Abstract: Image convolution similar to the receptive fields
found in mammalian visual pathways has long been used in
conventional image processing in the form of Gabor masks.
However, no VLSI implementation of parallel, multi-layered pulsed
processing has been brought forward which would emulate this
property. We present a technical realization of such a pulsed image
processing scheme. The discussed IC also serves as a general testbed
for VLSI-based pulsed information processing, which is of interest
especially with regard to the robustness of representing an analog
signal in the phase or duration of a pulsed, quasi-digital signal, as
well as the possibility of direct digital manipulation of such an
analog signal. The network connectivity and processing properties
are reconfigurable so as to allow adaptation to various processing
tasks.
Abstract: In this paper, novel techniques in increasing the accuracy
and speed of convergence of a Feed forward Back propagation
Artificial Neural Network (FFBPNN) with polynomial activation
function reported in literature is presented. These technique was
subsequently used to determine the coefficients of Autoregressive
Moving Average (ARMA) and Autoregressive (AR) system. The
results obtained by introducing sequential and batch method of weight
initialization, batch method of weight and coefficient update, adaptive
momentum and learning rate technique gives more accurate result
and significant reduction in convergence time when compared t the
traditional method of back propagation algorithm, thereby making
FFBPNN an appropriate technique for online ARMA coefficient
determination.
Abstract: This paper examines many mathematical methods for
molding the hourly price forward curve (HPFC); the model will be
constructed by numerous regression methods, like polynomial
regression, radial basic function neural networks & a furrier series.
Examination the models goodness of fit will be done by means of
statistical & graphical tools. The criteria for choosing the model will
depend on minimize the Root Mean Squared Error (RMSE), using the
correlation analysis approach for the regression analysis the optimal
model will be distinct, which are robust against model
misspecification. Learning & supervision technique employed to
determine the form of the optimal parameters corresponding to each
measure of overall loss. By using all the numerical methods that
mentioned previously; the explicit expressions for the optimal model
derived and the optimal designs will be implemented.
Abstract: One-way functions are functions that are easy to
compute but hard to invert. Their existence is an open conjecture; it
would imply the existence of intractable problems (i.e. NP-problems
which are not in the P complexity class).
If true, the existence of one-way functions would have an impact
on the theoretical framework of physics, in particularly, quantum
mechanics. Such aspect of one-way functions has never been shown
before.
In the present work, we put forward the following.
We can calculate the microscopic state (say, the particle spin in the
z direction) of a macroscopic system (a measuring apparatus
registering the particle z-spin) by the system macroscopic state (the
apparatus output); let us call this association the function F. The
question is: can we compute the function F in the inverse direction?
In other words, can we compute the macroscopic state of the system
through its microscopic state (the preimage F -1)?
In the paper, we assume that the function F is a one-way function.
The assumption implies that at the macroscopic level the Schrödinger
equation becomes unfeasible to compute. This unfeasibility plays a
role of limit of the validity of the linear Schrödinger equation.
Abstract: In this paper, we focus on the problem of driving and
herding a collection of autonomous actors to a given area. Then, a
new method based on multi-agent coordination is proposed for
solving the problem.
In our proposed method, we assume that the environment is
covered by sensors. When an event is occurred, sensors forward
information to a sink node. Based on received information, the sink
node will estimate the direction and the speed of movement of actors
and announce the obtained value to the actors. The actors coordinate
to reach the target location.
Abstract: With the advantage of wireless network technology,
there are a variety of mobile applications which make the issue of
wireless sensor networks as a popular research area in recent years.
As the wireless sensor network nodes move arbitrarily with the
topology fast change feature, mobile nodes are often confronted with
the void issue which will initiate packet losing, retransmitting,
rerouting, additional transmission cost and power consumption.
When transmitting packets, we would not predict void problem
occurring in advance. Thus, how to improve geographic routing with
void avoidance in wireless networks becomes an important issue. In
this paper, we proposed a greedy geographical void routing algorithm
to solve the void problem for wireless sensor networks. We use the
information of source node and void area to draw two tangents to
form a fan range of the existence void which can announce voidavoiding
message. Then we use source and destination nodes to draw
a line with an angle of the fan range to select the next forwarding
neighbor node for routing. In a dynamic wireless sensor network
environment, the proposed greedy void avoiding algorithm can be
more time-saving and more efficient to forward packets, and improve
current geographical void problem of wireless sensor networks.
