Abstract: Guaranteeing the availability of the required parts at
the scheduled time represents a key logistical challenge. This is
especially important when several parts are required together. This
article describes a tool that supports the positioning in the area of
conflict between low stock costs and a high service level for a
consumer.
Abstract: This paper presents the development of analysis tools
for Home Agriculture project. The tools are required for monitoring
the condition of greenhouse which involves two components:
measurement hardware and data analysis engine. Measurement
hardware is functioned to measure environment parameters such as
temperature, humidity, air quality, dust and etc while analysis tool is
used to analyse and interpret the integrated data against the condition
of weather, quality of health, irradiance, quality of soil and etc. The
current development of the tools is completed for off-line data
recorded technique. The data is saved in MMC and transferred via
ZigBee to Environment Data Manager (EDM) for data analysis.
EDM converts the raw data and plot three combination graphs. It has
been applied in monitoring three months data measurement for
irradiance, temperature and humidity of the greenhouse..
Abstract: The data is available in abundance in any business
organization. It includes the records for finance, maintenance,
inventory, progress reports etc. As the time progresses, the data keep
on accumulating and the challenge is to extract the information from
this data bank. Knowledge discovery from these large and complex
databases is the key problem of this era. Data mining and machine
learning techniques are needed which can scale to the size of the
problems and can be customized to the application of business. For
the development of accurate and required information for particular
problem, business analyst needs to develop multidimensional models
which give the reliable information so that they can take right
decision for particular problem. If the multidimensional model does
not possess the advance features, the accuracy cannot be expected.
The present work involves the development of a Multidimensional
data model incorporating advance features. The criterion of
computation is based on the data precision and to include slowly
change time dimension. The final results are displayed in graphical
form.
Abstract: Resistance spot welding process comprises of electric,
thermal and mechanical phenomenon, which makes this process
complex and highly non-linear and thus, it becomes difficult to model
it. In order to obtain good weld nugget during spot welding, hit and
trial welds are usually done which is very costly. Therefore the
numerical simulation research has been conducted to understand the
whole process. In this paper three different cases were analyzed by
varying the tip contact area and it was observed that, with the
variation of tip contact area the nugget formation at the faying
surface is affected. The tip contact area of the welding electrode
becomes large with long welding cycles. Therefore in order to
maintain consistency of nugget formation during the welding process,
the current compensation in control feedback is required. If the
contact area of the welding electrode tip is reduced, a large amount of
current flows through the faying surface, as a result of which
sputtering occurs.
Abstract: The mechanism of abiotic stress tolerance is crucial
for plants to survive in harsh condition and the knowledge of this
mechanism can be use to solve the problem of declining productivity
of plants or crops around the world. However in-depth description is
still unclear and it is argued, in particular that there is a relationship
between high salinity tolerance and the ability to tolerate high light
condition. In this study, Dunaliella salina, which can withstand high
salt was used as a model. Chlorophyll fluorometer for nonphotochemical
quenching (NPQ) measurement and high-performance
liquid chromatography for pigment determination was used. The
results show that NPQ value and the amount of pigment were
increased along with the levels of salinity. However, it establish a
clear relationship between high salt and high light but the further
study to optimized the solutions mentioned above is still required.
Abstract: In the present study, a steady-state simulation model
has been developed to evaluate the system performance of a
transcritical carbon dioxide heat pump system for simultaneous water
cooling and heating. Both the evaporator (including both two-phase
and superheated zone) and gas cooler models consider the highly
variable heat transfer characteristics of CO2 and pressure drop. The
numerical simulation model of transcritical CO2 heat pump has been
validated by test data obtained from experiments on the heat pump
prototype. Comparison between the test results and the model
prediction for system COP variation with compressor discharge
pressure shows a modest agreement with a maximum deviation of
15% and the trends are fairly similar. Comparison for other operating
parameters also shows fairly similar deviation between the test
results and the model prediction. Finally, the simulation results are
presented to study the effects of operating parameters such as,
temperature of heat exchanger fluid at the inlet, discharge pressure,
compressor speed on system performance of CO2 heat pump, suitable
in a dairy plant where simultaneous cooling at 4oC and heating at
73oC are required. Results show that good heat transfer properties of
CO2 for both two-phase and supercritical region and efficient
compression process contribute a lot for high system COPs.
