Abstract: The purpose of the research is to investigate the energetic feature of the backpack load on soldier’s gait with variation of the trunk flexion angle. It is believed that the trunk flexion variation of the loaded gait may cause a significant difference in the energy cost which is often in practice in daily life. To this end, seven healthy Korea military personnel participated in the experiment and are tested under three different walking postures comprised of the small, natural and large trunk flexion. There are around 5 degree differences of waist angle between each trunk flexion. The ground reaction forces were collected from the force plates and motion kinematic data are measured by the motion capture system. Based on these data, the impulses, momentums and mechanical works done on the center of body mass (COM) during the double support phase were computed. The result shows that the push-off and heel strike impulse are not relevant to the trunk flexion change, however the mechanical work by the push-off and heel strike were changed by the trunk flexion variation. It is because the vertical velocity of the COM during the double support phase is increased significantly with an increase in the trunk flexion. Therefore, we can know that the gait efficiency of the loaded gait depends on the trunk flexion angle. Also, even though the gravitational impulse and pre-collision momentum are changed by the trunk flexion variation, the after-collision momentum is almost constant regardless of the trunk flexion variation.
Abstract: This paper presents the study of strengthening R/C
beams with large circular and square opening located at flexure zone
by Carbon Fiber Reinforced Polymer (CFRP) laminates. A total of
five beams were tested to failure under four point loading to
investigate the structural behavior including crack patterns, failure
mode, ultimate load and load deflection behaviour. Test results show
that large opening at flexure reduces the beam capacity and stiffness;
and increases cracking and deflection. A strengthening configuration
was designed for each un-strengthened beams based on their
respective crack patterns. CFRP laminates remarkably restore the
beam capacity of beam with large circular opening at flexure location
while 10% re-gain of beam capacity with square opening. The use of
CFRP laminates with the designed strengthening configuration could
significantly reduce excessive cracking and deflection and increase
the ultimate capacity and stiffness of beam.
Abstract: Learning the gradient of neuron's activity function
like the weight of links causes a new specification which is
flexibility. In flexible neural networks because of supervising and
controlling the operation of neurons, all the burden of the learning is
not dedicated to the weight of links, therefore in each period of
learning of each neuron, in fact the gradient of their activity function,
cooperate in order to achieve the goal of learning thus the number of
learning will be decreased considerably.
Furthermore, learning neurons parameters immunes them against
changing in their inputs and factors which cause such changing.
Likewise initial selecting of weights, type of activity function,
selecting the initial gradient of activity function and selecting a fixed
amount which is multiplied by gradient of error to calculate the
weight changes and gradient of activity function, has a direct affect
in convergence of network for learning.
Abstract: In this paper, backstepping method (BM) is proposed for a single-link flexible mechanical manipulator. In each step of this method a positive value is obtained. Selections of the gain factor values are very important because controller will have different behavior for each different set of values. Improper selection of these gains can lead to instability of the system. In order to choose proper values for gains BELBIC method has been used in this work. Finally, to prove the efficiency of this method, the obtained results of proposed model are compared with robust controller one. Results show that the combination of backstepping and BELBIC that is presented here, can stabilized the system with higher speed, shorter settling time and lower overshoot in than robust controller.
Abstract: One of the major features of hypermedia learning is its non-linear structure, allowing learners, the opportunity of flexible navigation to accommodate their own needs. Nevertheless, such flexibility can also cause problems such as insufficient navigation and disorientation for some learners, especially those with Field Dependent cognitive styles. As a result students learning performance can be deteriorated and in turn, they can have negative attitudes with hypermedia learning systems. It was suggested that visual elements can be used to compensate dilemmas. However, it is unclear whether these visual elements improve their learning or whether problems still exist. The aim of this study is to investigate the effect of students cognitive styles and visual elements on students learning performance and attitudes in hypermedia learning environment. Cognitive Style Analysis (CSA), Learning outcome in terms of pre and post-test, practical task, and Attitude Questionnaire (AQ) were administered to a sample of 60 university students. The findings revealed that FD students preformed equally to those of FI. Also, FD students experienced more disorientation in the hypermedia learning system where they depend a lot on the visual elements for navigation and orientation purposes. Furthermore, they had more positive attitudes towards the visual elements which escape them from experiencing navigation and disorientation dilemmas. In contrast, FI students were more comfortable, did not get disturbed or did not need some of the visual elements in the hypermedia learning system.
