Abstract: Many factors affect the success of Machine Learning
(ML) on a given task. The representation and quality of the instance
data is first and foremost. If there is much irrelevant and redundant
information present or noisy and unreliable data, then knowledge
discovery during the training phase is more difficult. It is well known
that data preparation and filtering steps take considerable amount of
processing time in ML problems. Data pre-processing includes data
cleaning, normalization, transformation, feature extraction and
selection, etc. The product of data pre-processing is the final training
set. It would be nice if a single sequence of data pre-processing
algorithms had the best performance for each data set but this is not
happened. Thus, we present the most well know algorithms for each
step of data pre-processing so that one achieves the best performance
for their data set.
Abstract: Lean manufacturing is a production philosophy made
popular by Toyota Motor Corporation (TMC). It is globally known as
the Toyota Production System (TPS) and has the ultimate aim of
reducing cost by thoroughly eliminating wastes or muda. TPS
embraces the Just-in-time (JIT) manufacturing; achieving cost
reduction through lead time reduction. JIT manufacturing can be
achieved by implementing Pull system in the production.
Furthermore, TPS aims to improve productivity and creating
continuous flow in the production by arranging the machines and
processes in cellular configurations. This is called as Cellular
Manufacturing Systems (CMS). This paper studies on integrating the
CMS with the Pull system to establish a Big Island-Pull system
production for High Mix Low Volume (HMLV) products in an
automotive component industry. The paper will use the build-in JIT
system steps adapted from TMC to create the Pull system production
and also create a shojinka line which, according to takt time, has the
flexibility to adapt to demand changes simply by adding and taking
out manpower. This will lead to optimization in production.
Abstract: This article proposes modeling, simulation and
kinematic and workspace analysis of a spatial cable suspended robot
as incompletely Restrained Positioning Mechanism (IRPM). These
types of robots have six cables equal to the number of degrees of
freedom. After modeling, the kinds of workspace are defined then an
statically reachable combined workspace for different geometric
structures of fixed and moving platform is obtained. This workspace
is defined as the situations of reference point of the moving platform
(center of mass) which under external forces such as weight and with
ignorance of inertial effects, the moving platform should be in static
equilibrium under conditions that length of all cables must not be
exceeded from the maximum value and all of cables must be at
tension (they must have non-negative tension forces). Then the effect
of various parameters such as the size of moving platform, the size of
fixed platform, geometric configuration of robots, magnitude of
applied forces and moments to moving platform on workspace of
these robots with different geometric configuration are investigated.
Obtained results should be effective in employing these robots under
different conditions of applied wrench for increasing the workspace
volume.
Abstract: Wireless Sensor Network (WSN) comprises of sensor
nodes which are designed to sense the environment, transmit sensed
data back to the base station via multi-hop routing to reconstruct
physical phenomena. Since physical phenomena exists significant
overlaps between temporal redundancy and spatial redundancy, it is
necessary to use Redundancy Suppression Algorithms (RSA) for sensor
node to lower energy consumption by reducing the transmission
of redundancy. A conventional algorithm of RSAs is threshold-based
RSA, which sets threshold to suppress redundant data. Although
many temporal and spatial RSAs are proposed, temporal-spatial RSA
are seldom to be proposed because it is difficult to determine when
to utilize temporal or spatial RSAs. In this paper, we proposed a
novel temporal-spatial redundancy suppression algorithm, Codebookbase
Redundancy Suppression Mechanism (CRSM). CRSM adopts
vector quantization to generate a codebook, which is easily used to
implement temporal-spatial RSA. CRSM not only achieves power
saving and reliability for WSN, but also provides the predictability
of network lifetime. Simulation result shows that the network lifetime
of CRSM outperforms at least 23% of that of other RSAs.
Abstract: The paper discusses the results obtained to predict
reinforcement in singly reinforced beam using Neural Net (NN),
Support Vector Machines (SVM-s) and Tree Based Models. Major
advantage of SVM-s over NN is of minimizing a bound on the
generalization error of model rather than minimizing a bound on
mean square error over the data set as done in NN. Tree Based
approach divides the problem into a small number of sub problems to
reach at a conclusion. Number of data was created for different
parameters of beam to calculate the reinforcement using limit state
method for creation of models and validation. The results from this
study suggest a remarkably good performance of tree based and
SVM-s models. Further, this study found that these two techniques
work well and even better than Neural Network methods. A
comparison of predicted values with actual values suggests a very
good correlation coefficient with all four techniques.
