Artificial Neural Network with Steepest Descent Backpropagation Training Algorithm for Modeling Inverse Kinematics of Manipulator
Inverse kinematics analysis plays an important role in developing a robot manipulator. But it is not too easy to derive the inverse kinematic equation of a robot manipulator especially robot manipulator which has numerous degree of freedom. This paper describes an application of Artificial Neural Network for modeling the inverse kinematics equation of a robot manipulator. In this case, the robot has three degree of freedoms and the robot was implemented for drilling a printed circuit board. The artificial neural network architecture used for modeling is a multilayer perceptron networks with steepest descent backpropagation training algorithm. The designed artificial neural network has 2 inputs, 2 outputs and varies in number of hidden layer. Experiments were done in variation of number of hidden layer and learning rate. Experimental results show that the best architecture of artificial neural network used for modeling inverse kinematics of is multilayer perceptron with 1 hidden layer and 38 neurons per hidden layer. This network resulted a RMSE value of 0.01474.
A Comparison of Deterministic and Probabilistic Methods for Determining the Required Amount of Spinning Reserve
In an electric power system, spinning reserve
requirements can be determined by using deterministic and/or
probabilistic measures. Although deterministic methods are usual in
many systems, application of probabilistic methods becomes
increasingly important in the new environment of the electric power
utility industry. This is because of the increased uncertainty
associated with competition. In this paper 1) a new probabilistic
method is presented which considers the reliability of transmission
system in a simplified manner and 2) deterministic and probabilistic
methods are compared. The studied methods are applied to the Roy
Billinton Test System (RBTS).
Object Tracking using MACH filter and Optical Flow in Cluttered Scenes and Variable Lighting Conditions
Vision based tracking problem is solved through a
combination of optical flow, MACH filter and log r-θ mapping.
Optical flow is used for detecting regions of movement in video
frames acquired under variable lighting conditions. The region of
movement is segmented and then searched for the target. A template
is used for target recognition on the segmented regions for detecting
the region of interest. The template is trained offline on a sequence of
target images that are created using the MACH filter and log r-θ
mapping. The template is applied on areas of movement in
successive frames and strong correlation is seen for in-class targets.
Correlation peaks above a certain threshold indicate the presence of
target and the target is tracked over successive frames.
High Level Synthesis of Kahn Process Networks(KPN) for Streaming Applications
Streaming Applications usually run in parallel or in
series that incrementally transform a stream of input data. It poses a
design challenge to break such an application into distinguishable
blocks and then to map them into independent hardware processing
elements. For this, there is required a generic controller that
automatically maps such a stream of data into independent processing
elements without any dependencies and manual considerations. In
this paper, Kahn Process Networks (KPN) for such streaming
applications is designed and developed that will be mapped on
MPSoC. This is designed in such a way that there is a generic Cbased
compiler that will take the mapping specifications as an input
from the user and then it will automate these design constraints and
automatically generate the synthesized RTL optimized code for
Development of a Non-invasive System to Measure the Thickness of the Subcutaneous Adipose Tissue Layer for Human
To measure the thickness of the subcutaneous adipose
tissue layer, a non-invasive optical measurement system (λ=1300 nm)
is introduced. Animal and human subjects are used for the
experiments. The results of human subjects are compared with the data
of ultrasound device measurements, and a high correlation (r=0.94 for
n=11) is observed. There are two modes in the corresponding signals
measured by the optical system, which can be explained by
two-layered and three-layered tissue models. If the target tissue is
thinner than the critical thickness, detected data using diffuse
reflectance method follow the three-layered tissue model, so the data
increase as the thickness increases. On the other hand, if the target
tissue is thicker than the critical thickness, the data follow the
two-layered tissue model, so they decrease as the thickness increases.
Hand Gesture Recognition Based on Combined Features Extraction
Hand gesture is an active area of research in the vision
community, mainly for the purpose of sign language recognition and
Human Computer Interaction. In this paper, we propose a system to
recognize alphabet characters (A-Z) and numbers (0-9) in real-time
from stereo color image sequences using Hidden Markov Models
(HMMs). Our system is based on three main stages; automatic segmentation
and preprocessing of the hand regions, feature extraction
and classification. In automatic segmentation and preprocessing stage,
color and 3D depth map are used to detect hands where the hand
trajectory will take place in further step using Mean-shift algorithm
and Kalman filter. In the feature extraction stage, 3D combined features
of location, orientation and velocity with respected to Cartesian
systems are used. And then, k-means clustering is employed for
HMMs codeword. The final stage so-called classification, Baum-
Welch algorithm is used to do a full train for HMMs parameters.
