Abstract: The goal of a network-based intrusion detection
system is to classify activities of network traffics into two major
categories: normal and attack (intrusive) activities. Nowadays, data
mining and machine learning plays an important role in many
sciences; including intrusion detection system (IDS) using both
supervised and unsupervised techniques. However, one of the
essential steps of data mining is feature selection that helps in
improving the efficiency, performance and prediction rate of
proposed approach. This paper applies unsupervised K-means
clustering algorithm with information gain (IG) for feature selection
and reduction to build a network intrusion detection system. For our
experimental analysis, we have used the new NSL-KDD dataset,
which is a modified dataset for KDDCup 1999 intrusion detection
benchmark dataset. With a split of 60.0% for the training set and the
remainder for the testing set, a 2 class classifications have been
implemented (Normal, Attack). Weka framework which is a java
based open source software consists of a collection of machine
learning algorithms for data mining tasks has been used in the testing
process. The experimental results show that the proposed approach is
very accurate with low false positive rate and high true positive rate
and it takes less learning time in comparison with using the full
features of the dataset with the same algorithm.
Abstract: This paper has, as its point of departure, the foundational
axiomatic theory of E. De Giorgi (1996, Scuola Normale
Superiore di Pisa, Preprints di Matematica 26, 1), based on two
primitive notions of quality and relation. With the introduction of
a unary relation, we develop a system totally based on the sole
primitive notion of relation. Such a modification enables a definition
of the concept of dynamic unary relation. In this way we construct a
simple language capable to express other well known theories such
as Robinson-s arithmetic or a piece of a theory of concatenation. A
key role in this system plays an abstract relation designated by “( )",
which can be interpreted in different ways, but in this paper we will
focus on the case when we can perform computations and obtain
results.
Abstract: Mostly transforms are used for speech data
compressions which are lossy algorithms. Such algorithms are
tolerable for speech data compression since the loss in quality is not
perceived by the human ear. However the vector quantization (VQ)
has a potential to give more data compression maintaining the same
quality. In this paper we propose speech data compression algorithm
using vector quantization technique. We have used VQ algorithms
LBG, KPE and FCG. The results table shows computational
complexity of these three algorithms. Here we have introduced a new
performance parameter Average Fractional Change in Speech
Sample (AFCSS). Our FCG algorithm gives far better performance
considering mean absolute error, AFCSS and complexity as
compared to others.
Abstract: This paper proposes a novel improvement of forecasting approach based on using time-invariant fuzzy time series. In contrast to traditional forecasting methods, fuzzy time series can be also applied to problems, in which historical data are linguistic values. It is shown that proposed time-invariant method improves the performance of forecasting process. Further, the effect of using different number of fuzzy sets is tested as well. As with the most of cited papers, historical enrollment of the University of Alabama is used in this study to illustrate the forecasting process. Subsequently, the performance of the proposed method is compared with existing fuzzy time series time-invariant models based on forecasting accuracy. It reveals a certain performance superiority of the proposed method over methods described in the literature.
Abstract: A vertical SOI-based MOSFET with trench body
structure operated as 1T DRAM cell at various temperatures has been
studied and investigated. Different operation temperatures are
assigned for the device for its performance comparison, thus the
thermal stability is carefully evaluated for the future memory device
applications. Based on the simulation, the vertical SOI-based
MOSFET with trench body structure demonstrates the electrical
characteristics properly and possess conspicuous kink effect at
various operation temperatures. Transient characteristics were also
performed to prove that its programming window values and
retention time behaviors are acceptable when the new 1T DRAM cell
is operated at high operation temperature.
Abstract: A packet analyzer is a tool for debugging sensor
network systems and is convenient for developers. In this paper, we
introduce a new packet analyzer based on an embedded system. The
proposed packet analyzer is compatible with IEEE 802.15.4, which is
suitable for the wireless communication standard for sensor networks,
and is available for remote control by adopting a server-client scheme
based on the Ethernet interface. To confirm the operations of the
packet analyzer, we have developed two types of sensor nodes based
on PIC4620 and ATmega128L microprocessors and tested the
functions of the proposed packet analyzer by obtaining the packets
from the sensor nodes.