Abstract: The use of neural networks for recognition application is generally constrained by their inherent parameters inflexibility after the training phase. This means no adaptation is accommodated for input variations that have any influence on the network parameters. Attempts were made in this work to design a neural network that includes an additional mechanism that adjusts the threshold values according to the input pattern variations. The new approach is based on splitting the whole network into two subnets; main traditional net and a supportive net. The first deals with the required output of trained patterns with predefined settings, while the second tolerates output generation dynamically with tuning capability for any newly applied input. This tuning comes in the form of an adjustment to the threshold values. Two levels of supportive net were studied; one implements an extended additional layer with adjustable neuronal threshold setting mechanism, while the second implements an auxiliary net with traditional architecture performs dynamic adjustment to the threshold value of the main net that is constructed in dual-layer architecture. Experiment results and analysis of the proposed designs have given quite satisfactory conducts. The supportive layer approach achieved over 90% recognition rate, while the multiple network technique shows more effective and acceptable level of recognition. However, this is achieved at the price of network complexity and computation time. Recognition generalization may be also improved by accommodating capabilities involving all the innate structures in conjugation with Intelligence abilities with the needs of further advanced learning phases.
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: With a rapid growth in 3D graphics technology over the last few years, people are desired to see more flexible reacting motions of a biped in animations. In particular, it is impossible to anticipate all reacting motions of a biped while facing a perturbation. In this paper, we propose a three-level tracking method for animating a 3D humanoid character. First, we take the laws of physics into account to attach physical attributes, such as mass, gravity, friction, collision, contact, and torque, to bones and joints of a character. The next step is to employ PD controller to follow a reference motion as closely as possible. Once the character cannot tolerate a strong perturbation to prevent itself from falling down, we are capable of tracking a desirable falling-down action to avoid any falling condition inaccuracy. From the experimental results, we demonstrate the effectiveness and flexibility of the proposed method in comparison with conventional data-driven approaches.
Abstract: Schools today face ever-increasing demands in their attempts to ensure that students are well equipped to enter the workforce and navigate a complex world. Research indicates that computer technology can help support learning, implementation of various experiments or learning games, and that it is especially useful in developing the higher-order skills of critical thinking, observation, comprehension, implementation, comparison, analysis and active attention to activities such as research, field work, simulations and scientific inquiry. The ICT in education supports the learning procedure by enabling it to be more flexible and effective, create a rich and attractive training environment and equip the students with knowledge and potential useful for the competitive social environment in which they live. This paper presents the design, the development, and the results of the evaluation analysis of an interactive educational game which using real electric vehicles - toys (material) on a toy race track. When the game starts each student selects a specific vehicle toy. Then students are answering questionnaires in the computer. The vehicles' speed is related to the percentage of right answers in a multiple choice questionnaire (software). Every question has its own significant value depending of the different level of questionnaire. Via the developed software, each right or wrong answers in questionnaire increase or decrease the real time speed of their vehicle toys. Moreover the rate of vehicle's speed increase or decrease depends on the difficulty level of each question. The aim of the work is to attract the student’s interest in a learning process and also to improve their scores. The developed real time game was tested using independent populations of students of age groups: 8-10, 11-14, 15-18 years. Standard educational and statistical analysis tools were used for the evaluation analysis of the game. Results reveal that students using the developed real time control game scored much higher (60%) than students using a traditional simulation game on the same questionnaire. Results further indicate that student's interest in repeating the developed real time control gaming was far higher (70%) than the interest of students using a traditional simulation game.
Abstract: Behavior of dams against the seismic loads has been
studied by many researchers. Most of them proposed new numerical
methods to investigate the dam safety. In this paper, to study the
effect of nonlinear parameters of concrete in gravity dams, a twodimensional
approach was used including the finite element method,
staggered method and smeared crack approach. Effective parameters
in the models are physical properties of concrete such as modulus of
elasticity, tensile strength and specific fracture energy. Two different
models were used in foundation (mass-less and massed) in order to
determine the seismic response of concrete gravity dams. Results
show that when the nonlinear analysis includes the dam- foundation
interaction, the foundation-s mass, flexibility and radiation damping
are important in gravity dam-s response.
Abstract: The power system network is becoming more
complex nowadays and it is very difficult to maintain the stability
of the system. Today-s enhancement of technology makes it
possible to include new energy storage devices in the electric
power system. In addition, with the aid of power electronic
devices, it is possible to independently exchange active and
reactive power flow with the utility grid. The main purpose of this
paper proposes a Proportional – Integral (PI) control based 48 –
pulse Inverter based Static Synchronous Series Compensator
(SSSC) with and without Superconducting Magnetic Energy
Storage (SMES) used for enhancing the transient stability and
regulating power flow in automatic mode. Using a test power
system through the dynamic simulation in Matlab/Simulink
platform validates the performance of the proposed SSSC with and
without SMES system.