Abstract: Recently research on human wayfinding has focused
mainly on mental representations rather than processes of
wayfinding. The objective of this paper is to demonstrate the
rationality behind applying multi-agent simulation paradigm to the
modeling of rescuer team wayfinding in order to develop
computational theory of perceptual wayfinding in crisis situations
using image schemata and affordances, which explains how people
find a specific destination in an unfamiliar building such as a
hospital. The hypothesis of this paper is that successful navigation is
possible if the agents are able to make the correct decision through
well-defined cues in critical cases, so the design of the building
signage is evaluated through the multi-agent-based simulation. In
addition, a special case of wayfinding in a building, finding one-s
way through three hospitals, is used to demonstrate the model.
Thereby, total rescue time for rescue operation during building fire is
computed. This paper discuses the computed rescue time for various
signage localization and provides experimental result for
optimization of building signage design. Therefore the most
appropriate signage design resulted in the shortest total rescue time in
various situations.
Abstract: This paper addresses a stock-cutting problem with rotation of items and without the guillotine cutting constraint. In order to solve the large-scale problem effectively and efficiently, we propose a simple but fast heuristic algorithm. It is shown that this heuristic outperforms the latest published algorithms for large-scale problem instances.
Abstract: In this paper, a design methodology to implement low-power and high-speed 2nd order recursive digital Infinite Impulse Response (IIR) filter has been proposed. Since IIR filters suffer from a large number of constant multiplications, the proposed method replaces the constant multiplications by using addition/subtraction and shift operations. The proposed new 6T adder cell is used as the Carry-Save Adder (CSA) to implement addition/subtraction operations in the design of recursive section IIR filter to reduce the propagation delay. Furthermore, high-level algorithms designed for the optimization of the number of CSA blocks are used to reduce the complexity of the IIR filter. The DSCH3 tool is used to generate the schematic of the proposed 6T CSA based shift-adds architecture design and it is analyzed by using Microwind CAD tool to synthesize low-complexity and high-speed IIR filters. The proposed design outperforms in terms of power, propagation delay, area and throughput when compared with MUX-12T, MCIT-7T based CSA adder filter design. It is observed from the experimental results that the proposed 6T based design method can find better IIR filter designs in terms of power and delay than those obtained by using efficient general multipliers.
Abstract: The objective of this study was to investigate hydrogen production from alcohol wastewater by anaerobic sequencing batch reactor (ASBR) under thermophillic operation. The ASBR unit used in this study had a liquid holding volume of 4 L and was operated at 6 cycles per day. The seed sludge taken from an upflow anaerobic sludge blanket unit treating the same wastewater was boiled at 95 °C for 15 min before being fed to the ASBR unit. The ASBR system was operated at different COD loading rates at a thermophillic temperature (55 °C), and controlled pH of 5.5. When the system was operated under optimum conditions (providing maximum hydrogen production performance) at a feed COD of 60 000 mg/l, and a COD loading rate of 68 kg/m3 d, the produced gas contained 43 % H2 content in the produced gas. Moreover, the hydrogen yield and the specific hydrogen production rate (SHPR) were 130 ml H2/g COD removed and 2100 ml H2/l d, respectively.
Abstract: In this paper a numerical algorithm is described for solving the boundary value problem associated with axisymmetric, inviscid, incompressible, rotational (and irrotational) flow in order to obtain duct wall shapes from prescribed wall velocity distributions. The governing equations are formulated in terms of the stream function ψ (x,y)and the function φ (x,y)as independent variables where for irrotational flow φ (x,y)can be recognized as the velocity potential function, for rotational flow φ (x,y)ceases being the velocity potential function but does remain orthogonal to the stream lines. A numerical method based on the finite difference scheme on a uniform mesh is employed. The technique described is capable of tackling the so-called inverse problem where the velocity wall distributions are prescribed from which the duct wall shape is calculated, as well as the direct problem where the velocity distribution on the duct walls are calculated from prescribed duct geometries. The two different cases as outlined in this paper are in fact boundary value problems with Neumann and Dirichlet boundary conditions respectively. Even though both approaches are discussed, only numerical results for the case of the Dirichlet boundary conditions are given. A downstream condition is prescribed such that cylindrical flow, that is flow which is independent of the axial coordinate, exists.
