International Journal of Digital Electronics vol 2 issue 1

International Journal of
Digital Electronics
IJDE
JAN – JUNE 2016
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! Digital analogue circuits
! Integrated circuit
! Microelectronics
! Unconventional computing
! Digital system and binary numbers
! Asynchronous sequential logic
! Digital number system
! Boolean algebra and logic circuits
! Digital logic gates
! Digital combinational logic
! Combinational arithmetic circuits
! Sequential circuits
! Digital logic families
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Dr. Michael Loong Peng Tan
Universiti Teknologi Malaysia,
UTM Skudai Johor,
Malaysia
Dr.I.Kathir
Vice-President, Alumni Association,
Associate Professor, Department of Electrical
and Electronics Engineering, India
Dr. K A Lathief
Jimma Institute of Technology,
Jimma University,
Ethiopia
Dr. V. Balaji
Bahir Dar University,
Bahir Dar, Ethiopia
Dr. Sreejith S
Power Electronics and Drives Division,
School of Electrical Engineering,
Vellore Institute of Technology, India
Dr. Huang Mingzhi
Department of Water Resources and
Environment, Sun Yat-sen University,
Guangzhou, China
Dr. Amin Noura,
University Putra Malaysia,
43300 UPM serdang, Selangor Darul Ehsan,
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Mr. Dinesh Kumar
VITS,
Hyderabad,
India
Vijay R. Wadhankar
RTMNU University
India
Dr. S Murugan
Department of Computer Science and
Engineering, Alagappa University, Karaikudi,
Tamil Nadu, India
Amitav Pani
IPER Business School,
Bhubaneswar, Orissa, India
Dr. D Selvathi
Department of Electronics and Communication
Engineering, Mepco Schlenk Engineering
College, Sivakasi, TamilNadu, India
Dr. Vinod Kumar Sayal
Department of Physics
Institute of Technology Majitar,
Rangpo Sikkim, India
Sandeep Kumar Kautish
Engineering North West Institute of
Engineering and Technology
Dhudike (MOGA) Punjab, India
K.M. Mehata
Department of Computer Science and
Engineering Anna University,
Chennai, India
Dr. Pratibhamoy Das
Department of Mathematics,
Indian Institute of Science Education and
Research, Bhopal, India
Santanu K. Maiti
Physics and Applied Mathematics Unit,
Indian Statistical Institute,
Kolkata, India

From the Editor's Desk
Dear Readers,
We would like to present, with great pleasure, the inaugural volume of a new scholarly
journal, International Journal of Digital Electronics. This journal is part of the Electronics
and Telecommunication Engineering, and is devoted to the scope of present Digital
Electronics issues, from theoretical aspects to application-dependent studies and the
validationofemergingtechnologies.
This new journal was planned and established to represent the growing needs of International Journal of
Digital Electronics as an emerging and increasingly vital field, now widely recognized as an integral part of
scientific and technical investigations. Its mission is to become a voice of the Electronics and
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International Journal of Digital Electronics focuses on original high-quality research in the realm of Base
Station Management, Wide-band CDMA (W-CDMA), Direct sequence-CDMA (DS-CDMA),Multi-code
CDMA (MC-CDMA) ,Channel capacity, Multi-user MIMO systems, Multi-hop networks, Multiple-input
and multiple-output relay channel, MIMO antenna design, MIMO prototyping, Call establishment
procedures,Callclearingprocedures,Callinformationphase procedures.
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and TelecommunicationEngineeringandsolutionsinthearea.
Many scientists and researchers have contributed to the creation and the success of the Electronics and
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This issue would not have been possible without the great support of the Editorial Board members, and we
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It is our hope that this fine collection of articles will be a valuable resource for Electronics and
Telecommunication Engineering readers and will stimulate further research into the vibrant area of
ElectronicsandTelecommunicationEngineering.
PuneetMehrotra
ManagingDirector

1. Proposing New and Novel Kalman Filter for Estimating Chemical and Nanoparameters
Saeid Zoghi 1
2. Power Awareness by Distributed Voltage-Scaling Technique for Wireless Sensor Networks – Review
E.N. Ganesh 10
3. Number Plate Extraction and Detection Using Matlab
Swati, Chanchal Sarovar, Hitendra Singh 17
4. Challenges of Terahertz Radiations as Imaging and Sensing
Anant Bhardwaj, Govind Sharma, Vikas Gupta 23
5. Improved Routh Table Truncation Algorithm for Large Scale Uncertain Discrete Interval Models
Manish Kumar Sharma, Deepak Parashar, Aseem Chandel 27
6. Big Data Analysis and Framework
Sakshi Shewale, Joni Birla, Mahesh Kumar, Jitender Singh 34
7. Robotic System for Differentiating Color Objects
Santosh Kumar Agrahari, Kunal Saini, Ritesh Raj, Suraj Changotra, Love Sharma 44
Contents

