Abstract: As new challenges emerge in power electrical
workplace safety, it is the responsibility of the systems designer to
seek out new approaches and solutions that address them. Design
decisions made today will impact cost, safety and serviceability of
the installed systems for 40 or 50 years during the useful life for the
owner. Studies have shown that this cost is an order of magnitude of
7 to 10 times the installed cost of the power distribution equipment.
This paper reviews some aspects of earthing system design in power
substation surrounded by residential houses. The electrical potential
rise and split factors are discussed and a few recommendations are
provided to achieve a safety voltage in the area beyond the boundary
of the substation.
Abstract: Since prestressed concrete members rely on the tensile
strength of the prestressing strands to resist loads, loss of even few
them could result catastrophic. Therefore, it is important to measure
present residual prestress force. Although there are some techniques
for obtaining present prestress force, some problems still remain. One
method is to install load cell in front of anchor head but this may
increase cost. Load cell is a transducer using the elastic material
property. Anchor head is also an elastic material and this might result
in monitoring monitor present prestress force. Features of fiber optic
sensor such as small size, great sensitivity, high durability can assign
sensing function to anchor head. This paper presents the concept of
smart anchor head which acts as load cell and experiment for the
applicability of it. Test results showed the smart anchor head worked
good and strong linear relationship between load and response.
Abstract: Knowledge Discovery in Databases (KDD) has
evolved into an important and active area of research because of
theoretical challenges and practical applications associated with the
problem of discovering (or extracting) interesting and previously
unknown knowledge from very large real-world databases. Rough
Set Theory (RST) is a mathematical formalism for representing
uncertainty that can be considered an extension of the classical set
theory. It has been used in many different research areas, including
those related to inductive machine learning and reduction of
knowledge in knowledge-based systems. One important concept
related to RST is that of a rough relation. In this paper we presented
the current status of research on applying rough set theory to KDD,
which will be helpful for handle the characteristics of real-world
databases. The main aim is to show how rough set and rough set
analysis can be effectively used to extract knowledge from large
databases.
Abstract: Availability of high dimensional biological datasets such as from gene expression, proteomic, and metabolic experiments can be leveraged for the diagnosis and prognosis of diseases. Many classification methods in this area have been studied to predict disease states and separate between predefined classes such as patients with a special disease versus healthy controls. However, most of the existing research only focuses on a specific dataset. There is a lack of generic comparison between classifiers, which might provide a guideline for biologists or bioinformaticians to select the proper algorithm for new datasets. In this study, we compare the performance of popular classifiers, which are Support Vector Machine (SVM), Logistic Regression, k-Nearest Neighbor (k-NN), Naive Bayes, Decision Tree, and Random Forest based on mock datasets. We mimic common biological scenarios simulating various proportions of real discriminating biomarkers and different effect sizes thereof. The result shows that SVM performs quite stable and reaches a higher AUC compared to other methods. This may be explained due to the ability of SVM to minimize the probability of error. Moreover, Decision Tree with its good applicability for diagnosis and prognosis shows good performance in our experimental setup. Logistic Regression and Random Forest, however, strongly depend on the ratio of discriminators and perform better when having a higher number of discriminators.
Abstract: Continuation of an active call is one of the most important quality measurements in the cellular systems. Handoff process enables a cellular system to provide such a facility by transferring an active call from one cell to another. Different approaches are proposed and applied in order to achieve better handoff service. The principal parameters used to evaluate handoff techniques are: forced termination probability and call blocking probability. The mechanisms such as guard channels and queuing handoff calls decrease the forced termination probability while increasing the call blocking probability. In this paper we present an overview about the issues related to handoff initiation and decision and discuss about different types of handoff techniques available in the literature.
Abstract: Internet security attack could endanger the privacy of
World Wide Web users and the integrity of their data. The attack can
be carried out on today's most secure systems- browsers, including
Netscape Navigator and Microsoft Internet Explorer. There are too
many types, methods and mechanisms of attack where new attack
techniques and exploits are constantly being developed and
discovered. In this paper, various types of internet security attack
mechanisms are explored and it is pointed out that when different
types of attacks are combined together, network security can suffer
disastrous consequences.
Abstract: Motion estimation is the most computationally
intensive part in video processing. Many fast motion estimation
algorithms have been proposed to decrease the computational
complexity by reducing the number of candidate motion vectors.
However, these studies are for fast search algorithms themselves while
almost image and video compressions are operated with software
based. Therefore, the timing constraints for running these motion
estimation algorithms not only challenge for the video codec but also
overwhelm for some of processors. In this paper, the performance of
motion estimation is enhanced by using Intel's Streaming SIMD
Extension 2 (SSE2) technology with Intel Pentium 4 processor.