Abstract: Fundamental motivation of this paper is how gaze estimation can be utilized effectively regarding an application to games. In games, precise estimation is not always important in aiming targets but an ability to move a cursor to an aiming target accurately is also significant. Incidentally, from a game producing point of view, a separate expression of a head movement and gaze movement sometimes becomes advantageous to expressing sense of presence. A case that panning a background image associated with a head movement and moving a cursor according to gaze movement can be a representative example. On the other hand, widely used technique of POG estimation is based on a relative position between a center of corneal reflection of infrared light sources and a center of pupil. However, a calculation of a center of pupil requires relatively complicated image processing, and therefore, a calculation delay is a concern, since to minimize a delay of inputting data is one of the most significant requirements in games. In this paper, a method to estimate a head movement by only using corneal reflections of two infrared light sources in different locations is proposed. Furthermore, a method to control a cursor using gaze movement as well as a head movement is proposed. By using game-like-applications, proposed methods are evaluated and, as a result, a similar performance to conventional methods is confirmed and an aiming control with lower computation power and stressless intuitive operation is obtained.
Abstract: Protein structure determination and prediction has
been a focal research subject in the field of bioinformatics due to the
importance of protein structure in understanding the biological and
chemical activities of organisms. The experimental methods used by
biotechnologists to determine the structures of proteins demand
sophisticated equipment and time. A host of computational methods
are developed to predict the location of secondary structure elements
in proteins for complementing or creating insights into experimental
results. However, prediction accuracies of these methods rarely
exceed 70%.
Abstract: the intension in this work is to investigate the effect of
different bending manifold pipes on engine performance for different
engine speed. Power, Torque, and BSFC were calculated and
presented to show the effect of varying bending pipes angles on them
for all cases considered. A special program used to carry out the
calculations. A simulation model for 4-cylinders spark ignition
engine with turbocharger has been built and calculated. The analysis
of the results shows that for 120o angle the torque increases about
40% at 3000 rpm and 25% at 4000 rpm without changing in fuel
consumption. For 90o angle the increment in torque is about 10 %.
For the same bending angle the increment in brake power is around
40% at 3000 rpm and 25% at 4000 rpm. The increment in fuel
consumption is about 12% for 60o and 30% for 90o between (6000-
7000) rpm.
Abstract: This paper proposes an efficient learning method for the layered neural networks based on the selection of training data and input characteristics of an output layer unit. Comparing to recent neural networks; pulse neural networks, quantum neuro computation, etc, the multilayer network is widely used due to its simple structure. When learning objects are complicated, the problems, such as unsuccessful learning or a significant time required in learning, remain unsolved. Focusing on the input data during the learning stage, we undertook an experiment to identify the data that makes large errors and interferes with the learning process. Our method devides the learning process into several stages. In general, input characteristics to an output layer unit show oscillation during learning process for complicated problems. The multi-stage learning method proposes by the authors for the function approximation problems of classifying learning data in a phased manner, focusing on their learnabilities prior to learning in the multi layered neural network, and demonstrates validity of the multi-stage learning method. Specifically, this paper verifies by computer experiments that both of learning accuracy and learning time are improved of the BP method as a learning rule of the multi-stage learning method. In learning, oscillatory phenomena of a learning curve serve an important role in learning performance. The authors also discuss the occurrence mechanisms of oscillatory phenomena in learning. Furthermore, the authors discuss the reasons that errors of some data remain large value even after learning, observing behaviors during learning.
Abstract: Web sites are rapidly becoming the preferred media
choice for our daily works such as information search, company
presentation, shopping, and so on. At the same time, we live in a
period where visual appearances play an increasingly important
role in our daily life. In spite of designers- effort to develop a web
site which be both user-friendly and attractive, it would be difficult
to ensure the outcome-s aesthetic quality, since the visual
appearance is a matter of an individual self perception and opinion.
In this study, it is attempted to develop an automatic system for
web pages aesthetic evaluation which are the building blocks of
web sites. Based on the image processing techniques and artificial
neural networks, the proposed method would be able to categorize
the input web page according to its visual appearance and aesthetic
quality. The employed features are multiscale/multidirectional
textural and perceptual color properties of the web pages, fed to
perceptron ANN which has been trained as the evaluator. The
method is tested using university web sites and the results
suggested that it would perform well in the web page aesthetic
evaluation tasks with around 90% correct categorization.