IJDE (2016) 1–9 © JournalsPub 2016. All Rights Reserved Page 1
Vol. 2: Issue 1
www.journalspub.com
Proposing New and Novel Kalman Filter for Estimating Chemical
and Nanoparameters
Saeid Zoghi*
Department of Applied Chemistry, Shahrood Azad University, Shahrood, Iran
Abstract
The conservative input estimation methods assume constant input level and there are not
shielded a universal input modeling. In this article, an innovative system is advanced to
overcome these problems by using a new partitioned input dynamic modeling. In addition,
author suggests an improved two-stage Kalman estimator with a new arrangement, which is
an extension of the conventional input estimation methods and is optimal for common, linear
discrete-time systems. At the end of this paper, we propose new application for this estimator
in chemical engineering. Author of this paper, propose applying this for estimating and
predicting density volume or amount of dopants that need for a special structure.
Keywords: chemical engineering, density, estimation and prediction
INTRODUCTION
The well-known augmented state Kalman
estimator (AUSKE) or “full state” method
answers the general state estimation
difficult in a stochastic linear system with
unknown input variable. The AUSKE
answers the difficulties by comprising the
input factors as a part of an augmented
state to be estimated.[1,2]
Though, “reduced
state” approaches do not augment the state,
and usually return a better performance.[3]
.
The AUSKE suffers from difficulty of
computational work and numerical
difficulties when state dimensions are
large.
The input detection and estimation (IDE)
procedure was first advanced by Chan et
al., in[4]
using a simplified batch least
square data. While IDE method is
attractive since it intends to relax
restrictive assumptions about input
dynamics modeling, it suffers from a key
deficiency, being that little prior
knowledge is accessible for dynamics
estimation.[5]
For instance, we can cite
Wang et. al.,[6]
used the IDE method in the
maneuvering target tracking problem. In[7]
the indefinite input defined as a sum of
basic time functions. While this input
modeling is more common than the
constant-input model of the original IDE
procedure, the performance is cheap if
there is any input dynamics.
Friedland[8]
presented a system of
separating estimation of the unknown
input from the dynamic variables and Blair
used this technique in the MTT problem.[9]
The elementary idea was to decouple the
augmented Kalman filter (AKF) into two-
stage filters in order to lessen computation
and memory necessities.[10-13]
Lately,
Hsieh and Chen[10,11]
derived an optimal
two-stage Kalman estimator (OTSKE) for
a common case to reduce the
computational difficulty of AUSKE. The
two-stage filtering process, proposed for
MTT problem in[9]
suffers from two major
drawbacks. These problems stem from

Vol. 2: Issue 1
www.journalspub.com
Power Awareness by Distributed Voltage-Scaling Technique for
Wireless Sensor Networks – Review
E.N. Ganesh*
Electronics Communication Engineering Department, Saveetha Engineering College, Chennai, India
Abstract
Distributed Microsensor networks are emerging as a compelling new hardware platform for
remote environment monitoring. A distributed micro sensor network consists of many small
expendable and battery powered wireless nodes. When the nodes are deployed they collect
the data from the environment and sent to cluster head node and in turn to base station. The
 - Amps (Micro domain power aware sensors) use the enabling technologies for distributed
micro sensor networks. An essential component of power aware systems are the ability to
make intelligent trade-offs between energy and quality and energy scalability in micro sensor
networks. A Variable Voltage Microprocessor can reduce the energy consumed during low
workload periods through dynamic voltage scaling. Dynamic voltage scaling is the active
adjustment of supply voltage and frequency in response to fluctuations of processor
utilization. In this paper it is demonstrated on SA-1100 processor and converter circuit of
A/D – D/A and programmable logic controller with Buck voltage regulator circuit. The
controller is programmed with 4-bit value to regulate one of 32 voltages between 0.9 and
2.6 volts. A programmable logic in the controller controls the digital input and prevents
voltage delivering beyond 2.6 volts. We have proposed our approach and simulated each
circuit individually and waveforms are presented.
Keywords: A/D converter, distributed voltage scaling, microprocessor, voltage regulator
BACKGROUND
Distributed micro sensor networks are
emerging as a compelling new hardware
platform for remote environment
monitoring. Researchers are considering a
range of applications including remote
climate monitoring, battle – field
surveillance and intramachine monitoring
etc. A distributed network consists of
many small, expendable, battery –
powered wireless nodes. Once the nodes
been deployed throughout an area, they
collect data from the environment and
automatically establish dedicated networks
to transmit their data to base station. The
nodes collaborate to gather data and
extend the operating lifetime of the entire
system. Comparing with larger macro
sensor based systems; micro sensor
networks offer a longevity, robustness and
ease of deployment that is ideal for
environments where maintenance or
battery replacement may be inconvenient
or impossible. So therefore older methods
for deployment of components at remote
places requires replaceable power supply
units, maintenance etc. But nowadays due
to technology power of about 2 volts is
more than enough for the same kind of
applications. Figure 1 illustrates operation
of distributed micro sensor network.
Figure 1 illustrates operation of distributed
micro sensor network.[1]

