Abstract: This work aims to describe the process of developing
services and applications of seamless communication within a
Telecom Italia long-term research project, which takes as central aim
the design of a wearable communication device. In particular, the
objective was to design a wrist phone integrated into everyday life of
people in full transparency. The methodology used to design the
wristwatch was developed through several subsequent steps also
involving the Personas Layering Framework. The data collected in
this phases have been very useful for designing an improved version
of the first two concepts of wrist phone going to change aspects
related to the four critical points expressed by the users.
Abstract: In this paper the Differential Quadrature Method (DQM) is employed to study the coupled lateral-torsional free vibration behavior of the laminated composite beams. In such structures due to the fiber orientations in various layers, the lateral displacement leads to a twisting moment. The coupling of lateral and torsional vibrations is modeled by the bending-twisting material coupling rigidity. In the present study, in addition to the material coupling, the effects of shear deformation and rotary inertia are taken into account in the definition of the potential and kinetic energies of the beam. The governing differential equations of motion which form a system of three coupled PDEs are solved numerically using DQ procedure under different boundary conditions consist of the combinations of simply, clamped, free and other end conditions. The resulting natural frequencies and mode shapes for cantilever beam are compared with similar results in the literature and good agreement is achieved.
Abstract: This study aims to investigate mechanical behavior of
deep-drawn cups consisting of aluminum (A1050)/ duralumin
(A2017) multi-layered clad structures with micro- and macro-scale
functional gradients. Such multi-layered clad structures are possibly
used for a new type of crash-boxes in automobiles to effectively
absorb the impact forces generated when automobiles having
collisions. The effect of heat treatments on microstructure,
compositional gradient, micro hardness in 2 and 6-layered aluminum/
duralumin clad structures, which were fabricated by hot rolling, have
been investigated. Impact compressive behavior of deep-drawn cups
consisting of such aluminum/ duralumin clad structures has been also
investigated in terms of energy absorption and maximum force.
Deep-drawn cups consisting of 6-layerd clad structures with microand
macro-scale functional gradients exhibit superior properties in
impact compressive tests.
Abstract: This paper proposes an architectural and graphical
user interface (GUI) design of a traditional Thai musical instrument
application for tablet computers for practicing “Ranaad Ek" which is
a trough-resonated keyboard percussion instrument. The application
provides percussion methods for a player as real as a physical
instrument. The application consists of two playing modes. The first
mode is free playing, a player can freely multi touches on wooden bar
to produce instrument sounds. The second mode is practicing mode
that guilds the player to follow percussions and rhythms of practice
songs. The application has achieved requirements and specifications.
Abstract: The objective of this paper is to a design of pattern
classification model based on the back-propagation (BP) algorithm for
decision support system. Standard BP model has done full connection
of each node in the layers from input to output layers. Therefore, it
takes a lot of computing time and iteration computing for good
performance and less accepted error rate when we are doing some
pattern generation or training the network.
However, this model is using exclusive connection in between
hidden layer nodes and output nodes. The advantage of this model is
less number of iteration and better performance compare with standard
back-propagation model. We simulated some cases of classification
data and different setting of network factors (e.g. hidden layer number
and nodes, number of classification and iteration). During our
simulation, we found that most of simulations cases were satisfied by
BP based using exclusive connection network model compared to
standard BP. We expect that this algorithm can be available to
identification of user face, analysis of data, mapping data in between
environment data and information.
Abstract: Benefits to the organisation are just as important as technical ability when it comes to software success. The challenge is to provide industry with professionals who understand this. In other words: How to teach computer engineering students to look beyond technology, and at the benefits of software to organizations? This paper reports on the conceptual design of a section of the computer networks module aimed to sensitize the students to the organisational context.
Checkland focuses on different worldviews represented by various role players in the organisation. He developed the Soft Systems Methodology that guides purposeful action in organisations, while incorporating different worldviews in the modeling process. If we can sensitize students to these methods, they are likely to appreciate the wider context of application of system software. This paper will provide literature on these concepts as well as detail on how the students will be guided to adopt these concepts.
Abstract: In built-up structures, one of the effective ways of
dissipating unwanted vibration is to exploit the occurrence of slip at
the interfaces of structural laminates. The present work focuses on
the dynamic analysis of welded structures. A mathematical
formulation has been developed for the mechanism of slip damping
in layered and welded mild steel beams with unequal thickness
subjected to both periodic and non-periodic forces. It is observed that
a number of vital parameters such as; thickness ratio, pressure
distribution characteristics, relative slip and kinematic co-efficient of
friction at the interfaces, nature of exciting forces, length and
thickness of the beam specimen govern the damping characteristics of
these structures. Experimental verification has been carried out to
validate the analysis and study the effect of these parameters. The
developed damping model for the structure is found to be in fairly
good agreement with the measured data. Finally, the results of the
analysis are discussed and rationalized.