Abstract: State-based testing is frequently used in software testing. Test data generation is one of the key issues in software testing. A properly generated test suite may not only locate the errors in a software system, but also help in reducing the high cost associated with software testing. It is often desired that test data in the form of test sequences within a test suite can be automatically generated to achieve required test coverage. This paper proposes an Ant Colony Optimization approach to test data generation for the state-based software testing.
Abstract: This paper presents methodologies for developing an
intelligent CAD system assisting in analysis and design of
reconfigurable special machines. It describes a procedure for
determining feasibility of utilizing these machines for a given part
and presents a model for developing an intelligent CAD system. The
system analyzes geometrical and topological information of the given
part to determine possibility of the part being produced by
reconfigurable special machines from a technical point of view. Also
feasibility of the process from a economical point of view is
analyzed. Then the system determines proper positioning of the part
considering details of machining features and operations needed.
This involves determination of operation types, cutting tools and the
number of working stations needed. Upon completion of this stage
the overall layout of the machine and machining equipment required
are determined.
Abstract: For high-speed control of robots, a good knowledge of system modelling is necessary to obtain the desired bandwidth. In this paper, we present a cartesian robot with a pan/tilt unit in end-effector (5 dof). This robot is implemented with powerful direct drive AC induction machines. The dynamic model, parameter identification and model validation of the robot are studied (including actuators). This work considers the cartesian robot coupled and non linear (contrary to normal considerations for this type of robots). The mechanical and control architecture proposed in this paper is efficient for industrial and research application in which high speed, well known model and very high accuracy are required.
Abstract: Fast forecasting of stock market prices is very important for
strategic planning. In this paper, a new approach for fast forecasting of
stock market prices is presented. Such algorithm uses new high speed
time delay neural networks (HSTDNNs). The operation of these
networks relies on performing cross correlation in the frequency
domain between the input data and the input weights of neural
networks. It is proved mathematically and practically that the number
of computation steps required for the presented HSTDNNs is less
than that needed by traditional time delay neural networks
(TTDNNs). Simulation results using MATLAB confirm the
theoretical computations.
Abstract: The objective of this paper is to study the analysis and testing for determining the torsional stiffness of the student formula-s space frame. From past study, the space frame for Chulalongkorn University Student Formula team used in 2011 TSAE Auto Challenge Student Formula in Thailand was designed by considering required mass and torsional stiffness based on the numerical method and experimental method. The numerical result was compared with the experimental results to verify the torsional stiffness of the space frame. It can be seen from the large error of torsional stiffness of 2011 frame that the experimental result can not verify by the numerical analysis due to the different between the numerical model and experimental setting. In this paper, the numerical analysis and experiment of the same 2011 frame model is performed by improving the model setting. The improvement of both numerical analysis and experiment are discussed to confirm that the models from both methods are same. After the frame was analyzed and tested, the results are compared to verify the torsional stiffness of the frame. It can be concluded that the improved analysis and experiments can used to verify the torsional stiffness of the space frame.
Abstract: Since the actuator capacity is limited, in the real
application of active control systems under sever earthquakes it is
conceivable that the actuators saturate, hence the actuator saturation
should be considered as a constraint in design of optimal controllers.