Vol. 2: Issue 1
www.journalspub.com
Number Plate Extraction and Detection Using Matlab
Swati*
, Chanchal Sarovar, Hitendra Singh
Raja Balwant Singh Engineering Technical Campus, ETC, Bichpuri, Agra, India
Abstract
For the efficient regulation and monitoring of traffic in present era, tracking of vehicles is
quite important and essential. This is quite a major issue which demands smart as well as
intelligent solution in concern with traffic surveillance. Monitoring vehicles for Law
Enforcement and security purpose is a difficult problem because of the number of
automobiles running on the road today. So there should exist a way for vehicle identification
for detecting and identifying license plate without constant human intervention. Various
efforts have been made in this direction. These approaches were applicable for limited
number of vehicles and were able to achieve limited efficiency of about 40%. By the help of
this work we aim to present a new graphical interface in MATLAB which will help to extract
information from the number plate of vehicle.
Keywords: graphical user interface, MATLAB, intelligent transportation systems
INTRODUCTION
Today vehicles play vital role in
transportation and due to surplus growth in
human population, the use of vehicles is
also increasing consistently.[1-8]
From
years, intelligent transportation systems
(ITSs) had a wide impact in people’s life
as their scope is to improve transportation
safety and mobility and to enhance
productivity through the use of advanced
technologies. There are different types of
license plates in India on the basis of color,
size, and number of rows of characters
present as well as the types of font utilized.
Therefore it is quite complicated to make
an intermediate system that can overcome
with all of these unpredictable
changes.[9,10]
Therefore for the effective
control of the vehicles an automatic
number plate recognition system has been
developed which is being used and so
many efforts have been done in order to
enhance its efficiency at quite large
scale.[8]
Image processing has been utilized
in controlling vehicle parking system,
doing vehicle access to specific area,
traffic monitoring system and highway
electronic toll collection as computer
possess capacity to process image and
convert it into useful data .
For this purpose, the computer needs to
capture the vehicle license plate number
and process it in the computer.[5]
For this,
many efforts have been done and
continuous approaches are being made to
achieve maximum efficiency. By this
approach we aim to propose a new method
for dealing with the discussed issues. A
graphical user interface (GUI) is a pictorial
interface related to program that can make
the programs easier by providing them a
consistent appearance and with intuitive
controls. GUI being developed in
MATLAB in which the captured image is
being processed so as to remove all the
kind of noise present in it and also the
information from the database with the

