Abstract: Gurus of the Classical Management School (like
Taylor, Fayol and Ford) had an opinion that work must be delegated
to the individual and the individual has to be instructed, his work
assessed and paid based on individual performance. The theories of
the Human Relations School have changed this mentality regarding
the concept of groups. They came to the conclusion that the influence
of groups greatly affects the behaviour and performance of its
members.
Group theories today are characterized by problem-solving teams
and self-managing groups authorized to make decisions and execute;
professional communities also play an important role during the
operation of knowledge management systems.
In this theoretical research we try to find answers to a question:
what kind of characteristics (professional competencies, personal
features, etc.) a successful team needs to manage a change to operate
a knowledge management system step by step.
Abstract: The methodology of numerical simulation and calculation of aerodynamic characteristics of aircraft taking into account impact of wake on it has been developed. The results of numerical experiment in comparison with the data obtained in the wind tunnel are presented. Efficiency of methodology of calculation and the reliability of the results is shown.
Abstract: Globalisation is a phenomenon that cannot be avoided.
As globalisation allowed free flow of inputs including labour, it may
affect job opportunities for the locals. Therefore, investigate the
determinants of labour supply is essential in understanding the
structure of labour market in the new era of globalization. The
objective of this article is to examine labour supply by taking into
account the globalisation effect. The study covers 3885 households in
Peninsular Malaysia who are chosen using stratified random
sampling. The labour supply model will be the basis for the analysis.
The basic labour supply determinants are own wage and non-labour
income. However, the extended labour supply model incorporates
other variables like spouse wage，number of children and
individuals characteristics like education level and age. Besides, the
globalization indicator will also be incorporated as another
independent variable.
Abstract: Due to their high power-to-weight ratio and low cost, pneumatic actuators are attractive for robotics and automation applications; however, achieving fast and accurate control of their position have been known as a complex control problem. The paper presents a methodology for obtaining controllers that achieve high position accuracy and preserve the closed-loop characteristics over a broad operating range. Experimentation with a number of conventional (or "classical") three-term controllers shows that, as repeated operations accumulate, the characteristics of the pneumatic actuator change requiring frequent re-tuning of the controller parameters (PID gains). Furthermore, three-term controllers are found to perform poorly in recovering the closed-loop system after the application of load or other external disturbances. The key reason for these problems lies in the non-linear exchange of energy inside the cylinder relating, in particular, to the complex friction forces that develop on the piston-wall interface. In order to overcome this problem but still remain within the boundaries of classical control methods, we designed an auto selective classicaql controller so that the system performance would benefit from all three control gains (KP, Kd, Ki) according to system requirements and the characteristics of each type of controller. This challenging experimentation took place for consistent performance in the face of modelling imprecision and disturbances. In the work presented, a selective PID controller is presented for an experimental rig comprising an air cylinder driven by a variable-opening pneumatic valve and equipped with position and pressure sensors. The paper reports on tests carried out to investigate the capability of this specific controller to achieve consistent control performance under, repeated operations and other changes in operating conditions.
Abstract: Most of the collision warning systems currently
available in the automotive market are mainly designed to warn
against imminent rear-end and lane-changing collisions. No collision
warning system is commercially available to warn against imminent
turning collisions at intersections, especially for left-turn collisions
when a driver attempts to make a left-turn at either a signalized or
non-signalized intersection, conflicting with the path of other
approaching vehicles traveling on the opposite-direction traffic
stream. One of the major factors that lead to left-turn collisions is the
human error and misjudgment of the driver of the turning vehicle
when perceiving the speed and acceleration of other vehicles
traveling on the opposite-direction traffic stream; therefore, using a
properly-designed collision warning system will likely reduce, or
even eliminate, this type of collisions by reducing human error. This
paper introduces perceptual framework for a proposed collision
warning system that can detect imminent left-turn collisions at
intersections. The system utilizes a commercially-available detection
sensor (either a radar sensor or a laser detector) to detect approaching
vehicles traveling on the opposite-direction traffic stream and
calculate their speeds and acceleration rates to estimate the time-tocollision
and compare that time to the time required for the turning
vehicle to clear the intersection. When calculating the time required
for the turning vehicle to clear the intersection, consideration is given
to the perception-reaction time of the driver of the turning vehicle,
which is the time required by the driver to perceive the message
given by the warning system and react to it by engaging the throttle.