In this paper optimal design of active controllers for nonlinear
structures by considering actuator saturation, has been studied. The
proposed method for designing optimal controllers is based on
defining an optimization problem which the objective has been to
minimize the maximum displacement of structure when a limited
capacity for actuator has been used. To this end a single degree of
freedom (SDF) structure with a bilinear hysteretic behavior has been
simulated under a white noise ground acceleration of different
amplitudes. Active tendon control mechanism, comprised of prestressed
tendons and an actuator, and extended nonlinear Newmark
method based instantaneous optimal control algorithm have been
used. To achieve the best results, the weights corresponding to
displacement, velocity, acceleration and control force in the
performance index have been optimized by the Distributed Genetic
Algorithm (DGA). Results show the effectiveness of the proposed
method in considering actuator saturation. Also based on the
numerical simulations it can be concluded that the actuator capacity
and the average value of required control force are two important
factors in designing nonlinear controllers which consider the actuator
saturation.
Abstract: Access control is a critical security service in Wire- less
Sensor Networks (WSNs). To prevent malicious nodes from joining
the sensor network, access control is required. On one hand, WSN
must be able to authorize and grant users the right to access to the
network. On the other hand, WSN must organize data collected by
sensors in such a way that an unauthorized entity (the adversary)
cannot make arbitrary queries. This restricts the network access only
to eligible users and sensor nodes, while queries from outsiders will
not be answered or forwarded by nodes. In this paper we presentee
different access control schemes so as to ?nd out their objectives,
provision, communication complexity, limits, etc. Using the node
density parameter, we also provide a comparison of these proposed
access control algorithms based on the network topology which can
be flat or hierarchical.
Abstract: Fixed-point simulation results are used for the
performance measure of inverting matrices by Cholesky
decomposition. The fixed-point Cholesky decomposition algorithm
is implemented using a fixed-point reconfigurable processing
element. The reconfigurable processing element provides all
mathematical operations required by Cholesky decomposition. The
fixed-point word length analysis is based on simulations using
different condition numbers and different matrix sizes. Simulation
results show that 16 bits word length gives sufficient performance
for small matrices with low condition number. Larger matrices and
higher condition numbers require more dynamic range for a fixedpoint
implementation.
Abstract: Since straightness error of linear motor stage is hardly
dependent upon machining accuracy and assembling accuracy, there is
limit on maximum realizable accuracy. To cope with this limitation,
this paper proposed a servo system to compensate straightness error of
a linear motor stage. The servo system is mounted on the slider of the
linear motor stage and moves in the direction of the straightness error
so as to compensate the error. From position dependency and
repeatability of the straightness error of the slider, a feedforward
compensation control is applied to the platform servo control. In the
consideration of required fine positioning accuracy, a platform driven
by an electro-magnetic actuator is suggested and a sliding mode
control was applied. The effectiveness of the sliding mode control was
verified along with some experimental results.
Abstract: Non-saturated soils that while saturation greatly
decrease their volume, have sudden settlement due to increasing
humidity, fracture and structural crack are called loess soils. Whereas
importance of civil projects including: dams, canals and
constructions bearing this type of soil and thereof problems, it is
required for carrying out more research and study in relation to loess
soils. This research studies shear strength parameters by using
grading test, Atterberg limit, compression, direct shear and
consolidation and then effect of using cement and lime additives on
stability of loess soils is studied. In related tests, lime and cement are
separately added to mixed ratios under different percentages of soil
and for different times the stabilized samples are processed and effect
of aforesaid additives on shear strength parameters of soil is studied.
Results show that upon passing time the effect of additives and
collapsible potential is greatly decreased and upon increasing
percentage of cement and lime the maximum dry density is
decreased; however, optimum humidity is increased. In addition,
liquid limit and plastic index is decreased; however, plastic index
limit is increased. It is to be noted that results of direct shear test
reveal increasing shear strength of soil due to increasing cohesion
parameter and soil friction angle.
Abstract: Power cables are vulnerable to failure due to aging or
defects that occur with the passage of time under continuous
operation and loading stresses. PD detection and characterization
provide information on the location, nature, form and extent of the
degradation. As a result, PD monitoring has become an important
part of condition based maintenance (CBM) program among power
utilities. Online partial discharge (PD) localization of defect sources
in power cable system is possible using the time of flight method.
