Abstract: Laboratory activities have produced benefits in
student learning. With current drives of new technology resources
and evolving era of education methods, renewal status of learning
and teaching in laboratory methods are in progress, for both learners
and the educators. To enhance learning outcomes in laboratory works
particularly in engineering practices and testing, learning via handson
by instruction may not sufficient. This paper describes and
compares techniques and implementation of traditional (expository)
with open-ended laboratory (problem-based) for two consecutive
cohorts studying environmental laboratory course in civil engineering
program. The transition of traditional to problem-based findings and
effect were investigated in terms of course assessment student
feedback survey, course outcome learning measurement and student
performance grades. It was proved that students have demonstrated
better performance in their grades and 12% increase in the course
outcome (CO) in problem-based open-ended laboratory style than
traditional method; although in perception, students has responded
less favorable in their feedback.
Abstract: This paper employs a new approach to regulate the
blood glucose level of type I diabetic patient under an intensive
insulin treatment. The closed-loop control scheme incorporates
expert knowledge about treatment by using reinforcement learning
theory to maintain the normoglycemic average of 80 mg/dl and the
normal condition for free plasma insulin concentration in severe
initial state. The insulin delivery rate is obtained off-line by using Qlearning
algorithm, without requiring an explicit model of the
environment dynamics. The implementation of the insulin delivery
rate, therefore, requires simple function evaluation and minimal
online computations. Controller performance is assessed in terms of
its ability to reject the effect of meal disturbance and to overcome the
variability in the glucose-insulin dynamics from patient to patient.
Computer simulations are used to evaluate the effectiveness of the
proposed technique and to show its superiority in controlling
hyperglycemia over other existing algorithms
Abstract: This paper offers a case study, in which
methodological aspects of cell design for transformation the
production process are applied. The cell redesign in this work is
tightly focused to reach optimization of material flows under real
manufacturing conditions. Accordingly, more individual techniques
were aggregated into compact methodical procedure with aim to built
one-piece flow production. Case study was concentrated on relatively
typical situation of transformation from batch production to cellular
manufacturing.
Abstract: Investment in a constructed facility represents a cost in
the short term that returns benefits only over the long term use of the
facility. Thus, the costs occur earlier than the benefits, and the owners
of facilities must obtain the capital resources to finance the costs of
construction. A project cannot proceed without an adequate
financing, and the cost of providing an adequate financing can be
quite large. For these reasons, the attention to the project finance is an
important aspect of project management. Finance is also a concern to
the other organizations involved in a project such as the general
contractor and material suppliers. Unless an owner immediately and
completely covers the costs incurred by each participant, these
organizations face financing problems of their own. At a more
general level, the project finance is the only one aspect of the general
problem of corporate finance. If numerous projects are considered
and financed together, then the net cash flow requirements constitute
the corporate financing problem for capital investment. Whether
project finance is performed at the project or at the corporate level
does not alter the basic financing problem .In this paper, we will first
consider facility financing from the owner's perspective, with due
consideration for its interaction with other organizations involved in a
project. Later, we discuss the problems of construction financing
which are crucial to the profitability and solvency of construction
contractors. The objective of this paper is to present the steps utilized
to determine the best combination of minimum project financing.
The proposed model considers financing; schedule and maximum net
area .The proposed model is called Project Financing and Schedule
Integration using Genetic Algorithms "PFSIGA". This model
intended to determine more steps (maximum net area) for any project
with a subproject. An illustrative example will demonstrate the
feature of this technique. The model verification and testing are put
into consideration.
Abstract: To improve the classification rate of the face
recognition, features combination and a novel non-linear kernel are
proposed. The feature vector concatenates three different radius of
local binary patterns and Gabor wavelet features. Gabor features are
the mean, standard deviation and the skew of each scaling and
orientation parameter. The aim of the new kernel is to incorporate
the power of the kernel methods with the optimal balance between
the features. To verify the effectiveness of the proposed method,
numerous methods are tested by using four datasets, which are
consisting of various emotions, orientations, configuration,
expressions and lighting conditions. Empirical results show the
superiority of the proposed technique when compared to other
methods.
