Abstract: Detection of human emotions has many potential applications. One of application is to quantify attentiveness audience in order evaluate acoustic quality in concern hall. The subjective audio preference that based on from audience is used. To obtain fairness evaluation of acoustic quality, the research proposed system for multimodal emotion detection; one modality based on brain signals that measured using electroencephalogram (EEG) and the second modality is sequences of facial images. In the experiment, an audio signal was customized which consist of normal and disorder sounds. Furthermore, an audio signal was played in order to stimulate positive/negative emotion feedback of volunteers. EEG signal from temporal lobes, i.e. T3 and T4 was used to measured brain response and sequence of facial image was used to monitoring facial expression during volunteer hearing audio signal. On EEG signal, feature was extracted from change information in brain wave, particularly in alpha and beta wave. Feature of facial expression was extracted based on analysis of motion images. We implement an advance optical flow method to detect the most active facial muscle form normal to other emotion expression that represented in vector flow maps. The reduce problem on detection of emotion state, vector flow maps are transformed into compass mapping that represents major directions and velocities of facial movement. The results showed that the power of beta wave is increasing when disorder sound stimulation was given, however for each volunteer was giving different emotion feedback. Based on features derived from facial face images, an optical flow compass mapping was promising to use as additional information to make decision about emotion feedback.
Abstract: A concern that researchers usually face in different
applications of Artificial Neural Network (ANN) is determination of
the size of effective domain in time series. In this paper, trial and
error method was used on groundwater depth time series to determine
the size of effective domain in the series in an observation well in
Union County, New Jersey, U.S. different domains of 20, 40, 60, 80,
100, and 120 preceding day were examined and the 80 days was
considered as effective length of the domain. Data sets in different
domains were fed to a Feed Forward Back Propagation ANN with
one hidden layer and the groundwater depths were forecasted. Root
Mean Square Error (RMSE) and the correlation factor (R2) of
estimated and observed groundwater depths for all domains were
determined. In general, groundwater depth forecast improved, as
evidenced by lower RMSEs and higher R2s, when the domain length
increased from 20 to 120. However, 80 days was selected as the
effective domain because the improvement was less than 1% beyond
that. Forecasted ground water depths utilizing measured daily data
(set #1) and data averaged over the effective domain (set #2) were
compared. It was postulated that more accurate nature of measured
daily data was the reason for a better forecast with lower RMSE
(0.1027 m compared to 0.255 m) in set #1. However, the size of input
data in this set was 80 times the size of input data in set #2; a factor
that may increase the computational effort unpredictably. It was
concluded that 80 daily data may be successfully utilized to lower the
size of input data sets considerably, while maintaining the effective
information in the data set.
Abstract: A novel circuit for generating a signal embedded with
features about data from three sensors is presented. This suggested
circuit is making use of a resistance-to-time converter employing a
bridge amplifier, an integrator and a comparator. The second resistive
sensor (Rz) is transformed into duty cycle. Another bridge with
varying resistor, (Ry) in the feedback of an OP AMP is added in
series to change the amplitude of the resulting signal in a proportional
relationship while keeping the same frequency and duty cycle
representing proportional changes in resistors Rx and Rz already
mentioned. The resultant output signal carries three types of
information embedded as variations of its frequency, duty cycle and
amplitude.
Abstract: Magnetic Resonance Imaging play a vital role in the decision-diagnosis process of brain MR images. For an accurate diagnosis of brain related problems, the experts mostly compares both T1 and T2 weighted images as the information presented in these two images are complementary. In this paper, rotational and translational invariant form of Local binary Pattern (LBP) with additional gray scale information is used to retrieve similar slices of T1 weighted images from T2 weighted images or vice versa. The incorporation of additional gray scale information on LBP can extract more local texture information. The accuracy of retrieval can be improved by extracting moment features of LBP and reweighting the features based on users feedback. Here retrieval is done in a single subject scenario where similar images of a particular subject at a particular level are retrieved, and multiple subjects scenario where relevant images at a particular level across the subjects are retrieved.
Abstract: Although backpropagation ANNs generally predict
better than decision trees do for pattern classification problems, they
are often regarded as black boxes, i.e., their predictions cannot be
explained as those of decision trees. In many applications, it is
desirable to extract knowledge from trained ANNs for the users to
gain a better understanding of how the networks solve the problems.
