Abstract: The computer has become an essential tool in modern
life, and the combined use of a computer with a projector is very
common in teaching and presentations. However, as typical computer
operating devices involve a mouse or keyboard, when making
presentations, users often need to stay near the computer to execute
functions such as changing pages, writing, and drawing, thus, making
the operation time-consuming, and reducing interactions with the
audience. This paper proposes a laser pointer interaction system able
to simulate mouse functions in order that users need not remain near
the computer, but can directly use laser pointer operations from at a
distance. It can effectively reduce the users- time spent by the
computer, allowing for greater interactions with the audience.
Abstract: The lifelong learning is a crucial element in the
modernization of European education and training systems. The most
important actors in the development process of the lifelong learning
are the trainers, whose professional characteristics need new
competences and skills in the current labour market. The main
objective of this paper is to establish an importance ranking of the
new competences, capabilities and skills that the lifelong learning
Spanish trainers must possess nowadays. A wide study of secondary
sources has allowed the design of a questionnaire that organizes the
trainer-s skills and competences. The e-Delphi method is used for
realizing a creative, individual and anonymous evaluation by experts
on the importance ranking that presents the criteria, sub-criteria and
indicators of the e-Delphi questionnaire. Twenty Spanish experts in
the lifelong learning have participated in two rounds of the e-
DELPHI method. In the first round, the analysis of the experts-
evaluation has allowed to establish the ranking of the most
importance criteria, sub-criteria and indicators and to eliminate the
least valued. The minimum level necessary to reach the consensus
among experts has been achieved in the second round.
Abstract: Recently electric vehicles are becoming popular as an
alternative of conventional fossil fuel vehicles. Conventional Internal
Combustion Engine (ICE) vehicle uses fossil fuel which contributing
a major part of overall carbon emission in the environment. Carbon
and other green house gas emission are responsible for global
warming and resulting climate change. It becomes vital to evaluate
performance of vehicle based on emission. In this paper an effort has
been made to depict the picture of emission caused by vehicle and
scenario of Australia has taken into account. Effort has been made to
compare the fossil based vehicle with electric vehicle in phases. The
study also evaluates advancement in electric vehicle technology,
required infrastructure for sustainability and future scope of
developments. This paper also includes the evaluation of electric
vehicle concept for pollution control and sustainable transport
systems in future. This study can be a benchmark for development of
electric vehicle as low carbon emission alternative for the cities of
tomorrow.
Abstract: Rarefied gas flows are often occurred in micro electro
mechanical systems and classical CFD could not precisely anticipate
the flow and thermal behavior due to the high Knudsen number.
Therefore, the heat transfer and the fluid dynamics characteristics of
rarefied gas flows in both a two-dimensional simple microchannel
and geometry similar to single Knudsen compressor have been
investigated with a goal of increasing performance of a actual
Knudsen compressor by using a particle simulation method. Thermal
transpiration and thermal creep, which are rarefied gas dynamic
phenomena, that cause movement of the flow from less to higher
temperature is generated by using two different longitude temperature
gradients (Linear, Step) along the walls of the flow microchannel. In
this study the influence of amount of temperature gradient and
governing pressure in various Knudsen numbers and length-to-height
ratios have been examined.
Abstract: This paper proposes a new parameter identification
method based on Linear Fractional Transformation (LFT). It is
assumed that the target linear system includes unknown parameters.
The parameter deviations are separated from a nominal system via
LFT, and identified by organizing I/O signals around the separated
deviations of the real system. The purpose of this paper is to apply LFT
to simultaneously identify the parameter deviations in systems with
fewer outputs than unknown parameters. As a fundamental example,
this method is implemented to one degree of freedom vibratory system.
Via LFT, all physical parameters were simultaneously identified in this
system. Then, numerical simulations were conducted for this system to
verify the results. This study shows that all the physical parameters of a
system with fewer outputs than unknown parameters can be effectively
identified simultaneously using LFT.
Abstract: In this paper, a new K-means clustering based
approach for identification of voltage control areas is developed.
Voltage control areas are important for efficient reactive power
management in power systems operating under deregulated
environment. Although, voltage control areas are formed using
conventional hierarchical clustering based method, but the present
paper investigate the capability of K-means clustering for the
purpose of forming voltage control areas. The proposed method is
tested and compared for IEEE 14 bus and IEEE 30 bus systems. The
results show that this K-means based method is competing with
conventional hierarchical approach
Abstract: Methods to detect and localize time singularities of polynomial and quasi-polynomial ordinary differential equations are systematically presented and developed. They are applied to examples taken form different fields of applications and they are also compared to better known methods such as those based on the existence of linear first integrals or Lyapunov functions.