The gesture of alphabets and numbers is recognized using Left-Right
Banded model in conjunction with Viterbi algorithm. Experimental
results demonstrate that, our system can successfully recognize hand
gestures with 98.33% recognition rate.
Optimal Planning of Ground Grid Based on Particle Swam Algorithm
This paper presents an application of particle swarm
optimization (PSO) to the grounding grid planning which compares to
the application of genetic algorithm (GA). Firstly, based on IEEE
Std.80, the cost function of the grounding grid and the constraints of
ground potential rise, step voltage and touch voltage are constructed
for formulating the optimization problem of grounding grid planning.
Secondly, GA and PSO algorithms for obtaining optimal solution of
grounding grid are developed. Finally, a case of grounding grid
planning is shown the superiority and availability of the PSO
algorithm and proposal planning results of grounding grid in cost and
BER Performance of UWB Modulations through S-V Channel Model
BER analysis of Impulse Radio Ultra Wideband (IRUWB) pulse modulations over S-V channel model is proposed in this paper. The UWB pulse is Gaussian monocycle pulse modulated using Pulse Amplitude Modulation (PAM) and Pulse Position Modulation (PPM). The channel model is generated from a modified S-V model. Bit-error rate (BER) is measured over several of bit rates. The result shows that all modulation are appropriate for both LOS and NLOS channel, but PAM gives better performance in bit rates and SNR. Moreover, as standard of speed has been given for UWB, the communication is appropriate with high bit rates in LOS channel.
Fuzzy Controller Design for TCSC to Improve Power Oscillations Damping
Series compensators have been used for many years,
to increase the stability and load ability of transmission line. They
compensate retarded or advanced volt drop of transmission lines
by placing advanced or retarded voltage in series with them to
compensate the effective reactance, which cause to increase load
ability of transmission lines. In this paper, two method of fuzzy
controller, based on power reference tracking and impedance
reference tracking have been developed on TCSC controller in
order to increase load ability and improving power oscillation
damping of system. In these methods, fire angle of thyristors are
determined directly through the special Rule-bases with the error
and change of error as the inputs. The simulation results of two
area four- machines power system show the good performance of
power oscillation damping in system. Comparison of this method
with classical PI controller shows the increasing speed of system
response in power oscillation damping.
Wireless Sensor Networks for Swiftlet Farms Monitoring
This paper provides an in-depth study of Wireless
Sensor Network (WSN) application to monitor and control the
swiftlet habitat. A set of system design is designed and developed
that includes the hardware design of the nodes, Graphical User
Interface (GUI) software, sensor network, and interconnectivity for
remote data access and management. System architecture is proposed
to address the requirements for habitat monitoring. Such applicationdriven
design provides and identify important areas of further work
in data sampling, communications and networking. For this
monitoring system, a sensor node (MTS400), IRIS and Micaz radio
transceivers, and a USB interfaced gateway base station of Crossbow
(Xbow) Technology WSN are employed. The GUI of this monitoring
system is written using a Laboratory Virtual Instrumentation
Engineering Workbench (LabVIEW) along with Xbow Technology
drivers provided by National Instrument. As a result, this monitoring
system is capable of collecting data and presents it in both tables and
waveform charts for further analysis. This system is also able to send
notification message by email provided Internet connectivity is
available whenever changes on habitat at remote sites (swiftlet farms)
occur. Other functions that have been implemented in this system
are the database system for record and management purposes; remote
access through the internet using LogMeIn software. Finally, this
research draws a conclusion that a WSN for monitoring swiftlet
habitat can be effectively used to monitor and manage swiftlet
farming industry in Sarawak.
Study on Discharge Current Phenomena of Epoxy Resin Insulator Specimen
This paper presents the experimental results of
discharge current phenomena on various humidity, temperature,
pressure and pollutant conditions of epoxy resin specimen. The
leakage distance of specimen was 3 cm, that it was supplied by high
voltage. The polluted condition was given with NaCl artificial
pollutant. The conducted measurements were discharge current and
applied voltage. The specimen was put in a hermetically sealed
chamber, and the current waveforms were analyzed with FFT.
