Abstract: This paper presents a boarding on biometric
authentication through the Keystrokes Dynamics that it intends to
identify a person from its habitual rhythm to type in conventional
keyboard. Seven done experiments: verifying amount of prototypes,
threshold, features and the variation of the choice of the times of the
features vector. The results show that the use of the Keystroke
Dynamics is simple and efficient for personal authentication, getting
optimum resulted using 90% of the features with 4.44% FRR and 0%
FAR.
Abstract: Content-based music retrieval generally involves analyzing, searching and retrieving music based on low or high level features of a song which normally used to represent artists, songs or music genre. Identifying them would normally involve feature extraction and classification tasks. Theoretically the greater features analyzed, the better the classification accuracy can be achieved but with longer execution time. Technique to select significant features is important as it will reduce dimensions of feature used in classification and contributes to the accuracy. Artificial Immune System (AIS) approach will be investigated and applied in the classification task. Bio-inspired audio content-based retrieval framework (B-ACRF) is proposed at the end of this paper where it embraces issues that need further consideration in music retrieval performances.
Abstract: Partitioning is a critical area of VLSI CAD. In order to build complex digital logic circuits its often essential to sub-divide multi -million transistor design into manageable Pieces. This paper looks at the various partitioning techniques aspects of VLSI CAD, targeted at various applications. We proposed an evolutionary time-series model and a statistical glitch prediction system using a neural network with selection of global feature by making use of clustering method model, for partitioning a circuit. For evolutionary time-series model, we made use of genetic, memetic & neuro-memetic techniques. Our work focused in use of clustering methods - K-means & EM methodology. A comparative study is provided for all techniques to solve the problem of circuit partitioning pertaining to VLSI design. The performance of all approaches is compared using benchmark data provided by MCNC standard cell placement benchmark net lists. Analysis of the investigational results proved that the Neuro-memetic model achieves greater performance then other model in recognizing sub-circuits with minimum amount of interconnections between them.
Abstract: Although Face detection is not a recent activity in the
field of image processing, it is still an open area for research. The
greatest step in this field is the work reported by Viola and its recent
analogous is Huang et al. Both of them use similar features and also
similar training process. The former is just for detecting upright
faces, but the latter can detect multi-view faces in still grayscale
images using new features called 'sparse feature'. Finding these
features is very time consuming and inefficient by proposed methods.
Here, we propose a new approach for finding sparse features using a
genetic algorithm system. This method requires less computational
cost and gets more effective features in learning process for face
detection that causes more accuracy.
Abstract: This paper presents an approach for an unequal error
protection of facial features of personal ID images coding. We
consider unequal error protection (UEP) strategies for the efficient
progressive transmission of embedded image codes over noisy
channels. This new method is based on the progressive image
compression embedded zerotree wavelet (EZW) algorithm and UEP
technique with defined region of interest (ROI). In this case is ROI
equal facial features within personal ID image. ROI technique is
important in applications with different parts of importance. In ROI
coding, a chosen ROI is encoded with higher quality than the
background (BG). Unequal error protection of image is provided by
different coding techniques and encoding LL band separately. In our
proposed method, image is divided into two parts (ROI, BG) that
consist of more important bytes (MIB) and less important bytes
(LIB). The proposed unequal error protection of image transmission
has shown to be more appropriate to low bit rate applications,
producing better quality output for ROI of the compresses image.
The experimental results verify effectiveness of the design. The
results of our method demonstrate the comparison of the UEP of
image transmission with defined ROI with facial features and the
equal error protection (EEP) over additive white gaussian noise
(AWGN) channel.
