Abstract: Horizontal platform system (HPS) is popularly applied
in offshore and earthquake technology, but it is difficult and
time-consuming for regulation. In order to understand the nonlinear
dynamic behavior of HPS and reduce the cost when using it, this paper
employs differential transformation method to study the bifurcation
behavior of HPS. The numerical results reveal a complex dynamic
behavior comprising periodic, sub-harmonic, and chaotic responses.
Furthermore, the results reveal the changes which take place in the
dynamic behavior of the HPS as the external torque is increased.
Therefore, the proposed method provides an effective means of
gaining insights into the nonlinear dynamics of horizontal platform
system.
Abstract: This paper presents the analysis of similarity between local decisions, in the process of alphanumeric hand-prints classification. From the analysis of local characteristics of handprinted numerals and characters, extracted by a zoning method, the set of classification decisions is obtained and the similarity among them is investigated. For this purpose the Similarity Index is used, which is an estimator of similarity between classifiers, based on the analysis of agreements between their decisions. The experimental tests, carried out using numerals and characters from the CEDAR and ETL database, respectively, show to what extent different parts of the patterns provide similar classification decisions.
Abstract: The paper researched and presented a virtual simulation system based on a full-digital lunar terrain, integrated with kinematics and dynamics module as well as autonomous navigation simulation module. The system simulation models are established. Enabling technologies such as digital lunar surface module, kinematics and dynamics simulation, Autonomous navigation are investigated. A prototype system for lunar rover locomotion simulation is developed based on these technologies. Autonomous navigation is a key echnology in lunar rover system, but rarely involved in virtual simulation system. An autonomous navigation simulation module have been integrated in this prototype system, which was proved by the simulation results that the synthetic simulation and visualizing analysis system are established in the system, and the system can provide efficient support for research on the autonomous navigation of lunar rover.
Abstract: Avionics software is safe-critical embedded software
and its architecture is evolving from traditional federated architectures
to Integrated Modular Avionics (IMA) to improve resource usability.
ARINC 653 (Avionics Application Standard Software Interface) is a
software specification for space and time partitioning in Safety-critical
avionics Real-time operating systems. Arinc653 uses two-level
scheduling strategies, but current modeling tools only apply to simple
problems of Arinc653 two-level scheduling, which only contain time
property. In avionics industry, we are always manually allocating
tasks and calculating the timing table of a real-time system to ensure
it-s running as we design. In this paper we represent an automatically
generating strategy which applies to the two scheduling problems with
dependent constraints in Arinc653 partition run-time environment. It
provides the functionality of automatic generation from the task and partition models to scheduling policy through allocating the tasks to the partitions while following the constraints, and then we design a simulating mechanism to check whether our policy is schedulable or
not
Abstract: The automatic construction of large, high-resolution
image vistas (mosaics) is an active area of research in the fields of
photogrammetry [1,2], computer vision [1,4], medical image
processing [4], computer graphics [3] and biometrics [8]. Image
stitching is one of the possible options to get image mosaics. Vista
Creation in image processing is used to construct an image with a
large field of view than that could be obtained with a single
photograph. It refers to transforming and stitching multiple images
into a new aggregate image without any visible seam or distortion in
the overlapping areas. Vista creation process aligns two partial
images over each other and blends them together. Image mosaics
allow one to compensate for differences in viewing geometry. Thus
they can be used to simplify tasks by simulating the condition in
which the scene is viewed from a fixed position with single camera.
While obtaining partial images the geometric anomalies like rotation,
scaling are bound to happen. To nullify effect of rotation of partial
images on process of vista creation, we are proposing rotation
invariant vista creation algorithm in this paper. Rotation of partial
image parts in the proposed method of vista creation may introduce
some missing region in the vista. To correct this error, that is to fill
the missing region further we have used image inpainting method on
the created vista. This missing view regeneration method also
overcomes the problem of missing view [31] in vista due to cropping,
irregular boundaries of partial image parts and errors in digitization
[35]. The method of missing view regeneration generates the missing
view of vista using the information present in vista itself.
