È veramente sorprendente considerare le cose da una prospettiva diversa dal solito
e con un’altra scala di valori.
C’è da restare attoniti e affascinati.
Le dimensioni del nostro pur piccolo universo rendono già l’idea. Ma più in là del nostro sole c’è il grande universo.
Il nostro mondo è un puntino azzurro!
HARDWARE SOFTWARE CO-SIMULATION FOR TRAFFIC LOAD COMPUTATION USING MATLAB SIM...ijcsity
Due to increase in number of vehicles, Traffic is a major problem faced in urban areas throughout the
world. This document presents a newly developed Matlab Simulink model to compute traffic load for real
time traffic signal control. Signal processing, video and image processing and Xilinx Blockset have been
extensively used for traffic load computation. The approach used is Edge detection operation, wherein,
Edges are extracted to identify the number of vehicles. The developed model computes the results with
greater degrees of accuracy and is capable of being used to set the green signal duration so as to release
the traffic dynamically on traffic junctions.
Xilinx System Generator (XSG) provides Simulink Blockset for several hardware operations that could be
implemented on various Xilinx Field programmable gate arrays (FPGAs). The method described in this
paper involves object feature identification and detection. Xilinx System Generator provides some blocks to
transform data provided from the software side of the simulation environment to the hardware side. In our
case it is MATLAB Simulink to System Generator blocks. This is an important concept to understand in the
design process using Xilinx System Generator. The Xilinx System Generator, embedded in MATLAB
Simulink is used to program the model and then test on the FPGA board using the properties of hardware
co-simulation tools.
Mine Blood Donors Information through Improved K-Means Clusteringijcsity
The number of accidents and health diseases which are increasing at an alarming rate are resulting in a huge increase in the demand for blood. There is a necessity for the organized analysis of the blood donor database or blood banks repositories. Clustering analysis is one of the data mining applications and K-means clustering algorithm is the fundamental algorithm for modern clustering techniques. K-means clustering algorithm is traditional approach and iterative algorithm. At every iteration, it attempts to find the distance from the centroid of each cluster to each and every data point. This paper gives the improvement to the original k-means algorithm by improving the initial centroids with distribution of data. Results and discussions show that improved K-means algorithm produces accurate clusters in less computation time to find the donors information
An efficient feature extraction method with pseudo zernike moment for facial ...ijcsity
Face recognition is one of the most challenging problems in the domain of image processing and machine
vision. Face recognition system is critical when individuals have very similar biometric signature such as
identical twins. In this paper, new efficient facial-based identical twins recognition is proposed according
to the geometric moment. The utilized geometric moment is Pseudo-Zernike Moment (PZM) as a feature
extractor inside the facial area of identical twins images. Also, the facial area inside an image is detected
using Ada Boost approach. The proposed method is evaluated on two datasets, Twins Days Festival and
Iranian Twin Society which contain scaled, which contain the shifted and rotated facial images of identical
twins in different illuminations. The results prove the ability of proposed method to recognize a pair of
identical twins. Also, results show that the proposed method is robust to rotation, scaling and changing
illumination.
È veramente sorprendente considerare le cose da una prospettiva diversa dal solito
e con un’altra scala di valori.
C’è da restare attoniti e affascinati.
Le dimensioni del nostro pur piccolo universo rendono già l’idea. Ma più in là del nostro sole c’è il grande universo.
Il nostro mondo è un puntino azzurro!
HARDWARE SOFTWARE CO-SIMULATION FOR TRAFFIC LOAD COMPUTATION USING MATLAB SIM...ijcsity
Due to increase in number of vehicles, Traffic is a major problem faced in urban areas throughout the
world. This document presents a newly developed Matlab Simulink model to compute traffic load for real
time traffic signal control. Signal processing, video and image processing and Xilinx Blockset have been
extensively used for traffic load computation. The approach used is Edge detection operation, wherein,
Edges are extracted to identify the number of vehicles. The developed model computes the results with
greater degrees of accuracy and is capable of being used to set the green signal duration so as to release
the traffic dynamically on traffic junctions.
Xilinx System Generator (XSG) provides Simulink Blockset for several hardware operations that could be
implemented on various Xilinx Field programmable gate arrays (FPGAs). The method described in this
paper involves object feature identification and detection. Xilinx System Generator provides some blocks to
transform data provided from the software side of the simulation environment to the hardware side. In our
case it is MATLAB Simulink to System Generator blocks. This is an important concept to understand in the
design process using Xilinx System Generator. The Xilinx System Generator, embedded in MATLAB
Simulink is used to program the model and then test on the FPGA board using the properties of hardware
co-simulation tools.
Mine Blood Donors Information through Improved K-Means Clusteringijcsity
The number of accidents and health diseases which are increasing at an alarming rate are resulting in a huge increase in the demand for blood. There is a necessity for the organized analysis of the blood donor database or blood banks repositories. Clustering analysis is one of the data mining applications and K-means clustering algorithm is the fundamental algorithm for modern clustering techniques. K-means clustering algorithm is traditional approach and iterative algorithm. At every iteration, it attempts to find the distance from the centroid of each cluster to each and every data point. This paper gives the improvement to the original k-means algorithm by improving the initial centroids with distribution of data. Results and discussions show that improved K-means algorithm produces accurate clusters in less computation time to find the donors information
An efficient feature extraction method with pseudo zernike moment for facial ...ijcsity
Face recognition is one of the most challenging problems in the domain of image processing and machine
vision. Face recognition system is critical when individuals have very similar biometric signature such as
identical twins. In this paper, new efficient facial-based identical twins recognition is proposed according
to the geometric moment. The utilized geometric moment is Pseudo-Zernike Moment (PZM) as a feature
extractor inside the facial area of identical twins images. Also, the facial area inside an image is detected
using Ada Boost approach. The proposed method is evaluated on two datasets, Twins Days Festival and
Iranian Twin Society which contain scaled, which contain the shifted and rotated facial images of identical
twins in different illuminations. The results prove the ability of proposed method to recognize a pair of
identical twins. Also, results show that the proposed method is robust to rotation, scaling and changing
illumination.
