Abstract: In countries with hot climates, air-conditioning forms
a large proportion of annual peak electrical demand, requiring
expansion of power plants to meet the peak demand, which goes
unused most of the time. Use of well-designed cool storage can offset
the peak demand to a large extent. In this study, an air conditioning
system with naturally stratified storage tank was designed,
constructed and tested. A new type of diffuser was designed and used
in this study. Factors that influence the performance of chilled water
storage tanks were investigated. The results indicated that stratified
storage tank consistently stratified well without any physical barrier.
Investigation also showed that storage efficiency decreased with
increasing flow rate due to increased mixing of warm and chilled
water. Diffuser design and layout primarily affected the mixing near
the inlet diffuser and the extent of this mixing had primary influence
on the shape of the thermocline. The heat conduction through tank
walls and through the thermocline caused widening of mixed volume.
Thermal efficiency of stratified storage tanks was as high as 90
percent, which indicates that stratified tanks can effectively be used
as a load management technique.
Abstract: Partial coherence between two signals removing the contribution of a periodic, deterministic signal is proposed for evaluating the interrelationship in multivariate systems. The estimator expression was derived and shown to be independent of such periodic signal. Simulations were used for obtaining its critical value, which were found to be the same as those for Gaussian signals, as well as for evaluating the technique. An Illustration with eletroencephalografic (EEG) signals during photic stimulation is also provided. The application of the proposed technique in both simulation and real EEG data indicate that it seems to be very specific in removing the contribution of periodic sources. The estimate independence of the periodic signal may widen partial coherence application to signal analysis, since it could be used together with simple coherence to test for contamination in signals by a common, periodic noise source.
Abstract: In this paper we propose a Particle Swarm heuristic
optimized Multi-Antenna (MA) system. Efficient MA systems
detection is performed using a robust stochastic evolutionary
computation algorithm based on movement and intelligence of
swarms. This iterative particle swarm optimized (PSO) detector
significantly reduces the computational complexity of conventional
Maximum Likelihood (ML) detection technique. The simulation
results achieved with this proposed MA-PSO detection algorithm
show near optimal performance when compared with ML-MA
receiver. The performance of proposed detector is convincingly
better for higher order modulation schemes and large number of
antennas where conventional ML detector becomes non-practical.
Abstract: Generalized Center String (GCS) problem are
generalized from Common Approximate Substring problem
and Common substring problems. GCS are known to be
NP-hard allowing the problems lies in the explosion of
potential candidates. Finding longest center string without
concerning the sequence that may not contain any motifs is
not known in advance in any particular biological gene
process. GCS solved by frequent pattern-mining techniques
and known to be fixed parameter tractable based on the
fixed input sequence length and symbol set size. Efficient
method known as Bpriori algorithms can solve GCS with
reasonable time/space complexities. Bpriori 2 and Bpriori
3-2 algorithm are been proposed of any length and any
positions of all their instances in input sequences. In this
paper, we reduced the time/space complexity of Bpriori
algorithm by Constrained Based Frequent Pattern mining
(CBFP) technique which integrates the idea of Constraint
Based Mining and FP-tree mining. CBFP mining technique
solves the GCS problem works for all center string of any
length, but also for the positions of all their mutated copies
of input sequence. CBFP mining technique construct TRIE
like with FP tree to represent the mutated copies of center
string of any length, along with constraints to restraint
growth of the consensus tree. The complexity analysis for
Constrained Based FP mining technique and Bpriori
algorithm is done based on the worst case and average case
approach. Algorithm's correctness compared with the
Bpriori algorithm using artificial data is shown.
Abstract: In this paper, based on steady-state models of Flexible
AC Transmission System (FACTS) devices, the sizing of static
synchronous series compensator (SSSC) controllers in transmission
network is formed as an optimization problem. The objective of this
problem is to reduce the transmission losses in the network. The
optimization problem is solved using particle swarm optimization
(PSO) technique. The Newton-Raphson load flow algorithm is
modified to consider the insertion of the SSSC devices in the
network. A numerical example, illustrating the effectiveness of the
proposed algorithm, is introduced. In addition, a novel model of a 3-
phase voltage source converter (VSC) that is suitable for series
connected FACTS a controller is introduced. The model is verified
by simulation using Power System Blockset (PSB) and Simulink
software.
Abstract: A rare phenomenon of SDS-induced activation of a latent protease activity associated with the purified silkworm excretory red fluorescent protein (SE-RFP) was noticed. SE-RFP aliquots incubated with SDS for different time intervals indicated that the protein undergoes an obligatory breakdown into a number of subunits which exhibit autoproteolytic (acting upon themselves) and/or heteroproteolytic (acting on other proteins) activities. A strong serine protease activity of SE-RFP subunits on Bombyx mori nucleopolyhedrovirus (BmNPV) polyhedral protein was detected by zymography technique. A complete inhibition of BmNPV infection to silkworms was observed by the oral administration assay of the SE-RFP. Here, it is proposed that the SE-RFP prevents the initial infection of BmNPV to silkworms by obliterating the polyhedral protein. This is the first report on a silkworm red fluorescent protein that exhibits a protease activity on exposure to SDS. The present studies would help in understanding the antiviral mechanism of silkworm red fluorescent proteins.
