Abstract: Handwritten signature is accepted widely as a biometric characteristic for personal authentication. The use of appropriate features plays an important role in determining accuracy of signature verification; therefore, this paper presents a feature based on the geometrical concept. To achieve the aim, triangle attributes are exploited to design a new feature since the triangle possesses orientation, angle and transformation that would improve accuracy. The proposed feature uses triangulation geometric set comprising of sides, angles and perimeter of a triangle which is derived from the center of gravity of a signature image. For classification purpose, Euclidean classifier along with Voting-based classifier is used to verify the tendency of forgery signature. This classification process is experimented using triangular geometric feature and selected global features. Based on an experiment that was validated using Grupo de Senales 960 (GPDS-960) signature database, the proposed triangular geometric feature achieves a lower Average Error Rates (AER) value with a percentage of 34% as compared to 43% of the selected global feature. As a conclusion, the proposed triangular geometric feature proves to be a more reliable feature for accurate signature verification.
Abstract: Recently, Automatic Speech Recognition (ASR) systems were used to assist children in language acquisition as it has the ability to detect human speech signal. Despite the benefits offered by the ASR system, there is a lack of ASR systems for Malay-speaking children. One of the contributing factors for this is the lack of continuous speech database for the target users. Though cross-lingual adaptation is a common solution for developing ASR systems for under-resourced language, it is not viable for children as there are very limited speech databases as a source model. In this research, we propose a two-stage adaptation for the development of ASR system for Malay-speaking children using a very limited database. The two stage adaptation comprises the cross-lingual adaptation (first stage) and cross-age adaptation. For the first stage, a well-known speech database that is phonetically rich and balanced, is adapted to the medium-sized Malay adults using supervised MLLR. The second stage adaptation uses the speech acoustic model generated from the first adaptation, and the target database is a small-sized database of the target users. We have measured the performance of the proposed technique using word error rate, and then compare them with the conventional benchmark adaptation. The two stage adaptation proposed in this research has better recognition accuracy as compared to the benchmark adaptation in recognizing children’s speech.
Abstract: This paper presents a SAC-OCDMA code with zero cross correlation property to minimize the Multiple Access Interface (MAI) as New Zero Cross Correlation code (NZCC), which is found to be more scalable compared to the other existing SAC-OCDMA codes. This NZCC code is constructed using address segment and data segment. In this work, the proposed NZCC code is implemented in an optical system using the Opti-System software for the spectral amplitude coded optical code-division multiple-access (SAC-OCDMA) scheme. The main contribution of the proposed NZCC code is the zero cross correlation, which reduces both the MAI and PIIN noises. The proposed NZCC code reveals properties of minimum cross-correlation, flexibility in selecting the code parameters and supports a large number of users, combined with high data rate and longer fiber length. Simulation results reveal that the optical code division multiple access system based on the proposed NZCC code accommodates maximum number of simultaneous users with higher data rate transmission, lower Bit Error Rates (BER) and longer travelling distance without any signal quality degradation, as compared to the former existing SAC-OCDMA codes.
Abstract: Orthogonal Frequency Division Multiplexing
(OFDM) has been used in many advanced wireless communication
systems due to its high spectral efficiency and robustness to
frequency selective fading channels. However, the major concern
with OFDM system is the high peak-to-average power ratio (PAPR)
of the transmitted signal. Some of the popular techniques used for
PAPR reduction in OFDM system are conventional partial transmit
sequences (CPTS) and clipping. In this paper, a parallel
combination/hybrid scheme of PAPR reduction using clipping and
CPTS algorithms is proposed. The proposed method intelligently
applies both the algorithms in order to reduce both PAPR as well as
computational complexity. The proposed scheme slightly degrades
bit error rate (BER) performance due to clipping operation and it can
be reduced by selecting an appropriate value of the clipping ratio
(CR). The simulation results show that the proposed algorithm
achieves significant PAPR reduction with much reduced
computational complexity.