Abstract: The Lattice Boltzmann Method (LBM) with double populations is applied to solve the steady-state laminar natural convective heat transfer in a triangular cavity filled with water. The bottom wall is heated, the vertical wall is cooled, and the inclined wall is kept adiabatic. The buoyancy effect was modeled by applying the Boussinesq approximation to the momentum equation. The fluid velocity is determined by D2Q9 LBM and the energy equation is discritized by D2Q4 LBM to compute the temperature field. Comparisons with previously published work are performed and found to be in excellent agreement. Numerical results are obtained for a wide range of parameters: the Rayleigh number from to and the inclination angle from 0° to 360°. Flow and thermal fields were exhibited by means of streamlines and isotherms. It is observed that inclination angle can be used as a relevant parameter to control heat transfer in right-angled triangular enclosures.
Abstract: To offer a large variety of products while maintaining
low costs, high speed, and high quality in a mass customization
product development environment, platform based product
development has much benefit and usefulness in many industry fields.
This paper proposes a product configuration strategy by similarity
measure, incorporating the knowledge engineering principles such as
product information model, ontology engineering, and formal concept
analysis.
Abstract: A retrospective study was undertaken to record the
occurrence and pattern of fractures in small animals (dogs and cats)
from year 2005 to 2010. A total of 650 cases were presented in small
animal surgery unit out of which of 116 (dogs and cats) were
presented with history of fractures of different bones. A total of
17.8% (116/650) cases were of fractures which constituted dogs 67%
while cats were 23%. The majority of animals were intact. Trauma in
the form of road side accident was the principal cause of fractures in
dogs whereas as in cats it was fall from height. The ages of the
fractured dog ranged from 4 months to 12 years whereas in cat it was
from 4 weeks to 10 years. The femoral fractures represented 37.5%
and 25% respectively in dogs and cats. Diaphysis, distal metaphyseal
and supracondylar fractures were the most affected sites in dog and
cats. Tibial fracture in dogs and cats represented 21.5% and 10%
while humoral fractures were 7.9% and 14% in dogs and cats
respectively. Humoral condyler fractures were most commonly seen
in puppies aged 4 to 6 months. Fractured radius-ulna incidence was
19% and 14% in dogs and cats respectively. Other fractures recorded
were of lumbar vertebrae, mandible and metacarpals etc. The
management comprised of external and internal fixation in both the
species. The most common internal fixation technique employed was
Intramedullary fixation in long followed by other methods like stack
or cross pinning, wiring etc as per findings in the cases. The cast
bandage was used majorly as mean for external coaptation. The
paper discusses the outcome of the case as per the technique
employed.
Abstract: Nowadays, we are facing with network threats that
cause enormous damage to the Internet community day by day. In
this situation, more and more people try to prevent their network
security using some traditional mechanisms including firewall,
Intrusion Detection System, etc. Among them honeypot is a versatile
tool for a security practitioner, of course, they are tools that are meant
to be attacked or interacted with to more information about attackers,
their motives and tools. In this paper, we will describe usefulness of
low-interaction honeypot and high-interaction honeypot and
comparison between them. And then we propose hybrid honeypot
architecture that combines low and high -interaction honeypot to
mitigate the drawback. In this architecture, low-interaction honeypot
is used as a traffic filter. Activities like port scanning can be
effectively detected by low-interaction honeypot and stop there.
Traffic that cannot be handled by low-interaction honeypot is handed
over to high-interaction honeypot. In this case, low-interaction
honeypot is used as proxy whereas high-interaction honeypot offers
the optimal level realism. To prevent the high-interaction honeypot
from infections, containment environment (VMware) is used.
Abstract: A 1.2 V, 0.61 mA bias current, low noise amplifier
(LNA) suitable for low-power applications in the 2.4 GHz band is
presented. Circuit has been implemented, laid out and simulated using
a UMC 130 nm RF-CMOS process. The amplifier provides a 13.3 dB
power gain a noise figure NF< 2.28 dB and a 1-dB compression point
of -15.69 dBm, while dissipating 0.74 mW. Such performance make
this design suitable for wireless sensor networks applications such as
ZigBee.