Abstract: In data mining, the association rules are used to search
for the relations of items of the transactions database. Following the
data is collected and stored, it can find rules of value through
association rules, and assist manager to proceed marketing strategy
and plan market framework. In this paper, we attempt fuzzy partition
methods and decide membership function of quantitative values of
each transaction item. Also, by managers we can reflect the
importance of items as linguistic terms, which are transformed as
fuzzy sets of weights. Next, fuzzy weighted frequent pattern growth
(FWFP-Growth) is used to complete the process of data mining. The
method above is expected to improve Apriori algorithm for its better
efficiency of the whole association rules. An example is given to
clearly illustrate the proposed approach.
Abstract: HIV-1 genome is highly heterogeneous. Due to this
variation, features of HIV-I genome is in a wide range. For this
reason, the ability to infection of the virus changes depending on
different chemokine receptors. From this point of view, R5 HIV
viruses use CCR5 coreceptor while X4 viruses use CXCR5 and
R5X4 viruses can utilize both coreceptors. Recently, in
Bioinformatics, R5X4 viruses have been studied to classify by using
the experiments on HIV-1 genome.
In this study, R5X4 type of HIV viruses were classified using
Auto Regressive (AR) model through Artificial Neural Networks
(ANNs). The statistical data of R5X4, R5 and X4 viruses was
analyzed by using signal processing methods and ANNs. Accessible
residues of these virus sequences were obtained and modeled by AR
model since the dimension of residues is large and different from
each other. Finally the pre-processed data was used to evolve various
ANN structures for determining R5X4 viruses. Furthermore ROC
analysis was applied to ANNs to show their real performances. The
results indicate that R5X4 viruses successfully classified with high
sensitivity and specificity values training and testing ROC analysis
for RBF, which gives the best performance among ANN structures.
Abstract: PROFIBUS (PROcess FIeld BUS) which is defined with international standarts (IEC61158, EN50170) is the most popular fieldbus, and provides a communication between industrial applications which are located in different control environment and location in manufacturing, process and building automation. Its communication speed is from 9.6 Kbps to 12 Mbps over distances from 100 to 1200 meters, and so it is to be often necessary to interconnect them in order to break these limits. Unfortunately this interconnection raises several issues and the solutions found so far are not very satisfactory. In this paper, we propose a new solution to interconnect PROFIBUS segments, which uses a wireless MAN based on the IEEE 802.16 standard as a backbone system. Also, the solution which is described a model for internetworking unit integrates the traffic generated by PROFIBUS segments into IEEE 802.16 wireless MAN using encapsulation technique.
Abstract: The prediction of meteorological parameters at a
meteorological station is an interesting and open problem. A firstorder
linear dynamic model GM(1,1) is the main component of the
grey system theory. The grey model requires only a few previous data
points in order to make a real-time forecast. In this paper, we
consider the daily average ambient temperature as a time series and
the grey model GM(1,1) applied to local prediction (short-term
prediction) of the temperature. In the same case study we use a fuzzy
predictive model for global prediction. We conclude the paper with a
comparison between local and global prediction schemes.
Abstract: Most of researches for conventional simulations were
studied focusing on flocks with a single species. While there exist the
flocking behaviors with a single species in nature, the flocking
behaviors are frequently observed with multi-species. This paper
studies on the flocking simulation for heterogeneous agents. In order
to simulate the flocks for heterogeneous agents, the conventional
method uses the identifier of flock, while the proposed method defines
the feature vector of agent and uses the similarity between agents by
comparing with those feature vectors. Based on the similarity, the
paper proposed the attractive force and repulsive force and then
executed the simulation by applying two forces. The results of
simulation showed that flock formation with heterogeneous agents is
very natural in both cases. In addition, it showed that unlike the
existing method, the proposed method can not only control the density
of the flocks, but also be possible for two different groups of agents to
flock close to each other if they have a high similarity.
Abstract: Computational techniques derived from digital image processing are playing a significant role in the security and digital copyrights of multimedia and visual arts. This technology has the effect within the domain of computers. This research presents discrete M-band wavelet transform (MWT) and cosine transform (DCT) based watermarking algorithm by incorporating the principal component analysis (PCA). The proposed algorithm is expected to achieve higher perceptual transparency. Specifically, the developed watermarking scheme can successfully resist common signal processing, such as geometric distortions, and Gaussian noise. In addition, the proposed algorithm can be parameterized, thus resulting in more security. To meet these requirements, the image is transformed by a combination of MWT & DCT. In order to improve the security further, we randomize the watermark image to create three code books. During the watermark embedding, PCA is applied to the coefficients in approximation sub-band. Finally, first few component bands represent an excellent domain for inserting the watermark.
Abstract: Metrics is the process by which numbers or symbols
are assigned to attributes of entities in the real world in such a way as
to describe them according to clearly defined rules. Software metrics
are instruments or ways to measuring all the aspect of software
product. These metrics are used throughout a software project to
assist in estimation, quality control, productivity assessment, and
project control. Object oriented software metrics focus on
measurements that are applied to the class and other characteristics.