A new rule extraction algorithm, called rule extraction from artificial
neural networks (REANN) is proposed and implemented to extract
symbolic rules from ANNs. A standard three-layer feedforward ANN
is the basis of the algorithm. A four-phase training algorithm is
proposed for backpropagation learning. Explicitness of the extracted
rules is supported by comparing them to the symbolic rules generated
by other methods. Extracted rules are comparable with other methods
in terms of number of rules, average number of conditions for a rule,
and predictive accuracy. Extensive experimental studies on several
benchmarks classification problems, such as breast cancer, iris,
diabetes, and season classification problems, demonstrate the
effectiveness of the proposed approach with good generalization
ability.
Abstract: In this paper, we will implement three-dimensional pursuit guidance law with feedback linearization control method and study the effects of parameters. First, we introduce guidance laws and equations of motion of a missile. Pursuit guidance law is our highlight. We apply feedback linearization control method to obtain the accelerations to implement pursuit guidance law. The solution makes warhead direction follow with line-of-sight. Final, the simulation results show that the exact solution derived in this paper is correct and some factors e.g. control gain, time delay, are important to implement pursuit guidance law.
Abstract: In a none-super-competitive environment the concepts
of closed system, management control remains to be the dominant
guiding concept to management. The merits of closed loop have been
the sources of most of the management literature and culture for
many decades. It is a useful exercise to investigate and poke into the
dynamics of the control loop phenomenon and draws some lessons to
use for refining the practice of management. This paper examines the
multitude of lessons abstracted from the behavior of the Input /output
/feedback control loop model, which is the core of control theory.
There are numerous lessons that can be learned from the insights this
model would provide and how it parallels the management dynamics
of the organization. It is assumed that an organization is basically a
living system that interacts with the internal and external variables. A
viable control loop is the one that reacts to the variation in the
environment and provide or exert a corrective action. In managing
organizations this is reflected in organizational structure and
management control practices. This paper will report findings that
were a result of examining several abstract scenarios that are
exhibited in the design, operation, and dynamics of the control loop
and how they are projected on the functioning of the organization.
Valuable lessons are drawn in trying to find parallels and new
paradigms, and how the control theory science is reflected in the
design of the organizational structure and management practices. The
paper is structured in a logical and perceptive format. Further
research is needed to extend these findings.
Abstract: This research presents a system for post processing of
data that takes mined flat rules as input and discovers crisp as well as
fuzzy hierarchical structures using Learning Classifier System
approach. Learning Classifier System (LCS) is basically a machine
learning technique that combines evolutionary computing,
reinforcement learning, supervised or unsupervised learning and
heuristics to produce adaptive systems. A LCS learns by interacting
with an environment from which it receives feedback in the form of
numerical reward. Learning is achieved by trying to maximize the
amount of reward received. Crisp description for a concept usually
cannot represent human knowledge completely and practically. In the
proposed Learning Classifier System initial population is constructed
as a random collection of HPR–trees (related production rules) and
crisp / fuzzy hierarchies are evolved. A fuzzy subsumption relation is
suggested for the proposed system and based on Subsumption Matrix
(SM), a suitable fitness function is proposed. Suitable genetic
operators are proposed for the chosen chromosome representation
method. For implementing reinforcement a suitable reward and
punishment scheme is also proposed. Experimental results are
presented to demonstrate the performance of the proposed system.
Abstract: The demand on High voltage (HV) infrastructures is growing due to the corresponding growth in industries and population. New or upgraded HV infrastructure has safety implications since Transmission mains usually occupy the same easement in the vicinity of neighbouring residents. Transmission mains consist of underground (UG) and overhead (OH) sections and the transition between the UG and OH section is known as the UGOH pole. The existence of two transmission mains in the same easement can dictate to resort to more complicated earthing design in order to mitigate the effect of AC interference, and in some cases it can also necessitates completing a Split Study of the system. This paper provides an overview of the AC interference, Split Study and the earthing of an underground feeder including the UGOH pole .In addition, this paper discusses the use of different link boxes on the UG feeder and presents a case study that represent a clear example of the Ac interference and Split factor. Finally, a few recommendations are provided to achieve a safety zone in the area beyond the boundary of the HV system.