Abstract: Urban road network traffic has become one of the
most studied research topics in the last decades. This is mainly due to
the enlargement of the cities and the growing number of motor
vehicles traveling in this road network. One of the most sensitive
problems is to verify if the network is congestion-free. Another
related problem is the automatic reconfiguration of the network
without building new roads to alleviate congestions. These problems
require an accurate model of the traffic to determine the steady state
of the system. An alternative is to simulate the traffic to see if there
are congestions and when and where they occur. One key issue is to
find an adequate model for road intersections. Once the model
established, either a large scale model is built or the intersection is
represented by its performance measures and simulation for analysis.
In both cases, it is important to seek the queueing model to represent
the road intersection. In this paper, we propose to model the road
intersection as a BCMP queueing network and we compare this
analytical model against a simulation model for validation.
Abstract: Routing places an important role in determining the
quality of service in wireless networks. The routing methods adopted
in wireless networks have many drawbacks. This paper aims to
review the current routing methods used in wireless networks. This
paper proposes an innovative solution to overcome the problems in
routing. This solution is aimed at improving the Quality of Service.
This solution is different from others as it involves the resuage of the
part of the virtual circuits. This improvement in quality of service is
important especially in propagation of multimedia applications like
video, animations etc. So it is the dire need to propose a new solution
to improve the quality of service in ATM wireless networks for
multimedia applications especially during this era of multimedia
based applications.
Abstract: In this paper, the application of GRNN in
modeling of SOFC fuel cells were studied. The parameters
are of interested as voltage and power value and the current
changes are investigated. In addition, the comparison between
GRNN neural network application and conventional method
was made. The error value showed the superlative results.
Abstract: A novel typical day prediction model have been built and validated by the measured data of a grid-connected solar photovoltaic (PV) system in Macau. Unlike conventional statistical method used by previous study on PV systems which get results by averaging nearby continuous points, the present typical day statistical method obtain the value at every minute in a typical day by averaging discontinuous points at the same minute in different days. This typical day statistical method based on discontinuous point averaging makes it possible for us to obtain the Gaussian shape dynamical distributions for solar irradiance and output power in a yearly or monthly typical day. Based on the yearly typical day statistical analysis results, the maximum possible accumulated output energy in a year with on site climate conditions and the corresponding optimal PV system running time are obtained. Periodic Gaussian shape prediction models for solar irradiance, output energy and system energy efficiency have been built and their coefficients have been determined based on the yearly, maximum and minimum monthly typical day Gaussian distribution parameters, which are obtained from iterations for minimum Root Mean Squared Deviation (RMSD). With the present model, the dynamical effects due to time difference in a day are kept and the day to day uncertainty due to weather changing are smoothed but still included. The periodic Gaussian shape correlations for solar irradiance, output power and system energy efficiency have been compared favorably with data of the PV system in Macau and proved to be an improvement than previous models.
Abstract: In this paper, we consider components of discrete event imitating model, implementing a simulation model by using JAVA and performing an input analysis of the data and an output analysis of the simulation results. Was lead development of imitating model of mass service system with n (n≥1) devices of service. On the basis of the developed process of a multithreading simulated the distributed processes with presence of synchronization. Was developed the algorithm of event-oriented simulation, was received results of system functioning with n devices of service.
Abstract: System-level design based on high-level abstractions
is becoming increasingly important in hardware and embedded
system design. This paper analyzes meta-design techniques oriented
at developing meta-programs and meta-models for well-understood
domains. Meta-design techniques include meta-programming and
meta-modeling. At the programming level of design process, metadesign
means developing generic components that are usable in a
wider context of application than original domain components. At the
modeling level, meta-design means developing design patterns that
describe general solutions to the common recurring design problems,
and meta-models that describe the relationship between different
types of design models and abstractions. The paper describes and
evaluates the implementation of meta-design in hardware design
domain using object-oriented and meta-programming techniques.
The presented ideas are illustrated with a case study.
Abstract: The counting and analysis of blood cells allows the
evaluation and diagnosis of a vast number of diseases. In particular,
the analysis of white blood cells (WBCs) is a topic of great interest to
hematologists. Nowadays the morphological analysis of blood cells is
performed manually by skilled operators. This involves numerous
drawbacks, such as slowness of the analysis and a nonstandard
accuracy, dependent on the operator skills. In literature there are only
few examples of automated systems in order to analyze the white
blood cells, most of which only partial. This paper presents a
complete and fully automatic method for white blood cells
identification from microscopic images. The proposed method firstly
individuates white blood cells from which, subsequently, nucleus and
cytoplasm are extracted. The whole work has been developed using
MATLAB environment, in particular the Image Processing Toolbox.