Abstract: Performance of vehicle depends on driving patterns
and vehicle drive train configuration. Driving patterns depends on
traffic condition, road condition and driver behavior. HEV design is
carried out under certain constrain like vehicle operating range,
acceleration, decelerations, maximum speed and road grades which
are directly related to the driving patterns. Therefore the detailed
study on HEV performance over a different drive cycle is required
for selection and sizing of HEV components. A simple hardware is
design to measured velocity v/s time profile of the vehicle by
operating vehicle on Indian roads under real traffic conditions. To
size the HEV components, a detailed dynamic model of the vehicle is
developed considering the effect of inertia of rotating components
like wheels, drive chain, engine and electric motor. Using vehicle
model and different Indian drive cycles data, total tractive power
demanded by vehicle and power supplied by individual components
has been calculated.Using above information selection and estimation
of component sizing for HEV is carried out so that HEV performs
efficiently under hostile driving condition. Complete analysis is
carried out in LABVIEW.
Abstract: This article simulates the wind generator set which has
two fault bearing collar rail destruction and the gear box oil leak fault.
The electric current signal which produced by the generator, We use
Empirical Mode Decomposition (EMD) as well as Fast Fourier
Transform (FFT) obtains the frequency range-s signal figure and
characteristic value. The last step is use a kind of Artificial Neural
Network (ANN) classifies which determination fault signal's type and
reason. The ANN purpose of the automatic identification wind
generator set fault..
Abstract: The lecture represents significant advances in
understanding of the transfer processes mechanism in turbulent
separated flows. Based upon experimental data suggesting the
governing role of generated local pressure gradient that takes place in
the immediate vicinity of the wall in separated flow as a result of
intense instantaneous accelerations induced by large-scale vortex
flow structures similarity laws for mean velocity and temperature and
spectral characteristics and heat and mass transfer law for turbulent
separated flows have been developed. These laws are confirmed by
available experimental data. The results obtained were employed for
analysis of heat and mass transfer in some very complex processes
occurring in technological applications such as impinging jets, heat
transfer of cylinders in cross flow and in tube banks, packed beds
where processes manifest distinct properties which allow them to be
classified under turbulent separated flows. Many facts have got an
explanation for the first time.
Abstract: The presented work is motivated by a french law regarding nuclear waste management. In order to avoid the limitation coming with the usage of the existing scenario codes, as COSI, VISION or FAMILY, the Core Library for Advance Scenario Simulation (CLASS) is being develop. CLASS is an open source tool, which allows any user to simulate an electronuclear scenario. The main CLASS asset, is the possibility to include any type of reactor, even a complitely new concept, through the generation of its ACSII evolution database. In the present article, the CLASS working basis will be presented as well as a simple exemple in order to show his potentiel. In the considered exemple, the effect of the transmutation will be assessed on Minor Actinide Inventory produced by PWR reactors.
Abstract: Evidence-based medicine is a new direction in modern healthcare. Its task is to prevent, diagnose and medicate diseases using medical evidence. Medical data about a large patient population is analyzed to perform healthcare management and medical research. In order to obtain the best evidence for a given disease, external clinical expertise as well as internal clinical experience must be available to the healthcare practitioners at right time and in the right manner. External evidence-based knowledge can not be applied directly to the patient without adjusting it to the patient-s health condition. We propose a data warehouse based approach as a suitable solution for the integration of external evidence-based data sources into the existing clinical information system and data mining techniques for finding appropriate therapy for a given patient and a given disease. Through integration of data warehousing, OLAP and data mining techniques in the healthcare area, an easy to use decision support platform, which supports decision making process of care givers and clinical managers, is built. We present three case studies, which show, that a clinical data warehouse that facilitates evidence-based medicine is a reliable, powerful and user-friendly platform for strategic decision making, which has a great relevance for the practice and acceptance of evidence-based medicine.
Abstract: Airbag deployment has been known to be responsible
for huge death, incidental injuries and broken bones due to low crash
severity and wrong deployment decisions. Therefore, the authorities
and industries have been looking for more innovative and intelligent
products to be realized for future enhancements in the vehicle safety
systems (VSSs). Although the VSSs technologies have advanced
considerably, they still face challenges such as how to avoid
unnecessary and untimely airbag deployments that can be hazardous
and fatal. Currently, most of the existing airbag systems deploy
without regard to occupant size and position. As such, this paper will
focus on the occupant and crash sensing performances due to frontal
collisions for the new breed of so called smart airbag systems. It
intends to provide a thorough discussion relating to the occupancy
detection, occupant size classification, occupant off-position
detection to determine safe distance zone for airbag deployment,
crash-severity analysis and airbag decision algorithms via a computer
modeling. The proposed system model consists of three main
modules namely, occupant sensing, crash severity analysis and
decision fusion. The occupant sensing system module utilizes the
weight sensor to determine occupancy, classify the occupant size,
and determine occupant off-position condition to compute safe
distance for airbag deployment. The crash severity analysis module is
used to generate relevant information pertinent to airbag deployment
decision. Outputs from these two modules are fused to the decision
module for correct and efficient airbag deployment action. Computer
modeling work is carried out using Simulink, Stateflow,
SimMechanics and Virtual Reality toolboxes.
