Abstract: The aim of the paper work is to investigate and predict
the static performance of journal bearing in turbulent flow condition
considering micropolar lubrication. The Reynolds equation has been
modified considering turbulent micropolar lubrication and is solved
for steady state operations. The Constantinescu-s turbulence model is
adopted using the coefficients. The analysis has been done for a
parallel and inertia less flow. Load capacity and friction factor have
been evaluated for various operating parameters.
Abstract: Biplot can be used to evaluate cultivars for their oil
percent potential and stability and to evaluate trial sites for their
discriminating ability and representativeness. Multi-environmental
trial (MET) data for oil percent of 10 open pollinating sunflower
cultivars were analyzed to investigate the genotype-environment
interactions. The genotypes were evaluated in four locations with
different climatic conditions in Iran in 2010. In each location, a
Randomized Complete Block design with four replications was used.
According to both mean and stability, Zaria, Master and R453, had
highest performances among all cultivars. The graphical analysis
identified best cultivar for each environment. Cultivars Berezans and
Record performed best in Khoy and Islamabad. Zaria and R453 were
the best genotypes in Sari and Karaj followed by Master and Favorit.
The GGE bi-plot indicated two mega-environments, group one
contained Karaj, Khoy and Islamabad and the second group
contained Sari. The best discriminating location was Karaj followed
with Khoy, Islamabad and Sari. The best representative genotypes
were Zaria, R453, Master and Favorit. Ranking of ten cultivars based
their oil percent was as Zaria > R453 ≈ Master ≈ Favorit > Record ≈
Berezans > Sor > Lakumka > Bulg3 > Bulg5.
Abstract: Accurate demand forecasting is one of the most key
issues in inventory management of spare parts. The problem of
modeling future consumption becomes especially difficult for lumpy
patterns, which characterized by intervals in which there is no
demand and, periods with actual demand occurrences with large
variation in demand levels. However, many of the forecasting
methods may perform poorly when demand for an item is lumpy.
In this study based on the characteristic of lumpy demand patterns
of spare parts a hybrid forecasting approach has been developed,
which use a multi-layered perceptron neural network and a
traditional recursive method for forecasting future demands. In the
described approach the multi-layered perceptron are adapted to
forecast occurrences of non-zero demands, and then a conventional
recursive method is used to estimate the quantity of non-zero
demands. In order to evaluate the performance of the proposed
approach, their forecasts were compared to those obtained by using
Syntetos & Boylan approximation, recently employed multi-layered
perceptron neural network, generalized regression neural network
and elman recurrent neural network in this area. The models were
applied to forecast future demand of spare parts of Arak
Petrochemical Company in Iran, using 30 types of real data sets. The
results indicate that the forecasts obtained by using our proposed
mode are superior to those obtained by using other methods.
Abstract: Precast concrete has been widely adopted in public
housing construction of Hong Kong since the mid-1980s. While
pre-casting is considered an environmental friendly solution, there is
lack of study to investigate the life cycle performance of precast
concrete units. This study aims to bridge the knowledge gap by
providing a comprehensive life cycle assessment (LCA) study for two
precast elements namely façade and bathroom. The results show that
raw material is the most significant contributor of environmental
impact accounting for about 90% to the total impact. Furthermore,
human health is more affected by the production of precast concrete
than the ecosystems.
Abstract: Gas turbine systems with wet compression have a
potential for future power generation, since they can offer a high
efficiency and a high specific power with a relatively low cost. In this
study influence of ambient condition on the performance of the wet
compression process is investigated with a non-equilibrium analytical
modeling based on droplet evaporation. Transient behaviors of droplet
diameter and temperature of mixed air are investigated for various
ambient temperatures. Special attention is paid for the effects of
ambient temperature, pressure ratio, and water injection ratios on the
important wet compression variables including compressor outlet
temperature and compression work. Parametric studies show that
downing of the ambient temperature leads to lower compressor outlet
temperature and consequently lower consumption of compression
work even in wet compression processes.
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: The development of distributed systems has been affected by the need to accommodate an increasing degree of flexibility, adaptability, and autonomy. The Mobile Agent technology is emerging as an alternative to build a smart generation of highly distributed systems. In this work, we investigate the performance aspect of agent-based technologies for information retrieval. We present a comparative performance evaluation model of Mobile Agents versus Remote Method Invocation by means of an analytical approach. We demonstrate the effectiveness of mobile agents for dynamic code deployment and remote data processing by reducing total latency and at the same time producing minimum network traffic. We argue that exploiting agent-based technologies significantly enhances the performance of distributed systems in the domain of information retrieval.