Abstract: To satisfy the need of outfield tests of star sensors, a
method is put forward to construct the reference attitude benchmark.
Firstly, its basic principle is introduced; Then, all the separate
conversion matrixes are deduced, which include: the conversion
matrix responsible for the transformation from the Earth Centered
Inertial frame i to the Earth-centered Earth-fixed frame w according to
the time of an atomic clock, the conversion matrix from frame w to the
geographic frame t, and the matrix from frame t to the platform frame
p, so the attitude matrix of the benchmark platform relative to the
frame i can be obtained using all the three matrixes as the
multiplicative factors; Next, the attitude matrix of the star sensor
relative to frame i is got when the mounting matrix from frame p to the
star sensor frame s is calibrated, and the reference attitude angles for
star sensor outfield tests can be calculated from the transformation
from frame i to frame s; Finally, the computer program is finished to
solve the reference attitudes, and the error curves are drawn about the
three axis attitude angles whose absolute maximum error is just 0.25ÔÇ│.
The analysis on each loop and the final simulating results manifest that
the method by precise timing to acquire the absolute reference attitude
is feasible for star sensor outfield tests.
Abstract: In order to make environmental test centrifuge balance
automatically and accurately, reduce unbalance centrifugal force,
balance adjusting system of centrifuge is designed. The new balance
adjusting system comprises motor-reducer, timing belt, screw pair,
slider-guideway and four rocker force sensors. According to
information obtained by the four rocker force sensors, unbalanced
value at both ends of the big arm is computed and heavy block is
moved to achieve balance adjusting. In this paper, motor power and
torque to move the heavy block is calculated. In full load running
progress of centrifuge, the stress-strain of screw pair composed by
adjusting nut and big arm are analyzed. A successful application of the
balance adjusting system is also put forwarded. The results show that
the balance adjusting system can satisfy balance require of
environmental test centrifuge.
Abstract: In this paper, a Cooperative Multi-robot for Carrying
Targets (CMCT) algorithm is proposed. The multi-robot team
consists of three robots, one is a supervisor and the others are
workers for carrying boxes in a store of 100×100 m2. Each robot has
a self recharging mechanism. The CMCT minimizes robot-s worked
time for carrying many boxes during day by working in parallel. That
is, the supervisor detects the required variables in the same time
another robots work with previous variables. It works with
straightforward mechanical models by using simple cosine laws. It
detects the robot-s shortest path for reaching the target position
avoiding obstacles by using a proposed CMCT path planning
(CMCT-PP) algorithm. It prevents the collision between robots
during moving. The robots interact in an ad hoc wireless network.
Simulation results show that the proposed system that consists of
CMCT algorithm and its accomplished CMCT-PP algorithm
achieves a high improvement in time and distance while performing
the required tasks over the already existed algorithms.
Abstract: Chemical industry project management involves
complex decision making situations that require discerning abilities
and methods to make sound decisions. Project managers are faced
with decision environments and problems in projects that are
complex. In this work, case study is Research and Development
(R&D) project selection. R&D is an ongoing process for forward
thinking technology-based chemical industries. R&D project
selection is an important task for organizations with R&D project
management. It is a multi-criteria problem which includes both
tangible and intangible factors. The ability to make sound decisions
is very important to success of R&D projects. Multiple-criteria
decision making (MCDM) approaches are major parts of decision
theory and analysis. This paper presents all of MCDM approaches
for use in R&D project selection. It is hoped that this work will
provide a ready reference on MCDM and this will encourage the
application of the MCDM by chemical engineering management.
Abstract: The paper deals with the estimation of amplitude and phase of an analogue multi-harmonic band-limited signal from irregularly spaced sampling values. To this end, assuming the signal fundamental frequency is known in advance (i.e., estimated at an independent stage), a complexity-reduced algorithm for signal reconstruction in time domain is proposed. The reduction in complexity is achieved owing to completely new analytical and summarized expressions that enable a quick estimation at a low numerical error. The proposed algorithm for the calculation of the unknown parameters requires O((2M+1)2) flops, while the straightforward solution of the obtained equations takes O((2M+1)3) flops (M is the number of the harmonic components). It is applied in signal reconstruction, spectral estimation, system identification, as well as in other important signal processing problems. The proposed method of processing can be used for precise RMS measurements (for power and energy) of a periodic signal based on the presented signal reconstruction. The paper investigates the errors related to the signal parameter estimation, and there is a computer simulation that demonstrates the accuracy of these algorithms.