Abstract: The purpose of this research was to study the
influence of learning efficiency on local accountants’ job
performance effectiveness. This paper drew upon the survey data
collected from 335 local accountants survey conducted at Nakhon
Ratchasima province, Thailand. The statistics utilized in this paper
included percentage, mean, standard deviation, and regression
analysis. The findings revealed that the majority of samples were
between 31-40 years old, married, held an undergraduate degree, and
had an average income between 10,000-15,000 baht. The majority of
respondents had less than five years of accounting experience and
worked for local administrations. The overall learning efficiency
score was in the highest level while the local accountants’ job
performance effectiveness score was also in the high level. The
hypothesis testing’s result disclosed that learning efficiency factors
which were knowledge, Skill, and Attitude had an influence on local
accountants’ job the performance effectiveness.
Abstract: Manufacturing Industries face a crucial change as products and processes are required to, easily and efficiently, be reconfigurable and reusable. In order to stay competitive and flexible, situations also demand distribution of enterprises globally, which requires implementation of efficient communication strategies. A prototype system called the “Broadcaster" has been developed with an assumption that the control environment description has been engineered using the Component-based system paradigm. This prototype distributes information to a number of globally distributed partners via an adoption of the circular-based data processing mechanism. The work highlighted in this paper includes the implementation of this mechanism in the domain of the manufacturing industry. The proposed solution enables real-time remote propagation of machine information to a number of distributed supply chain client resources such as a HMI, VRML-based 3D views and remote client instances regardless of their distribution nature and/ or their mechanisms. This approach is presented together with a set of evaluation results. Authors- main concentration surrounds the reliability and the performance metric of the adopted approach. Performance evaluation is carried out in terms of the response times taken to process the data in this domain and compared with an alternative data processing implementation such as the linear queue mechanism. Based on the evaluation results obtained, authors justify the benefits achieved from this proposed implementation and highlight any further research work that is to be carried out.
Abstract: The paper describes a self supervised parallel self organizing neural network (PSONN) architecture for true color image segmentation. The proposed architecture is a parallel extension of the standard single self organizing neural network architecture (SONN) and comprises an input (source) layer of image information, three single self organizing neural network architectures for segmentation of the different primary color components in a color image scene and one final output (sink) layer for fusion of the segmented color component images. Responses to the different shades of color components are induced in each of the three single network architectures (meant for component level processing) by applying a multilevel version of the characteristic activation function, which maps the input color information into different shades of color components, thereby yielding a processed component color image segmented on the basis of the different shades of component colors. The number of target classes in the segmented image corresponds to the number of levels in the multilevel activation function. Since the multilevel version of the activation function exhibits several subnormal responses to the input color image scene information, the system errors of the three component network architectures are computed from some subnormal linear index of fuzziness of the component color image scenes at the individual level. Several multilevel activation functions are employed for segmentation of the input color image scene using the proposed network architecture. Results of the application of the multilevel activation functions to the PSONN architecture are reported on three real life true color images. The results are substantiated empirically with the correlation coefficients between the segmented images and the original images.
Abstract: For evaluating the severity of Chronic Obstructive Pulmonary Disease (COPD), one is interested in inspecting the airway wall thickening due to inflammation. Although airway segmentations have being well developed to reconstruct in high order, airway wall segmentation remains a challenge task. While tackling such problem as a multi-surface segmentation, the interrelation within surfaces needs to be considered. We propose a new method for three-dimensional airway wall segmentation using spring structural active contour model. The method incorporates the gravitational field of the image and repelling force field of the inner lumen as the soft constraint and the geometric spring structure of active contour as the hard constraint to approximate a three-dimensional coupled surface readily for thickness measurements. The results show the preservation of topology constraints of coupled surfaces. In conclusion, our springy, soft-tissue-like structure ensures the globally optimal solution and waives the shortness following by the inevitable improper inner surface constraint.