Abstract: The present work deals with the structural analysis of
turbine blades and modeling of turbine blades. A common failure
mode for turbine machines is high cycle of fatigue of compressor and
turbine blades due to high dynamic stresses caused by blade vibration
and resonance within the operation range of the machinery. In this
work, proper damping system will be analyzed to reduce the
vibrating blade. The main focus of the work is the modeling of under
platform damper to evaluate the dynamic analysis of turbine-blade
vibrations. The system is analyzed using Bond graph technique. Bond
graph is one of the most convenient ways to represent a system from
the physical aspect in foreground. It has advantage of putting together
multi-energy domains of a system in a single representation in a
unified manner. The bond graph model of dry friction damper is
simulated on SYMBOLS-shakti® software. In this work, the blades
are modeled as Timoshenko beam. Blade Vibrations under different
working conditions are being analyzed numerically.
Abstract: The hydrologic time series data display periodic
structure and periodic autoregressive process receives considerable
attention in modeling of such series. In this communication long
term record of monthly waste flow of Lyari river is utilized to
quantify by using PAR modeling technique. The parameters of
model are estimated by using Frances & Paap methodology. This
study shows that periodic autoregressive model of order 2 is the most
parsimonious model for assessing periodicity in waste flow of the
river. A careful statistical analysis of residuals of PAR (2) model is
used for establishing goodness of fit. The forecast by using proposed
model confirms significance and effectiveness of the model.
Abstract: The toxicity of aqueous extracts of two plants,
Nicotiana tobacum and Eucalyptus globulus were investigated against second instar larvae of Lycoriella auripila, one of the most
important pests of button mushroom, using agar dilution technique.
Seven concentrations of aqueous extracts of both plants were applied
on second instar larvae and their mortality were evaluated after 24, 48 and 72 h. The obtained results revealed that aqueous extracts of N.
tabacum and E. globulus caused 77.55 and 72.5% mortality of larvae
of L. auripila at concentration of 4000 ppm after 72h, respectively. Toxicities of tobacco extract after 24, 48 and 72 h were 1.52, 1.85
and 1.70 times greather than eucalyptus, respectively. The estimated LC50 after 24, 48 and 72 h were 7316.5, 2468.5 and 2013.1 ppm for
tobacco and 64870.0, 6839.5 and 3326.4 ppm for eucalyptus, respectively. These plants merit further study as potential insecticides
for the control of L. auripila.
Abstract: This study describes the methodology for the development of a validated in-vitro in-vivo correlation (IVIVC) for metoprolol tartrate modified release dosage forms with distinctive release rate characteristics. Modified release dosage forms were formulated by microencapsulation of metoprolol tartrate into different amounts of ethylcellulose by non-solvent addition technique. Then in-vitro and in-vivo studies were conducted to develop and validate level A IVIVC for metoprolol tartrate. The values of regression co-efficient (R2-values) for IVIVC of T2 and T3 formulations were not significantly (p
Abstract: This paper presents the design of a low power second-order continuous-time sigma-delta modulator for low power
applications. The loop filter of this modulator has been implemented based on the nonlinear transconductance-capacitor (Gm-C) by employing current-mode technique. The nonlinear transconductance uses floating gate MOS (FG-MOS) transistors that operate in weak inversion region. The proposed modulator features low power consumption (
Abstract: A new data fusion method called joint probability density matrix (JPDM) is proposed, which can associate and fuse measurements from spatially distributed heterogeneous sensors to identify the real target in a surveillance region. Using the probabilistic grids representation, we numerically combine the uncertainty regions of all the measurements in a general framework. The NP-hard multisensor data fusion problem has been converted to a peak picking problem in the grids map. Unlike most of the existing data fusion method, the JPDM method dose not need association processing, and will not lead to combinatorial explosion. Its convergence to the CRLB with a diminishing grid size has been proved. Simulation results are presented to illustrate the effectiveness of the proposed technique.
Abstract: The typical coupled-tanks process that is TITO
plant has the difficulty in controller design because changing
of system dynamics and interacting of process. This paper
presents design methodology of auto-adjustable PI controller
using MRAC technique. The proposed method can adjust the
controller parameters in response to changes in plant and
disturbance real time by referring to the reference model that
specifies properties of the desired control system.