The result indicated that on discharge condition, the fifth
harmonics still had dominant, rather than third one. The third
harmonics tent to be appeared on low pressure heavily polluted
condition, and followed by high humidity heavily polluted condition.
On the heavily polluted specimen, the peaks discharge current points
would be high and more frequent. Nevertheless, the specimen still
had capacitive property. Besides that, usually discharge current
points were more frequent. The influence of low pressure was still
dominant to be easier to discharge. The non-linear property would be
appear explicitly on low pressure and heavily polluted condition.
Performance Study on Audio Codec and Session Transfer of Open Source VoIP applications
Voice over Internet Protocol (VoIP) application or commonly known as softphone has been developing an increasingly large market in today-s telecommunication world and the trend is expected to continue with the enhancement of additional features. This includes leveraging on the existing presence services, location and contextual information to enable more ubiquitous and seamless communications. In this paper, we discuss the concept of seamless session transfer for real-time application such as VoIP and IPTV, and our prototype implementation of such concept on a selected open source VoIP application. The first part of this paper is about conducting performance evaluation and assessments across some commonly found open source VoIP applications that are Ekiga, Kphone, Linphone and Twinkle so as to identify one of them for implementing our design of seamless session transfer. Subjective testing has been carried out to evaluate the audio performance on these VoIP applications and rank them according to their Mean Opinion Score (MOS) results. The second part of this paper is to discuss on the performance evaluations of our prototype implementation of session transfer using Linphone.
A Study of Grounding Grid Characteristics with Conductive Concrete
The purpose of this paper is to improve electromagnetic characteristics on grounding grid by applying the conductive concrete. The conductive concrete in this study is under an extra high voltage (EHV, 345kV) system located in a high-tech industrial park or science park. Instead of surrounding soil of grounding grid, the application of conductive concrete can reduce equipment damage and body damage caused by switching surges. The focus of the two cases on the EHV distribution system in a high-tech industrial park is presented to analyze four soil material styles. By comparing several soil material styles, the study results have shown that the conductive concrete can effectively reduce the negative damages caused by electromagnetic transient. The adoption of the style of grounding grid located 1.0 (m) underground and conductive concrete located from the ground surface to 1.25 (m) underground can obviously improve the electromagnetic characteristics so as to advance protective efficiency.
Transformation of Vocal Characteristics: A Review of Literature
The transformation of vocal characteristics aims at
modifying voice such that the intelligibility of aphonic voice is
increased or the voice characteristics of a speaker (source speaker) to
be perceived as if another speaker (target speaker) had uttered it. In
this paper, the current state-of-the-art voice characteristics
transformation methodology is reviewed. Special emphasis is placed
on voice transformation methodology and issues for improving the
transformed speech quality in intelligibility and naturalness are
discussed. In particular, it is suggested to use the modulation theory
of speech as a base for research on high quality voice transformation.
This approach allows one to separate linguistic, expressive, organic
and perspective information of speech, based on an analysis of how
they are fused when speech is produced. Therefore, this theory
provides the fundamentals not only for manipulating non-linguistic,
extra-/paralinguistic and intra-linguistic variables for voice
transformation, but also for paving the way for easily transposing the
existing voice transformation methods to emotion-related voice
quality transformation and speaking style transformation. From the
perspectives of human speech production and perception, the popular
voice transformation techniques are described and classified them
based on the underlying principles either from the speech production
or perception mechanisms or from both. In addition, the advantages
and limitations of voice transformation techniques and the
experimental manipulation of vocal cues are discussed through
examples from past and present research. Finally, a conclusion and
road map are pointed out for more natural voice transformation
algorithms in the future.