Abstract: Robust face recognition under various illumination
environments is very difficult and needs to be accomplished for
successful commercialization. In this paper, we propose an improved
illumination normalization method for face recognition. Illumination
normalization algorithm based on anisotropic smoothing is well known
to be effective among illumination normalization methods but
deteriorates the intensity contrast of the original image, and incurs less
sharp edges. The proposed method in this paper improves the previous
anisotropic smoothing-based illumination normalization method so
that it increases the intensity contrast and enhances the edges while
diminishing the effect of illumination variations. Due to the result of
these improvements, face images preprocessed by the proposed
illumination normalization method becomes to have more distinctive
feature vectors (Gabor feature vectors) for face recognition. Through
experiments of face recognition based on Gabor feature vector
similarity, the effectiveness of the proposed illumination
normalization method is verified.
Abstract: Natural frequencies and dynamic response of a spur
gear sector are investigated using a two dimensional finite element
model that offers significant advantages for dynamic gear analyses.
The gear teeth are analyzed for different operating speeds. A primary
feature of this modeling is determination of mesh forces using a
detailed contact analysis for each time step as the gears roll through
the mesh. ANSYS software has been used on the proposed model to
find the natural frequencies by Block Lanczos technique and
displacements and dynamic stresses by transient mode super position
method. The effect of rotational speed of the gear on the dynamic
response of gear tooth has been studied and design limits have been
discussed.
Abstract: Fake finger submission attack is a major problem in fingerprint recognition systems. In this paper, we introduce an aliveness detection method based on multiple static features, which derived from a single fingerprint image. The static features are comprised of individual pore spacing, residual noise and several first order statistics. Specifically, correlation filter is adopted to address individual pore spacing. The multiple static features are useful to reflect the physiological and statistical characteristics of live and fake fingerprint. The classification can be made by calculating the liveness scores from each feature and fusing the scores through a classifier. In our dataset, we compare nine classifiers and the best classification rate at 85% is attained by using a Reduced Multivariate Polynomial classifier. Our approach is faster and more convenient for aliveness check for field applications.
Abstract: This paper aims to provide a conceptual framework to examine competitive disadvantage of banks that suffer from poor performance. Banks generate revenues mainly from the interest rate spread on taking deposits and making loans while collecting fees in the process. To maximize firm value, banks seek loan growth and expense control while managing risk associated with loans with respect to non-performing borrowers or narrowing interest spread between assets and liabilities. Competitive disadvantage refers to the failure to access imitable resources and to build managing capabilities to gain sustainable return given appropriate risk management. This paper proposes a four-quadrant framework of organizational typology is subsequently proposed to examine the features of competitive disadvantage in the banking sector. A resource configuration model, which is extracted from CAMEL indicators to examine the underlying features of bank failures.
Abstract: In this research the separation efficiency of deoiling hydrocyclone is evaluated using three-dimensional simulation of multiphase flow based on Eulerian-Eulerian finite volume method. The mixture approach of Reynolds Stress Model is also employed to capture the features of turbulent multiphase swirling flow. The obtained separation efficiency of Colman's design is compared with available experimental data and showed that the separation curve of deoiling hydrocyclones can be predicted using numerical simulation.
Abstract: The network traffic data provided for the design of
intrusion detection always are large with ineffective information and
enclose limited and ambiguous information about users- activities.
We study the problems and propose a two phases approach in our
intrusion detection design. In the first phase, we develop a
correlation-based feature selection algorithm to remove the worthless
information from the original high dimensional database. Next, we
design an intrusion detection method to solve the problems of
uncertainty caused by limited and ambiguous information. In the
experiments, we choose six UCI databases and DARPA KDD99
intrusion detection data set as our evaluation tools. Empirical studies
indicate that our feature selection algorithm is capable of reducing the
size of data set. Our intrusion detection method achieves a better
performance than those of participating intrusion detectors.
Abstract: This paper demonstrates design and construction of
microcontroller-based telephone exchange system and the aims of
this paper is to study telecommunication, connection with
PIC16F877A and DTMF MT8870D. In microcontroller system, PIC
16F877 microcontroller is used to control the call processing. Dial
tone, busy tone and ring tone are provided during call progress.
Instead of using ready made tone generator IC, oscillator based tone
generator is used. The results of this telephone exchange system are
perfect for homes and small businesses needing the extensions. It
requires the phone operation control system, the analog interface
circuit and the switching circuit. This exchange design will contain
eight channels.
