Abstract: Application of Expert System in the area of agriculture would take the form of Integrated Crop Management decision aids and would encompass water management, fertilizer management, crop protection systems and identification of implements. In order to remain competitive, the modern farmer often relies on agricultural specialists and advisors to provide information for decision-making. An expert system normally composed of a knowledge base (information, heuristics, etc.), inference engine (analyzes knowledge base), and end user interface (accepting inputs, generating outputs). Software named 'CROP-9-DSS' incorporating all modern features like, graphics, photos, video clippings etc. has been developed. This package will aid as a decision support system for identification of pest and diseases with control measures, fertilizer recommendation system, water management system and identification of farm implements for leading crops of Kerala (India) namely Coconut, Rice, Cashew, Pepper, Banana, four vegetables like Amaranthus, Bhindi, Brinjal and Cucurbits. 'CROP-9-DSS' will act as an expert system to agricultural officers, scientists in the field of agriculture and extension workers for decision-making and help them in suggesting suitable recommendations.
Abstract: This study presents a simulation model for converting coal to methanol, based on gasification technology with the commercial chemical process simulator, Pro/II® V8.1.1. The methanol plant consists of air separation unit (ASU), gasification unit, gas clean-up unit, and methanol synthetic unit. The clean syngas is produced with the first three operating units, and the model has been verified with the reference data from United States Environment Protection Agency. The liquid phase methanol (LPMEOHTM) process is adopted in the methanol synthetic unit. Clean syngas goes through gas handing section to reach the reaction requirement, reactor loop/catalyst to generate methanol, and methanol distillation to get desired purity over 99.9 wt%. The ratio of the total energy combined with methanol and dimethyl ether to that of feed coal is 78.5% (gross efficiency). The net efficiency is 64.2% with the internal power consumption taken into account, based on the assumption that the efficiency of electricity generation is 40%.
Abstract: In this paper, we introduce an effective strategy for
subgoal division and ordering based upon recursive subgoals and
combine this strategy with a genetic-based planning approach. This
strategy can be applied to domains with conjunctive goals. The main
idea is to recursively decompose a goal into a set of serializable
subgoals and to specify a strict ordering among the subgoals.
Empirical results show that the recursive subgoal strategy reduces the
size of the search space and improves the quality of solutions to
planning problems.
Abstract: In this paper, the structural genetic algorithm is used to optimize the neural network to control the joint movements of robotic arm. The robotic arm has also been modeled in 3D and simulated in real-time in MATLAB. It is found that Neural Networks provide a simple and effective way to control the robot tasks. Computer simulation examples are given to illustrate the significance of this method. By combining Genetic Algorithm optimization method and Neural Networks for the given robotic arm with 5 D.O.F. the obtained the results shown that the base joint movements overshooting time without controller was about 0.5 seconds, while with Neural Network controller (optimized with Genetic Algorithm) was about 0.2 seconds, and the population size of 150 gave best results.
Abstract: This research studied the simulation of increased
ambient ozone to estimate nutrient content and genetic changes in
two Thai soybean cultivars (Chiang Mai 60 and Srisumrong 1).
Ozone stress conditions affected proteins and lipids. It was found
that proteins decreased, but lipids increased. Srisumrong 1 cultivars
were more sensitive to ozone stress than Chiang Mai 60 cultivars.
The effect of ozone stress conditions on plant phenotype and
genotype was analyzed using the AFLP technique for the 2 Thai
soybean cultivars (Chiang Mai 60 and Srisumrong 1).
Abstract: Markov games can be effectively used to design
controllers for nonlinear systems. The paper presents two novel
controller design algorithms by incorporating ideas from gametheory
literature that address safety and consistency issues of the
'learned' control strategy. A more widely used approach for
controller design is the H∞ optimal control, which suffers from high
computational demand and at times, may be infeasible. We generate
an optimal control policy for the agent (controller) via a simple
Linear Program enabling the controller to learn about the unknown
environment. The controller is facing an unknown environment and
in our formulation this environment corresponds to the behavior rules
of the noise modeled as the opponent. Proposed approaches aim to
achieve 'safe-consistent' and 'safe-universally consistent' controller
behavior by hybridizing 'min-max', 'fictitious play' and 'cautious
fictitious play' approaches drawn from game theory. We empirically
evaluate the approaches on a simulated Inverted Pendulum swing-up
task and compare its performance against standard Q learning.