Abstract: In this paper, the problem of asymptotical stability of neutral systems with nonlinear perturbations is investigated. Based on a class of novel augment Lyapunov functionals which contain freeweighting matrices, some new delay-dependent asymptotical stability criteria are formulated in terms of linear matrix inequalities (LMIs) by using new inequality analysis technique. Numerical examples are given to demonstrate the derived condition are much less conservative than those given in the literature.
Abstract: This paper deals with an adaptive multiuser detector for direct sequence code division multiple-access (DS-CDMA) systems. A modified receiver, precombinig LMMSE is considered under time varying channel environment. Detector updating is performed with two criterions, mean square estimation (MSE) and MOE optimization technique. The adaptive implementation issues of these two schemes are quite different. MSE criterion updates the filter weights by minimizing error between data vector and adaptive vector. MOE criterion together with canonical representation of the detector results in a constrained optimization problem. Even though the canonical representation is very complicated under time varying channels, it is analyzed with assumption of average power profile of multipath replicas of user of interest. The performance of both schemes is studied for practical SNR conditions. Results show that for poor SNR, MSE precombining LMMSE is better than the blind precombining LMMSE but for greater SNR, MOE scheme outperforms with better result.
Abstract: In this work we report on preliminary analysis of a novel optoelectronic gas sensor based on an optical fiber integrated with a tetrakis(4-sulfonatophenyl)porphyrin (TPPS) thin film. The sensitive materials are selectively deposited on the core region of a fiber tip by UV light induced deposition technique. A simple and cheap process which can be easily extended to different porphyrin derivatives. When the TPPS film on the fiber tip is exposed to acid and/or base vapors, dramatic changes occur in the aggregation structure of the dye molecules in the film, from J- to H-type, resulting in a profound modification of their corresponding reflectance spectra. From the achieved experimental results it is evident that the presence of intense and narrow band peaks in the reflected spectra could be monitored to detect hazardous vapors.
Abstract: An alternative approach to the use of Discrete Fourier
Transform (DFT) for Magnetic Resonance Imaging (MRI) reconstruction
is the use of parametric modeling technique. This method
is suitable for problems in which the image can be modeled by
explicit known source functions with a few adjustable parameters.
Despite the success reported in the use of modeling technique as an
alternative MRI reconstruction technique, two important problems
constitutes challenges to the applicability of this method, these are
estimation of Model order and model coefficient determination. In
this paper, five of the suggested method of evaluating the model
order have been evaluated, these are: The Final Prediction Error
(FPE), Akaike Information Criterion (AIC), Residual Variance (RV),
Minimum Description Length (MDL) and Hannan and Quinn (HNQ)
criterion. These criteria were evaluated on MRI data sets based on the
method of Transient Error Reconstruction Algorithm (TERA). The
result for each criterion is compared to result obtained by the use of a
fixed order technique and three measures of similarity were evaluated.
Result obtained shows that the use of MDL gives the highest measure
of similarity to that use by a fixed order technique.
Abstract: A new Markovianity approach is introduced in this
paper. This approach reduces the response time of classic Markov
Random Fields approach. First, one region is determinated by a
clustering technique. Then, this region is excluded from the study.
The remaining pixel form the study zone and they are selected for a
Markovianity segmentation task. With Selective Markovianity
approach, segmentation process is faster than classic one.
Abstract: A SnO2/CdS/CdTe heterojunction was fabricated by
thermal evaporation technique. The fabricated cells were annealed at
573K for periods of 60, 120 and 180 minutes. The structural
properties of the solar cells have been studied by using X-ray
diffraction. Capacitance- voltage measurements were studied for the
as-prepared and annealed cells at a frequency of 102 Hz. The
capacitance- voltage measurements indicated that these cells are
abrupt. The capacitance decreases with increasing annealing time.
The zero bias depletion region width and the carrier concentration
increased with increasing annealing time. The carrier transport
mechanism for the CdS/CdTe heterojunction in dark is tunneling
recombination. The ideality factor is 1.56 and the reverse bias
saturation current is 9.6×10-10A. The energy band lineup for the n-
CdS/p-CdTe heterojunction was investigated using current - voltage
and capacitance - voltage characteristics.
Abstract: Due to memory leaks, often-valuable system memory
gets wasted and denied for other processes thereby affecting the
computational performance. If an application-s memory usage
exceeds virtual memory size, it can leads to system crash. Current
memory leak detection techniques for clusters are reactive and
display the memory leak information after the execution of the
process (they detect memory leak only after it occur).
This paper presents a Dynamic Memory Monitoring Agent
(DMMA) technique. DMMA framework is a dynamic memory leak
detection, that detects the memory leak while application is in
execution phase, when memory leak in any process in the cluster is
identified by DMMA it gives information to the end users to enable
them to take corrective actions and also DMMA submit the affected
process to healthy node in the system. Thus provides reliable service
to the user. DMMA maintains information about memory
consumption of executing processes and based on this information
and critical states, DMMA can improve reliability and
efficaciousness of cluster computing.