Abstract: Small-scale RC models of both piles and tunnel ducts
were produced as mockups of reality and loaded under soil
confinement conditionsto investigate the damage evolution of
structural RC interacting with soil. Experimental verifications usinga
3D nonlinear FE analysis program called COM3D, which was
developed at the University of Tokyo, are introduced. This analysis
has been used in practice for seismic performance assessment of
underground ducts and in-ground LNG storage tanks in consideration
of soil-structure interactionunder static and dynamic loading. Varying
modes of failure of RCpilessubjected to different magnitudes of soil
confinement were successfully reproduced in the proposed small-scale
experiments and numerically simulated as well. Analytical simulation
was applied to RC tunnel mockups under a wide variety of depth and
soil confinement conditions, and reasonable matching was confirmed.
Abstract: Augmented Reality (AR) shows great promises for
its usage as a tool for simulation and verification of design proposal
of new technological systems. Main advantage of augmented reality
application usage is possibility of creation and simulation of new
technological unit before its realization. This may contribute to
increasing of safety and ergonomics and decreasing of economical
aspects of new proposed unit. Virtual model of proposed workcell
could reveal hidden errors which elimination in later stage of new
workcell creation should cause great difficulties. Paper describes
process of such virtual model creation and possibilities of its
simulation and verification by augmented reality tools.
Abstract: Multi criteria decision making (MCDM) methods like analytic hierarchy process, ELECTRE and multi-attribute utility theory are critically studied. They have irregularities in terms of the reliability of ranking of the best alternatives. The Routing Decision Support (RDS) algorithm is trying to improve some of their deficiencies. This paper gives a mathematical verification that the RDS algorithm conforms to the test criteria for an effective MCDM method when a linear preference function is considered.
Abstract: In this paper we propose a novel approach for ascertaining human identity based on fusion of profile face and gait biometric cues The identification approach based on feature learning in PCA-LDA subspace, and classification using multivariate Bayesian classifiers allows significant improvement in recognition accuracy for low resolution surveillance video scenarios. The experimental evaluation of the proposed identification scheme on a publicly available database [2] showed that the fusion of face and gait cues in joint PCA-LDA space turns out to be a powerful method for capturing the inherent multimodality in walking gait patterns, and at the same time discriminating the person identity..
Abstract: This work offers a study of new simple compact model
of dual-drain Magnetic Field Effect Transistor (MAGFET) including
geometrical effects and biasing dependency. An explanation of the
sensitivity is investigated, involving carrier deflection as the dominant
operating principle. Finally, model verification with simulation results
is introduced to ensure that acceptable error of 2% is achieved.
Abstract: Increasing use of cell phone as a medium of human interaction is playing a vital role in solving riddles of crime as well. A young girl went missing from her home late in the evening in the month of August, 2008 when her enraged relatives and villagers physically assaulted and chased her fiancée who often frequented her home. Two years later, her mother lodged a complaint against the relatives and the villagers alleging that after abduction her daughter was either sold or killed as she had failed to trace her. On investigation, a rusted cell phone with partial visible IMEI number, clothes, bangles, human skeleton etc. recovered from abandoned well in the month of May, 2011 were examined in the lab. All hopes pinned on identity of cell phone, for only linking evidence to fix the scene of occurrence supported by call detail record (CDR) and to dispel doubts about mode of sudden disappearance or death as DNA technology did not help in establishing identity of the deceased. The conventional scientific methods were used without success and international mobile equipment identification number of the cell phone could be generated by using statistical analysis followed by online verification.
Abstract: Signature represents an individual characteristic of a
person which can be used for his / her validation. For such application
proper modeling is essential. Here we propose an offline signature
recognition and verification scheme which is based on extraction of
several features including one hybrid set from the input signature
and compare them with the already trained forms. Feature points
are classified using statistical parameters like mean and variance.
The scanned signature is normalized in slant using a very simple
algorithm with an intention to make the system robust which is
found to be very helpful. The slant correction is further aided by the
use of an Artificial Neural Network (ANN). The suggested scheme
discriminates between originals and forged signatures from simple
and random forgeries. The primary objective is to reduce the two
crucial parameters-False Acceptance Rate (FAR) and False Rejection
Rate (FRR) with lesser training time with an intension to make the
system dynamic using a cluster of ANNs forming a multiple classifier
system.