Abstract: A strategy is implemented to find the improved configuration design of an existing aircraft structure by executing topology and shape optimizations. Structural analysis of the Initial Design Space is performed in ANSYS under the loads pertinent to operating and ground conditions. By using the FEA results and data, an initial optimized layout configuration is attained by exploiting nonparametric topology optimization in TOSCA software. Topological optimized surfaces are then smoothened and imported in ANSYS to develop the geometrical features. Nodes at the critical locations of resulting voids are selected for sketching rough profiles. Rough profiles are further refined and CAD feasible geometric features are generated. The modified model is then analyzed under the same loadings and constraints as defined for topology optimization. Shape at the peak stress concentration areas are further optimized by exploiting the shape optimization in TOSCA.shape module. The harmonized stressed model with the modified surfaces is then imported in CATIA to develop the final design.
Abstract: Earthquakes are natural phenomena that occur with influence of a lot of parameters such as seismic activity, changing in the ground waters' motion, changing in the water-s temperature, etc. On the other hand, the radon gas concentrations in soil vary as nonlinear generally with earthquakes. Continuous measurement of the soil radon gas is very important for determination of characteristic of the seismic activity. The radon gas changes as continuous with strain occurring within the Earth-s surface during an earthquake and effects from the physical and the chemical processes such as soil structure, soil permeability, soil temperature, the barometric pressure, etc. Therefore, at the modeling researches are notsufficient to knowthe concentration ofradon gas. In this research, we determined relationships between radon emissions based on the environmental parameters and earthquakes occurring along the East Anatolian Fault Zone (EAFZ), Turkiye and predicted magnitudes of some earthquakes with the artificial neural network (ANN) model.
Abstract: The general purpose processors that are used in
embedded systems must support constraints like execution time,
power consumption, code size and so on. On the other hand an
Application Specific Instruction-set Processor (ASIP) has advantages
in terms of power consumption, performance and flexibility. In this
paper, a 16-bit Application Specific Instruction-set processor for the
sensor data transfer is proposed. The designed processor architecture
consists of on-chip transmitter and receiver modules along with the
processing and controlling units to enable the data transmission and
reception on a single die. The data transfer is accomplished with less
number of instructions as compared with the general purpose
processor. The ASIP core operates at a maximum clock frequency of
1.132GHz with a delay of 0.883ns and consumes 569.63mW power
at an operating voltage of 1.2V. The ASIP is implemented in Verilog
HDL using the Xilinx platform on Virtex4.
Abstract: Nowaday-s, many organizations use systems that
support business process as a whole or partially. However, in some
application domains, like software development and health care
processes, a normative Process Aware System (PAS) is not suitable,
because a flexible support is needed to respond rapidly to new
process models. On the other hand, a flexible Process Aware System
may be vulnerable to undesirable and fraudulent executions, which
imposes a tradeoff between flexibility and security. In order to make
this tradeoff available, a genetic-based anomaly detection model for
logs of Process Aware Systems is presented in this paper. The
detection of an anomalous trace is based on discovering an
appropriate process model by using genetic process mining and
detecting traces that do not fit the appropriate model as anomalous
trace; therefore, when used in PAS, this model is an automated
solution that can support coexistence of flexibility and security.
Abstract: The genetic algorithm (GA) based solution techniques
are found suitable for optimization because of their ability of
simultaneous multidimensional search. Many GA-variants have been
tried in the past to solve optimal power flow (OPF), one of the
nonlinear problems of electric power system. The issues like
convergence speed and accuracy of the optimal solution obtained
after number of generations using GA techniques and handling
system constraints in OPF are subjects of discussion. The results
obtained for GA-Fuzzy OPF on various power systems have shown
faster convergence and lesser generation costs as compared to other
approaches. This paper presents an enhanced GA-Fuzzy OPF (EGAOPF)
using penalty factors to handle line flow constraints and load
bus voltage limits for both normal network and contingency case
with congestion. In addition to crossover and mutation rate
adaptation scheme that adapts crossover and mutation probabilities
for each generation based on fitness values of previous generations, a
block swap operator is also incorporated in proposed EGA-OPF. The
line flow limits and load bus voltage magnitude limits are handled by
incorporating line overflow and load voltage penalty factors
respectively in each chromosome fitness function. The effects of
different penalty factors settings are also analyzed under contingent
state.