Abstract: Multiple Input Multiple Output (MIMO) systems are
wireless systems with multiple antenna elements at both ends of the
link. Wireless communication systems demand high data rate and
spectral efficiency with increased reliability. MIMO systems have
been popular techniques to achieve these goals because increased
data rate is possible through spatial multiplexing scheme and
diversity. Spatial Multiplexing (SM) is used to achieve higher
possible throughput than diversity. In this paper, we propose a Zero-
Forcing (ZF) detection using a combination of Ordered Successive
Interference Cancellation (OSIC) and Zero Forcing using
Interference Cancellation (ZF-IC). The proposed method used an
OSIC based on Signal to Noise Ratio (SNR) ordering to get the
estimation of last symbol, then the estimated last symbol is
considered to be an input to the ZF-IC. We analyze the Bit Error Rate
(BER) performance of the proposed MIMO system over Rayleigh
Fading Channel, using Binary Phase Shift Keying (BPSK)
modulation scheme. The results show better performance than the
previous methods.
Abstract: In internet of things (IoT) system, the communication
scheme with reliability and low power is required to connect a
terminal. Cooperative communication can achieve reliability and
lower power than multiple-input multiple-output (MIMO) system.
Cooperative communication increases the reliability with low
power, but decreases a throughput. It has a weak point that the
communication throughput is decreased. In this paper, a novel scheme
is proposed to increase the communication throughput. The novel
scheme is a transmission structure that increases transmission rate.
A decoding scheme according to the novel transmission structure is
proposed. Simulation results show that the proposed scheme increases
the throughput without bit error rate (BER) performance degradation.
Abstract: Multiple User Interference (MUI) considers the
primary problem in Optical Code-Division Multiple Access
(OCDMA), which resulting from the overlapping among the users. In
this article we aim to mitigate this problem by studying an
interference cancellation scheme called successive interference
cancellation (SIC) scheme. This scheme will be tested on two
different detection schemes, spectral amplitude coding (SAC) and
direct detection systems (DS), using partial modified prime (PMP) as
the signature codes. It was found that SIC scheme based on both SAC
and DS methods had a potential to suppress the intensity noise, that is
to say it can mitigate MUI noise. Furthermore, SIC/DS scheme
showed much lower bit error rate (BER) performance relative to
SIC/SAC scheme for different magnitude of effective power. Hence,
many more users can be supported by SIC/DS receiver system.
Abstract: In the cooperative transmission scheme, both the
cellular system and broadcasting system are composed. Two cellular
base stations (CBSs) communicating with a user in the cell edge use
cooperative transmission scheme in the conventional scheme. In the
case that the distance between two CBSs and the user is distant, the
conventional scheme does not guarantee the quality of the
communication because the channel condition is bad. Therefore, if the
distance between CBSs and a user is distant, the performance of the
conventional scheme is decreased. Also, the bad channel condition has
bad effects on the performance. The proposed scheme uses two relays
to communicate well with CBSs when the channel condition between
CBSs and the user is poor. Using the relay in the high attenuation
environment can obtain both advantages of the high bit error rate
(BER) and throughput performance.
Abstract: In this paper, improved performance scheme for
joint transmission (JT) is proposed in downlink (DL) coordinated
multi-point (CoMP) in case of the constraint transmission power.
This scheme is that a serving transmission point (TP) requests the
JT to an inter-TP and it selects a precoding technique according
to the channel state information (CSI) from user equipment (UE).
The simulation results show that the bit error rate (BER) and the
throughput performances of the proposed scheme provide the high
spectral efficiency and the reliable data at the cell edge.
Abstract: The Orthogonal Frequency Division Multiplexing
(OFDM) with high data rate, high spectral efficiency and its ability to
mitigate the effects of multipath makes them most suitable in wireless
application. Impulsive noise distorts the OFDM transmission and
therefore methods must be investigated to suppress this noise. In this
paper, a State Space Recursive Least Square (SSRLS) algorithm
based adaptive impulsive noise suppressor for OFDM
communication system is proposed. And a comparison with another
adaptive algorithm is conducted. The state space model-dependent
recursive parameters of proposed scheme enables to achieve steady
state mean squared error (MSE), low bit error rate (BER), and faster
convergence than that of some of existing algorithm.
