Abstract: In this paper, we consider a risk model involving two independent classes of insurance risks and random premium income. We assume that the premium income process is a Poisson Process, and the claim number processes are independent Poisson and generalized Erlang(n) processes, respectively. Both of the Gerber- Shiu functions with zero initial surplus and the probability generating functions (p.g.f.) of the Gerber-Shiu functions are obtained.
Abstract: This research presents a system for post processing of
data that takes mined flat rules as input and discovers crisp as well as
fuzzy hierarchical structures using Learning Classifier System
approach. Learning Classifier System (LCS) is basically a machine
learning technique that combines evolutionary computing,
reinforcement learning, supervised or unsupervised learning and
heuristics to produce adaptive systems. A LCS learns by interacting
with an environment from which it receives feedback in the form of
numerical reward. Learning is achieved by trying to maximize the
amount of reward received. Crisp description for a concept usually
cannot represent human knowledge completely and practically. In the
proposed Learning Classifier System initial population is constructed
as a random collection of HPR–trees (related production rules) and
crisp / fuzzy hierarchies are evolved. A fuzzy subsumption relation is
suggested for the proposed system and based on Subsumption Matrix
(SM), a suitable fitness function is proposed. Suitable genetic
operators are proposed for the chosen chromosome representation
method. For implementing reinforcement a suitable reward and
punishment scheme is also proposed. Experimental results are
presented to demonstrate the performance of the proposed system.
Abstract: In manufacturing industries, development of measurement leads to increase the number of monitoring variables and eventually the importance of multivariate control comes to the fore. Statistical process control (SPC) is one of the most widely used as multivariate control chart. Nevertheless, SPC is restricted to apply in processes because its assumption of data as following specific distribution. Unfortunately, process data are composed by the mixture of several processes and it is hard to estimate as one certain distribution. To alternative conventional SPC, therefore, nonparametric control chart come into the picture because of the strength of nonparametric control chart, the absence of parameter estimation. SVDD based control chart is one of the nonparametric control charts having the advantage of flexible control boundary. However,basic concept of SVDD has been an oversight to the important of data characteristic, density distribution. Therefore, we proposed DW-SVDD (Density Weighted SVDD) to cover up the weakness of conventional SVDD. DW-SVDD makes a new attempt to consider dense of data as introducing the notion of density Weight. We extend as control chart using new proposed SVDD and a simulation study of various distributional data is conducted to demonstrate the improvement of performance.
Abstract: Fractional Fourier Transform is a generalization of the classical Fourier Transform which is often symbolized as the rotation in time- frequency plane. Similar to the product of time and frequency span which provides the Uncertainty Principle for the classical Fourier domain, there has not been till date an Uncertainty Principle for the Fractional Fourier domain for a generalized class of finite energy signals. Though the lower bound for the product of time and Fractional Fourier span is derived for the real signals, a tighter lower bound for a general class of signals is of practical importance, especially for the analysis of signals containing chirps. We hence formulate a mathematical derivation that gives the lower bound of time and Fractional Fourier span product. The relation proves to be utmost importance in taking the Fractional Fourier Transform with adaptive time and Fractional span resolutions for a varied class of complex signals.
Abstract: Evolvable Hardware (EHW) has been regarded as adaptive system acquired by wide application market. Consumer market of any good requires diversity to satisfy consumers- preferences. Adaptation of EHW is a key technology that could provide individual approach to every particular user. This situation raises a question: how to set target for evolutionary algorithm? The existing techniques do not allow consumer to influence evolutionary process. Only designer at the moment is capable to influence the evolution. The proposed consumer-triggered evolution overcomes this problem by introducing new features to EHW that help adaptive system to obtain targets during consumer stage. Classification of EHW is given according to responsiveness, imitation of human behavior and target circuit response. Home intelligent water heating system is considered as an example.
Abstract: The early diagnostic decision making in industrial processes is absolutely necessary to produce high quality final products. It helps to provide early warning for a special event in a process, and finding its assignable cause can be obtained. This work presents a hybrid diagnostic schmes for batch processes. Nonlinear representation of raw process data is combined with classification tree techniques. The nonlinear kernel-based dimension reduction is executed for nonlinear classification decision boundaries for fault classes. In order to enhance diagnosis performance for batch processes, filtering of the data is performed to get rid of the irrelevant information of the process data. For the diagnosis performance of several representation, filtering, and future observation estimation methods, four diagnostic schemes are evaluated. In this work, the performance of the presented diagnosis schemes is demonstrated using batch process data.