These measurements convey the software engineer to the behavior of
the software and how changes can be made that will reduce
complexity and improve the continuing capability of the software.
Object oriented software metric can be classified in two types static
and dynamic. Static metrics are concerned with all the aspects of
measuring by static analysis of software and dynamic metrics are
concerned with all the measuring aspect of the software at run time.
Major work done before, was focusing on static metric. Also some
work has been done in the field of dynamic nature of the software
measurements. But research in this area is demanding for more work.
In this paper we give a set of dynamic metrics specifically for
polymorphism in object oriented system.
Abstract: The pseudorandom number generators based on linear
feedback shift registers (LFSRs), are very quick, easy and secure in
the implementation of hardware and software. Thus they are very
popular and widely used. But LFSRs lead to fairly easy
cryptanalysis due to their completely linearity properties. In this
paper, we propose a stochastic generator, which is called Random
Feedback Shift Register (RFSR), using stochastic transformation
(Random block) with one-way and non-linearity properties.
Abstract: Intrusion detection systems (IDS)are crucial components
of the security mechanisms of today-s computer systems.
Existing research on intrusion detection has focused on sequential
intrusions. However, intrusions can also be formed by concurrent
interactions of multiple processes. Some of the intrusions caused
by these interactions cannot be detected using sequential intrusion
detection methods. Therefore, there is a need for a mechanism that
views the distributed system as a whole. L-BIDS (Lattice-Based
Intrusion Detection System) is proposed to address this problem. In
the L-BIDS framework, a library of intrusions and distributed traces
are represented as lattices. Then these lattices are compared in order
to detect intrusions in the distributed traces.
Abstract: The fast growth in complexity coupled with requests for shorter development periods for embedded systems are bringing demands towards a more effective, i.e. higher-abstract, design process for hardaware/software integrated design. In Software Engineering area, Model Driven Architecture (MDA) and Executable UML (xUML) has been accepted to bring further improvement in software design. This paper constructs MDA and xUML stepwise transformations from an abstract specification model to a more concrete implementation model using the refactoring technique for hardaware/software integrated design. This approach provides clear and structured models which enables quick exploration and synthesis, and early stage verification.
Abstract: Mobile learning (M-learning) integrates mobile
devices and wireless computing technology to enhance the current
conventional learning system. However, there are constraints which
are affecting the implementation of platform and device independent
M-learning. The main aim of this research is to fulfill the following
main objectives: to develop platform independent mobile learning
tool (M-LT) for structured programming course, and evaluate its
effectiveness and usability using ADDIE instructional design model
(ISD) as M-LT life cycle. J2ME (Java 2 micro edition) and XML
(Extensible Markup Language) were used to develop platform
independent M-LT. It has two modules lecture materials and quizzes.
This study used Quasi experimental design to measure effectiveness
of the tool. Meanwhile, questionnaire is used to evaluate the usability
of the tool. Finally, the results show that the system was effective and
also usability evaluation was positive.
Abstract: At present, dictionary attack has been the basic tool for
recovering key passwords. In order to avoid dictionary attack, users
purposely choose another character strings as passwords. According to
statistics, about 14% of users choose keys on a keyboard (Kkey, for
short) as passwords. This paper develops a framework system to attack
the password chosen from Kkeys and analyzes its efficiency. Within
this system, we build up keyboard rules using the adjacent and parallel
relationship among Kkeys and then use these Kkey rules to generate
password databases by depth-first search method. According to the
experiment results, we find the key space of databases derived from
these Kkey rules that could be far smaller than the password databases
generated within brute-force attack, thus effectively narrowing down
the scope of attack research. Taking one general Kkey rule, the
combinations in all printable characters (94 types) with Kkey adjacent
and parallel relationship, as an example, the derived key space is about
240 smaller than those in brute-force attack. In addition, we
demonstrate the method's practicality and value by successfully
cracking the access password to UNIX and PC using the password
databases created
Abstract: Chinese Idioms are a type of traditional Chinese idiomatic
expressions with specific meanings and stereotypes structure
which are widely used in classical Chinese and are still common in
vernacular written and spoken Chinese today. Currently, Chinese
Idioms are retrieved in glossary with key character or key word in
morphology or pronunciation index that can not meet the need of
searching semantically. OCIRS is proposed to search the desired
idiom in the case of users only knowing its meaning without any key
character or key word. The user-s request in a sentence or phrase will
be grammatically analyzed in advance by word segmentation, key
word extraction and semantic similarity computation, thus can be
mapped to the idiom domain ontology which is constructed to provide
ample semantic relations and to facilitate description logics-based
reasoning for idiom retrieval. The experimental evaluation shows that
OCIRS realizes the function of searching idioms via semantics, obtaining
preliminary achievement as requested by the users.
Abstract: This paper deals with stability analysis for synchronous reluctance motors drive. Special attention is paid to the transient performance with variations in motor's parameters such as Ld and Rs. A study of the dynamic control using d-q model is presented first in order to clarify the stability of the motor drive system. Based on the experimental parameters of the synchronous reluctance motor, this paper gives some simulation results using MATLAB/SIMULINK software packages. It is concluded that the motor parameters, especially Ld, affect the estimator stability and hence the whole drive system.