Abstract: In this paper, we proposed a new framework to incorporate an intelligent agent software robot into a crisis communication portal (CCNet) in order to send alert news to subscribed users via email and other mobile services such as Short Message Service (SMS), Multimedia Messaging Service (MMS) and General Packet Radio Services (GPRS). The content on the mobile services can be delivered either through mobile phone or Personal Digital Assistance (PDA). This research has shown that with our proposed framework, the embodied conversation agents system can handle questions intelligently with our multilayer architecture. At the same time, the extended framework can take care of delivery content through a more humanoid interface on mobile devices.
Abstract: Response surface methodology with Box–Benhken (BB) design of experiment approach has been utilized to study the mechanism of interface slip damping in layered and jointed tack welded beams with varying surface roughness. The design utilizes the initial amplitude of excitation, tack length and surface roughness at the interfaces to develop the model for the logarithmic damping decrement of the layered and jointed welded structures. Statistically designed experiments have been performed to estimate the coefficients in the mathematical model, predict the response, and check the adequacy of the model. Comparison of predicted and experimental response values outside the design conditions have shown good correspondence, implying that empirical model derived from response surface approach can be effectively used to describe the mechanism of interface slip damping in layered and jointed tack welded structures.
Abstract: In this paper two models using a functional network
were employed to solving classification problem. Functional networks
are generalized neural networks, which permit the specification of
their initial topology using knowledge about the problem at hand. In
this case, and after analyzing the available data and their relations, we
systematically discuss a numerical analysis method used for
functional network, and apply two functional network models to
solving XOR problem. The XOR problem that cannot be solved with
two-layered neural network can be solved by two-layered functional
network, which reveals a potent computational power of functional
networks, and the performance of the proposed model was validated
using classification problems.
Abstract: Proprietary sensor network systems are typically expensive, rigid and difficult to incorporate technologies from other vendors. When using competing and incompatible technologies, a non-proprietary system is complex to create because it requires significant technical expertise and effort, which can be more expensive than a proprietary product. This paper presents the Sensor Abstraction Layer (SAL) that provides middleware architectures with a consistent and uniform view of heterogeneous sensor networks, regardless of the technologies involved. SAL abstracts and hides the hardware disparities and specificities related to accessing, controlling, probing and piloting heterogeneous sensors. SAL is a single software library containing a stable hardware-independent interface with consistent access and control functions to remotely manage the network. The end-user has near-real-time access to the collected data via the network, which results in a cost-effective, flexible and simplified system suitable for novice users. SAL has been used for successfully implementing several low-cost sensor network systems.
Abstract: Generally flow behavior in centrifugal fan is observed
to be in a state of instability with flow separation zones on suction
surface as well as near the front shroud. Overall performance of the
diffusion process in a centrifugal fan could be enhanced by
judiciously introducing the boundary layer suction slots. With easy
accessibility of CFD as an analytical tool, an extensive numerical
whole field analysis of the effect of boundary layer suction slots in
discrete regions of suspected separation points is possible. This paper
attempts to explore the effect of boundary layer suction slots
corresponding to various geometrical locations on the impeller with
converging configurations for the slots. The analysis shows that the
converging suction slots located on the impeller blade about 25%
from the trailing edge, significantly improves the static pressure
recovery across the fan. Also it is found that Slots provided at a
radial distance of about 12% from the leading and trailing edges
marginally improve the static pressure recovery across the fan.
Abstract: Markov games are a generalization of Markov
decision process to a multi-agent setting. Two-player zero-sum
Markov game framework offers an effective platform for designing
robust controllers. This paper presents two novel controller design
algorithms that use ideas from game-theory literature to produce
reliable controllers that are able to maintain performance in presence
of noise and parameter variations. A more widely used approach for
controller design is the H∞ optimal control, which suffers from high
computational demand and at times, may be infeasible. Our approach
generates an optimal control policy for the agent (controller) via a
simple Linear Program enabling the controller to learn about the
unknown environment. The controller is facing an unknown
environment, and in our formulation this environment corresponds to
the behavior rules of the noise modeled as the opponent. Proposed
controller architectures attempt to improve controller reliability by a
gradual mixing of algorithmic approaches drawn from the game
theory literature and the Minimax-Q Markov game solution
approach, in a reinforcement-learning framework. We test the
proposed algorithms on a simulated Inverted Pendulum Swing-up
task and compare its performance against standard Q learning.
Abstract: The application of agro-industrial waste in Aluminum
Metal Matrix Composites has been getting more attention as they
can reinforce particles in metal matrix which enhance the strength
properties of the composites. In addition, by applying these agroindustrial
wastes in useful way not only save the manufacturing cost
of products but also reduce the pollutions on environment. This
paper represents a literature review on a range of industrial wastes
and their utilization in metal matrix composites. The paper describes
the synthesis methods of agro-industrial waste filled metal matrix
composite materials and their mechanical, wear, corrosion, and
physical properties. It also highlights the current application and
future potential of agro-industrial waste reinforced composites in
aerospace, automotive and other construction industries.