Abstract: Power flow (PF) study, which is performed to
determine the power system static states (voltage magnitudes and
voltage angles) at each bus to find the steady state operating
condition of a system, is very important and is the most frequently
carried out study by power utilities for power system planning,
operation and control. In this paper, a counterpropagation neural
network (CPNN) is proposed to solve power flow problem under
different loading/contingency conditions for computing bus voltage
magnitudes and angles of the power system. The counterpropagation
network uses a different mapping strategy namely
counterpropagation and provides a practical approach for
implementing a pattern mapping task, since learning is fast in this
network. The composition of the input variables for the proposed
neural network has been selected to emulate the solution process of a
conventional power flow program. The effectiveness of the proposed
CPNN based approach for solving power flow is demonstrated by
computation of bus voltage magnitudes and voltage angles for
different loading conditions and single line-outage contingencies in
IEEE 14-bus system.
Abstract: Multi-agent system is composed by several agents
capable of reaching the goal cooperatively. The system needs an agent
platform for efficient and stable interaction between intelligent agents.
In this paper we propose a flexible and scalable agent platform by
composing the containers with multiple hierarchical agent groups. It
also allows efficient implementation of multiple domain presentations
of the agents unlike JADE. The proposed platform provides both
group management and individual management of agents for
efficiency. The platform has been implemented and tested, and it can
be used as a flexible foundation of the dynamic multi-agent system
targeting seamless delivery of ubiquitous services.
Abstract: This work presents a multiple objective linear programming (MOLP) model based on the desirability function approach for solving the aggregate production planning (APP) decision problem upon Masud and Hwang-s model. The proposed model minimises total production costs, carrying or backordering costs and rates of change in labor levels. An industrial case demonstrates the feasibility of applying the proposed model to the APP problems with three scenarios of inventory levels. The proposed model yields an efficient compromise solution and the overall levels of DM satisfaction with the multiple combined response levels. There has been a trend to solve complex planning problems using various metaheuristics. Therefore, in this paper, the multi-objective APP problem is solved by hybrid metaheuristics of the hunting search (HuSIHSA) and firefly (FAIHSA) mechanisms on the improved harmony search algorithm. Results obtained from the solution of are then compared. It is observed that the FAIHSA can be used as a successful alternative solution mechanism for solving APP problems over three scenarios. Furthermore, the FAIHSA provides a systematic framework for facilitating the decision-making process, enabling a decision maker interactively to modify the desirability function approach and related model parameters until a good optimal solution is obtained with proper selection of control parameters when compared.
Abstract: This paper deals with the tuning of parameters for Automatic Generation Control (AGC). A two area interconnected hydrothermal system with PI controller is considered. Genetic Algorithm (GA) and Particle Swarm optimization (PSO) algorithms have been applied to optimize the controller parameters. Two objective functions namely Integral Square Error (ISE) and Integral of Time-multiplied Absolute value of the Error (ITAE) are considered for optimization. The effectiveness of an objective function is considered based on the variation in tie line power and change in frequency in both the areas. MATLAB/SIMULINK was used as a simulation tool. Simulation results reveal that ITAE is a better objective function than ISE. Performances of optimization algorithms are also compared and it was found that genetic algorithm gives better results than particle swarm optimization algorithm for the problems of AGC.
Abstract: Human activity is a major concern in a wide variety of
applications, such as video surveillance, human computer interface
and face image database management. Detecting and recognizing
faces is a crucial step in these applications. Furthermore, major
advancements and initiatives in security applications in the past years
have propelled face recognition technology into the spotlight. The
performance of existing face recognition systems declines significantly
if the resolution of the face image falls below a certain level.
This is especially critical in surveillance imagery where often, due to
many reasons, only low-resolution video of faces is available. If these
low-resolution images are passed to a face recognition system, the
performance is usually unacceptable. Hence, resolution plays a key
role in face recognition systems. In this paper we introduce a new
low resolution face recognition system based on mixture of expert
neural networks. In order to produce the low resolution input images
we down-sampled the 48 × 48 ORL images to 12 × 12 ones using
the nearest neighbor interpolation method and after that applying
the bicubic interpolation method yields enhanced images which is
given to the Principal Component Analysis feature extractor system.
Comparison with some of the most related methods indicates that
the proposed novel model yields excellent recognition rate in low
resolution face recognition that is the recognition rate of 100% for
the training set and 96.5% for the test set.
Abstract: In this paper, we propose a new model of English-
Vietnamese bilingual Information Retrieval system. Although there
are so many CLIR systems had been researched and built, the accuracy of searching results in different languages that the CLIR
system supports still need to improve, especially in finding bilingual documents. The problems identified in this paper are the limitation of
machine translation-s result and the extra large collections of document to be found. So we try to establish a different model to overcome these problems.