Abstract: The main aim of this research is to investigate a novel technique for implementing a more natural and intelligent conversation system. Conversation systems are designed to converse like a human as much as their intelligent allows. Sometimes, we can think that they are the embodiment of Turing-s vision. It usually to return a predetermined answer in a predetermined order, but conversations abound with uncertainties of various kinds. This research will focus on an integrated natural language processing approach. This approach includes an integrated knowledge-base construction module, a conversation understanding and generator module, and a state manager module. We discuss effectiveness of this approach based on an experiment.
Abstract: The aim of this paper is to present a methodology in
three steps to forecast supply chain demand. In first step, various data
mining techniques are applied in order to prepare data for entering
into forecasting models. In second step, the modeling step, an
artificial neural network and support vector machine is presented
after defining Mean Absolute Percentage Error index for measuring
error. The structure of artificial neural network is selected based on
previous researchers' results and in this article the accuracy of
network is increased by using sensitivity analysis. The best forecast
for classical forecasting methods (Moving Average, Exponential
Smoothing, and Exponential Smoothing with Trend) is resulted based
on prepared data and this forecast is compared with result of support
vector machine and proposed artificial neural network. The results
show that artificial neural network can forecast more precisely in
comparison with other methods. Finally, forecasting methods'
stability is analyzed by using raw data and even the effectiveness of
clustering analysis is measured.
Abstract: A 10bit, 40 MSps, sample and hold, implemented in 0.18-μm CMOS technology with 3.3V supply, is presented for application in the front-end stage of an analog-to-digital converter. Topology selection, biasing, compensation and common mode feedback are discussed. Cascode technique has been used to increase the dc gain. The proposed opamp provides 149MHz unity-gain bandwidth (wu), 80 degree phase margin and a differential peak to peak output swing more than 2.5v. The circuit has 55db Total Harmonic Distortion (THD), using the improved fully differential two stage operational amplifier of 91.7dB gain. The power dissipation of the designed sample and hold is 4.7mw. The designed system demonstrates relatively suitable response in different process, temperature and supply corners (PVT corners).
Abstract: This paper describes a CMOS four-quadrant
multiplier intended for use in the front-end receiver by utilizing the
square-law characteristic of the MOS transistor in the saturation
region. The circuit is based on 0.35 um CMOS technology simulated
using HSPICE software. The mixer has a third-order inter the power
consumption is 271uW from a single 1.2V power supply. One of the
features of the proposed design is using two MOS transistors
limitation to reduce the supply voltage, which leads to reduce the
power consumption. This technique provides a GHz bandwidth
response and low power consumption.
Abstract: Choosing the right metadata is a critical, as good
information (metadata) attached to an image will facilitate its
visibility from a pile of other images. The image-s value is enhanced
not only by the quality of attached metadata but also by the technique
of the search. This study proposes a technique that is simple but
efficient to predict a single human image from a website using the
basic image data and the embedded metadata of the image-s content
appearing on web pages. The result is very encouraging with the
prediction accuracy of 95%. This technique may become a great
assist to librarians, researchers and many others for automatically and
efficiently identifying a set of human images out of a greater set of
images.
Abstract: In-core memory requirement is a bottleneck in solving
large three dimensional Navier-Stokes finite element problem
formulations using sparse direct solvers. Out-of-core solution
strategy is a viable alternative to reduce the in-core memory
requirements while solving large scale problems. This study
evaluates the performance of various out-of-core sequential solvers
based on multifrontal or supernodal techniques in the context of
finite element formulations for three dimensional problems on a
Windows platform. Here three different solvers, HSL_MA78,
MUMPS and PARDISO are compared. The performance of these
solvers is evaluated on a 64-bit machine with 16GB RAM for finite
element formulation of flow through a rectangular channel. It is
observed that using out-of-core PARDISO solver, relatively large
problems can be solved. The implementation of Newton and
modified Newton's iteration is also discussed.