A regression model was developed to estimate perception-reaction
time based on age and gender of the driver of the host vehicle.
Desired acceleration rate selected by the driver of the turning vehicle,
when making the left-turn movement, is another human factor that is
considered by the system. Another regression model was developed
to estimate the acceleration rate selected by the driver of the turning
vehicle based on driver-s age and gender as well as on the location
and speed of the nearest approaching vehicle along with the
maximum acceleration rate provided by the mechanical
characteristics of the turning vehicle. By comparing time-to-collision
with the time required for the turning vehicle to clear the intersection,
the system displays a message to the driver of the turning vehicle
when departure is safe. An application example is provided to
illustrate the logic algorithm of the proposed system.
Abstract: In this paper, we propose a method to reduce the
various kinds of noise while gathering and recording the
electrocardiogram (ECG) signal. Because of the defects of former
method in the noise elimination of ECG signal, we use translation
invariant (TI) multiwavelet denoising method to the noise elimination.
The advantage of the proposed method is that it may not only remain
the geometrical characteristics of the original ECG signal and keep the
amplitudes of various ECG waveforms efficiently, but also suppress
impulsive noise to some extent. The simulation results indicate that the
proposed method are better than former removing noise method in
aspects of remaining geometrical characteristics of ECG signal and the
signal-to-noise ratio (SNR).
Abstract: Many metrics were proposed to evaluate the
characteristics of the analysis and design model of a given product
which in turn help to assess the quality of the product. Function point
metric is a measure of the 'functionality' delivery by the software.
This paper presents an analysis of a set of programs of a project
developed in Cµ through Function Points metric. Function points
are measured for a Data Flow Diagram (DFD) of the case developed
at initial stage. Lines of Codes (LOCs) and possible errors are
calculated with the help of measured Function Points (FPs). The
calculations are performed using suitable established functions.
Calculated LOCs and errors are compared with actual LOCs and
errors found at the time of analysis & design review, implementation
and testing. It has been observed that actual found errors are more
than calculated errors. On the basis of analysis and observations,
authors conclude that function point provides useful insight and helps
to analyze the drawbacks in the development process.
Abstract: By analyzing the sources of energy and power
loss in PWM (Pulse Width Modulation) controlled drivers of
water electrolysis cells, it is possible to reduce the power
dissipation and enhance the efficiency of such hydrogen
production units. A PWM controlled power driver is based on
a semiconductor switching element where its power
dissipation might be a remarkable fraction of the total power
demand of an electrolysis system. Power dissipation in a
semiconductor switching element is related to many different
parameters which could be fitted into two main categories:
switching losses and conduction losses. Conduction losses are
directly related to the built, structure and capabilities of a
switching device itself and indeed the conditions in which the
element is handling the switching application such as voltage,
current, temperature and of course the fabrication technology.
On the other hand, switching losses have some other
influencing variables other than the mentioned such as control
system, switching method and power electronics circuitry of
the PWM power driver. By analyzings the characteristics of
recently developed power switching transistors from different
families of Bipolar Junction Transistors (BJT), Metal Oxide
Semiconductor Field Effect Transistors (MOSFET) and
Insulated Gate Bipolar Transistors (IGBT), some
recommendations are made in this paper which are able to
lead to achieve higher hydrogen production efficiency by
utilizing PWM controlled water electrolysis cells.
Abstract: The massive proliferation of affordable computers, Internet broadband connectivity and rich education content has created a global phenomenon in which information and communication technology (ICT) is being used to transform education. Therefore, there is a need to redesign the educational system to meet the needs better. The advent of computers with sophisticated software has made it possible to solve many complex problems very fast and at a lower cost. This paper introduces the characteristics of the current E-Learning and then analyses the concept of cloud computing and describes the architecture of cloud computing platform by combining the features of E-Learning. The authors have tried to introduce cloud computing to e-learning, build an e-learning cloud, and make an active research and exploration for it from the following aspects: architecture, construction method and external interface with the model.
