Abstract: In this paper, we present a new learning algorithm for
anomaly based network intrusion detection using improved self
adaptive naïve Bayesian tree (NBTree), which induces a hybrid of
decision tree and naïve Bayesian classifier. The proposed approach
scales up the balance detections for different attack types and keeps
the false positives at acceptable level in intrusion detection. In
complex and dynamic large intrusion detection dataset, the detection
accuracy of naïve Bayesian classifier does not scale up as well as
decision tree. It has been successfully tested in other problem
domains that naïve Bayesian tree improves the classification rates in
large dataset. In naïve Bayesian tree nodes contain and split as
regular decision-trees, but the leaves contain naïve Bayesian
classifiers. The experimental results on KDD99 benchmark network
intrusion detection dataset demonstrate that this new approach scales
up the detection rates for different attack types and reduces false
positives in network intrusion detection.
Abstract: Sexual behavior and semen charactertistics were
evaluated in young male Boer goats in tropical condition during time
period of September to November 2009. The animal was let to have
adaptation for five months after importation from Australian climate.
A total of 20 bucks were observed for sexual behavior and ability of
semen production. Out of this number, 4 faild to libido and 3
produced poor semen. The remaing 13 animals were divided into
three groups according to the ages (11-13, 15-16 and 18-25 months).
Sexual behavior consisting response time to female teaser,
ejaculation time, fixing strenght to female and erection status were
normaly observer in 13 bucks, and there was no significant difference
between age groups. Semen characteristics from 13 bucks were in
normal quality in the volume, sperm mass motility, individual
motility, percentage of live- and abnormal sperm. We concluded that
is possible to collect semen of Boer goats during the period of
September to November under tropical condition. Collection during
other time period should be analyzed.
Abstract: In this paper an open agent-based modular framework
for personalized and adaptive curriculum generation in e-learning
environment is proposed. Agent-based approaches offer several
potential advantages over alternative approaches. Agent-based
systems exhibit high levels of flexibility and robustness in dynamic
or unpredictable environments by virtue of their intrinsic autonomy.
The presented framework enables integration of different types of
expert agents, various kinds of learning objects and user modeling
techniques. It creates possibilities for adaptive e-learning process.
The KM e-learning system is in a process of implementation in
Varna Free University and will be used for supporting the
educational process at the University.
Abstract: Successful intelligence (SI) is the integrated set of the
ability needed to attain success in life, within individual-s sociocultural
context. People are successfully intelligent by recognizing
their strengths and weaknesses. They will find ways to strengthen
their weakness and maintain their strength or even improve it. SI
people can shape, select, and adapt to the environments by using
balance of higher-ordered thinking abilities including; critical,
creative, and applicative. Aims: The purposes of this study were to;
1) develop curriculum that promotes SI for nursing students, and 2)
study the effectiveness of the curriculum development. Method:
Research and Development was a method used for this study. The
design was divided into two phases; 1) the curriculum development
which composed of three steps (needs assessment, curriculum
development and curriculum field trail), and 2) the curriculum
implementation. In this phase, a pre-experimental research design
(one group pretest-posttest design) was conducted. The sample
composed of 49 sophomore nursing students of Boromarajonani
College of Nursing, Surin, Thailand who enrolled in Nursing care of
Health problem course I in 2011 academic year. Data were carefully
collected using 4 instruments; 1) Modified essay questions test
(MEQ) 2) Nursing Care Plan evaluation form 3) Group processing
observation form (α = 0.74) and 4) Satisfied evaluation form of
learning (α = 0.82). Data were analyzed using descriptive statistics
and content analysis. Results: The results revealed that the sample
had post-test average score of SI higher than pre-test average score
(mean difference was 5.03, S.D. = 2.84). Fifty seven percentages of
the sample passed the MEQ posttest at the criteria of 60 percentages.
Students demonstrated the strategies of how to develop nursing care
plan. Overall, students- satisfaction on teaching performance was at
high level (mean = 4.35, S.D. = 0.46). Conclusion: This curriculum
can promote the attribute of characteristic of SI person and was
highly required to be continued.