Abstract: With the rapid usage of portable devices mobility in
IP networks becomes more important issue in the recent years. IETF
standardized Mobile IP that works in Network Layer, which involves
tunneling of IP packets from HA to Foreign Agent. Mobile IP suffers
many problems of Triangular Routing, conflict with private
addressing scheme, increase in load in HA, need of permanent home
IP address, tunneling itself, and so on. In this paper, we proposed
mobility management in Application Layer protocol SIP and show
some comparative analysis between Mobile IP and SIP in context of
mobility.
Abstract: Power consumption of nodes in ad hoc networks is a
critical issue as they predominantly operate on batteries. In order to
improve the lifetime of an ad hoc network, all the nodes must be
utilized evenly and the power required for connections must be
minimized. In this project a link layer algorithm known as Power
Aware medium Access Control (PAMAC) protocol is proposed
which enables the network layer to select a route with minimum total
power requirement among the possible routes between a source and a
destination provided all nodes in the routes have battery capacity
above a threshold. When the battery capacity goes below a
predefined threshold, routes going through these nodes will be
avoided and these nodes will act only as source and destination.
Further, the first few nodes whose battery power drained to the set
threshold value are pushed to the exterior part of the network and the
nodes in the exterior are brought to the interior. Since less total
power is required to forward packets for each connection. The
network layer protocol AOMDV is basically an extension to the
AODV routing protocol. AOMDV is designed to form multiple
routes to the destination and it also avoid the loop formation so that it
reduces the unnecessary congestion to the channel. In this project, the
performance of AOMDV is evaluated using PAMAC as a MAC layer
protocol and the average power consumption, throughput and
average end to end delay of the network are calculated and the results
are compared with that of the other network layer protocol AODV.
Abstract: The feature of HIV genome is in a wide range because
of it is highly heterogeneous. Hence, the infection ability of the virus changes related with different chemokine receptors. From this point,
R5 and X4 HIV viruses use CCR5 and CXCR5 coreceptors respectively while R5X4 viruses can utilize both coreceptors. Recently, in Bioinformatics, R5X4 viruses have been studied to
classify by using the coreceptors of HIV genome.
The aim of this study is to develop the optimal Multilayer
Perceptron (MLP) for high classification accuracy of HIV sub-type viruses. To accomplish this purpose, the unit number in hidden layer
was incremented one by one, from one to a particular number. The statistical data of R5X4, R5 and X4 viruses was preprocessed by the
signal processing methods. Accessible residues of these virus sequences were extracted and modeled by Auto-Regressive Model
(AR) due to the dimension of residues is large and different from each other. Finally the pre-processed dataset was used to evolve MLP with various number of hidden units to determine R5X4
viruses. Furthermore, ROC analysis was used to figure out the optimal MLP structure.
Abstract: We introduce an algorithm based on the
morphological shared-weight neural network. Being nonlinear and
translation-invariant, the MSNN can be used to create better
generalization during face recognition. Feature extraction is
performed on grayscale images using hit-miss transforms that are
independent of gray-level shifts. The output is then learned by
interacting with the classification process. The feature extraction and
classification networks are trained together, allowing the MSNN to
simultaneously learn feature extraction and classification for a face.
For evaluation, we test for robustness under variations in gray levels
and noise while varying the network-s configuration to optimize
recognition efficiency and processing time. Results show that the
MSNN performs better for grayscale image pattern classification
than ordinary neural networks.
Abstract: This study examined the effects of neuromuscular
training (NT) on limits of stability (LOS) in female individuals.
Twenty female basketball amateurs were assigned into NT
experimental group or control group by volunteer. All the players were
underwent regular basketball practice, 90 minutes, 3 times per week
for 6 weeks, but the NT experimental group underwent extra NT with
plyometric and core training, 50 minutes, 3 times per week for 6 weeks
during this period. Limits of stability (LOS) were evaluated by the
Biodex Balance System. One factor ANCOVA was used to examine
the differences between groups after training. The significant level for
statistic was set at p
Abstract: In this study, the Multi-Layer Perceptron (MLP)with Back-Propagation learning algorithm are used to classify to effective diagnosis Parkinsons disease(PD).It-s a challenging problem for medical community.Typically characterized by tremor, PD occurs due to the loss of dopamine in the brains thalamic region that results in involuntary or oscillatory movement in the body. A feature selection algorithm along with biomedical test values to diagnose Parkinson disease.Clinical diagnosis is done mostly by doctor-s expertise and experience.But still cases are reported of wrong diagnosis and treatment. Patients are asked to take number of tests for diagnosis.In many cases,not all the tests contribute towards effective diagnosis of a disease.Our work is to classify the presence of Parkinson disease with reduced number of attributes.Original,22 attributes are involved in classify.We use Information Gain to determine the attributes which reduced the number of attributes which is need to be taken from patients.The Artificial neural networks is used to classify the diagnosis of patients.Twenty-Two attributes are reduced to sixteen attributes.The accuracy is in training data set is 82.051% and in the validation data set is 83.333%.