Abstract: The Time-Domain Boundary Element Method (TDBEM)
is a well known numerical technique that handles quite
properly dynamic analyses considering infinite dimension media.
However, when these analyses are also related to nonlinear behavior,
very complex numerical procedures arise considering the TD-BEM,
which may turn its application prohibitive. In order to avoid this
drawback and model nonlinear infinite media, the present work
couples two BEM formulations, aiming to achieve the best of two
worlds. In this context, the regions expected to behave nonlinearly
are discretized by the Domain Boundary Element Method (D-BEM),
which has a simpler mathematical formulation but is unable to deal
with infinite domain analyses; the TD-BEM is employed as in the
sense of an effective non-reflexive boundary. An iterative procedure
is considered for the coupling of the TD-BEM and D-BEM, which is
based on a relaxed renew of the variables at the common interfaces.
Elastoplastic models are focused and different time-steps are allowed
to be considered by each BEM formulation in the coupled analysis.
Abstract: Textile structures are engineered and fabricated to
meet worldwide structural applications. Nevertheless, research
varying textile structure on natural fibre as composite reinforcement
was found to be very limited. Most of the research is focusing on
short fibre and random discontinuous orientation of the reinforcement
structure. Realizing that natural fibre (NF) composite had been
widely developed to be used as synthetic fibre composite
replacement, this research attempted to examine the influence of
woven and cross-ply laminated structure towards its mechanical
performances. Laminated natural fibre composites were developed
using hand lay-up and vacuum bagging technique. Impact and
flexural strength were investigated as a function of fibre type (coir
and kenaf) and reinforcement structure (imbalanced plain woven,
0°/90° cross-ply and +45°/-45° cross-ply). Multi-level full factorial
design of experiment (DOE) and analysis of variance (ANOVA) was
employed to impart data as to how fibre type and reinforcement
structure parameters affect the mechanical properties of the
composites. This systematic experimentation has led to determination
of significant factors that predominant influences the impact and
flexural properties of the textile composites. It was proven that both
fibre type and reinforcement structure demonstrated significant
difference results. Overall results indicated that coir composite and
woven structure exhibited better impact and flexural strength. Yet,
cross-ply composite structure demonstrated better fracture resistance.
Abstract: This paper presents an algorithm of particle swarm
optimization with reduction for global optimization problems. Particle
swarm optimization is an algorithm which refers to the collective
motion such as birds or fishes, and a multi-point search algorithm
which finds a best solution using multiple particles. Particle
swarm optimization is so flexible that it can adapt to a number
of optimization problems. When an objective function has a lot of
local minimums complicatedly, the particle may fall into a local
minimum. For avoiding the local minimum, a number of particles are
initially prepared and their positions are updated by particle swarm
optimization. Particles sequentially reduce to reach a predetermined
number of them grounded in evaluation value and particle swarm
optimization continues until the termination condition is met. In order
to show the effectiveness of the proposed algorithm, we examine the
minimum by using test functions compared to existing algorithms.
Furthermore the influence of best value on the initial number of
particles for our algorithm is discussed.
Abstract: This paper presents a new Hybrid Fuzzy (HF) PID type controller based on Genetic Algorithms (GA-s) for solution of the Automatic generation Control (AGC) problem in a deregulated electricity environment. In order for a fuzzy rule based control system to perform well, the fuzzy sets must be carefully designed. A major problem plaguing the effective use of this method is the difficulty of accurately constructing the membership functions, because it is a computationally expensive combinatorial optimization problem. On the other hand, GAs is a technique that emulates biological evolutionary theories to solve complex optimization problems by using directed random searches to derive a set of optimal solutions. For this reason, the membership functions are tuned automatically using a modified GA-s based on the hill climbing method. The motivation for using the modified GA-s is to reduce fuzzy system effort and take large parametric uncertainties into account. The global optimum value is guaranteed using the proposed method and the speed of the algorithm-s convergence is extremely improved, too. This newly developed control strategy combines the advantage of GA-s and fuzzy system control techniques and leads to a flexible controller with simple stricture that is easy to implement. The proposed GA based HF (GAHF) controller is tested on a threearea deregulated power system under different operating conditions and contract variations. The results of the proposed GAHF controller are compared with those of Multi Stage Fuzzy (MSF) controller, robust mixed H2/H∞ and classical PID controllers through some performance indices to illustrate its robust performance for a wide range of system parameters and load changes.