Abstract: This paper addresses the problem of peak-to-average
power ratio (PAPR) in orthogonal frequency division multiplexing
(OFDM) systems. It also introduces a new PAPR reduction technique
based on adaptive square-rooting (SQRT) companding process. The
SQRT process of the proposed technique changes the statistical
characteristics of the OFDM output signals from Rayleigh
distribution to Gaussian-like distribution. This change in statistical
distribution results changes of both the peak and average power
values of OFDM signals, and consequently reduces significantly the
PAPR. For the 64QAM OFDM system using 512 subcarriers, up to 6
dB reduction in PAPR was achieved by square-rooting technique
with fixed degradation in bit error rate (BER) equal to 3 dB.
However, the PAPR is reduced at the expense of only -15 dB out-ofband
spectral shoulder re-growth below the in-band signal level. The
proposed adaptive SQRT technique is superior in terms of BER
performance than the original, non-adaptive, square-rooting
technique when the required reduction in PAPR is no more than 5
dB. Also, it provides fixed amount of PAPR reduction in which it is
not available in the original SQRT technique.
Abstract: It is shown that the relationship of tick-borne
encephalitis virus with the human body comes in two ways, the
development of acute infection with the outcome in convalescence
and long stay by the virus in the body, its persistence in the nervous
tissue with periodic reactivation and prolonged circulating
immunoglobulin M. In spite of the fact that tick-borne encephalitis
virus has a tropism for nerve tissue, involvement in the process of
blood cells is an integral component of the infection. Comprehensive
study of the relation of factors of innate and adaptive immunity in the
tick-borne encephalitis providing insight into the features of chronic
disease.
Abstract: The aim of this paper is to study the oblique
stagnation point flow on vertical plate with uniform surface heat flux
in presence of magnetic field. Using Stream function, partial
differential equations corresponding to the momentum and energy
equations are converted into non-linear ordinary differential
equations. Numerical solutions of these equations are obtained using
Runge-Kutta Fehlberg method with the help of shooting technique.
In the present work the effects of striking angle, magnetic field
parameter, Grashoff number, the Prandtl number on velocity and heat
transfer characteristics have been discussed. Effect of above
mentioned parameter on the position of stagnation point are also
studied.
Abstract: A prototype model of an emulsion separator was
designed and manufactured. Generally, it is a cylinder filled with
different fractal modules. The emulsion was fed into the reactor by a
peristaltic pump through an inlet placed at the boundary between the
two phases. For hydrodynamic design and sizing of the reactor the
assumptions of the theory of filtration were used and methods to
describe the separation process were developed. Based on this
methodology and using numerical methods and software of Autodesk
the process is simulated in different operating modes. The basic
hydrodynamic characteristics - speed and performance for different
types of fractal systems and decisions to optimize the design of the
reactor were also defined.
Abstract: This paper presents Simulation and experimental
study aimed at investigating the effectiveness of an adaptive artificial
neural network stabilizer on enhancing the damping torque of a
synchronous generator. For this purpose, a power system comprising
a synchronous generator feeding a large power system through a
short tie line is considered. The proposed adaptive neuro-control
system consists of two multi-layered feed forward neural networks,
which work as a plant model identifier and a controller. It generates
supplementary control signals to be utilized by conventional
controllers. The details of the interfacing circuits, sensors and
transducers, which have been designed and built for use in tests, are
presented. The synchronous generator is tested to investigate the
effect of tuning a Power System Stabilizer (PSS) on its dynamic
stability. The obtained simulation and experimental results verify the
basic theoretical concepts.
Abstract: Partial combustion of biomass in the gasifier generates producer gas that can be used for heating purposes and as supplementary or sole fuel in internal combustion engines. In this study, the virgin biomass obtained from hingan shell is used as the feedstock for gasifier to generate producer gas. The gasifier-engine system is operated on diesel and on esters of vegetable oil of hingan in liquid fuel mode operation and then on liquid fuel and producer gas combination in dual fuel mode operation. The performance and emission characteristics of the CI engine is analyzed by running the engine in liquid fuel mode operation and in dual fuel mode operation at different load conditions with respect to maximum diesel savings in the dual fuel mode operation. It was observed that specific energy consumption in the dual fuel mode of operation is found to be in the higher side at all load conditions. The brake thermal efficiency of the engine using diesel or hingan oil methyl ester (HOME) is higher than that of dual fuel mode operation. A diesel replacement in the tune of 60% in dual fuel mode is possible with the use of hingan shell producer gas. The emissions parameters such CO, HC, NOx, CO2 and smoke are higher in the case of dual fuel mode of operation as compared to that of liquid fuel mode.