Google Analytics is a great tool, but do you know how to get the data you need to make intelligent digital marketing decisions? In this presentation I delivered at the Triangle American Marketing Association 2013 Funnel Fuel conference in Raleigh, NC, I took a look at some of the newer reports available in Google Analytics and how they can be used to solve common digital marketing problems.
Novel text categorization by amalgamation of augmented k nearest neighbourhoo...ijcsity
Machine learning for text classification is the
underpinning
of document
cataloging
, news filtering,
document
steering
and
exemplif
ication
. In text mining realm, effective feature selection is significant to
make the learning task more accurate and competent. One of the
traditional
lazy
text classifier
k
-
Nearest
Neighborhood (
k
NN) has
a
major pitfall in calculating the similarity between
all
the
objects in training and
testing se
t
s,
there by leads to exaggeration of
both
computational complexity
of the algorithm
and
massive
consumption
of
main memory
. To diminish these shortcomings
in
viewpoint
of a
data
-
mining
practitioner
a
n
amalgamati
ve technique is proposed in this paper using
a novel restructured version of
k
NN called
Augmented
k
NN
(AkNN)
and
k
-
Medoids
(kMdd)
clustering.
The proposed work
comprises
preprocesses
on
the
initial training
set
by
imposing
attribute feature selection
for reduc
tion of high dimensionality, also it
detects and excludes the high
-
fliers
samples
in t
he
initial
training set
and
re
structure
s
a
constricted
training
set
.
The kMdd clustering algorithm generates the cluster centers (as interior objects) for each category
and
restructures
the constricted training set
with centroids
. This technique
is
amalgamated with
AkNN
classifier
that
was prearranged with
text mining similarity measure
s.
Eventually, s
ignifican
tweights
and ranks were
assigned to each object in the new
training set based upon the
ir
accessory towards the
object in testing set
.
Experiments
conducted
on Reuters
-
21578 a
UCI benchmark
text mining
data
set
, and
comparisons with
traditional
k
NN
classifier designates
the
referred
method
yield
spreeminentrecital
in b
oth clustering and
classification
Convergence tendency of genetic algorithms and artificial immune system in so...ijcsity
By the advances in the Evolution Algorithms (EAs) and the intelligent optimization metho
ds we witness the
big revolutions in solving the optimization problems. The application of the evolution algorithms are not
only not limited to the combined optimization problems, but also are vast in domain to the continuous
optimization problems. In this
paper we analyze and study the Genetic Algorithm (GA) and the Artificial
Immune System (AIS)
algorithm
which are capable in escaping the local optimization and also fastening
reaching the global optimization and to show the efficiency of the GA and AIS th
e application of them in
Solving Continuous Optimization Functions (SCOFs) are studied. Because of the multi variables and the
multi
-
dimensional spaces in SCOFs the use of the classic optimization methods, is generally non
-
efficient
and high cost. In other
words the use of the classic optimization methods for SCOFs generally leads to a
local optimized solution. A possible solution for SCOFs is to use the EAs which are high in probability of
succeeding reaching the local optimized solution. The results in pa
per show that GA is more efficient than
AIS in reaching the optimized solution in SCOFs.
ANALYSE THE PERFORMANCE OF MOBILE PEER TO PEER NETWORK USING ANT COLONY OPTIM...ijcsity
A mobile peer-to-peer computer network is the one in which each computer in the network can act as a
client or server for the other computers in the network. The communication process among the nodes in the
mobile peer to peer network requires more no of messages. Due to this large number of messages passing,
propose an interconnection structure called distributed Spanning Tree (DST) and it improves the efficiency
of the mobile peer to peer network. The proposed method improves the data availability and consistency
across the entire network and also reduces the data latency and the required number of message passes for
any specific application in the network. Further to enhance the effectiveness of the proposed system, the
DST network is optimized with the Ant Colony Optimization method. It gives the optimal solution of the
DST method and increased availability, enhanced consistency and scalability of the network. The
simulation results shows that reduces the number of message sent for any specific application and average
delay and increases the packet delivery ratio in the network.
7. Antares è la quindicesima stella più brillante del cielo. Sta a più di 1000 anni luce.
SOLE – 1 pixel
Giove è invisible a
questa scala
8. Ora, quanto sei grande tu?
E, quanto sono grandi le cose che ti preoccupano oggi?
O, relativo a questo, quali sono le cose che realmente sono importanti?
L’IMPORTANTE È LA PROSPETTIVA!
9. Mandalo alle persone che conosci.
Può aiutare qualcuno a sentirsi meglio rispetto alle cose importanti della vita.
Ti auguro una felice giornata
10. Mandalo alle persone che conosci.
Può aiutare qualcuno a sentirsi meglio rispetto alle cose importanti della vita.
Ti auguro una felice giornata