Abstract: In this paper, several improvements are proposed to
previous work of automated classification of alcoholics and nonalcoholics.
In the previous paper, multiplayer-perceptron neural
network classifying energy of gamma band Visual Evoked Potential
(VEP) signals gave the best classification performance using 800
VEP signals from 10 alcoholics and 10 non-alcoholics. Here, the
dataset is extended to include 3560 VEP signals from 102 subjects:
62 alcoholics and 40 non-alcoholics. Three modifications are
introduced to improve the classification performance: i) increasing
the gamma band spectral range by increasing the pass-band width of
the used filter ii) the use of Multiple Signal Classification algorithm
to obtain the power of the dominant frequency in gamma band VEP
signals as features and iii) the use of the simple but effective knearest
neighbour classifier. To validate that these two modifications
do give improved performance, a 10-fold cross validation
classification (CVC) scheme is used. Repeat experiments of the
previously used methodology for the extended dataset are performed
here and improvement from 94.49% to 98.71% in maximum
averaged CVC accuracy is obtained using the modifications. This
latest results show that VEP based classification of alcoholics is
worth exploring further for system development.
Abstract: The move from cash accounting to accrual accounting, or rule-based to principle-based accounting, by many governments is part of an ongoing efforts in promoting a more business-like and performance-focused public sector. Using questionnaire responses from preparers of financial statements of public universities in Malaysia, this study examines the implementation challenges and benefits of principle-based accounting. Results from these responses suggest that most respondents perceived significant costs would be incurred in relation to staff training and recruitment of staffs with relevant technical knowledge. In addition, most respondents also perceived that there will be significant changes in the current accounting system and structure in order to comply with the principle-based accounting requirements. However, most respondents perceived that these changes might not result in significant benefits for management purposes, for example, financial management, budgeting and allocation of resources. Nevertheless, most respondents perceived that principle-based accounting information would facilitate the monitoring function of the board. The general perception is that adoption of principle-based accounting information is not significantly useful than rule-based accounting information is expected to change over time as preparers of the financial statements gradually understand and appreciate the benefits of principle-based accounting information. This infers that the perceived usefulness of different accounting system is a function of familiarity by the preparers.
Abstract: In this paper we propose a simple adaptive algorithm
iteratively solving the unit-norm constrained optimization problem.
Instead of conventional parameter norm based normalization,
the proposed algorithm incorporates scalar normalization which is
computationally much simpler. The analysis of stationary point is
presented to show that the proposed algorithm indeed solves the
constrained optimization problem. The simulation results illustrate
that the proposed algorithm performs as good as conventional ones
while being computationally simpler.
Abstract: In Content-Based Image Retrieval systems it is
important to use an efficient indexing technique in order to perform
and accelerate the search in huge databases. The used indexing
technique should also support the high dimensions of image features.
In this paper we present the hierarchical index NOHIS-tree (Non
Overlapping Hierarchical Index Structure) when we scale up to very
large databases. We also present a study of the influence of clustering
on search time. The performance test results show that NOHIS-tree
performs better than SR-tree. Tests also show that NOHIS-tree keeps
its performances in high dimensional spaces. We include the
performance test that try to determine the number of clusters in
NOHIS-tree to have the best search time.
Abstract: The picture of a perfect road construction site is the one that utilizes conventional vertical road signs and a flagman to optimize the traffic flow with minimum hazel to the public. Former research has been carried out by Department of Occupational Safety and Health (DOSH) and Ministry of Works to further enhance smoothness in traffic operations and particularly in safety issues within work zones. This paper highlights on hazardous zones in a certain road construction or road maintenance site. Most cases show that the flagman falls into high risk of fatal accidents within work zone. Various measures have been taken by both the authorities and contractors to overcome such miseries, yet it-s impossible to eliminate the usage of a flagman since it is considered the best practice. With the implementation of new technologies in automating the traffic flow in road construction site, it is possible to eliminate the usage of a flagman. The intelligent traffic light system is designed to solve problems which contribute hazardous at road construction site and to be inline with the road safety regulation which is taken into granted.