Abstract: IETF defines mobility support in IPv6, i.e. MIPv6, to
allow nodes to remain reachable while moving around in the IPv6
internet. When a node moves and visits a foreign network, it is still
reachable through the indirect packet forwarding from its home
network. This triangular routing feature provides node mobility but
increases the communication latency between nodes. This deficiency
can be overcome by using a Binding Update (BU) scheme, which let
nodes keep up-to-date IP addresses and communicate with each other
through direct IP routing. To further protect the security of BU, a
Return Routability (RR) procedure was developed. However, it has
been found that RR procedure is vulnerable to many attacks. In this
paper, we will propose a lightweight RR procedure based on
geometric computing. In consideration of the inherent limitation of
computing resources in mobile node, the proposed scheme is
developed to minimize the cost of computations and to eliminate the
overhead of state maintenance during binding updates. Compared with
other CGA-based BU schemes, our scheme is more efficient and
doesn-t need nonce tables in nodes.
Abstract: Logistics is part of the supply chain processes that plans, implements, and controls the efficient and effective forward and reverse flow and storage of goods, services, and related information between the point of origin and the point of consumption in order to meet customer requirements. This research aims to investigate the current status and future direction of the use of Information Technology (IT) for logistics, focusing on Supply Chain Management (SCM) and E-Commerce adoption in Johor. Therefore, this research stresses on the type of technology being adopted, factors, benefits and barriers affecting the innovation in SCM and ECommerce technology adoption among Logistics Service Providers (LSP). A mailed questionnaire survey was conducted to collect data from 265 logistics companies in Johor. The research revealed that SCM technology adoption among LSP was higher as they had adopted SCM technology in various business processes while they perceived a high level of benefits from SCM adoption. Obviously, ECommerce technology adoption among LSP is relatively low.
Abstract: This paper describes an optimal approach for feature
subset selection to classify the leaves based on Genetic Algorithm
(GA) and Kernel Based Principle Component Analysis (KPCA). Due
to high complexity in the selection of the optimal features, the
classification has become a critical task to analyse the leaf image
data. Initially the shape, texture and colour features are extracted
from the leaf images. These extracted features are optimized through
the separate functioning of GA and KPCA. This approach performs
an intersection operation over the subsets obtained from the
optimization process. Finally, the most common matching subset is
forwarded to train the Support Vector Machine (SVM). Our
experimental results successfully prove that the application of GA
and KPCA for feature subset selection using SVM as a classifier is
computationally effective and improves the accuracy of the classifier.
Abstract: The objective of this research was to investigate the efficiency of the light emitting diode (LED) tube in various color lights used to lure the adult coconut hispine beetle. The research was conducted by setting the forward bias on LED tubes, and the next step was to test luminous efficacy and quantity of electricity used to power each LED tube in different color lights. Finally, the researcher examined the efficiency of each color-light LED tube to lure the adult coconut hispine beetle.
The results showed that the ultraviolet LED tubes had the most capacity to allure the adult coconut hispine beetles with the percentage of 82.92, followed by the blue LED tubes with the percentage of 59.76. Whereas the yellow, pink, red and warm white LED tubes had no influence to the adult coconut hispine beetles.
Abstract: Herein, the organic semiconductor methyl orange
(MO), is investigated for the first time for its electronic applications.
For this purpose, Al/MO/n-Si heterojunction is fabricated through
economical cheap and simple “drop casting” technique. The currentvoltage
(I-V) measurements of the device are made at room
temperature under dark conditions. The I-V characteristics of
Al/MO/n-Si junction exhibits asymmetrical and rectifying behavior
that confirms the formation of diode. The diode parameters such as
rectification ratio (RR), turn on voltage (Vturn on), reverse saturation
current (I0), ideality factor (n), barrier height ( b
f ), series resistance
(Rs) and shunt resistance (Rsh) are determined from I-V curves using
Schottky equations. These values of these parameters are also
extracted and verified by applying Cheung’s functions. The
conduction mechanisms are explained from the forward bias I-V
characteristics using the power law.