Abstract: In the semiconductor manufacturing process, large
amounts of data are collected from various sensors of multiple
facilities. The collected data from sensors have several different characteristics
due to variables such as types of products, former processes
and recipes. In general, Statistical Quality Control (SQC) methods
assume the normality of the data to detect out-of-control states of
processes. Although the collected data have different characteristics,
using the data as inputs of SQC will increase variations of data,
require wide control limits, and decrease performance to detect outof-
control. Therefore, it is necessary to separate similar data groups
from mixed data for more accurate process control. In the paper,
we propose a regression tree using split algorithm based on Pearson
distribution to handle non-normal distribution in parametric method.
The regression tree finds similar properties of data from different
variables. The experiments using real semiconductor manufacturing
process data show improved performance in fault detecting ability.
Abstract: Evolutionary Programming (EP) represents a
methodology of Evolutionary Algorithms (EA) in which mutation is
considered as a main reproduction operator. This paper presents a
novel EP approach for Artificial Neural Networks (ANN) learning.
The proposed strategy consists of two components: the self-adaptive,
which contains phenotype information and the dynamic, which is
described by genotype. Self-adaptation is achieved by the addition of
a value, called the network weight, which depends on a total number
of hidden layers and an average number of neurons in hidden layers.
The dynamic component changes its value depending on the fitness
of a chromosome, exposed to mutation. Thus, the mutation step size
is controlled by two components, encapsulated in the algorithm,
which adjust it according to the characteristics of a predefined ANN
architecture and the fitness of a particular chromosome. The
comparative analysis of the proposed approach and the classical EP
(Gaussian mutation) showed, that that the significant acceleration of
the evolution process is achieved by using both phenotype and
genotype information in the mutation strategy.
Abstract: An application of the highly biosensor based on pH-sensitive field immobilized urease for urea analysis was demo The main analytical characteristics of the bios determined; the conditions of urea measureme blood were optimized. A conceptual possibility biosensor for detection of urea concentratio patients suffering from renal insufficiency was sensitive and selective effect transistor and monstrated in this work. iosensor developed were ment in real samples of ility of application of the tion in blood serum of as shown.
Abstract: This paper attempts to establish the fact that Multi
State Network Classification is essential for performance
enhancement of Transport protocols over Satellite based Networks. A
model to classify Multi State network condition taking into
consideration both congestion and channel error is evolved. In order
to arrive at such a model an analysis of the impact of congestion and
channel error on RTT values has been carried out using ns2. The
analysis results are also reported in the paper. The inference drawn
from this analysis is used to develop a novel statistical RTT based
model for multi state network classification.
An Adaptive Multi State Proactive Transport Protocol consisting
of Proactive Slow Start, State based Error Recovery, Timeout Action
and Proactive Reduction is proposed which uses the multi state
network state classification model. This paper also confirms through
detail simulation and analysis that a prior knowledge about the
overall characteristics of the network helps in enhancing the
performance of the protocol over satellite channel which is
significantly affected due to channel noise and congestion.
The necessary augmentation of ns2 simulator is done for
simulating the multi state network classification logic. This
simulation has been used in detail evaluation of the protocol under
varied levels of congestion and channel noise. The performance
enhancement of this protocol with reference to established protocols
namely TCP SACK and Vegas has been discussed. The results as
discussed in this paper clearly reveal that the proposed protocol
always outperforms its peers and show a significant improvement in
very high error conditions as envisaged in the design of the protocol.
Abstract: The clustering ensembles combine multiple partitions
generated by different clustering algorithms into a single clustering
solution. Clustering ensembles have emerged as a prominent method
for improving robustness, stability and accuracy of unsupervised
classification solutions. So far, many contributions have been done to
find consensus clustering. One of the major problems in clustering
ensembles is the consensus function. In this paper, firstly, we
introduce clustering ensembles, representation of multiple partitions,
its challenges and present taxonomy of combination algorithms.
Secondly, we describe consensus functions in clustering ensembles
including Hypergraph partitioning, Voting approach, Mutual
information, Co-association based functions and Finite mixture
model, and next explain their advantages, disadvantages and
computational complexity. Finally, we compare the characteristics of
clustering ensembles algorithms such as computational complexity,
robustness, simplicity and accuracy on different datasets in previous
techniques.