Abstract: Method of Parallel Joint Channel Coding and
Cryptography has been analyzed and simulated in this paper. The
method is an extension of Soft Input Decryption with feedback,
which is used for improvement of channel decoding of secured
messages. Parallel Joint Channel Coding and Cryptography results in
improved coding gain of channel decoding, which achieves more
than 2 dB. Such results are an implication of a combination of
receiver components and their interoperability.
Abstract: The aim of this paper is to study the internal
stabilization of the Bernoulli-Euler equation numerically. For this,
we consider a square plate subjected to a feedback/damping force
distributed only in a subdomain. An algorithm for obtaining an
approximate solution to this problem was proposed and implemented.
The numerical method used was the Finite Difference Method.
Numerical simulations were performed and showed the behavior of
the solution, confirming the theoretical results that have already been
proved in the literature. In addition, we studied the validation of the
numerical scheme proposed, followed by an analysis of the numerical
error; and we conducted a study on the decay of the energy associated.
Abstract: In cryptography, confusion and diffusion are very
important to get confidentiality and privacy of message in block
ciphers and stream ciphers. There are two types of network to provide
confusion and diffusion properties of message in block ciphers. They
are Substitution- Permutation network (S-P network), and Feistel
network. NLFS (Non-Linear feedback stream cipher) is a fast and
secure stream cipher for software application. NLFS have two modes
basic mode that is synchronous mode and self synchronous mode.
Real random numbers are non-deterministic. R-box (random box)
based on the dynamic properties and it performs the stochastic
transformation of data that can be used effectively meet the
challenges of information is protected from international destructive
impacts. In this paper, a new implementation of stochastic
transformation will be proposed.
Abstract: The use of buffer thresholds, blocking and adequate
service strategies are well-known techniques for computer networks
traffic congestion control. This motivates the study of series queues
with blocking, feedback (service under Head of Line (HoL) priority
discipline) and finite capacity buffers with thresholds. In this paper,
the external traffic is modelled using the Poisson process and the
service times have been modelled using the exponential distribution.
We consider a three-station network with two finite buffers, for
which a set of thresholds (tm1 and tm2) is defined. This computer
network behaves as follows. A task, which finishes its service at
station B, gets sent back to station A for re-processing with
probability o. When the number of tasks in the second buffer exceeds
a threshold tm2 and the number of task in the first buffer is less than
tm1, the fed back task is served under HoL priority discipline. In
opposite case, for fed backed tasks, “no two priority services in
succession" procedure (preventing a possible overflow in the first
buffer) is applied. Using an open Markovian queuing schema with
blocking, priority feedback service and thresholds, a closed form
cost-effective analytical solution is obtained. The model of servers
linked in series is very accurate. It is derived directly from a twodimensional
state graph and a set of steady-state equations, followed
by calculations of main measures of effectiveness. Consequently,
efficient expressions of the low computational cost are determined.
Based on numerical experiments and collected results we conclude
that the proposed model with blocking, feedback and thresholds can
provide accurate performance estimates of linked in series networks.
Abstract: The possibility of producing drinking water from
brackish ground water using Vacuum membrane distillation (VMD)
process was studied. It is a rising technology for seawater or brine
desalination process. The process simply consists of a flat sheet
hydrophobic micro porous PTFE membrane and diaphragm vacuum
pump without a condenser for the water recovery or trap. In this
work, VMD performance was investigated for aqueous NaCl solution
and natural ground water. The influence of operational parameters
such as feed flow rate (30 to 55 l/h), feed temperature (313 to 333 K),
feed salt concentration (5000 to 7000 mg/l) and permeate pressure
(1.5 to 6 kPa) on the membrane distillation (MD) permeation flux
have been investigated. The maximum flux reached to 28.34 kg/m2 h
at feed temperature, 333 K; vacuum pressure, 1.5 kPa; feed flow rate,
55 l/h and feed salt concentration, 7000 mg/l. The negligible effects
in the reduction of permeate flux found over 150 h experimental run
for salt water. But for the natural ground water application over 75 h,
scale deposits observed on the membrane surface and 29% reduction
in the permeate flux over 75 h. This reduction can be eliminated by
acidification of feed water. Hence, promote the research attention in
apply of VMD for the ground water purification over today-s
conventional RO operation.