Abstract: The purpose of this study was to develop and examine a
Teaching Commitment Scale of Health and Physical Education
(TCS-HPE) for Taiwanese elementary school teachers. First of all,
based on teaching commitment related theory and literatures to
develop a original scale with 40 items, later both stratified random
sampling and cluster sampling were used to sample participants.
During the first stage, 300 teachers were sampled and 251 valid scales
(83.7%) returned. Later, the data was analyzed by exploratory factor
analysis to obtain 74.30% of total variance for the construct validity.
The Cronbach-s alpha coefficient of sum scale reliability was 0.94, and
subscale coefficients were between 0.80 and 0.96. In the second stage,
400 teachers were sampled and 318 valid scales (79.5%) returned.
Finally, this study used confirmatory factor analysis to test validity and
reliability of TCS-HPE. The result showed that the fit indexes reached
acceptable criteria(¤ç2
(246 ) =557.64 , p
Abstract: In this paper, a nonlinear model predictive swing-up
and stabilizing sliding controller is proposed for an inverted
pendulum-cart system. In the swing up phase, the nonlinear model
predictive control is formulated as a nonlinear programming problem
with energy based objective function. By solving this problem at
each sampling instant, a sequence of control inputs that optimize the
nonlinear objective function subject to various constraints over a
finite horizon are obtained. Then, this control drives the pendulum to
a predefined neighborhood of the upper equilibrium point, at where
sliding mode based model predictive control is used to stabilize the
systems with the specified constraints. It is shown by the simulations
that, due to the way of formulating the problem, short horizon
lengths are sufficient for attaining the swing up goal.
Abstract: Repetitive systems stand for a kind of systems that
perform a simple task on a fixed pattern repetitively, which are
widely spread in industrial fields. Hence, many researchers have been
interested in those systems, especially in the field of iterative learning
control (ILC). In this paper, we propose a finite-horizon tracking
control scheme for linear time-varying repetitive systems with uncertain
initial conditions. The scheme is derived both analytically
and numerically for state-feedback systems and only numerically for
output-feedback systems. Then, it is extended to stable systems with
input constraints. All numerical schemes are developed in the forms
of linear matrix inequalities (LMIs). A distinguished feature of the
proposed scheme from the existing iterative learning control is that
the scheme guarantees the tracking performance exactly even under
uncertain initial conditions. The simulation results demonstrate the
good performance of the proposed scheme.
Abstract: In today-s global and competitive market,
manufacturing companies are working hard towards improving their
production system performance. Most companies develop production
systems that can help in cost reduction. Manufacturing systems
consist of different elements including production methods,
machines, processes, control and information systems. Human issues
are an important part of manufacturing systems, yet most companies
do not pay sufficient attention to them. In this paper, a workforce
planning (WP) model is presented. A non-linear programming model
is developed in order to minimize the hiring, firing, training and
overtime costs. The purpose is to determine the number of workers
for each worker type, the number of workers trained, and the number
of overtime hours. Moreover, a decision support system (DSS) based
on the proposed model is introduced using the Excel-Lingo software
interfacing feature. This model will help to improve the interaction
between the workers, managers and the technical systems in
manufacturing.
Abstract: In modern distributed software systems, the issue of communication among composing parts represents a critical point, but the idea of extending conventional programming languages with general purpose communication constructs seems difficult to realize. As a consequence, there is a (growing) gap between the abstraction level required by distributed applications and the concepts provided by platforms that enable communication. This work intends to discuss how the Model Driven Software Development approach can be considered as a mature technology to generate in automatic way the schematic part of applications related to communication, by providing at the same time high level specialized languages useful in all the phases of software production. To achieve the goal, a stack of languages (meta-meta¬models) has been introduced in order to describe – at different levels of abstraction – the collaborative behavior of generic entities in terms of communication actions related to a taxonomy of messages. Finally, the generation of platforms for communication is viewed as a form of specification of language semantics, that provides executable models of applications together with model-checking supports and effective runtime environments.
Abstract: This paper presents a new approach for busbar protection with stable operation of current transformer during saturation, using fuzzy neuro and symmetrical components theory. This technique uses symmetrical components of current signals to learn the hidden relationship existing in the input patterns. Simulation studies are preformed and the influence of changing system parameters such as inception fault and source impedance is studied. Details of the design procedure and the results of performance studies with the proposed relay are given in the paper. An analysis of the performance of the proposed technique during ct saturation conditions is presented. The performance of the technique was investigated for a variety of operating conditions and for several busbar configurations. Data generated by EMTDC simulations of model power systems were used in the investigations. The results indicate that the proposed technique is stable during ct saturation conditions.