An ACO Based Algorithm for Distribution Networks Including Dispersed Generations
With Power system movement toward restructuring along with factors such as life environment pollution, problems of transmission expansion and with advancement in construction technology of small generation units, it is expected that small units like wind turbines, fuel cells, photovoltaic, ... that most of the time connect to the distribution networks play a very essential role in electric power industry. With increase in developing usage of small generation units, management of distribution networks should be reviewed. The target of this paper is to present a new method for optimal management of active and reactive power in distribution networks with regard to costs pertaining to various types of dispersed generations, capacitors and cost of electric energy achieved from network. In other words, in this method it-s endeavored to select optimal sources of active and reactive power generation and controlling equipments such as dispersed generations, capacitors, under load tapchanger transformers and substations in a way that firstly costs in relation to them are minimized and secondly technical and physical constraints are regarded. Because the optimal management of distribution networks is an optimization problem with continuous and discrete variables, the new evolutionary method based on Ant Colony Algorithm has been applied. The simulation results of the method tested on two cases containing 23 and 34 buses exist and will be shown at later sections.
Two Stage Control Method Using a Disturbance Observer and a Kalman Filter
This paper describes the two stage control using a disturbance observer and a Kalman filter. The system feedback uses the estimated state when it controls the speed. After the change-over point, its feedback uses the controlled plant output when it controls the position. To change the system continually, a change-over point has to be determined pertinently, and the controlled plant input has to be adjusted by the addition of the appropriate value. The proposed method has noise-reduction effect. It changes the system continually, even if the controlled plant identification has the error. Although the conventional method needs a speed sensor, the proposed method does not need it. The proposed method has a superior robustness compared with the conventional two stage control.
Contourlet versus Wavelet Transform for a Robust Digital Image Watermarking Technique
In this paper, a watermarking algorithm that uses the wavelet transform with Multiple Description Coding (MDC) and Quantization Index Modulation (QIM) concepts is introduced. Also, the paper investigates the role of Contourlet Transform (CT) versus Wavelet Transform (WT) in providing robust image watermarking. Two measures are utilized in the comparison between the waveletbased and the contourlet-based methods; Peak Signal to Noise Ratio (PSNR) and Normalized Cross-Correlation (NCC). Experimental results reveal that the introduced algorithm is robust against different attacks and has good results compared to the contourlet-based algorithm.
Power System Contingency Analysis Using Multiagent Systems
The demand of the energy management systems (EMS) set forth by modern power systems requires fast energy management systems. Contingency analysis is among the functions in EMS which is time consuming. In order to handle this limitation, this paper introduces agent based technology in the contingency analysis. The main function of agents is to speed up the performance. Negotiations process in decision making is explained and the issue set forth is the minimization of the operating costs. The IEEE 14 bus system and its line outage have been used in the research and simulation results are presented.
Network Application Identification Based on Communication Characteristics of Application Messages
A person-to-person information sharing is easily realized
by P2P networks in which servers are not essential. Leakage
of information, which are caused by malicious accesses for P2P
networks, has become a new social issues. To prevent information
leakage, it is necessary to detect and block traffics of P2P software.
Since some P2P softwares can spoof port numbers, it is difficult to
detect the traffics sent from P2P softwares by using port numbers.
It is more difficult to devise effective countermeasures for detecting
the software because their protocol are not public.
In this paper, a discriminating method of network applications
based on communication characteristics of application messages
without port numbers is proposed. The proposed method is based
on an assumption that there can be some rules about time intervals
to transmit messages in application layer and the number of necessary
packets to send one message. By extracting the rule from network
traffic, the proposed method can discriminate applications without
Neural Networks and Particle Swarm Optimization Based MPPT for Small Wind Power Generator
This paper proposes the method combining artificial
neural network (ANN) with particle swarm optimization (PSO) to
implement the maximum power point tracking (MPPT) by controlling
the rotor speed of the wind generator. First, the measurements of wind
speed, rotor speed of wind power generator and output power of wind
power generator are applied to train artificial neural network and to
estimate the wind speed. Second, the method mentioned above is
applied to estimate and control the optimal rotor speed of the wind
turbine so as to output the maximum power. Finally, the result reveals
that the control system discussed in this paper extracts the maximum
output power of wind generator within the short duration even in the
conditions of wind speed and load impedance variation.
