRTF produces well controlled horizontal as well as vertical effects. The implemented HRTF is a signal processing model which tries to mimic the physical effects of the sounds interacting with different parts of the body. The effectiveness of the method is tested by synthesizing spatial audio, in MATLAB, for use in listening tests with human subjects and is found to yield satisfactory results in comparison with existing models.
Abstract: This paper presents results of an experimental study performed to investigate effect of incorporating silica fume on physico-mechanical properties and durability of resulting fly ash geopolymers. Geopolymer specimens were prepared by activating fly ash incorporated with additional silica fume in the range of 2.5% to 5%, with a mixture of sodium hydroxide and sodium silicate solution having Na2O content of 8%. For studying durability, 10% magnesium sulphate solution was used to immerse the specimens up to a period of 15 weeks during which visual observation, weight changes and strength changes were monitored regularly. Addition of silica fume lowers performance of geopolymer pastes. However, in mortars, addition of silica fume significantly enhanced physico-mechanical properties and durability.
Abstract: This paper presents an effective technique for harmonic current mitigation using an adaptive notch filter (ANF) to estimate current harmonics. The proposed filter consists of multiple units of ANF connected in parallel structure; each unit is governed by two ordinary differential equations. The frequency estimation is carried out based on the output of these units. The simulation and experimental results show the ability of the proposed tracking scheme to accurately estimate harmonics. The proposed filter was implemented digitally in TMS320F2808 and used in the control of hybrid active power filter (HAPF). The theoretical expectations are verified and demonstrated experimentally.
Abstract: Spatial outliers in remotely sensed imageries represent
observed quantities showing unusual values compared to their
neighbor pixel values. There have been various methods to detect the
spatial outliers based on spatial autocorrelations in statistics and data
mining. These methods may be applied in detecting forest fire pixels
in the MODIS imageries from NASA-s AQUA satellite. This is
because the forest fire detection can be referred to as finding spatial
outliers using spatial variation of brightness temperature. This point is
what distinguishes our approach from the traditional fire detection
methods. In this paper, we propose a graph-based forest fire detection
algorithm which is based on spatial outlier detection methods, and test
the proposed algorithm to evaluate its applicability. For this the
ordinary scatter plot and Moran-s scatter plot were used. In order to
evaluate the proposed algorithm, the results were compared with the
MODIS fire product provided by the NASA MODIS Science Team,
which showed the possibility of the proposed algorithm in detecting
the fire pixels.