Abstract: The survey and classification of the different security
attacks in structured peer-to-peer (P2P) overlay networks can be
useful to computer system designers, programmers, administrators,
and users. In this paper, we attempt to provide a taxonomy of
structured P2P overlay networks security attacks. We have specially
focused on the way these attacks can arise at each level of the
network. Moreover, we observed that most of the existing systems
such as Content Addressable Network (CAN), Chord, Pastry,
Tapestry, Kademlia, and Viceroy suffer from threats and vulnerability
which lead to disrupt and corrupt their functioning. We hope that our
survey constitutes a good help for who-s working on this area of
research.
Abstract: Infrared focal plane arrays (IRFPA) sensors, due to
their high sensitivity, high frame frequency and simple structure, have
become the most prominently used detectors in military applications.
However, they suffer from a common problem called the fixed pattern
noise (FPN), which severely degrades image quality and limits the
infrared imaging applications. Therefore, it is necessary to perform
non-uniformity correction (NUC) on IR image. The algorithms of
non-uniformity correction are classified into two main categories, the
calibration-based and scene-based algorithms. There exist some
shortcomings in both algorithms, hence a novel non-uniformity
correction algorithm based on non-linear fit is proposed, which
combines the advantages of the two algorithms. Experimental results
show that the proposed algorithm acquires a good effect of NUC with
a lower non-uniformity ratio.
Abstract: The aim of this paper is to introduce and study a new concept of strong double χ2 (M,A, Δ) of fuzzy numbers and also some properties of the resulting sequence spaces of fuzzy numbers were examined.
Abstract: The main purpose of the research is to investigate the computer experiences and computer attitudes of prospective class teachers. The research also investigated the differences between computer attitudes and computer experiences, computer competencies and the influence of genders. Ninety prospective class teachers participated in the research. Computer Attitude Scale- Marmara (CAS-M), and a questionnaire, about their computer experiences, and opinions toward the use of computers in the classroom setting, were administrated. The major findings are as follows: (1) 62% of prospective class teachers have computer at home; (2) 50% of the computer owners have computers less than three years; (3) No significant differences were found between computer attitudes and gender; (4) Differences were found between general computer attitudes and computer liking attitudes of prospective class teachers based on their computer competencies in favor of more competent ones.
Abstract: We developed a new method based on quasimolecular
modeling to simulate the cavity flow in three cavity
shapes: rectangular, half-circular and bucket beer in cgs units. Each
quasi-molecule was a group of particles that interacted in a fashion
entirely analogous to classical Newtonian molecular interactions.
When a cavity flow was simulated, the instantaneous velocity vector
fields were obtained by using an inverse distance weighted
interpolation method. In all three cavity shapes, fluid motion was
rotated counter-clockwise. The velocity vector fields of the three
cavity shapes showed a primary vortex located near the upstream
corners at time t ~ 0.500 s, t ~ 0.450 s and t ~ 0.350 s, respectively.
The configurational kinetic energy of the cavities increased as time
increased until the kinetic energy reached a maximum at time t ~
0.02 s and, then, the kinetic energy decreased as time increased. The
rectangular cavity system showed the lowest kinetic energy, while
the half-circular cavity system showed the highest kinetic energy.
The kinetic energy of rectangular, beer bucket and half-circular
cavities fluctuated about stable average values 35.62 x 103, 38.04 x
103 and 40.80 x 103 ergs/particle, respectively. This indicated that the
half-circular shapes were the most suitable shape for a shrimp pond
because the water in shrimp pond flows best when we compared with
rectangular and beer bucket shape.
Abstract: The main goal of data mining is to extract accurate, comprehensible and interesting knowledge from databases that may be considered as large search spaces. In this paper, a new, efficient type of Genetic Algorithm (GA) called uniform two-level GA is proposed as a search strategy to discover truly interesting, high-level prediction rules, a difficult problem and relatively little researched, rather than discovering classification knowledge as usual in the literatures. The proposed method uses the advantage of uniform population method and addresses the task of generalized rule induction that can be regarded as a generalization of the task of classification. Although the task of generalized rule induction requires a lot of computations, which is usually not satisfied with the normal algorithms, it was demonstrated that this method increased the performance of GAs and rapidly found interesting rules.