Abstract: In the past few years, the use of wireless sensor networks (WSNs) potentially increased in applications such as intrusion detection, forest fire detection, disaster management and battle field. Sensor nodes are generally battery operated low cost devices. The key challenge in the design and operation of WSNs is to prolong the network life time by reducing the energy consumption among sensor nodes. Node clustering is one of the most promising techniques for energy conservation. This paper presents a novel clustering algorithm which maximizes the network lifetime by reducing the number of communication among sensor nodes. This approach also includes new distributed cluster formation technique that enables self-organization of large number of nodes, algorithm for maintaining constant number of clusters by prior selection of cluster head and rotating the role of cluster head to evenly distribute the energy load among all sensor nodes.
Abstract: A multilayer self organizing neural neural network
(MLSONN) architecture for binary object extraction, guided by a beta
activation function and characterized by backpropagation of errors
estimated from the linear indices of fuzziness of the network output
states, is discussed. Since the MLSONN architecture is designed to
operate in a single point fixed/uniform thresholding scenario, it does
not take into cognizance the heterogeneity of image information in
the extraction process. The performance of the MLSONN architecture
with representative values of the threshold parameters of the beta
activation function employed is also studied. A three layer bidirectional
self organizing neural network (BDSONN) architecture
comprising fully connected neurons, for the extraction of objects from
a noisy background and capable of incorporating the underlying image
context heterogeneity through variable and adaptive thresholding,
is proposed in this article. The input layer of the network architecture
represents the fuzzy membership information of the image scene to
be extracted. The second layer (the intermediate layer) and the final
layer (the output layer) of the network architecture deal with the self
supervised object extraction task by bi-directional propagation of the
network states. Each layer except the output layer is connected to the
next layer following a neighborhood based topology. The output layer
neurons are in turn, connected to the intermediate layer following
similar topology, thus forming a counter-propagating architecture
with the intermediate layer. The novelty of the proposed architecture
is that the assignment/updating of the inter-layer connection weights
are done using the relative fuzzy membership values at the constituent
neurons in the different network layers. Another interesting feature
of the network lies in the fact that the processing capabilities of
the intermediate and the output layer neurons are guided by a beta
activation function, which uses image context sensitive adaptive
thresholding arising out of the fuzzy cardinality estimates of the
different network neighborhood fuzzy subsets, rather than resorting to
fixed and single point thresholding. An application of the proposed
architecture for object extraction is demonstrated using a synthetic
and a real life image. The extraction efficiency of the proposed
network architecture is evaluated by a proposed system transfer index
characteristic of the network.
Abstract: Multimedia security is an incredibly significant area of concern. The paper aims to discuss a robust image watermarking scheme, which can withstand geometric attacks. The source image is initially moment normalized in order to make it withstand geometric attacks. The moment normalized image is wavelet transformed. The first level wavelet transformed image is segmented into blocks if size 8x8. The product of mean and standard and standard deviation of each block is computed. The second level wavelet transformed image is divided into 8x8 blocks. The product of block mean and the standard deviation are computed. The difference between products in the two levels forms the watermark. The watermark is inserted by modulating the coefficients of the mid frequencies. The modulated image is inverse wavelet transformed and inverse moment normalized to generate the watermarked image. The watermarked image is now ready for transmission. The proposed scheme can be used to validate identification cards and financial instruments. The performance of this scheme has been evaluated using a set of parameters. Experimental results show the effectiveness of this scheme.
Abstract: An accurate optimal design of laminated composite
structures may present considerable difficulties due to the complexity
and multi-modality of the functional design space. The Big Bang
– Big Crunch (BB-BC) optimization method is a relatively new
technique and has already proved to be a valuable tool for structural
optimization. In the present study the exceptional efficiency of the
method is demonstrated by an example of the lay-up optimization
of multilayered anisotropic cylinders based on a three-dimensional
elasticity solution. It is shown that, due to its simplicity and speed,
the BB-BC is much more efficient for this class of problems when
compared to the genetic algorithms.
Abstract: This paper reviews the greenhouse gas emissions of prefabrication elements for residential development in Hong Kong. Prefabrication becomes a common practice in residential development in Hong Kong and is considered as a green approach. In Hong Kong, prefabrication took place at factories in Pearl River Delta. Although prefabrication reduces construction wastage, it might generate more greenhouse gas emission from transportation and manufacturing processes. This study attempts to measure the “cradle to site" greenhouse gas emission from prefabrication elements for a public housing development in Kai Tak area. The findings could help further reduction of greenhouse gas emissions through process improvement.