Abstract: Matching algorithms have significant importance in
speaker recognition. Feature vectors of the unknown utterance are
compared to feature vectors of the modeled speakers as a last step in
speaker recognition. A similarity score is found for every model in
the speaker database. Depending on the type of speaker recognition,
these scores are used to determine the author of unknown speech
samples. For speaker verification, similarity score is tested against a
predefined threshold and either acceptance or rejection result is
obtained. In the case of speaker identification, the result depends on
whether the identification is open set or closed set. In closed set
identification, the model that yields the best similarity score is
accepted. In open set identification, the best score is tested against a
threshold, so there is one more possible output satisfying the
condition that the speaker is not one of the registered speakers in
existing database. This paper focuses on closed set speaker
identification using a modified version of a well known matching
algorithm. The results of new matching algorithm indicated better
performance on YOHO international speaker recognition database.
Abstract: In this paper, numerical simulations are performed to investigate the effect of disturbance block on flow field of the classical square lid-driven cavity. Attentions are focused on vortex formation and studying the effect of block position on its structure. Corner vortices are different upon block position and new vortices are produced because of the block. Finite volume method is used to solve Navier-Stokes equations and PISO algorithm is employed for the linkage of velocity and pressure. Verification and grid independency of results are reported. Stream lines are sketched to visualize vortex structure in different block positions.
Abstract: This paper presents a general trainable framework
for fast and robust upright human face and non-human object
detection and verification in static images. To enhance the
performance of the detection process, the technique we develop is
based on the combination of fast neural network (FNN) and
classical neural network (CNN). In FNN, a useful correlation is
exploited to sustain high level of detection accuracy between input
image and the weight of the hidden neurons. This is to enable the
use of Fourier transform that significantly speed up the time
detection. The combination of CNN is responsible to verify the
face region. A bootstrap algorithm is used to collect non human
object, which adds the false detection to the training process of the
human and non-human object. Experimental results on test images
with both simple and complex background demonstrate that the
proposed method has obtained high detection rate and low false
positive rate in detecting both human face and non-human object.
Abstract: When a small H/W IP is designed, we can develop an
appropriate verification environment by observing the simulated
signal waves, or using the serial test vectors for the fixed output. In the
case of design and verification of a massive parallel processor with
multiple IPs, it-s difficult to make a verification system with existing
common verification environment, and to verify each partial IP. A
TestDrive verification environment can build easy and reliable
verification system that can produce highly intuitive results by
applying Modelsim and SystemVerilog-s DPI. It shows many
advantages, for example a high-level design of a GPGPU processor
design can be migrate to FPGA board immediately.
Abstract: In this paper an extensive verification of the extraction
method (published earlier) that consistently accounts for self-heating
and Early effect to accurately extract both base and thermal resistance
of bipolar junction transistors is presented. The method verification is
demonstrated on advanced RF SiGe HBTs were the extracted results
for the thermal resistance are compared with those from another
published method that ignores the effect of Early effect on internal
base-emitter voltage and the extracted results of the base resistance
are compared with those determined from noise measurements. A
self-consistency of our method in the extracted base resistance and
thermal resistance using compact model simulation results is also
carried out in order to study the level of accuracy of the method.
Abstract: In this paper is described a new conception of the
Cartesian robot for automated assembly and also disassembly
process. The advantage of this conception is the utilization the
Cartesian assembly robot with its all peripheral automated devices for
assembly of the assembled product. The assembly product in the end
of the lifecycle can be disassembled with the same Cartesian
disassembly robot with the use of the same peripheral automated
devices and equipment. It is a new approach to problematic solving
and development of the automated assembly systems with respect to
lifecycle management of the assembly product and also assembly
system with Cartesian robot. It is also important to develop the
methodical process for design of automated assembly and
disassembly system with Cartesian robot. Assembly and disassembly
system use the same Cartesian robot input and output devices,
assembly and disassembly units in one workplace with different
application. Result of design methodology is the verification and
proposition of real automated assembly and disassembly workplace
with Cartesian robot for known verified model of assembled actuator.
Abstract: IEEE has designed 802.11i protocol to address the
security issues in wireless local area networks. Formal analysis is
important to ensure that the protocols work properly without having
to resort to tedious testing and debugging which can only show the
presence of errors, never their absence. In this paper, we present
the formal verification of an abstract protocol model of 802.11i.
We translate the 802.11i protocol into the Strand Space Model and
then prove the authentication property of the resulting model using
the Strand Space formalism. The intruder in our model is imbued
with powerful capabilities and repercussions to possible attacks are
evaluated. Our analysis proves that the authentication of 802.11i is
not compromised in the presented model. We further demonstrate
how changes in our model will yield a successful man-in-the-middle
attack.