Abstract: Nowadays, engineering ceramics have significant
applications in different industries such as; automotive, aerospace,
electrical, electronics and even martial industries due to their
attractive physical and mechanical properties like very high hardness
and strength at elevated temperatures, chemical stability, low friction
and high wear resistance. However, these interesting properties plus
low heat conductivity make their machining processes too hard,
costly and time consuming. Many attempts have been made in order
to make the grinding process of engineering ceramics easier and
many scientists have tried to find proper techniques to economize
ceramics' machining processes. This paper proposes a new diamond
plunge grinding technique using ultrasonic vibration for grinding
Alumina ceramic (Al2O3). For this purpose, a set of laboratory
equipments have been designed and simulated using Finite Element
Method (FEM) and constructed in order to be used in various
measurements. The results obtained have been compared with the
conventional plunge grinding process without ultrasonic vibration
and indicated that the surface roughness and fracture strength
improved and the grinding forces decreased.
Abstract: In this paper, we propose a Perceptually Optimized Foveation based Embedded ZeroTree Image Coder (POEFIC) that introduces a perceptual weighting to wavelet coefficients prior to control SPIHT encoding algorithm in order to reach a targeted bit rate with a perceptual quality improvement with respect to a given bit rate a fixation point which determines the region of interest ROI. The paper also, introduces a new objective quality metric based on a Psychovisual model that integrates the properties of the HVS that plays an important role in our POEFIC quality assessment. Our POEFIC coder is based on a vision model that incorporates various masking effects of human visual system HVS perception. Thus, our coder weights the wavelet coefficients based on that model and attempts to increase the perceptual quality for a given bit rate and observation distance. The perceptual weights for all wavelet subbands are computed based on 1) foveation masking to remove or reduce considerable high frequencies from peripheral regions 2) luminance and Contrast masking, 3) the contrast sensitivity function CSF to achieve the perceptual decomposition weighting. The new perceptually optimized codec has the same complexity as the original SPIHT techniques. However, the experiments results show that our coder demonstrates very good performance in terms of quality measurement.
Abstract: This paper presents the significant factor and give
some suggestion that should know before design. The main objective of this paper is guide the first step for someone who attends to design of grounding system before study in details later. The overview of
grounding system can protect damage from fault such as can save a human life and power system equipment. The unsafe conditions have
three cases. Case 1) maximum touch voltage exceeds the safety
criteria. In this case, the conductor compression ratio of the ground gird should be first adjusted to have optimal spacing of ground grid
conductors. If it still over limit, earth resistivity should be consider afterward. Case 2) maximum step voltage exceeds the safety criteria.
In this case, increasing the number of ground grid conductors around
the boundary can solve this problem. Case 3) both of maximum touch
and step voltage exceed the safety criteria. In this case, follow the solutions explained in case 1 and case 2. Another suggestion, vary depth of ground grid until maximum step and touch voltage do not
exceed the safety criteria.
Abstract: A model predictive controller based on recursive learning is proposed. In this SISO adaptive controller, a model is automatically updated using simple recursive equations. The identified models are then stored in the memory to be re-used in the future. The decision for model update is taken based on a new control performance index. The new controller allows the use of simple linear model predictive controllers in the control of nonlinear time varying processes.
Abstract: In this paper, a tooth shape optimization method for
cogging torque reduction in Permanent Magnet (PM) motors is
developed by using the Reduced Basis Technique (RBT) coupled by
Finite Element Analysis (FEA) and Design of Experiments (DOE)
methods. The primary objective of the method is to reduce the
enormous number of design variables required to define the tooth
shape. RBT is a weighted combination of several basis shapes. The
aim of the method is to find the best combination using the weights
for each tooth shape as the design variables. A multi-level design
process is developed to find suitable basis shapes or trial shapes at
each level that can be used in the reduced basis technique. Each level
is treated as a separated optimization problem until the required
objective – minimum cogging torque – is achieved. The process is
started with geometrically simple basis shapes that are defined by
their shape co-ordinates. The experimental design of Taguchi method
is used to build the approximation model and to perform
optimization. This method is demonstrated on the tooth shape
optimization of a 8-poles/12-slots PM motor.