Control of a DC Servomotor Using Fuzzy Logic Sliding Mode Model Following Controller
A DC servomotor position control system using a Fuzzy Logic Sliding mode Model Following Control or FLSMFC approach is presented. The FLSMFC structure consists of an integrator and variable structure system. The integral control is introduced into it in order to eliminated steady state error due to step and ramp command inputs and improve control precision, while the fuzzy control would maintain the insensitivity to parameter variation and disturbances. The FLSMFC strategy is implemented and applied to a position control of a DC servomotor drives. Experimental results indicated that FLSMFC system performance with respect to the sensitivity to parameter variations is greatly reduced. Also, excellent control effects and avoids the chattering phenomenon.
A Voltage Based Maximum Power Point Tracker for Low Power and Low Cost Photovoltaic Applications
This paper describes the design of a voltage based maximum power point tracker (MPPT) for photovoltaic (PV) applications. Of the various MPPT methods, the voltage based method is considered to be the simplest and cost effective. The major disadvantage of this method is that the PV array is disconnected from the load for the sampling of its open circuit voltage, which inevitably results in power loss. Another disadvantage, in case of rapid irradiance variation, is that if the duration between two successive samplings, called the sampling period, is too long there is a considerable loss. This is because the output voltage of the PV array follows the unchanged reference during one sampling period. Once a maximum power point (MPP) is tracked and a change in irradiation occurs between two successive samplings, then the new MPP is not tracked until the next sampling of the PV array voltage. This paper proposes an MPPT circuit in which the sampling interval of the PV array voltage, and the sampling period have been shortened. The sample and hold circuit has also been simplified. The proposed circuit does not utilize a microcontroller or a digital signal processor and is thus suitable for low cost and low power applications.
Enhanced Parallel-Connected Comb Filter Method for Multiple Pitch Estimation
This paper presents an improvement method of
the multiple pitch estimation algorithm using comb filters.
Conventionally the pitch was estimated by using parallel
-connected comb filters method (PCF). However, PCF has
problems which often fail in the pitch estimation when there is
the fundamental frequency of higher tone near harmonics of
lower tone. Therefore the estimation is assigned to a wrong
note when shared frequencies happen. This issue often occurs
in estimating octave 3 or more. Proposed method, for solving
the problem, estimates the pitch with every harmonic instead of
every octave. As a result, our method reaches the accuracy of
more than 80%.
Hybrid Optimization of Emission and Economic Dispatch by the Sigmoid Decreasing Inertia Weight Particle Swarm Optimization
This paper present an efficient and reliable technique of optimization which combined fuel cost economic optimization and emission dispatch using the Sigmoid Decreasing Inertia Weight Particle Swarm Optimization algorithm (PSO) to reduce the cost of fuel and pollutants resulting from fuel combustion by keeping the output of generators, bus voltages, shunt capacitors and transformer tap settings within the security boundary. The performance of the proposed algorithm has been demonstrated on IEEE 30-bus system with six generating units. The results clearly show that the proposed algorithm gives better and faster speed convergence then linearly decreasing inertia weight.
Distance Transmission Line Protection Based on Radial Basis Function Neural Network
To determine the presence and location of faults in a transmission by the adaptation of protective distance relay based on the measurement of fixed settings as line impedance is achieved by several different techniques. Moreover, a fast, accurate and robust technique for real-time purposes is required for the modern power systems. The appliance of radial basis function neural network in transmission line protection is demonstrated in this paper. The method applies the power system via voltage and current signals to learn the hidden relationship presented in the input patterns. It is experiential that the proposed technique is competent to identify the particular fault direction more speedily. System simulations studied show that the proposed approach is able to distinguish the direction of a fault on a transmission line swiftly and correctly, therefore suitable for the real-time purposes.
Discrete Modified Internal Model Control for a nth-order Plant with an Integrator and Dead-time
This paper deals with a design method of a discrete
modified Internal Model Control (IMC) for a plant with an integrator
and dead time. If there is a load disturbance in the input or output side
of the plant, the proposed control system can eliminate the steady-state
error caused by it. The disturbance compensator in this method is
simple and its order is low regardless of that of a plant. The simulation
studies show that the proposed method has superior performance for a
load disturbance rejection and robustness.
Analysis of Partially Shaded PV Modules Using Piecewise Linear Parallel Branches Model
This paper presents an equivalent circuit model based on piecewise linear parallel branches (PLPB) to study solar cell modules which are partially shaded. The PLPB model can easily be used in circuit simulation software such as the ElectroMagnetic Transients Program (EMTP). This PLPB model allows the user to simulate several different configurations of solar cells, the influence of partial shadowing on a single or multiple cells, the influence of the number of solar cells protected by a bypass diode and the effect of the cell connection configuration on partial shadowing.