Abstract: Research papers are usually evaluated via peer
review. However, peer review has limitations in evaluating research
papers. In this paper, Scienstein and the new idea of 'collaborative
document evaluation' are presented. Scienstein is a project to
evaluate scientific papers collaboratively based on ratings, links,
annotations and classifications by the scientific community using the
internet. In this paper, critical success factors of collaborative
document evaluation are analyzed. That is the scientists- motivation
to participate as reviewers, the reviewers- competence and the
reviewers- trustworthiness. It is shown that if these factors are
ensured, collaborative document evaluation may prove to be a more
objective, faster and less resource intensive approach to scientific
document evaluation in comparison to the classical peer review
process. It is shown that additional advantages exist as collaborative
document evaluation supports interdisciplinary work, allows
continuous post-publishing quality assessments and enables the
implementation of academic recommendation engines. In the long
term, it seems possible that collaborative document evaluation will
successively substitute peer review and decrease the need for
journals.
Abstract: In this paper, we studied some properties of geodesic on some open surfaces: Hyperboloid, Paraboloid and Funnel Surface. Geodesic equation in the v-Clairaut parameterization was calculated and reduced to definite integral. Some geodesics on some open surfaces as mention above were classified by Clairaut's relation.
Abstract: Multimedia, as it stands now is perhaps the most
diverse and rich culture around the globe. One of the major needs of
Multimedia is to have a single system that enables people to
efficiently search through their multimedia catalogues. Many
Domain Specific Systems and architectures have been proposed but
up till now no generic and complete architecture is proposed. In this
paper, we have suggested a generic architecture for Multimedia
Database. The main strengths of our architecture besides being
generic are Semantic Libraries to reduce semantic gap, levels of
feature extraction for more specific and detailed feature extraction
according to classes defined by prior level, and merging of two types
of queries i.e. text and QBE (Query by Example) for more accurate
yet detailed results.
Abstract: Eigenvector methods are gaining increasing acceptance in the area of spectrum estimation. This paper presents a successful attempt at testing and evaluating the performance of two of the most popular types of subspace techniques in determining the parameters of multiexponential signals with real decay constants buried in noise. In particular, MUSIC (Multiple Signal Classification) and minimum-norm techniques are examined. It is shown that these methods perform almost equally well on multiexponential signals with MUSIC displaying better defined peaks.
Abstract: Lately there has been a significant boost of interest in
music digital libraries, which constitute an attractive area of research
and development due to their inherent interesting issues and
challenging technical problems, solutions to which will be highly
appreciated by enthusiastic end-users. We present here a DL that we
have developed to support users in their quest for classical music
pieces within a particular collection of 18,000+ audio recordings.
To cope with the early DL model limitations, we have used a refined
socio-semantic and contextual model that allows rich bibliographic
content description, along with semantic annotations, reviewing,
rating, knowledge sharing etc. The multi-layered service model
allows incorporation of local and distributed information,
construction of rich hypermedia documents, expressing the complex
relationships between various objects and multi-dimensional spaces,
agents, actors, services, communities, scenarios etc., and facilitates
collaborative activities to offer to individual users the needed
collections and services.
Abstract: In this work, an attempt is made to design an optimal
wind/pv/diesel hybrid power system for a village of Ain Merane,
Chlef, Algeria, where the wind speed and solar radiation
measurements were made. The aim of this paper is the optimization
of a hybrid wind/solar/diesel system applied in term of technical and
economic feasibility by simulation using HOMER. A comparison
was made between the performance of wind/pv/diesel system and the
classic connecting system.
Abstract: Mammographic images and data analysis to
facilitate modelling or computer aided diagnostic (CAD) software development should best be done using a common database that can handle various mammographic image file
formats and relate these to other patient information.
This would optimize the use of the data as both primary
reporting and enhanced information extraction of research data could be performed from the single dataset. One desired
improvement is the integration of DICOM file header information into the database, as an efficient and reliable source of supplementary patient information intrinsically
available in the images.
The purpose of this paper was to design a suitable database to link and integrate different types of image files and gather common information that can be further used for research
purposes. An interface was developed for accessing, adding,
updating, modifying and extracting data from the common
database, enhancing the future possible application of the data in CAD processing.
Technically, future developments envisaged include the creation of an advanced search function to selects image files
based on descriptor combinations. Results can be further used for specific CAD processing and other research. Design of a
user friendly configuration utility for importing of the required fields from the DICOM files must be done.
Abstract: Based on the classical algorithm LSQR for solving (unconstrained) LS problem, an iterative method is proposed for the least-squares like-minimum-norm symmetric solution of AXB+CYD=E. As the application of this algorithm, an iterative method for the least-squares like-minimum-norm biymmetric solution of AXB=E is also obtained. Numerical results are reported that show the efficiency of the proposed methods.