Abstract: This article reports on the studies of porous GaN prepared by ultra-violet (UV) assisted electrochemical etching in a solution of 4:1:1 HF: CH3OH:H2O2 under illumination of an UV lamp with 500 W power for 10, 25 and 35 minutes. The optical properties of porous GaN sample were compared to the corresponding as grown GaN. Porosity induced photoluminescence (PL) intensity enhancement was found in these samples. The resulting porous GaN displays blue shifted PL spectra compared to the as-grown GaN. Appearance of the blue shifted emission is correlated with the development of highly anisotropic structures in the morphology. An estimate of the size of the GaN nanostructure can be obtained with the help of a quantized state effective mass theory.
Abstract: Multi-Radio Multi-Channel (MRMC) systems are key to power control problems in wireless mesh networks (WMNs). In this paper, we present asynchronous multiple-state based power control for MRMC WMNs. First, WMN is represented as a set of disjoint Unified Channel Graphs (UCGs). Second, each network interface card (NIC) or radio assigned to a unique UCG adjusts transmission power using predicted multiple interaction state variables (IV) across UCGs. Depending on the size of queue loads and intra- and inter-channel states, each NIC optimizes transmission power locally and asynchronously. A new power selection MRMC unification protocol (PMMUP) is proposed that coordinates interactions among radios. The efficacy of the proposed method is investigated through simulations.
Abstract: The Mobile IP Standard has been developed to support mobility over the Internet. This standard contains several drawbacks as in the cases where packets are routed via sub-optimal paths and significant amount of signaling messages is generated due to the home registration procedure which keeps the network aware of the current location of the mobile nodes. Recently, a dynamic hierarchical mobility management strategy for mobile IP networks (DHMIP) has been proposed to reduce home registrations costs. However, this strategy induces a packet delivery delay and increases the risk of packet loss. In this paper, we propose an enhanced version of the dynamic hierarchical strategy that reduces the packet delivery delay and minimizes the risk of packet loss. Preliminary results obtained from simulations are promising. They show that the enhanced version outperforms the original dynamic hierarchical mobility management strategy version.
Abstract: Keys to high-quality face-to-face education are ensuring flexibility in the way lectures are given, and providing care and responsiveness to learners. This paper describes a face-to-face education support system that is designed to raise the satisfaction of learners and reduce the workload on instructors. This system consists of a lecture adaptation assistance part, which assists instructors in adapting teaching content and strategy, and a Q&A assistance part, which provides learners with answers to their questions. The core component of the former part is a “learning achievement map", which is composed of a Bayesian network (BN). From learners- performance in exercises on relevant past lectures, the lecture adaptation assistance part obtains information required to adapt appropriately the presentation of the next lecture. The core component of the Q&A assistance part is a case base, which accumulates cases consisting of questions expected from learners and answers to them. The Q&A assistance part is a case-based search system equipped with a search index which performs probabilistic inference. A prototype face-to-face education support system has been built, which is intended for the teaching of Java programming, and this approach was evaluated using this system. The expected degree of understanding of each learner for a future lecture was derived from his or her performance in exercises on past lectures, and this expected degree of understanding was used to select one of three adaptation levels. A model for determining the adaptation level most suitable for the individual learner has been identified. An experimental case base was built to examine the search performance of the Q&A assistance part, and it was found that the rate of successfully finding an appropriate case was 56%.