Abstract: The problems arising from unbalanced data sets
generally appear in real world applications. Due to unequal class
distribution, many researchers have found that the performance of
existing classifiers tends to be biased towards the majority class. The
k-nearest neighbors’ nonparametric discriminant analysis is a method
that was proposed for classifying unbalanced classes with good
performance. In this study, the methods of discriminant analysis are
of interest in investigating misclassification error rates for classimbalanced
data of three diabetes risk groups. The purpose of this
study was to compare the classification performance between
parametric discriminant analysis and nonparametric discriminant
analysis in a three-class classification of class-imbalanced data of
diabetes risk groups. Data from a project maintaining healthy
conditions for 599 employees of a government hospital in Bangkok
were obtained for the classification problem. The employees were
divided into three diabetes risk groups: non-risk (90%), risk (5%),
and diabetic (5%). The original data including the variables of
diabetes risk group, age, gender, blood glucose, and BMI were
analyzed and bootstrapped for 50 and 100 samples, 599 observations
per sample, for additional estimation of the misclassification error
rate. Each data set was explored for the departure of multivariate
normality and the equality of covariance matrices of the three risk
groups. Both the original data and the bootstrap samples showed nonnormality
and unequal covariance matrices. The parametric linear
discriminant function, quadratic discriminant function, and the
nonparametric k-nearest neighbors’ discriminant function were
performed over 50 and 100 bootstrap samples and applied to the
original data. Searching the optimal classification rule, the choices of
prior probabilities were set up for both equal proportions (0.33: 0.33:
0.33) and unequal proportions of (0.90:0.05:0.05), (0.80: 0.10: 0.10)
and (0.70, 0.15, 0.15). The results from 50 and 100 bootstrap samples
indicated that the k-nearest neighbors approach when k=3 or k=4 and
the defined prior probabilities of non-risk: risk: diabetic as 0.90:
0.05:0.05 or 0.80:0.10:0.10 gave the smallest error rate of
misclassification. The k-nearest neighbors approach would be
suggested for classifying a three-class-imbalanced data of diabetes
risk groups.
Abstract: Previous studies on financial distress prediction choose
the conventional failing and non-failing dichotomy; however, the
distressed extent differs substantially among different financial
distress events. To solve the problem, “non-distressed”, “slightlydistressed”
and “reorganization and bankruptcy” are used in our article
to approximate the continuum of corporate financial health. This paper
explains different financial distress events using the two-stage method.
First, this investigation adopts firm-specific financial ratios, corporate
governance and market factors to measure the probability of various
financial distress events based on multinomial logit models.
Specifically, the bootstrapping simulation is performed to examine the
difference of estimated misclassifying cost (EMC). Second, this work
further applies macroeconomic factors to establish the credit cycle
index and determines the distressed cut-off indicator of the two-stage
models using such index. Two different models, one-stage and
two-stage prediction models are developed to forecast financial
distress, and the results acquired from different models are compared
with each other, and with the collected data. The findings show that the
one-stage model has the lower misclassification error rate than the
two-stage model. The one-stage model is more accurate than the
two-stage model.
Abstract: In this paper, we regard as a coded transmission over a
frequency-selective channel. We plan to study analytically the
convergence of the turbo-detector using a maximum a posteriori
(MAP) equalizer and a MAP decoder. We demonstrate that the
densities of the maximum likelihood (ML) exchanged during the
iterations are e-symmetric and output-symmetric. Under the Gaussian
approximation, this property allows to execute a one-dimensional
scrutiny of the turbo-detector. By deriving the analytical terminology
of the ML distributions under the Gaussian approximation, we confirm
that the bit error rate (BER) performance of the turbo-detector
converges to the BER performance of the coded additive white
Gaussian noise (AWGN) channel at high signal to noise ratio (SNR),
for any frequency selective channel.
Abstract: This paper introduces an original method of
parametric optimization of the structure for multimodal decisionlevel
fusion scheme which combines the results of the partial solution
of the classification task obtained from assembly of the mono-modal
classifiers. As a result, a multimodal fusion classifier which has the
minimum value of the total error rate has been obtained.
Abstract: The ad hoc networks are the future of wireless
technology as everyone wants fast and accurate error free information
so keeping this in mind Bit Error Rate (BER) and power is optimized
in this research paper by using the Genetic Algorithm (GA). The
digital modulation techniques used for this paper are Binary Phase
Shift Keying (BPSK), M-ary Phase Shift Keying (M-ary PSK), and
Quadrature Amplitude Modulation (QAM). This work is
implemented on Wireless Ad Hoc Networks (WLAN). Then it is
analyze which modulation technique is performing well to optimize
the BER and power of WLAN.