Abstract: Increasing growth of information volume in the
internet causes an increasing need to develop new (semi)automatic
methods for retrieval of documents and ranking them according to
their relevance to the user query. In this paper, after a brief review
on ranking models, a new ontology based approach for ranking
HTML documents is proposed and evaluated in various
circumstances. Our approach is a combination of conceptual,
statistical and linguistic methods. This combination reserves the
precision of ranking without loosing the speed. Our approach
exploits natural language processing techniques to extract phrases
from documents and the query and doing stemming on words. Then
an ontology based conceptual method will be used to annotate
documents and expand the query. To expand a query the spread
activation algorithm is improved so that the expansion can be done
flexible and in various aspects. The annotated documents and the
expanded query will be processed to compute the relevance degree
exploiting statistical methods. The outstanding features of our
approach are (1) combining conceptual, statistical and linguistic
features of documents, (2) expanding the query with its related
concepts before comparing to documents, (3) extracting and using
both words and phrases to compute relevance degree, (4) improving
the spread activation algorithm to do the expansion based on
weighted combination of different conceptual relationships and (5)
allowing variable document vector dimensions. A ranking system
called ORank is developed to implement and test the proposed
model. The test results will be included at the end of the paper.
Abstract: In this paper a new approach to face recognition is
presented that achieves double dimension reduction, making the
system computationally efficient with better recognition results and
out perform common DCT technique of face recognition. In pattern
recognition techniques, discriminative information of image
increases with increase in resolution to a certain extent, consequently
face recognition results change with change in face image resolution
and provide optimal results when arriving at a certain resolution
level. In the proposed model of face recognition, initially image
decimation algorithm is applied on face image for dimension
reduction to a certain resolution level which provides best
recognition results. Due to increased computational speed and feature
extraction potential of Discrete Cosine Transform (DCT), it is
applied on face image. A subset of coefficients of DCT from low to
mid frequencies that represent the face adequately and provides best
recognition results is retained. A tradeoff between decimation factor,
number of DCT coefficients retained and recognition rate with
minimum computation is obtained. Preprocessing of the image is
carried out to increase its robustness against variations in poses and
illumination level. This new model has been tested on different
databases which include ORL , Yale and EME color database.
Abstract: The bit error rate (BER) performance for ultra-wide
band (UWB) indoor communication with impact of metallic furniture
is investigated. The impulse responses of different indoor
environments for any transmitter and receiver location are computed
by shooting and bouncing ray/image and inverse Fourier transform
techniques. By using the impulse responses of these multipath
channels, the BER performance for binary pulse amplitude
modulation (BPAM) impulse radio UWB communication system are
calculated. Numerical results have shown that the multi-path effect
by the metallic cabinets is an important factor for BER performance.
Also the outage probability for the UWB multipath environment with
metallic cabinets is more serious (about 18%) than with wooden
cabinets. Finally, it is worth noting that in these cases the present
work provides not only comparative information but also quantitative
information on the performance reduction.
Abstract: In a particular case of behavioural model reduction by ANNs, a validity domain shortening has been found. In mechanics, as in other domains, the notion of validity domain allows the engineer to choose a valid model for a particular analysis or simulation. In the study of mechanical behaviour for a cantilever beam (using linear and non-linear models), Multi-Layer Perceptron (MLP) Backpropagation (BP) networks have been applied as model reduction technique. This reduced model is constructed to be more efficient than the non-reduced model. Within a less extended domain, the ANN reduced model estimates correctly the non-linear response, with a lower computational cost. It has been found that the neural network model is not able to approximate the linear behaviour while it does approximate the non-linear behaviour very well. The details of the case are provided with an example of the cantilever beam behaviour modelling.