Abstract: In recent decades, the lean methodology, and the
development of its principles and concepts have widely been applied
in supply chain management. One of the most important strategies of
being lean is having efficient inventory within the chain. On the other
hand, managing inventory efficiently requires appropriate
management of safety stock in order to protect against increasing
stretch in the breaking points of the supply chain, which in turn can
result in possible reduction of inventory. This paper applies a safety
stock cost minimization model in a manufacturing company. The
model results in optimum levels and locations of safety stock within
the company-s supply chain in order to minimize total logistics costs.
Abstract: It is important to retain customer satisfaction in
information technology services. When a service failure occurs,
companies need to take service recovery action to recover their
customer satisfaction. Although companies cannot avoid all problems
and complaints, they should try to make up. Therefore, service failure
and service recovery have become an important and challenging issue
for companies. In this paper, the literature and the problems in the
information technology services were reviewed. An integrated model
of profit driven for the service failure and service recovery was
established in view of the benefit of customer and enterprise.
Moreover, the interaction between service failure and service recovery
strategy was studied, the result of which verified the matching
principles of the service recovery strategy and the type of service
failure. In addition, the relationship between the cost of service
recovery and customer-s cumulative value of service after recovery
was analyzed with the model. The result attributes to managers in
deciding on appropriate resource allocations for recovery strategies.
Abstract: As a result of the daily workflow in the design
development departments of companies, databases containing huge
numbers of 3D geometric models are generated. According to the
given problem engineers create CAD drawings based on their design
ideas and evaluate the performance of the resulting design, e.g. by
computational simulations. Usually, new geometries are built either
by utilizing and modifying sets of existing components or by adding
single newly designed parts to a more complex design.
The present paper addresses the two facets of acquiring
components from large design databases automatically and providing
a reasonable overview of the parts to the engineer. A unified
framework based on the topographic non-negative matrix
factorization (TNMF) is proposed which solves both aspects
simultaneously. First, on a given database meaningful components
are extracted into a parts-based representation in an unsupervised
manner. Second, the extracted components are organized and
visualized on square-lattice 2D maps. It is shown on the example of
turbine-like geometries that these maps efficiently provide a wellstructured
overview on the database content and, at the same time,
define a measure for spatial similarity allowing an easy access and
reuse of components in the process of design development.
Abstract: Riprap is mostly used to prevent erosion by flows
down the steep slopes in river engineering. A total of 53 stability tests
performed on angular riprap with a median stone size ranging from
15 to 278 mm and slope ranging from 1 to 40% are used in this study.
The existing equations for the prediction of medium size of angular
stones are checked for their accuracy using the available data.
Predictions of median size using these equations are not satisfactory
and results show deviation by more than ±20% from the observed
values. A multivariable power regression analysis is performed to
propose a new equation relating the median size with unit discharge,
bed slope, riprap thickness and coefficient of uniformity. The
proposed relationship satisfactorily predicts the median angular stone
size with ±20% error. Further, the required size of the rounded stone
is more than the angular stone for the same unit discharge and the
ratio increases with unit discharge and also with embankment slope
of the riprap.
Abstract: In the hardening energy context, the transport sector
which constitutes a large worldwide energy demand has to be
improving for decrease energy demand and global warming impacts.
In a controversial situation where subsists an increasing demand for
long-distance and high-speed travels, high-speed trains offer many
advantages, as consuming significantly less energy than road or air
transports.
At the project phase of new rail infrastructures, it is nowadays
important to characterize accurately the energy that will be induced
by its operation phase, in addition to other more classical criteria as
construction costs and travel time.
Current literature consumption models used to estimate railways
operation phase are obsolete or not enough accurate for taking into
account the newest train or railways technologies.
In this paper, an updated model of consumption for high-speed is
proposed, based on experimental data obtained from full-scale tests
performed on a new high-speed line. The assessment of the model
is achieved by identifying train parameters and measured power
consumptions for more than one hundred train routes. Perspectives
are then discussed to use this updated model for accurately assess
the energy impact of future railway infrastructures.