Abstract: This paper presents a synthetic jet air blower actuated
by PZT for air blowing for air-breathing micro PEM fuel cell. The
several factors to affect the performance of air-breathing PEM fuel cell
such as air flow rate, opening ratio and cathode open type in the
cathode side were studied. Especially, an air flow rate is critical
condition to improve its performance. In this paper, we developed a
synthetic jet air blower to supply a high stoichiometric air flow. The
synthetic jet mechanism is a zero mass flux device that converts
electrical energy into the momentum. The synthetic jet actuation is
usually generated by a traditional PZT actuator, which consists of a
small cylindrical cavity, in/outlet channel and PZT diaphragms. The
flow rate of the fabricated synthetic jet air blower was 400cc/min at
550Hz and its power consumption was very low under 0.3W. The
proposed air-breathing PEM fuel cell which installed synthetic jet air
blower was higher performance and stability during continuous
operation than the air-breathing fuel cell without auxiliary device to
supply the air. The results showed that the maximum power density
was 188mW/cm2 at 400mA/cm2. This maximum power density and
durability were improved more than 40% and 20%, respectively.
Abstract: This paper explores the implementation of adaptive
coding and modulation schemes for Multiple-Input Multiple-Output
Orthogonal Frequency Division Multiplexing (MIMO-OFDM) feedback
systems. Adaptive coding and modulation enables robust and
spectrally-efficient transmission over time-varying channels. The basic
premise is to estimate the channel at the receiver and feed this estimate
back to the transmitter, so that the transmission scheme can be
adapted relative to the channel characteristics. Two types of codebook
based channel feedback techniques are used in this work. The longterm
and short-term CSI at the transmitter is used for efficient channel
utilization. OFDM is a powerful technique employed in communication
systems suffering from frequency selectivity. Combined with
multiple antennas at the transmitter and receiver, OFDM proves to be
robust against delay spread. Moreover, it leads to significant data rates
with improved bit error performance over links having only a single
antenna at both the transmitter and receiver. The coded modulation
increases the effective transmit power relative to uncoded variablerate
variable-power MQAM performance for MIMO-OFDM feedback
system. Hence proposed arrangement becomes an attractive approach
to achieve enhanced spectral efficiency and improved error rate
performance for next generation high speed wireless communication
systems.
Abstract: This paper presents the modeling and simulation of a hybrid proton exchange membrane fuel cell (PEMFC) with an energy storage system for use in a stand-alone distributed generation (DG) system. The simulation model consists of fuel cell DG, lead-acid battery, maximum power point tracking and power conditioning unit which is modeled in the MATLAB/Simulink platform. Poor loadfollowing characteristics and slow response to rapid load changes are some of the weaknesses of PEMFC because of the gas processing reaction and the fuel cell dynamics. To address the load-tracking issues in PEMFC, a hybrid PEMFC and battery storage system is considered and modelled. The model utilizes PEMFC as the main energy source whereas the battery functions as energy storage to compensate for the limitations of PEMFC.Simulation results are given to show the overall system performance under light and heavyloading conditions.
Abstract: Since IEC61850 substation communication standard represents the trend to develop new generations of Substation Automation System (SAS), many IED manufacturers pursue this technique and apply for KEMA. In order to put on the market to meet customer demand as fast as possible, manufacturers often apply their products only for basic environment standard certification but claim to conform to IEC61850 certification. Since verification institutes generally perform verification tests only on specific IEDs of the manufacturers, the interoperability between all certified IEDs cannot be guaranteed. Therefore the interoperability between IEDs from different manufacturers needs to be tested. Based upon the above reasons, this study applies the definitions of the information models, communication service, GOOSE functionality and Substation Configuration Language (SCL) of the IEC61850 to build the concept of communication protocols, and build the test environment. The procedures of the test of the data collection and exchange of the P2P communication mode and Client / Server communication mode in IEC61850 are outlined as follows. First, test the IED GOOSE messages communication capability from different manufacturers. Second, collect IED data from each IED with SCADA system and use HMI to display the SCADA platform. Finally, problems generally encountered in the test procedure are summarized.