Abstract: Gas chromatography (GC) is the most widely used
technique in analytical chemistry. However, GC has high initial cost
and requires frequent maintenance. This paper examines the
feasibility and potential of using a neural network model as an
alternative whenever GC is unvailable. It can also be part of system
verification on the performance of GC for preventive maintenance
activities. It shows the performance of MultiLayer Perceptron (MLP)
with Backpropagation structure. Results demonstrate that neural
network model when trained using this structure provides an
adequate result and is suitable for this purpose. cm.
Abstract: Graph has become increasingly important in modeling
complicated structures and schemaless data such as proteins, chemical
compounds, and XML documents. Given a graph query, it is desirable
to retrieve graphs quickly from a large database via graph-based
indices. Different from the existing methods, our approach, called
VFM (Vertex to Frequent Feature Mapping), makes use of vertices
and decision features as the basic indexing feature. VFM constructs
two mappings between vertices and frequent features to answer graph
queries. The VFM approach not only provides an elegant solution to
the graph indexing problem, but also demonstrates how database
indexing and query processing can benefit from data mining,
especially frequent pattern mining. The results show that the proposed
method not only avoids the enumeration method of getting subgraphs
of query graph, but also effectively reduces the subgraph isomorphism
tests between the query graph and graphs in candidate answer set in
verification stage.
Abstract: During the last decade ultrafine grained (UFG) and nano-structured (NS) materials have experienced a rapid development. In this research work finite element analysis has been carried out to investigate the plastic strain distribution in equal channel angular process (ECAP). The magnitudes of Standard deviation (S. D.) and inhomogeneity index (Ci) were compared for different ECAP passes. Verification of a three-dimensional finite element model was performed with experimental tests. Finally the mechanical property including impact energy of ultrafine grained pure commercially pure Aluminum produced by severe plastic deformation method has been examined. For this aim, equal channel angular pressing die with the channel angle, outer corner angle and channel diameter of 90°, 20° and 20mm had been designed and manufactured. Commercial pure Aluminum billets were ECAPed up to four passes by route BC at the ambient temperature. The results indicated that there is a great improvement at the hardness measurement, yield strength and ultimate tensile strength after ECAP process. It is found that the magnitudes of HV reach 67HV from 21HV after the final stage of process. Also, about 330% and 285% enhancement at the YS and UTS values have been obtained after the fourth pass as compared to the as-received conditions, respectively. On the other hand, the elongation to failure and impact energy have been reduced by 23% and 50% after imposing four passes of ECAP process, respectively.
Abstract: In this work, we present a novel active learning approach
for learning a visual object detection system. Our system
is composed of an active learning mechanism as wrapper around
a sub-algorithm which implement an online boosting-based learning
object detector. In the core is a combination of a bootstrap procedure
and a semi automatic learning process based on the online boosting
procedure. The idea is to exploit the availability of classifier during
learning to automatically label training samples and increasingly
improves the classifier. This addresses the issue of reducing labeling
effort meanwhile obtain better performance. In addition, we propose
a verification process for further improvement of the classifier.
The idea is to allow re-update on seen data during learning for
stabilizing the detector. The main contribution of this empirical study
is a demonstration that active learning based on an online boosting
approach trained in this manner can achieve results comparable or
even outperform a framework trained in conventional manner using
much more labeling effort. Empirical experiments on challenging data
set for specific object deteciton problems show the effectiveness of
our approach.
Abstract: Project selection problems on management
information system (MIS) are often considered a multi-criteria
decision-making (MCDM) for a solving method. These problems
contain two aspects, such as interdependencies among criteria and
candidate projects and qualitative and quantitative factors of projects.
However, most existing methods reported in literature consider these
aspects separately even though these two aspects are simultaneously
incorporated. For this reason, we proposed a hybrid method using
analytic network process (ANP) and fuzzy logic in order to represent
both aspects. We then propose a goal programming model to conduct
an optimization for the project selection problems interpreted by a
hybrid concept. Finally, a numerical example is conducted as
verification purposes.
Abstract: Recent advances in both the testing and verification of software based on formal specifications of the system to be built have reached a point where the ideas can be applied in a powerful way in the design of agent-based systems. The software engineering research has highlighted a number of important issues: the importance of the type of modeling technique used; the careful design of the model to enable powerful testing techniques to be used; the automated verification of the behavioural properties of the system; the need to provide a mechanism for translating the formal models into executable software in a simple and transparent way. This paper introduces the use of the X-machine formalism as a tool for modeling biology inspired agents proposing the use of the techniques built around X-machine models for the construction of effective, and reliable agent-based software systems.