It is the best low cost, good quality telephone exchange for today-s
telecommunication needs. It offers the features available in much
more expensive PBX units without using high-priced phones. It is for
long distance telephone services.
Abstract: Public awareness towards green energy are on the rise and this can be prove by many product being manufactured or prerequired to be made as energy saving devices mainly to save consumer from spending more on utility billing. These schemes are popular nowadays and many homemade appliances are turned into energy saving gadget which attracts the attention of consumers. Knowing the public demands and pattern towards purchasing home appliances thus the idea of “energy saving suction hood (ESSH)" is proposed. The ESSH can be used in many places that require smoke ventilation or even to reduce the room temperature as many conventional suction hoods (CSH) do, but this device works automatically by the usage of sensors that detects the smoke/temperature and automatically spins the exhaust fan. As it turns, the mechanical rotation rotates the AC generator which is coupled together with the fan and then charges the battery. The innovation of this product is, it does not rely on the utility supply as it is also hook up with a solar panel which also charges the battery, Secondly, it generates energy as the exhaust fan mechanically rotates. Thirdly, an energy loop back feature is introduced to this system which will supply for the ventilator fan. Another major innovation is towards interfacing this device with an in house production of generator. This generator is produced by proper design on stator as well as rotor to reduce the losses. A comparison is made between the ESSH and the CSH and result shows that the ESSH saves 172.8kWh/year of utility supply which is used by CSH. This amount of energy can save RM 3.14 from monthly utility bill and a total of RM 37.67 per year. In fact this product can generate 175 Watt of power from generator(75W) and solar panel(100W) that can be used either to supply other household appliances and/or to loop back to supply the fans motor. The innovation of this system is essential for future production of other equipment by using the loopback power method and turning most equipment into a standalone system.
Abstract: This paper presents a new approach to tackle the problem of recognizing machine-printed Arabic texts. Because of the difficulty of recognizing cursive Arabic words, the text has to be normalized and segmented to be ready for the recognition stage. The new scheme for recognizing Arabic characters depends on multiple parallel neural networks classifier. The classifier has two phases. The first phase categories the input character into one of eight groups. The second phase classifies the character into one of the Arabic character classes in the group. The system achieved high recognition rate.
Abstract: This study analyzes on the Social Network Game
(SNG), ANIPANG, in order to discover its unique fun elements, so
that suggest new methodologies for development of SNGs. ANIPANG
is the most popular SNG in the South Korea on 2012. Recently, the
game industry is paying close attention to mobile-based SNGs due to
the rapid prevalence of smart-phones and social network services.
However, SNGs are not online games simply. Although the fun of
most online games is the victory through competition with other
players or the game system, the fun of SNG is the communication
through the collaboration with other players. Thus, features of users
and environments of game should be considered for the game industry
and for the fun of SNG to users.
Abstract: This paper presents design features of a rescue robot, named CEO Mission II. Its body is designed to be the track wheel type with double front flippers for climbing over the collapse and the rough terrain. With 125 cm. long, 5-joint mechanical arm installed on the robot body, it is deployed not only for surveillance from the top view but also easier and faster access to the victims to get their vital signs. Two cameras and sensors for searching vital signs are set up at the tip of the multi-joint mechanical arm. The third camera is at the back of the robot for driving control. Hardware and software of the system, which controls and monitors the rescue robot, are explained. The control system is used for controlling the robot locomotion, the 5-joint mechanical arm, and for turning on/off devices. The monitoring system gathers all information from 7 distance sensors, IR temperature sensors, 3 CCD cameras, voice sensor, robot wheels encoders, yawn/pitch/roll angle sensors, laser range finder and 8 spare A/D inputs. All sensors and controlling data are communicated with a remote control station via IEEE 802.11b Wi-Fi. The audio and video data are compressed and sent via another IEEE 802.11g Wi-Fi transmitter for getting real-time response. At remote control station site, the robot locomotion and the mechanical arm are controlled by joystick. Moreover, the user-friendly GUI control program is developed based on the clicking and dragging method to easily control the movement of the arm. Robot traveling map is plotted from computing the information of wheel encoders and the yawn/pitch data. 2D Obstacle map is plotted from data of the laser range finder. The concept and design of this robot can be adapted to suit many other applications. As the Best Technique awardee from Thailand Rescue Robot Championship 2006, all testing results are satisfied.