Optimization Method Based MPPT for Wind Power Generators
This paper proposes the method combining artificial neural network with particle swarm optimization (PSO) to implement the maximum power point tracking (MPPT) by controlling the rotor speed of the wind generator. With the measurements of wind speed, rotor speed of wind generator and output power, the artificial neural network can be trained and the wind speed can be estimated. The proposed control system in this paper provides a manner for searching the maximum output power of wind generator even under the conditions of varying wind speed and load impedance.
Linear Cryptanalysis for a Chaos-Based Stream Cipher
Linear cryptanalysis methods are rarely used to improve the security of chaotic stream ciphers. In this paper, we apply linear cryptanalysis to a chaotic stream cipher which was designed by strictly using the basic design criterion of cryptosystem – confusion and diffusion. We show that this well-designed chaos-based stream cipher is still insecure against distinguishing attack. This distinguishing attack promotes the further improvement of the cipher.
A Servo Control System Using the Loop Shaping Design Procedure
This paper describes an expanded system for a servo
system design by using the Loop Shaping Design Procedure (LSDP).
LSDP is one of the H∞ design procedure. By conducting Loop
Shaping with a compensator and robust stabilization to satisfy the
index function, we get the feedback controller that makes the control
system stable. In this paper, we propose an expanded system for a
servo system design and apply to the DC motor. The proposed method
performs well in the DC motor positioning control. It has no
steady-state error in the disturbance response and it has robust
A Matching Algorithm of Minutiae for Real Time Fingerprint Identification System
A lot of matching algorithms with different characteristics have been introduced in recent years. For real time systems these algorithms are usually based on minutiae features. In this paper we introduce a novel approach for feature extraction in which the extracted features are independent of shift and rotation of the fingerprint and at the meantime the matching operation is performed much more easily and with higher speed and accuracy. In this new approach first for any fingerprint a reference point and a reference orientation is determined and then based on this information features are converted into polar coordinates. Due to high speed and accuracy of this approach and small volume of extracted features and easily execution of matching operation this approach is the most appropriate for real time applications.
Role of GIS in Distribution Power Systems
With the prevalence of computer and development of information technology, Geographic Information Systems (GIS) have long used for a variety of applications in electrical engineering. GIS are designed to support the analysis, management, manipulation and mapping of spatial data. This paper presents several usages of GIS in power utilities such as automated route selection for the construction of new power lines which uses a dynamic programming model for route optimization, load forecasting and optimizing planning of substation-s location and capacity with comprehensive algorithm which involves an accurate small-area electric load forecasting procedure and simulates the different cost functions of substations.
Adaptive Multi-Camera Shooting System Based on Dynamic Workflow in a Compact Studio
We developed a multi-camera control system that a (one) cameraman can operate several cameras at a compact studio. we analyzed a workflow of a cameraman of some program shootings with two cameras and clarified their heavy tasks. The system based on a dynamic workflow which adapts a program progressing and recommends of cameraman. we perform the automation of multicamera controls by modeling of studio environment and perform automatic camera adjustment for suitable angle of view with face detection. Our experiment at a real program shooting showed that one cameraman can carry out the task of shooting sufficiently.
Avoiding Catastrophic Forgetting by a Dual-Network Memory Model Using a Chaotic Neural Network
In neural networks, when new patterns are learned by a network, the new information radically interferes with previously stored patterns. This drawback is called catastrophic forgetting or catastrophic interference. In this paper, we propose a biologically inspired neural network model which overcomes this problem. The proposed model consists of two distinct networks: one is a Hopfield type of chaotic associative memory and the other is a multilayer neural network. We consider that these networks correspond to the hippocampus and the neocortex of the brain, respectively. Information given is firstly stored in the hippocampal network with fast learning algorithm. Then the stored information is recalled by chaotic behavior of each neuron in the hippocampal network. Finally, it is consolidated in the neocortical network by using pseudopatterns. Computer simulation results show that the proposed model has much better ability to avoid catastrophic forgetting in comparison with conventional models.