Abstract: Com Poisson distribution is capable of modeling the count responses irrespective of their mean variance relation and the parameters of this distribution when fitted to a simple cross sectional data can be efficiently estimated using maximum likelihood (ML) method. In the regression setup, however, ML estimation of the parameters of the Com Poisson based generalized linear model is computationally intensive. In this paper, we propose to use quasilikelihood (QL) approach to estimate the effect of the covariates on the Com Poisson counts and investigate the performance of this method with respect to the ML method. QL estimates are consistent and almost as efficient as ML estimates. The simulation studies show that the efficiency loss in the estimation of all the parameters using QL approach as compared to ML approach is quite negligible, whereas QL approach is lesser involving than ML approach.
Abstract: There are various kinds of medical equipment which
requires relatively accurate positional adjustments for successful
treatment. However, patients tend to move without notice during a
certain span of operations. Therefore, it is common practice that
accompanying operators adjust the focus of the equipment. In this
paper, tracking controllers for medical equipment are suggested to
replace the operators. The tracking controllers use AHRS sensor
information to recognize the movements of patients. Sensor fusion is
applied to reducing the error magnitudes through linear Kalman filters.
The image processing of optical markers is included to adjust the
accumulation errors of gyroscope sensor data especially for yaw
angles.
The tracking controller reduces the positional errors between the
current focus of a device and the target position on the body of a
patient. Since the sensing frequencies of AHRS sensors are very high
compared to the physical movements, the control performance is
satisfactory. The typical applications are, for example, ESWT or
rTMS, which have the error ranges of a few centimeters.
Abstract: Fuzzy logic approach is used in this study to predict
the tractive performance in terms of traction force, and motion
resistance for an intelligent air cushion track vehicle while it operates
in the swamp peat. The system is effective to control the intelligent
air –cushion system with measuring the vehicle traction force (TF),
motion resistance (MR), cushion clearance height (CH) and cushion
pressure (CP). Sinkage measuring sensor, magnetic switch, pressure
sensor, micro controller, control valves and battery are incorporated
with the Fuzzy logic system (FLS) to investigate experimentally the
TF, MR, CH, and CP. In this study, a comparison for tractive
performance of an intelligent air cushion track vehicle has been
performed with the results obtained from the predicted values of FLS
and experimental actual values. The mean relative error of actual and
predicted values from the FLS model on traction force, and total
motion resistance are found as 5.58 %, and 6.78 % respectively. For
all parameters, the relative error of predicted values are found to be
less than the acceptable limits. The goodness of fit of the prediction
values from the FLS model on TF, and MR are found as 0.90, and
0.98 respectively.
Abstract: Later marine propeller is the main component of ship
propulsion system. For a non-series propeller, it is difficult to
indicate the open water marine propeller performance without an
experimental study to measure the marine propeller parameters.
In the present study, the open water performance of a non-series
marine propeller has been carried out experimentally. The
geometrical aspects of a commercial non-series marine propeller
have been measured for a propeller blade area ratio of 0.3985. The
measured propeller performance parameters were the thrust and
torque coefficients for different propeller rotational speed and
different water channel flow velocity, then the open water
performance for the propeller has been plotted.
In addition, a direct comparison between the obtained
experimental results and a theoretical study of a B-series marine
propeller of the same blade area ratio has been carried out. A
correction factor has been introduced to apply the operating
conditions of the experimental results to that of the theoretical study
for the studied marine propeller.
Abstract: Implemented 5-bit 125-MS/s successive
approximation register (SAR) analog to digital converter (ADC) on
FPGA is presented in this paper.The design and modeling of a high
performance SAR analog to digital converter are based on monotonic
capacitor switching procedure algorithm .Spartan 3 FPGA is chosen
for implementing SAR analog to digital converter algorithm. SAR
VHDL program writes in Xilinx and modelsim uses for showing
results.
Abstract: The application of the synchronous dynamic random
access memory (SDRAM) has gone beyond the scope of personal
computers for quite a long time. It comes into hand whenever a big
amount of low price and still high speed memory is needed. Most of
the newly developed stand alone embedded devices in the field of
image, video and sound processing take more and more use of it. The
big amount of low price memory has its trade off – the speed. In
order to take use of the full potential of the memory, an efficient
controller is needed. Efficient stands for maximum random accesses
to the memory both for reading and writing and less area after
implementation. This paper proposes a target device independent
DDR SDRAM pipelined controller and provides performance
comparison with available solutions.
Abstract: In the last couple of years Bluetooth has gained a large share in the market of home and personal appliances. It is now a well established technology a short range supplement to the wireless world of 802.11. The two main trends of research that have sprung from these developments are directed towards the coexistence and performance issues of Bluetooth and 802.11 as well as the co-existence in the very short range of multiple Bluetooth devices. Our work aims at thoroughly investigating different aspects of co-channel interference and effects of transmission power, distance and 802.11 interference on Bluetooth connections.
Abstract: Recently, a great number of theoretical frameworks
have been proposed to develop the linkages between knowledge
management (KM) and organizational strategies. However, while
there has been much theorizing and case study in the area, validated
research models integrating KM and information technology
strategies for empirical testing of these theories have been scarce. In
this research, we try to develop a research model for explaining the
relationship between KM strategy and IT strategy and their effects on
performance. Finally, meaningful propositions and conclusions are
derived, and suggestions for future research are proposed and
discussed.