Abstract: Since Software testing becomes an important part of
Software development in order to improve the quality of software,
many automation tools are created to help testing functionality of
software. There are a few issues about usability of these tools, one is
that the result log which is generated from tools contains useless
information that the tester cannot use result log to communicate
efficiently, or the result log needs to use a specific application to open.
This paper introduces a new method, SBTAR that improves usability
of automated test tools in a part of a result log. The practice will use
the capability of tools named as IBM Rational Robot to create a
customized function, the function would generate new format of a
result log which contains useful information faster and easier to
understand than using the original result log which was generated
from the tools. This result log also increases flexibility by Microsoft
Word or WordPad to make them readable.
Abstract: This study is concerned with pH solution detection
using 2 × 4 flexible sensor array based on a plastic polyethylene
terephthalate (PET) substrate that is coated a conductive layer and a
ruthenium dioxide (RuO2) sensitive membrane with the technologies
of screen-printing and RF sputtering. For data analysis, we also
prepared a dynamic measurement system for acquiring the response
voltage and analyzing the characteristics of the working electrodes
(WEs), such as sensitivity and linearity. In this condition, an array
measurement system was designed to acquire the original signal from
sensor array, and it is based on the method of digital signal processing
(DSP). The DSP modifies the unstable acquisition data to a direct
current (DC) output using the technique of digital filter. Hence, this
sensor array can obtain a satisfactory yield, 62.5%, through the design
measurement and analysis system in our laboratory.
Abstract: This paper describes the use of artificial neural
networks (ANN) for predicting non-linear layer moduli of flexible
airfield pavements subjected to new generation aircraft (NGA)
loading, based on the deflection profiles obtained from Heavy
Weight Deflectometer (HWD) test data. The HWD test is one of the
most widely used tests for routinely assessing the structural integrity
of airport pavements in a non-destructive manner. The elastic moduli
of the individual pavement layers backcalculated from the HWD
deflection profiles are effective indicators of layer condition and are
used for estimating the pavement remaining life. HWD tests were
periodically conducted at the Federal Aviation Administration-s
(FAA-s) National Airport Pavement Test Facility (NAPTF) to
monitor the effect of Boeing 777 (B777) and Beoing 747 (B747) test
gear trafficking on the structural condition of flexible pavement
sections. In this study, a multi-layer, feed-forward network which
uses an error-backpropagation algorithm was trained to approximate
the HWD backcalculation function. The synthetic database generated
using an advanced non-linear pavement finite-element program was
used to train the ANN to overcome the limitations associated with
conventional pavement moduli backcalculation. The changes in
ANN-based backcalculated pavement moduli with trafficking were
used to compare the relative severity effects of the aircraft landing
gears on the NAPTF test pavements.
Abstract: Nowadays the market for industrial companies is becoming more and more globalized and highly competitive, forcing them to shorten the duration of the manufacturing system development time in order to reduce the time to market. In order to achieve this target, the hierarchical systems used in previous manufacturing systems are not enough because they cannot deal effectively with unexpected situations. To achieve flexibility in manufacturing systems, the concept of an Autonomous Decentralized Flexible Manufacturing System (AD-FMS) is useful. In this paper, we introduce a hypothetical reasoning based algorithm called the Algorithm for Future Anticipative Reasoning (AFAR) which is able to decide on a conceivable next action of an Automated Guided Vehicle (AGV) that works autonomously in the AD-FMS.
Abstract: Water borne polyurethane (PU) based on newly prepared hyperbranched poly (amine-ester) (HBPAE) was applied and evaluated as organic coating material. HBPAE was prepared through one-pot synthesis between trimethylol propane as a core and AB2 branched monomer which was obtained via Michal addition of methyl methacrylate (MMA) and diethanol amine (DEA). PU was prepared from HBPAE using different ratios of toluene diisocyanate (TDI) to form cured coating film. The prepared HBPAE was characterized using; GPC, FT-IR and 1H-NMR. The mechanical properties (impact, hardness, adhesion, and flexibility), thermal properties (DSC and TGA) and chemical resistance of the applied film were estimated. The results indicated 50% of TDI is the selected ratio. This formulation represents a promising candidate to be used as coating material.