Abstract: This paper attempts to model and design a simple
fuzzy logic controller with Variable Reference. The Variable
Reference (VR) is featured as an adaptability element which is
obtained from two known variables – desired system-input and actual
system-output. A simple fuzzy rule-based technique is simulated to
show how the actual system-input is gradually tuned in to a value
that closely matches the desired input. The designed controller is
implemented and verified on a simple heater which is controlled by
PIC Microcontroller harnessed by a code developed in embedded C.
The output response of the PIC-controlled heater is analyzed and
compared to the performances by conventional fuzzy logic
controllers. The novelty of this work lies in the fact that it gives
better performance by using less number of rules compared to
conventional fuzzy logic controllers.
Abstract: The motivation for adaptive modulation and coding is
to adjust the method of transmission to ensure that the maximum
efficiency is achieved over the link at all times. The receiver
estimates the channel quality and reports it back to the transmitter.
The transmitter then maps the reported quality into a link mode. This
mapping however, is not a one-to-one mapping. In this paper we
investigate a method for selecting the proper modulation scheme.
This method can dynamically adapt the mapping of the Signal-to-
Noise Ratio (SNR) into a link mode. It enables the use of the right
modulation scheme irrespective of changes in the channel conditions
by incorporating errors in the received data. We propose a Markov
model for this method, and use it to derive the average switching
thresholds and the average throughput. We show that the average
throughput of this method outperforms the conventional threshold
method.
Abstract: The Continuously Adaptive Mean-Shift (CamShift)
algorithm, incorporating scene depth information is combined with
the l1-minimization sparse representation based method to form a
hybrid kernel and state space-based tracking algorithm. We take
advantage of the increased efficiency of the former with the
robustness to occlusion property of the latter. A simple interchange
scheme transfers control between algorithms based upon drift and
occlusion likelihood. It is quantified by the projection of target
candidates onto a depth map of the 2D scene obtained with a low cost
stereo vision webcam. Results are improved tracking in terms of drift
over each algorithm individually, in a challenging practical outdoor
multiple occlusion test case.
Abstract: The purpose of this research is to increase our
knowledge as regards how Small-and-Medium-Sized Enterprises
(SMEs) tackle ERP implementation projects to achieve successful
adoption and use of these systems within the organization. SMEs
have scare resources to handle these kinds of projects which have
proved to be risky and costly. There are several studies focusing on
ERP implementation in larger companies, however, few studies
report on challenges experienced by SMEs. Our research seeks to
bridge this gap. Through a multiple case study of four companies, we
identified challenges and critical elements within the different phases
(pre-implementation, implementation and post-implementation) of
the ERP life cycle. To interpret our findings, we utilize a well-know
ERP life cycle model and critical success factors developed for larger
companies which are reported in former research literature. We
discuss if these models are relevant for SMEs and suggest additional
critical elements identified in this study to make a framework more
adapted to the SME context.
Abstract: In today-s highly globalised and competitive world
access to information plays key role in having an upper hand between
business rivals. Hence, proper protection of such crucial resource is
core to any modern business. Implementing a successful information
security system is basically centered around three pillars; technical
solution involving both software and hardware, information security
controls to translate the policies and procedure in the system and the
people to implement. This paper shows that a lot needs to be done for
countries adapting information technology to process, store and
distribute information to secure adequately such core resource.
Abstract: This paper presents a design method of self-tuning
Quantitative Feedback Theory (QFT) by using improved deadbeat
control algorithm. QFT is a technique to achieve robust control with
pre-defined specifications whereas deadbeat is an algorithm that
could bring the output to steady state with minimum step size.
Nevertheless, usually there are large peaks in the deadbeat response.
By integrating QFT specifications into deadbeat algorithm, the large
peaks could be tolerated. On the other hand, emerging QFT with
adaptive element will produce a robust controller with wider
coverage of uncertainty. By combining QFT-based deadbeat
algorithm and adaptive element, superior controller that is called selftuning
QFT-based deadbeat controller could be achieved. The output
response that is fast, robust and adaptive is expected. Using a grain
dryer plant model as a pilot case-study, the performance of the
proposed method has been evaluated and analyzed. Grain drying
process is very complex with highly nonlinear behaviour, long delay,
affected by environmental changes and affected by disturbances.