Abstract: In this paper, we introduce an mobile agent framework
with proactive load balancing for ambient intelligence (AmI) environments.
One of the main obstacles of AmI is the scalability in
which the openness of AmI environment introduces dynamic resource
requirements on agencies. To mediate this scalability problem, our
framework proposes a load balancing module to proactively analyze
the resource consumption of network bandwidth and preferred agencies
to suggest the optimal communication method to its user. The
framework generally formulates an AmI environment that consists
of three main components: (1) mobile devices, (2) hosts or agencies,
and (3) directory service center (DSC). A preliminary implementation
was conducted with NetLogo and the experimental results show that
the proposed approach provides enhanced system performance by
minimizing the network utilization to provide users with responsive
services.
Abstract: This paper presents a sensor-based motion planning algorithm for 3-DOF car-like robots with a nonholonomic constraint. Similar to the classic Bug family algorithms, the proposed algorithm enables the car-like robot to navigate in a completely unknown environment using only the range sensor information. The car-like robot uses the local range sensor view to determine the local path so that it moves towards the goal. To guarantee that the robot can approach the goal, the two modes of motion are repeated, termed motion-to-goal and wall-following. The motion-to-goal behavior lets the robot directly move toward the goal, and the wall-following behavior makes the robot circumnavigate the obstacle boundary until it meets the leaving condition. For each behavior, the nonholonomic motion for the car-like robot is planned in terms of the instantaneous turning radius. The proposed algorithm is implemented to the real robot and the experimental results show the performance of proposed algorithm.
Abstract: Reducing energy consumption of embedded systems requires careful memory management. It has been shown that Scratch- Pad Memories (SPMs) are low size, low cost, efficient (i.e. energy saving) data structures directly managed at the software level. In this paper, the focus is on heuristic methods for SPMs management. A method is efficient if the number of accesses to SPM is as large as possible and if all available space (i.e. bits) is used. A Tabu Search (TS) approach for memory management is proposed which is, to the best of our knowledge, a new original alternative to the best known existing heuristic (BEH). In fact, experimentations performed on benchmarks show that the Tabu Search method is as efficient as BEH (in terms of energy consumption) but BEH requires a sorting which can be computationally expensive for a large amount of data. TS is easy to implement and since no sorting is necessary, unlike BEH, the corresponding sorting time is saved. In addition to that, in a dynamic perspective where the maximum capacity of the SPM is not known in advance, the TS heuristic will perform better than BEH.
Abstract: The various types of frequent pattern discovery
problem, namely, the frequent itemset, sequence and graph mining
problems are solved in different ways which are, however, in certain
aspects similar. The main approach of discovering such patterns can
be classified into two main classes, namely, in the class of the levelwise
methods and in that of the database projection-based methods.
The level-wise algorithms use in general clever indexing structures
for discovering the patterns. In this paper a new approach is proposed
for discovering frequent sequences and tree-like patterns efficiently
that is based on the level-wise issue. Because the level-wise
algorithms spend a lot of time for the subpattern testing problem, the
new approach introduces the idea of using automaton theory to solve
this problem.
Abstract: The image segmentation method described in this
paper has been developed as a pre-processing stage to be used in
methodologies and tools for video/image indexing and retrieval by
content. This method solves the problem of whole objects extraction
from background and it produces images of single complete objects
from videos or photos. The extracted images are used for calculating
the object visual features necessary for both indexing and retrieval
processes.
The segmentation algorithm is based on the cooperation among an
optical flow evaluation method, edge detection and region growing
procedures. The optical flow estimator belongs to the class of
differential methods. It permits to detect motions ranging from a
fraction of a pixel to a few pixels per frame, achieving good results in
presence of noise without the need of a filtering pre-processing stage
and includes a specialised model for moving object detection.
The first task of the presented method exploits the cues from
motion analysis for moving areas detection. Objects and background
are then refined using respectively edge detection and seeded region
growing procedures. All the tasks are iteratively performed until
objects and background are completely resolved.
The method has been applied to a variety of indoor and outdoor
scenes where objects of different type and shape are represented on
variously textured background.
Abstract: The paper explores the development of an optimization of method and apparatus for retrieving extended high dynamic range from digital negative image. Architectural photo imaging can benefit from high dynamic range imaging (HDRI) technique for preserving and presenting sufficient luminance in the shadow and highlight clipping image areas. The HDRI technique that requires multiple exposure images as the source of HDRI rendering may not be effective in terms of time efficiency during the acquisition process and post-processing stage, considering it has numerous potential imaging variables and technical limitations during the multiple exposure process. This paper explores an experimental method and apparatus that aims to expand the dynamic range from digital negative image in HDRI environment. The method and apparatus explored is based on a single source of RAW image acquisition for the use of HDRI post-processing. It will cater the optimization in order to avoid and minimize the conventional HDRI photographic errors caused by different physical conditions during the photographing process and the misalignment of multiple exposed image sequences. The study observes the characteristics and capabilities of RAW image format as digital negative used for the retrieval of extended high dynamic range process in HDRI environment.