The information regarding the time difference between the main and
reflected pulses and cable length can help in locating the partial
discharge source along the cable length. However, if the length of
the cable is not known and the defect source is located at the extreme
ends of the cable or in the middle of the cable, then double ended
measurement is required to indicate the location of PD source. Use of
multiple sensors can also help in discriminating the cable PD or local/
external PD. This paper presents the experience and results from
online partial discharge measurements conducted in the laboratory
and the challenges in partial discharge source localization.
Abstract: A major challenge in camel productivity is the high
mortality rate of camel calves in the early stage due to the lack of
colostrums. This study investigates the time required for the calves to
obtain the optimum amount of the immunoglobulin (IgG). Eleven
pregnant female camels (Camelus Dromedarus) were selected
randomly and variant in age and gestation. After delivery, 7 calves
were obtained and used for this investigation. Colostrum samples
were collected from mothers immediately after parturition. Blood
samples were obtained from the calves as follow: 0 day (before
suckling), 24, 48, 72, 96, 120 and 144 hours, 2nd, 3rd, and 4th weeks
post suckling. Blood serum and colostrums whey were separated and
used to determine IgG concentration, total protein and concentration
of Cortisol and Thyroxin. The results showed high levels of IgG in
camel colostrums (328.8 ± 4.5 mg / ml). The IgG concentration in
serum of calves was the highest within 1st 24 h after suckling (140.75
mg /ml), and then declined gradually reached lower level at 144 h
(41.97 mg / ml). The average turnover rate (t 1/2) of serum IgG in
the all cases was 3.22 days. The turnover of ranged from 2.56 days
for calves have values of IgG more than average and 7.7 days for
those with values below average. In spite of very high levels of
thyroxin in sera of new born the results showed no correlation
between cortisol and thyroxin with IgG levels.
Abstract: The heuristic decision rules used for project
scheduling will vary depending upon the project-s size, complexity,
duration, personnel, and owner requirements. The concept of project
complexity has received little detailed attention. The need to
differentiate between easy and hard problem instances and the
interest in isolating the fundamental factors that determine the
computing effort required by these procedures inspired a number of
researchers to develop various complexity measures.
In this study, the most common measures of project complexity are
presented. A new measure of project complexity is developed. The
main privilege of the proposed measure is that, it considers size,
shape and logic characteristics, time characteristics, resource
demands and availability characteristics as well as number of critical
activities and critical paths. The degree of sensitivity of the proposed
measure for complexity of project networks has been tested and
evaluated against the other measures of complexity of the considered
fifty project networks under consideration in the current study. The
developed measure showed more sensitivity to the changes in the
network data and gives accurate quantified results when comparing
the complexities of networks.
Abstract: Self-Excited Induction Generator (SEIG) builds up voltage while it enters in its magnetic saturation region. Due to non-linear magnetic characteristics, the performance analysis of SEIG involves cumbersome mathematical computations. The dependence of air-gap voltage on saturated magnetizing reactance can only be established at rated frequency by conducting a laboratory test commonly known as synchronous run test. But, there is no laboratory method to determine saturated magnetizing reactance and air-gap voltage of SEIG at varying speed, terminal capacitance and other loading conditions. For overall analysis of SEIG, prior information of magnetizing reactance, generated frequency and air-gap voltage is essentially required. Thus, analytical methods are the only alternative to determine these variables. Non-existence of direct mathematical relationship of these variables for different terminal conditions has forced the researchers to evolve new computational techniques. Artificial Neural Networks (ANNs) are very useful for solution of such complex problems, as they do not require any a priori information about the system. In this paper, an attempt is made to use cascaded neural networks to first determine the generated frequency and magnetizing reactance with varying terminal conditions and then air-gap voltage of SEIG. The results obtained from the ANN model are used to evaluate the overall performance of SEIG and are found to be in good agreement with experimental results. Hence, it is concluded that analysis of SEIG can be carried out effectively using ANNs.