Abstract: This paper proposes a novel system for monitoring the
health of underground pipelines. Some of these pipelines transport
dangerous contents and any damage incurred might have catastrophic
consequences. However, most of these damage are unintentional and
usually a result of surrounding construction activities. In order to
prevent these potential damages, monitoring systems are
indispensable. This paper focuses on acoustically recognizing road
cutters since they prelude most construction activities in modern
cities. Acoustic recognition can be easily achieved by installing a
distributed computing sensor network along the pipelines and using
smart sensors to “listen" for potential threat; if there is a real threat,
raise some form of alarm. For efficient pipeline monitoring, a novel
monitoring approach is proposed. Principal Component Analysis
(PCA) was studied and applied. Eigenvalues were regarded as the
special signature that could characterize a sound sample, and were
thus used for the feature vector for sound recognition. The denoising
ability of PCA could make it robust to noise interference. One class
SVM was used for classifier. On-site experiment results show that the
proposed PCA and SVM based acoustic recognition system will be
very effective with a low tendency for raising false alarms.
Abstract: Previously, harmonic parameters (HPs) have been
selected as features extracted from EEG signals for automatic sleep
scoring. However, in previous studies, only one HP parameter was
used, which were directly extracted from the whole epoch of EEG
signal.
In this study, two different transformations were applied to extract
HPs from EEG signals: Hilbert-Huang transform (HHT) and wavelet
transform (WT). EEG signals are decomposed by the two
transformations; and features were extracted from different
components. Twelve parameters (four sets of HPs) were extracted.
Some of the parameters are highly diverse among different stages.
Afterward, HPs from two transformations were used to building a
rough sleep stages scoring model using the classifier SVM. The
performance of this model is about 78% using the features obtained by
our proposed extractions. Our results suggest that these features may
be useful for automatic sleep stages scoring.
Abstract: We presented results of research aimed on findings
influence of social - psychological training (realized with students of
Constantine the Philosopher University- future teachers within their
undergraduate preparation) on the choice of intrapersonal and
interpersonal features. After social- psychological training using
Interpersonal Check List (ICL) we found out shift of behavior to
more adaptive forms in categories, which are characterized by
extroversive friendly behavior, willingness to cooperation,
conformity regard to social situation, responsible and regardful
behavior.
Using State-Trait Anxiety Inventory (STAI) we found out the cut
down of state anxiety and of trait anxiety. The report was processed
within grants KEGA 3/5269/07 and VEGA 1/3675/06.
Abstract: Wavelet transform has been extensively used in
machine fault diagnosis and prognosis owing to its strength to deal
with non-stationary signals. The existing Wavelet transform based
schemes for fault diagnosis employ wavelet decomposition of the
entire vibration frequency which not only involve huge
computational overhead in extracting the features but also increases
the dimensionality of the feature vector. This increase in the
dimensionality has the tendency to 'over-fit' the training data and
could mislead the fault diagnostic model. In this paper a novel
technique, envelope wavelet packet transform (EWPT) is proposed in
which features are extracted based on wavelet packet transform of the
filtered envelope signal rather than the overall vibration signal. It not
only reduces the computational overhead in terms of reduced number
of wavelet decomposition levels and features but also improves the
fault detection accuracy. Analytical expressions are provided for the
optimal frequency resolution and decomposition level selection in
EWPT. Experimental results with both actual and simulated machine
fault data demonstrate significant gain in fault detection ability by
EWPT at reduced complexity compared to existing techniques.