Abstract: Although women have merit in their jobs, they still
are located very few in the top management in many sectors. There
are many causes of such situation. Such a situation creates obstacles;
especially invisible ones are called “glass ceiling syndrome”. Also,
studies which handle this subject in academic community are very
few. The aim of this research is to reach the results about glass
ceiling obstacles in terms of female teaching staff (academics)
working in higher education institutions. To this end, our study was
performed on female academics working at Selcuk University, Konya
/ Turkey. Our study's main aim can be expressed as to determine
whether there are glass ceiling obstacles for female academics
working at the higher education institution in question, to measure
their glass ceiling perceptions and, thus, to identify what the glass
ceiling barrier components for them to promotion to senior
management positions are.
Abstract: The objective of this work was to examine the
changes in the microstructure and macro physical properties caused
by the carbonation of normalised CEM II mortar. Samples were
prepared and subjected to accelerated carbonation at 20°C, 65%
relative humidity and 20% CO2 concentration. On the microstructure
scale, the evolutions of the cumulative pore volume, pore size
distribution, and specific surface area during carbonation were
calculated from the adsorption desorption isotherms of nitrogen. We
also examined the evolution of macro physical properties such as the
porosity accessible to water, the gas permeability, and thermal
conductivity. The conflict between the results of nitrogen porosity
and water porosity indicated that the porous domains explored using
these two techniques are different and help to complementarily
evaluate the effects of carbonation. This is a multi-scale study where
results on microstructural changes can help to explain the evolution
of macro physical properties.
Abstract: This paper presents the development of recurrent neural network based fuzzy inference system for identification and control of dynamic nonlinear plant. The structure and algorithms of fuzzy system based on recurrent neural network are described. To train unknown parameters of the system the supervised learning algorithm is used. As a result of learning, the rules of neuro-fuzzy system are formed. The neuro-fuzzy system is used for the identification and control of nonlinear dynamic plant. The simulation results of identification and control systems based on recurrent neuro-fuzzy network are compared with the simulation results of other neural systems. It is found that the recurrent neuro-fuzzy based system has better performance than the others.
Abstract: Swietenia mahagoni have been used in traditional
medicine for treatment of different diseases. Present study was
performed to evaluate anti-ulcerogenic activity of ethanol seed
extract against ethanol induced gastric mucosal injury in rats. Six
groups of rats were orally pre-treated respectively with
carboxymethyl cellulose, omeprazole 20 mg/kg, 50, 100, 200 and 400
mg/kg plant extract one hour before oral administration of absolute
ethanol to generate gastric mucosal injury. After additional hour, rats
were sacrificed and ulcer areas of gastric walls were determined.
Grossly, carboxymethyl cellulose group exhibited severe mucosal
injury, whereas pre-treatment with plant extract exhibited significant
protection of gastric mucosa. Histology, carboxymethyl cellulose
group exhibited severe damage of gastric mucosa; edema and
leucocytes infiltration of sub mucosa compared to plant extract which
showed gastric protection. Acute toxicity study did not manifest any
toxicological signs in rats. Conclusions, results suggest that S.
mahagoni promotes ulcer protection as ascertained grossly and
histologically.
Abstract: In deregulated operating regime power system security is an issue that needs due thoughtfulness from researchers in the horizon of unbundling of generation and transmission. Electric power systems are exposed to various contingencies. Network contingencies often contribute to overloading of branches, violation of voltages and also leading to problems of security/stability. To maintain the security of the systems, it is desirable to estimate the effect of contingencies and pertinent control measurement can be taken on to improve the system security. This paper presents the application of particle swarm optimization algorithm to find the optimal location of multi type FACTS devices in a power system in order to eliminate or alleviate the line over loads. The optimizations are performed on the parameters, namely the location of the devices, their types, their settings and installation cost of FACTS devices for single and multiple contingencies. TCSC, SVC and UPFC are considered and modeled for steady state analysis. The selection of UPFC and TCSC suitable location uses the criteria on the basis of improved system security. The effectiveness of the proposed method is tested for IEEE 6 bus and IEEE 30 bus test systems.