Abstract: The development of Internet technology in recent years has led to a more active role of users in creating Web content. This has significant effects both on individual learning and collaborative knowledge building. This paper will present an integrative framework model to describe and explain learning and knowledge building with shared digital artifacts on the basis of Luhmann-s systems theory and Piaget-s model of equilibration. In this model, knowledge progress is based on cognitive conflicts resulting from incongruities between an individual-s prior knowledge and the information which is contained in a digital artifact. Empirical support for the model will be provided by 1) applying it descriptively to texts from Wikipedia, 2) examining knowledge-building processes using a social network analysis, and 3) presenting a survey of a series of experimental laboratory studies.
Abstract: In the urban traffic network, the intersections are the
“bottleneck point" of road network capacity. And the arterials are the
main body in road network and the key factor which guarantees the
normal operation of the city-s social and economic activities. The
rapid increase in vehicles leads to seriously traffic jam and cause the
increment of vehicles- delay. Most cities of our country are
traditional single control system, which cannot meet the need for the
city traffic any longer. In this paper, Synchro6.0 as a platform to
minimize the intersection delay, optimizesingle signal cycle and split
for Zhonghua Street in Handan City. Meanwhile, linear control
system uses to optimize the phase for the t arterial road in this
system. Comparing before and after use the control, capacities and
service levels of this road and the adjacent road have improved
significantly.
Abstract: This paper proposes a prototype of a lower-limb
rehabilitation system for recovering and strengthening patients-
injured lower limbs. The system is composed of traction motors for
each leg position, a treadmill as a walking base, tension sensors,
microcontrollers controlling motor functions and a main system with
graphic user interface. For derivation of reference or normal velocity
profiles of the body segment point, kinematic method is applied based
on the humanoid robot model using the reference joint angle data of
normal walking.
Abstract: Long Term Evolution (LTE) is a 4G wireless
broadband technology developed by the Third Generation
Partnership Project (3GPP) release 8, and it's represent the
competitiveness of Universal Mobile Telecommunications System
(UMTS) for the next 10 years and beyond. The concepts for LTE
systems have been introduced in 3GPP release 8, with objective of
high-data-rate, low-latency and packet-optimized radio access
technology. In this paper, performance of different TCP variants
during LTE network investigated. The performance of TCP over
LTE is affected mostly by the links of the wired network and total
bandwidth available at the serving base station. This paper describes
an NS-2 based simulation analysis of TCP-Vegas, TCP-Tahoe, TCPReno,
TCP-Newreno, TCP-SACK, and TCP-FACK, with full
modeling of all traffics of LTE system. The Evaluation of the
network performance with all TCP variants is mainly based on
throughput, average delay and lost packet. The analysis of TCP
performance over LTE ensures that all TCP's have a similar
throughput and the best performance return to TCP-Vegas than other
variants.
Abstract: IT infrastructures are becoming more and more
difficult. Therefore, in the first industrial IT systems, the P2P
paradigm has replaced the traditional client server and methods of
self-organization are gaining more and more importance. From the
past it is known that especially regular structures like grids may
significantly improve the system behavior and performance. This
contribution introduces a new algorithm based on a biologic
analogue, which may provide the growth of several regular structures
on top of anarchic grown P2P- or social network structures.
Abstract: The prediction of financial time series is a very
complicated process. If the efficient market hypothesis holds, then the predictability of most financial time series would be a rather
controversial issue, due to the fact that the current price contains already all available information in the market. This paper extends
the Adaptive Neuro Fuzzy Inference System for High Frequency
Trading which is an expert system that is capable of using fuzzy reasoning combined with the pattern recognition capability of neural networks to be used in financial forecasting and trading in high
frequency. However, in order to eliminate unnecessary input in the
training phase a new event based volatility model was proposed.
Taking volatility and the scaling laws of financial time series into consideration has brought about the development of the Intraday Seasonality Observation Model. This new model allows the observation of specific events and seasonalities in data and subsequently removes any unnecessary data. This new event based
volatility model provides the ANFIS system with more accurate input
and has increased the overall performance of the system.
Abstract: Higher-order Statistics (HOS), also known as
cumulants, cross moments and their frequency domain counterparts,
known as poly spectra have emerged as a powerful signal processing
tool for the synthesis and analysis of signals and systems. Algorithms
used for the computation of cross moments are computationally
intensive and require high computational speed for real-time
applications. For efficiency and high speed, it is often advantageous
to realize computation intensive algorithms in hardware. A promising
solution that combines high flexibility together with the speed of a
traditional hardware is Field Programmable Gate Array (FPGA). In
this paper, we present FPGA-based parallel architecture for the
computation of third-order cross moments. The proposed design is
coded in Very High Speed Integrated Circuit (VHSIC) Hardware
Description Language (VHDL) and functionally verified by
implementing it on Xilinx Spartan-3 XC3S2000FG900-4 FPGA.
Implementation results are presented and it shows that the proposed
design can operate at a maximum frequency of 86.618 MHz.