Abstract: Soil organic carbon (SOC) plays a key role in soil
fertility, hydrology, contaminants control and acts as a sink or source
of terrestrial carbon content that can affect the concentration of
atmospheric CO2. SOC supports the sustainability and quality of
ecosystems, especially in semi-arid region. This study was
conducted to determine relative importance of 13 different
exploratory climatic, soil and geometric factors on the SOC contents
in one of the semiarid watershed zones in Iran. Two methods
canonical discriminate analysis (CDA) and feed-forward back
propagation neural networks were used to predict SOC. Stepwise
regression and sensitivity analysis were performed to identify
relative importance of exploratory variables. Results from sensitivity
analysis showed that 7-2-1 neural networks and 5 inputs in CDA
models output have highest predictive ability that explains %70 and
%65 of SOC variability. Since neural network models outperformed
CDA model, it should be preferred for estimating SOC.
Abstract: Wireless sensor networks (WSN) consists of many sensor nodes that are placed on unattended environments such as military sites in order to collect important information. Implementing a secure protocol that can prevent forwarding forged data and modifying content of aggregated data and has low delay and overhead of communication, computing and storage is very important. This paper presents a new protocol for concealed data aggregation (CDA). In this protocol, the network is divided to virtual cells, nodes within each cell produce a shared key to send and receive of concealed data with each other. Considering to data aggregation in each cell is locally and implementing a secure authentication mechanism, data aggregation delay is very low and producing false data in the network by malicious nodes is not possible. To evaluate the performance of our proposed protocol, we have presented computational models that show the performance and low overhead in our protocol.
Abstract: In this paper our aim is to explore the construction of schoolgirl femininities, drawing on the results of an ethnographic study conducted in a high school in Ankara, Turkey. In this case study which tries to explore the complexities of gender discourses, we were initially motivated by the questions that have been put forward by critical and feminist literature on education which emphasize the necessarily conflicting and partial nature of both reproduction and resistance and the importance of gendered power relations in the school context. Drawing on this paradigm our research tries to address to a more specific question: how are multiple schoolgirl femininities constructed within the context of gendered school culture, and especially in relation to hegemonic masculinity? Our study reveals that the general framework of multiple femininities is engendered by a tension between two inter-related positions. The first one is different strategies of accommodation and resistance to the gender-related problems of education. The second one is the school experience of girls which is conditioned by their differential position vis-à-vis the masculine resistance culture that is dominant in the school.
Abstract: Vehicle which are turning or maneuvering at high speeds
are susceptible to sliding and subsequently deviate from desired path. In
this paper the dynamics governing the Yaw/Roll behavior of a vehicle
has been simulated. Two different simulations have been used one for
the real vehicle, for which a fuzzy controller is designed to increase its
directional stability property. The other simulation is for a hypothetical
vehicle with much higher tire cornering stiffness which is capable of
developing the required lateral forces at the tire-ground patch contact to
attain the desired lateral acceleration for the vehicle to follow the
desired path without slippage. This simulation model is our reference
model.
The logic for keeping the vehicle on the desired track in the cornering
or maneuvering state is to have some braking forces on the inner or
outer tires based on the direction of vehicle deviation from the desired
path. The inputs to our vehicle simulation model is steer angle δ and
vehicle velocity V , and the outputs can be any kinematical parameters
like yaw rate, yaw acceleration, side slip angle, rate of side slip angle
and so on. The proposed fuzzy controller is a feed forward controller.
This controller has two inputs which are steer angle δ and vehicle
velocity V, and the output of the controller is the correcting moment M,
which guides the vehicle back to the desired track. To develop the
membership functions for the controller inputs and output and the fuzzy
rules, the vehicle simulation has been run for 1000 times and the
correcting moment have been determined by trial and error. Results of
the vehicle simulation with fuzzy controller are very promising
and show the vehicle performance is enhanced greatly over the
vehicle without the controller. In fact the vehicle performance
with the controller is very near the performance of the reference
ideal model.