Vol. 2: Issue 1
www.journalspub.com
Challenges of Terahertz Radiations as Imaging and Sensing
Anant Bhardwaj1*
, Govind Sharma2
, Vikas Gupta2
1
Department of Electronics and Communication Engineering, BSA College of Engineering & Technology,
Mathura, Uttar Pradesh, India
2
Department of Electronics and Communication Engineering, G.L. Bajaj Institute of Technology and
Management, Greater Noida, India
Abstract
In electromagnetic spectrum, terahertz (THz) region is an open research area & it can be
applied to diverse field of applications & in this region of the electromagnetic spectrum
consists of THz waves, which at 100 GHz to 10 THz fall between millimeter waves and the
infrared light. This article reviews the challenges faced by THz radiations in various
applications & its implementation. Terahertz (THz) radiation, which occupies a relatively
unexplored portion of the electromagnetic spectrum between the mid-infrared and microwave
bands, offers innovative sensing and imaging technologies that can provide information
unavailable through conventional methods such as microwave and X-ray techniques. With
the advancement of THz technologies, THz sensing and imaging will impact a broad range of
interdisciplinary fields, including chemical and biological detections and identifications.
Keywords: imaging, sensing, t-rays, time-domain spectroscopy
INTRODUCTION
The T-ray region of the electromagnetic
spectrum has proven to be one of the most
difficult to find region. T-ray radiation is
generally defined by the 0.1 to 10 THz
frequency range (where 1 THz is 1012
cycles/s). It is situated between infrared
(IR) light and millimeter wave radiation
(see Figure 1), the terahertz gap is resistant
to the techniques commonly employed in
the well-established, neighboring bands[1-3]
Much of the recent interest in terahertz
radiation stems from its ability to penetrate
deep into many organic materials without
the damage associated with ionizing
radiation such as X-rays (albeit without the
spatial resolution).[1]
Fig. 1. Terahertz Lies Between Gigahertz Radio Frequencies and Mid-Infrared Light on the
Electromagnetic Spectrum.
Also, because terahertz radiation is readily
absorbed by water, it can be used to
distinguish between materials having
varying water contents.[4-8]

Vol. 2: Issue 1
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Improved Routh Table Truncation Algorithm for Large Scale
Uncertain Discrete Interval Models
Manish Kumar Sharma1*
, Deepak Parashar2
, Aseem Chandel2
1
I.T.S. Engineering College, Greater Noida, Uttar Pradesh, India
2
B.S.A.C.E.T., Mathura, Uttar Pradesh, India
Abstract
Order reduction of complex uncertain discrete interval time system is considered. The novelty
of algorithm is that coefficient of known higher order model are within given uncertain
pattern and coefficient of reduced model are also derived in intervals, such that step response
and frequency response envelope of original and derived reduced model are optimally close
to each other. The developed algorithm ensured the stability aspect of reduced system if
higher order uncertain system is stable. A numerical example is included to illustrate the
proposed algorithm along with the comparison with existing techniques.
Keywords: discrete interval system, integral square error (ISE), interval system,model order
reduction
INTRODUCTION
Many different algorithm of system order
reduction are completely exploited by
control system engineers in skeleton
formation of typical control when the
complex higher order model is supposed
absolutely known and certain in nature.[1-3]
However, in real life control engineering
models, there are several sources of
inaccuracies and unpredictability about the
accurate values of model’s parameter.
Then, the fundamental question is that
what is the meaning of system order
reduction for models with uncertain and
inaccurate parameter?
The aforementioned question has not yet
been completely explained in the order
reduction literature. The choice of fixed or
uncertain reduced order system depends of
problem formulation, since both options
have their own advantages and
applications so both are equally important.
The fixed coefficient type reduced systems
is important when it is necessary to ease
the complexity of original higher order
system for simulation or design purpose.
Furthermore, interval type reduced system
is necessary for those systems in which
preserving the uncertainty of reduced
system is important. Being of several
advantages of practical system reduction,
various previous publications are available
which discussed the order reduction of
linear fixed-coefficient system in
frequency domain.[4-6]
Further, limitations
of continuous-time systems have provided
ample opportunity for study, analysis and
research of discrete-time systems
techniques.[7-9]
Also uncertain variation in
science and engineering design proposed
another research area termed as
continuous- time or discrete-time
parametric interval system modelling. On
the other hand in consequence of
Kharitonov’s theorem, several stable
mixed techniques and few unstable
techniques such as Routh Padé