Abstract: Clustering techniques have received attention in many areas including engineering, medicine, biology and data mining. The purpose of clustering is to group together data points, which are close to one another. The K-means algorithm is one of the most widely used techniques for clustering. However, K-means has two shortcomings: dependency on the initial state and convergence to local optima and global solutions of large problems cannot found with reasonable amount of computation effort. In order to overcome local optima problem lots of studies done in clustering. This paper is presented an efficient hybrid evolutionary optimization algorithm based on combining Particle Swarm Optimization (PSO) and Ant Colony Optimization (ACO), called PSO-ACO, for optimally clustering N object into K clusters. The new PSO-ACO algorithm is tested on several data sets, and its performance is compared with those of ACO, PSO and K-means clustering. The simulation results show that the proposed evolutionary optimization algorithm is robust and suitable for handing data clustering.
Abstract: New advancement of technology and never satisfying demands of the civilization are putting huge pressure on the natural fuel resources and these resources are at a constant threat to its sustainability. To get the best out of the automobile, the optimum balance between performance and fuel economy is important. In the present state of art, either of the above two aspects are taken into mind while designing and development process which puts the other in the loss as increase in fuel economy leads to decrement in performance and vice-versa. In-depth observation of the vehicle dynamics apparently shows that large amount of energy is lost during braking and likewise large amount of fuel is consumed to reclaim the initial state, this leads to lower fuel efficiency to gain the same performance. Current use of Kinetic Energy Recovery System is only limited to sports vehicles only because of the higher cost of this system. They are also temporary in nature as power can be squeezed only during a small time duration and use of superior parts leads to high cost, which results on concentration on performance only and neglecting the fuel economy. In this paper Kinetic Energy Recovery System for storing the power and then using the same while accelerating has been discussed. The major storing element in this system is a Flat Spiral Spring that will store energy by compression and torsion.
The use of spring ensure the permanent storage of energy until used by the driver unlike present mechanical regeneration system in which the energy stored decreases with time and is eventually lost. A combination of internal gears and spur gears will be used in order to make the energy release uniform which will lead to safe usage. The system can be used to improve the fuel efficiency by assisting in overcoming the vehicle’s inertia after braking or to provide instant acceleration whenever required by the driver. The performance characteristics of the system including response time, mechanical efficiency and overall increase in efficiency are demonstrated. This technology makes the KERS (Kinetic Energy Recovery System) more flexible and economical allowing specific application while at the same time increasing the time frame and ease of usage.
Abstract: The purpose of this study was to investigate the effectiveness of a recreational workout program for adults with disabilities over two semesters. This investigation was an action study conducted in a naturalistic setting. Participants included equal numbers of adults with severe cognitive impairments (n = 35) and adults without disabilities (n = 35). Adults with disabilities severe cognitive impairments were trained 6 self-initiated workout activities over two semesters by adults without disabilities. The numbers of task-analyzed steps of each activity performed correctly by each participant at the first and last weeks of each semester were used for data analysis. Results of the paired t-tests indicate that across two semesters, significant differences between the first and last weeks were found on 4 out of the 6 task-analyzed workout activities at a statistical level of significance p < .05. The recreational workout program developed in this study was effective.
Abstract: The conjugate gradient optimization algorithm is combined with the modified back propagation algorithm to yield a computationally efficient algorithm for training multilayer perceptron (MLP) networks (CGFR/AG). The computational efficiency is enhanced by adaptively modifying initial search direction as described in the following steps: (1) Modification on standard back propagation algorithm by introducing a gain variation term in the activation function, (2) Calculation of the gradient descent of error with respect to the weights and gains values and (3) the determination of a new search direction by using information calculated in step (2). The performance of the proposed method is demonstrated by comparing accuracy and computation time with the conjugate gradient algorithm used in MATLAB neural network toolbox. The results show that the computational efficiency of the proposed method was better than the standard conjugate gradient algorithm.
Abstract: In this paper we present an energy efficient match-line
(ML) sensing scheme for high-speed ternary content-addressable
memory (TCAM). The proposed scheme isolates the sensing unit of
the sense amplifier from the large and variable ML capacitance. It
employs feedback in the sense amplifier to successfully detect a
match while keeping the ML voltage swing low. This reduced voltage
swing results in large energy saving. Simulation performed using
130nm 1.2V CMOS logic shows at least 30% total energy saving in
our scheme compared to popular current race (CR) scheme for
similar search speed. In terms of speed, dynamic energy, peak power
consumption and transistor count our scheme also shows better
performance than mismatch-dependant (MD) power allocation
technique which also employs feedback in the sense amplifier.
Additionally, the implementation of our scheme is simpler than CR
or MD scheme because of absence of analog control voltage and
programmable delay circuit as have been used in those schemes.