Abstract: The stem cells have ability to differentiated
themselves through mitotic cell division and various range of
specialized cell types. Cellular differentiation is a way by which few
specialized cell develops into more specialized.This paper studies the
fundamental problem of computational schema for an artificial neural
network based on chemical, physical and biological variables of
state. By doing this type of study system could be model for a viable
propagation of various economically important stem cells
differentiation. This paper proposes various differentiation outcomes
of artificial neural network into variety of potential specialized cells
on implementing MATLAB version 2009. A feed-forward back
propagation kind of network was created to input vector (five input
elements) with single hidden layer and one output unit in output
layer. The efficiency of neural network was done by the assessment
of results achieved from this study with that of experimental data
input and chosen target data. The propose solution for the efficiency
of artificial neural network assessed by the comparatative analysis of
“Mean Square Error" at zero epochs. There are different variables of
data in order to test the targeted results.
Abstract: An optical fault monitoring in FTTH-PON using ACS
is demonstrated. This device can achieve real-time fault monitoring
for protection feeder fiber. In addition, the ACS can distinguish
optical fiber fault from the transmission services to other customers
in the FTTH-PON. It is essential to use a wavelength different from
the triple-play services operating wavelengths for failure detection.
ACS is using the operating wavelength 1625 nm for monitoring and
failure detection control. Our solution works on a standard local area
network (LAN) using a specially designed hardware interfaced with a
microcontroller integrated Ethernet.
Abstract: This paper presents a method for functional projective H∞ synchronization problem of chaotic systems with external disturbance. Based on Lyapunov theory and linear matrix inequality (LMI) formulation, the novel feedback controller is established to not only guarantee stable synchronization of both drive and response systems but also reduce the effect of external disturbance to an H∞ norm constraint.
Abstract: Vermicomposting is the conversion of organic waste
into bio-fertilizers through the action of earthworm. This technology
is widely used for organic solid waste management. Waste corn pulp
blended with cow dung manure was vermicomposted over 30 days
using Eisenia fetida earthworms species. pH, temperature, moisture
content, and electrical conductivity were daily monitored. The
feedstock, vermicompost and vermiwash were analyzed for nutrient
composition. The average temperature and moisture content in the
vermi-reactor was 22.5°C and 42.5% respectively. The vermicompost
and vermiwash had an almost neutral pH whilst the electrical
conductivity was 21% higher in the vermicompost. The nitrogen and
potassium content was 57% and 79.6% richer in the vermicompost
respectively compared to the vermiwash. However, the vermiwash
was 84% richer in phosphorous as compared to vermicompost.
Furthermore, the vermiwash was 89.1% and 97.6% richer in Ca and
Mg respectively and was 97.8% richer in Na salts compared to the
vermicompost. The vermiwash also indicated a significantly higher
amount of micronutrients. Both bio-fertilizers were rich in nutrients
specification for fertilizers.
Abstract: A generalized unified power quality conditioner
(GUPQC) by using three single-phase three-level voltage source
converters (VSCs) connected back-to-back through a common dc
link is proposed in this paper as a new custom power device for a
three-feeder distribution system. One of the converters is connected
in shunt with one feeder for mitigation of current harmonics and
reactive power compensation, while the other two VSCs are
connected in series with the other two feeders to maintain the load
voltage sinusoidal and at constant level. A new control scheme based
on synchronous reference frame is proposed for series converters.
The simulation analysis on compensation performance of GUPQC
based on PSCAD/EMTDC is reported.
Abstract: This study examines causal link between energy use and economic growth for five South Asian countries over period 1971-2006. Panel cointegration, ECM and FMOLS are applied for short and long run estimates. In short run unidirectional causality from per capita GDP to per capita energy consumption is found, but not vice versa. In long run one percent increase in per capita energy consumption tend to decrease 0.13 percent per capita GDP. i.e. Energy use discourage economic growth. This short and long run relationship indicate energy shortage crisis in South Asia due to increased energy use coupled with insufficient energy supply. Beside this long run estimated coefficient of error term suggest that short term adjustment to equilibrium are driven by adjustment back to long run equilibrium. Moreover, per capita energy consumption is responsive to adjustment back to equilibrium and it takes 59 years approximately. It specifies long run feedback between both variables.