Performance comparisons have been performed between the
proposed self-tuning QFT-based deadbeat, standard QFT and
standard dead-beat controllers. The efficiency of the self-tuning QFTbased
dead-beat controller has been proven from the tests results in
terms of controller’s parameters are updated online, less percentage
of overshoot and settling time especially when there are variations in
the plant.
Abstract: A generalized Digital Modulation Identification algorithm for adaptive demodulator has been developed and presented in this paper. The algorithm developed is verified using wavelet Transform and histogram computation to identify QPSK and QAM with GMSK and M–ary FSK modulations. It has been found that the histogram peaks simplifies the procedure for identification. The simulated results show that the correct modulation identification is possible to a lower bound of 5 dB and 12 dB for GMSK and QPSK respectively. When SNR is above 5 dB the throughput of the proposed algorithm is more than 97.8%. The receiver operating characteristics (ROC) has been computed to measure the performance of the proposed algorithm and the analysis shows that the probability of detection (Pd) drops rapidly when SNR is 5 dB and probability of false alarm (Pf) is smaller than 0.3. The performance of the proposed algorithm has been compared with existing methods and found it will identify all digital modulation schemes with low SNR.
Abstract: Mobile Ad hoc Networks is an autonomous system of
mobile nodes connected by multi-hop wireless links without
centralized infrastructure support. As mobile communication gains
popularity, the need for suitable ad hoc routing protocols will
continue to grow. Efficient dynamic routing is an important research
challenge in such a network. Bandwidth constrained mobile devices
use on-demand approach in their routing protocols because of its
effectiveness and efficiency. Many researchers have conducted
numerous simulations for comparing the performance of these
protocols under varying conditions and constraints. Most of them are
not aware of MAC Protocols, which will impact the relative
performance of routing protocols considered in different network
scenarios. In this paper we investigate the choice of MAC protocols
affects the relative performance of ad hoc routing protocols under
different scenarios. We have evaluated the performance of these
protocols using NS2 simulations. Our results show that the
performance of routing protocols of ad hoc networks will suffer when
run over different MAC Layer protocols.
Abstract: Recently, there have been an increasing interest in RFID system and RFID systems have been applied to various applications. Load balancing is a fundamental technique for providing scalability of systems by moving workload from overloaded nodes to under-loaded nodes. This paper presents an approach to adaptive load balancing for RFID middlewares. Workloads of RFID middlewares can have a considerable variation according to the location of the connected RFID readers and can abruptly change at a particular instance. The proposed approach considers those characteristics of RFID middle- wares to provide an efficient load balancing.
Abstract: In this paper, we propose a novel adaptive
spatiotemporal filter that utilizes image sequences in order to remove
noise. The consecutive frames include: current, previous and next
noisy frames. The filter proposed in this paper is based upon the
weighted averaging pixels intensity and noise variance in image
sequences. It utilizes the Appropriate Number of Consecutive Frames
(ANCF) based on the noisy pixels intensity among the frames. The
number of consecutive frames is adaptively calculated for each
region in image and its value may change from one region to another
region depending on the pixels intensity within the region. The
weights are determined by a well-defined mathematical criterion,
which is adaptive to the feature of spatiotemporal pixels of the
consecutive frames. It is experimentally shown that the proposed
filter can preserve image structures and edges under motion while
suppressing noise, and thus can be effectively used in image
sequences filtering. In addition, the AWA filter using ANCF is
particularly well suited for filtering sequences that contain segments
with abruptly changing scene content due to, for example, rapid
zooming and changes in the view of the camera.
Abstract: In this study, a robust intelligent backstepping tracking control (RIBTC) system combined with adaptive output recurrent cerebellar model articulation control (AORCMAC) and H∞ control technique is proposed for wheeled inverted pendulums (WIPs) real-time control with exact system dynamics unknown. Moreover, a robust H∞ controller is designed to attenuate the effect of the residual approximation errors and external disturbances with desired attenuation level. The experimental results indicate that the WIPs can stand upright stably when using the proposed RIBTC.