Vol. 2: Issue 1
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Big Data Analysis and Framework
Sakshi Shewale*
, Joni Birla, Mahesh Kumar, Jitender Singh
Department of Computer Science and Engineering, Ganga Institute of Technology and Management, Kablana,
Jhajjar, Haryana, India
Abstract
Big data is a wide span for data sets so great or composite that outdated data processing
submissions are insufficient. Challenges include study, capture, data curation, examine,
sharing, storage, transfer, imagining, and info privacy. The period often refers simply to the
use of prognostic analytics or other definite progressive procedures to excerpt value from
data, and seldom to a specific size of data set. Accuracy in big data may chief to more
assured decision making and better decisions can mean superior working efficiency, cost
reduction and reduced risk. Investigation of data sets can discover new connexions, to "spot
business tendencies, avert diseases, and combat crime and so on. Researchers, business
executives, practitioners of media, and marketing and administrations alike frequently meet
problems with large data sets in levels comprising Internet search, finance and business
informatics. Scientists encounter restrictions in e-Science work, comprising meteorology,
genomics, connectomics, complex physics simulations, and biological and environmental
investigation.
Keywords: big data, data scientist, analytics, business intelligence, information management,
strategy, Hadoop
INTRODUCTION
We live in the Information Era – the Age
of BIG data. As an example, Big Data’s
significance and power became apparent
when the results of the 2012 US
Presidential Elections were announced.
Complex analytics processing large data
not only predicted the exact election
results but may also have influenced it.
Further, leading business magazines and
economical newspapers run frequent
articles about Big Data’s success.
However, it should be recognised that Big
Data is not something new, it has long
been the playground of the elite. The aim
was to maximise expensive CPU
utilisation. As a result, it had a limited
audience as computation and storage was
expensive and difficult to utilise requiring
detailed systems knowledge where
capacity doubles every 18 months.
In the Big Data period, computation and
storing is cheap per TB. So, with ever-
growing computational competences,
system application is no lengthier as
dangerous a factor. It is currently possible
to use additional computational power to
do the similar work (hence with lower
utilisation). At the same time, the quantity
of data that wants indulgence has been
cumulative exponentially in the past era as
a result of developments in data generation
and storage capacity.[1]
Overhead all,
program design tools and practises have
aged with globalisation and the Internet. It
is progressively possible to reuse code
(and also share it), therefore, the focus has

Vol. 2: Issue 1
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Robotic System for Differentiating Color Objects
Santosh Kumar Agrahari, Kunal Saini*
, Ritesh Raj, Suraj Changotra, Love Sharma
Electronics and Communication, Poornima University, Jaipur, Rajasthan, India
Abstract
In this paper, we are designing robotic System for distinguishing various color objects using
Arduino UNO Board and a programmable color light-to-frequency converterTCS3200. This
system will automatically identify various colors which can detect any number of colored
objects and it picks the object and places at predefined location automatically. In the
TCS3200, the light-to-frequency converter reads an 8 × 8 array of photodiodes. Sixteen
photodiodes have blue filters, 16 photodiodes have green filters, 16 photodiodes have red
filters, and 16 photodiodes are clear with no filters. This system can be used in various
automation industries like food industries, pharmaceuticals, agricultures, etc.
Keywords: Arduino Uno Board, color sensor, light-to-frequency converter, microcontroller,
robotic system
INTRODUCTION
A Robotic System is required to fulfill the
requirement of pick and placing an object
from one source point to another
destination point according to their
different colors.[1–3]
This whole need to be
complete in practical can be done by this
project named as Robotic Arm System for
Distinguishing Color Objects. The inset
parts evolved the robot to differentiate
several objects with their colors as helping
nature of a color sensor.
This color sensor verifies colors according
to frequency reflected from various objects
sensed at the photodiode attached on
sensors. The sensor called ass
programmable color light-to-frequency
converters that combine configurable
silicon photodiodes and a current-to
frequency converter on a single monolithic
CMOS integrated circuit. The output is a
square wave (50% duty cycle) with
frequency directly proportional to light
intensity (irradiance).[4]
The full-scale output frequency can be
surmounted by one of three preset values
through two control input pins. Digital
inputs and digital output allow direct
interface to a microcontroller or other
logic circuitry. Output enable (OE) places
the output in the high-impedance state for
multiple-unit sharing of a microcontroller
input line. In the color sensor, the light-to-
frequency converter reads an 8 x 8 array of
photodiodes. Sixteen photodiodes have
blue filters, 16 photodiodes have green
filters, 16 photodiodes have red filters, and
16 photodiodes are clear with no filters.[5]
The next part of this project includes
Arduino Circuit confined of the output of
color sensor. Arduino is an open-source
prototyping platform based on easy-to-use
hardware and software. Arduino boards
are able to read inputs (light on a sensor)
and turn it into an output - activating a
motor, turning on an LED, display
message on LCD, publishing something
online. Arduino controls the operation of

International Journal of Digital Electronics vol 2 issue 1

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International Journal of Digital Electronics vol 2 issue 1