Abstract: In this paper, Fuzzy C-Means clustering with
Expectation Maximization-Gaussian Mixture Model based hybrid
modeling algorithm is proposed for Continuous Tamil Speech
Recognition. The speech sentences from various speakers are used
for training and testing phase and objective measures are between the
proposed and existing Continuous Speech Recognition algorithms.
From the simulated results, it is observed that the proposed algorithm
improves the recognition accuracy and F-measure up to 3% as
compared to that of the existing algorithms for the speech signal from
various speakers. In addition, it reduces the Word Error Rate, Error
Rate and Error up to 4% as compared to that of the existing
algorithms. In all aspects, the proposed hybrid modeling for Tamil
speech recognition provides the significant improvements for speechto-
text conversion in various applications.
Abstract: Children are more susceptible to medication errors
than adults. Medication administration process is the last stage in the
medication treatment process and most of the errors detected in this
stage. Little research has been undertaken about medication errors in
children in the Middle East countries. This study was aimed to
evaluate how the paediatric nurses adhere to the medication
administration policy and also to identify any medication preparation
and administration errors or any risk factors. An observational,
prospective study of medication administration process from when
the nurses preparing patient medication until administration stage
(May to August 2014) was conducted in Saudi Arabia. Twelve
paediatric nurses serving 90 paediatric patients were observed. 456
drug administered doses were evaluated. Adherence rate was variable
in 7 steps out of 16 steps. Patient allergy information, dose
calculation, drug expiry date were the steps in medication
administration with lowest adherence rates. 63 medication
preparation and administration errors were identified with error rate
13.8% of medication administrations. No potentially life-threating
errors were witnessed. Few logistic and administrative factors were
reported. The results showed that the medication administration
policy and procedure need an urgent revision to be more sensible for
nurses in practice. Nurses’ knowledge and skills regarding to the
medication administration process should be improved.
Abstract: We model and simulate the combined effect of fiber
dispersion and frequency chirp of a directly modulated high-speed
laser diode on the figures of merit of a non-amplified 40-Gbps optical
fiber link. We consider both the return to zero (RZ) and non-return to
zero (NRZ) patterns of the pseudorandom modulation bits. The
performance of the fiber communication system is assessed by the
fiber-length limitation due to the fiber dispersion. We study the
influence of replacing standard single-mode fibers by non-zero
dispersion-shifted fibers on the maximum fiber length and evaluate
the associated power penalty. We introduce new dispersion
tolerances for 1-dB power penalty of the RZ and NRZ 40-Gbps
optical fiber links.
Abstract: We introduced an all-optical multicasting
characteristics with wavelength conversion based on a novel
all-optical triode using negative feedback semiconductor optical
amplifier. This study was demonstrated with a transfer speed of 10
Gb/s to a non-return zero 231-1 pseudorandom bit sequence system.
This multi-wavelength converter device can simultaneously provide
three channels of output signal with the support of non-inverted and
inverted conversion. We studied that an all-optical multicasting and
wavelength conversion accomplishing cross gain modulation is
effective in a semiconductor optical amplifier which is effective to
provide an inverted conversion thus negative feedback. The
relationship of received power of back to back signal and output
signals with wavelength 1535 nm, 1540 nm, 1545 nm, 1550 nm, and
1555 nm with bit error rate was investigated. It was reported that the
output signal wavelengths were successfully converted and modulated
with a power penalty of less than 8.7 dB, which the highest is 8.6 dB
while the lowest is 4.4 dB. It was proved that all-optical multicasting
and wavelength conversion using an optical triode with a negative
feedback by three channels at the same time at a speed of 10 Gb/s is a
promising device for the new wavelength conversion technology.
Abstract: A relationship between face and signature biometrics
is established in this paper. A new approach is developed to predict
faces from signatures by using artificial intelligence. A multilayer
perceptron (MLP) neural network is used to generate face details
from features extracted from signatures, here face is the physical
biometric and signatures is the behavioural biometric. The new
method establishes a relationship between the two biometrics and
regenerates a visible face image from the signature features.
Furthermore, the performance efficiencies of our new technique are
demonstrated in terms of minimum error rates compared to published
work.