Abstract: In this paper, we propose a novel spatiotemporal fuzzy
based algorithm for noise filtering of image sequences. Our proposed algorithm uses adaptive weights based on a triangular membership
functions. In this algorithm median filter is used to suppress noise.
Experimental results show when the images are corrupted by highdensity
Salt and Pepper noise, our fuzzy based algorithm for noise filtering of image sequences, are much more effective in suppressing
noise and preserving edges than the previously reported algorithms such as [1-7]. Indeed, assigned weights to noisy pixels are very
adaptive so that they well make use of correlation of pixels. On the other hand, the motion estimation methods are erroneous and in highdensity noise they may degrade the filter performance. Therefore, our
proposed fuzzy algorithm doesn-t need any estimation of motion trajectory. The proposed algorithm admissibly removes noise without having any knowledge of Salt and Pepper noise density.
Abstract: Observations and long-term trends indicate that climate
change impacts would be significant and affects Taiwan directly and
severely. Taiwan engages not only in mitigation, but also in adaptation.
However, there are cognitive gaps on adaptation between government
and populace. Besides, a vision of zero-carbon and renewable energy
100% will be adopted in future. Therefore, the objectives of this
article are to 1) hold a National Forum for knowing differences
between the strategies of zero-carbon and renewable energy 100% and
cognitions of general populace, and 2) plan a clear roadmap for the
vision, strategy, and measures. In this forum, we set 5 group topics, 5
presumed themes, and issues mentioned review for concluding the
critical issues. Finally, there are 4 strategies and 14 critical issues
which correlate with the vision and strategy of government and the
cognition of the general populace.
Abstract: This paper presents a simple and original method for
the generation of short monocycle pulses based on the transient
response of a passive band-pass filter. The recorded sub-nanosecond
pulses show a good symmetry and a small ringing (13 % of the peak
amplitude). Their spectral density covers the range 3.1 GHz to
10.6 GHz. The possibility to adapt the pulse spectral density to the
indoor FCC frequency mask is demonstrated with a prototype
working at a reduced frequency (FCC/1000). A detection technique is
proposed.
Abstract: A nonlinear optimal controller with a fuzzy gain
scheduler has been designed and applied to a Line-Of-Sight (LOS)
stabilization system. Use of Linear Quadratic Regulator (LQR)
theory is an optimal and simple manner of solving many control
engineering problems. However, this method cannot be utilized
directly for multigimbal LOS systems since they are nonlinear in
nature. To adapt LQ controllers to nonlinear systems at least a
linearization of the model plant is required. When the linearized
model is only valid within the vicinity of an operating point a gain
scheduler is required. Therefore, a Takagi-Sugeno Fuzzy Inference
System gain scheduler has been implemented, which keeps the
asymptotic stability performance provided by the optimal feedback
gain approach. The simulation results illustrate that the proposed
controller is capable of overcoming disturbances and maintaining a
satisfactory tracking performance.
Abstract: The implementations of green roof have been widely
used in the developed countries such as Germany, United Kingdom,
United States and Canada. Green roof have many benefits such as
aesthetic and economic value, ecological gain which are optimization
of storm water management, urban heat island mitigation and energy
conservation. In term of pollution, green roof can control the air and
noise pollution in urban cities. The application of green roof in
Malaysian building has been studied with the previous work of green
roof either in Malaysia or other Asian region as like Indonesia,
Singapore, Thailand, Taiwan and several other countries that have
similar climate and environment as in Malaysia. These technologies
of adapting green roof have been compared to the Green Building
Index (GBI) of Malaysian buildings. The study has concentrated on
the technical aspect of green roof system having focused on i) waste
& recyclable materials ii) types of plants and method of planting and
iii) green roof as tool to reduce storm water runoff. The finding of
these areas will be compared to the suitability in achieving good
practice of the GBI in Malaysia. Results show that most of the
method are based on the countries own climate and environment.
This suggests that the method of using green roof must adhere to the
tropical climate of Malaysia. Suggestion of this research will be
viewed in term of the sustainability of the green roof. Further
research can be developed to implement the best method and
application in Malaysian climate especially in urban cities and
township.