Abstract: This work presents a study on the abrasive water jet
(AWJ) machining. An explicit finite element analysis (FEA) of
single abrasive particle impact on stainless steel 1.4304 (AISI 304) is
conducted. The abrasive water jet machining is modeled by FEA
software ABAQUS/CAE. Shapes of craters in FEM simulation
results were used and compared with the previous experimental and
FEM works by means of crater sphericity. The influence of impact
angle and particle velocity was observed. Adaptive mesh domain is
used to model the impact zone. Results are in good agreement with
those obtained from the experimental and FEM simulation. The
crater-s depth is also obtained for different impact angle and abrasive
particle velocities.
Abstract: In this paper, novel statistical sampling based equalization techniques and CNN based detection are proposed to increase the spectral efficiency of multiuser communication systems over fading channels. Multiuser communication combined with selective fading can result in interferences which severely deteriorate the quality of service in wireless data transmission (e.g. CDMA in mobile communication). The paper introduces new equalization methods to combat interferences by minimizing the Bit Error Rate (BER) as a function of the equalizer coefficients. This provides higher performance than the traditional Minimum Mean Square Error equalization. Since the calculation of BER as a function of the equalizer coefficients is of exponential complexity, statistical sampling methods are proposed to approximate the gradient which yields fast equalization and superior performance to the traditional algorithms. Efficient estimation of the gradient is achieved by using stratified sampling and the Li-Silvester bounds. A simple mechanism is derived to identify the dominant samples in real-time, for the sake of efficient estimation. The equalizer weights are adapted recursively by minimizing the estimated BER. The near-optimal performance of the new algorithms is also demonstrated by extensive simulations. The paper has also developed a (Cellular Neural Network) CNN based approach to detection. In this case fast quadratic optimization has been carried out by t, whereas the task of equalizer is to ensure the required template structure (sparseness) for the CNN. The performance of the method has also been analyzed by simulations.
Abstract: The effect of muscle loss due to transfemoral
amputation, on energy expenditure of hip joint and individual
residual muscles was simulated. During swing phase of gait, with
each muscle as an ideal force generator, the lower extremity was
modeled as a two-degree of freedom linkage, for which hip and knee
were joints. According to results, muscle loss will not lead to higher
energy expenditure of hip joint, as long as other parameters of limb
remain unaffected. This finding maybe due to the role of biarticular
muscles in hip and knee joints motion. Moreover, if hip flexors are
removed from the residual limb, residual flexors, and if hip extensors
are removed, residual extensors will do more work. In line with the
common practice in transfemoral amputation, this result demonstrates
during transfemoral amputation, it is important to maintain the length
of residual limb as much as possible.
Abstract: Protein subchloroplast locations are correlated with its
functions. In contrast to the large amount of available protein
sequences, the information of their locations and functions is less
known. The experiment works for identification of protein locations
and functions are costly and time consuming. The accurate prediction
of protein subchloroplast locations can accelerate the study of
functions of proteins in chloroplast. This study proposes a Random
Forest based method, ChloroRF, to predict protein subchloroplast
locations using interpretable physicochemical properties. In addition
to high prediction accuracy, the ChloroRF is able to select important
physicochemical properties. The important physicochemical
properties are also analyzed to provide insights into the underlying
mechanism.
Abstract: To calculate the temperature distribution of the slab in
a hot rolled reheating furnace a mathematical model has been
developed by considering the thermal radiation in the furnace and
transient conduction in the slab. The furnace is modeled as radiating
medium with spatially varying temperature. Radiative heat flux within
the furnace including the effect of furnace walls, combustion gases,
skid beams and buttons is calculated using the FVM and is applied as
the boundary condition of the transient conduction equation of the
slab. After determining the slab emissivity by comparison between
simulation and experimental work, variation of heating characteristics
in the slab is investigated in the case of changing furnace temperature
with various time and the slab residence time is optimized with this
evaluation.
Abstract: In this work, propagation of uncertainty during calibration
process of TRANUS, an integrated land use and transport model
(ILUTM), has been investigated. It has also been examined, through a
sensitivity analysis, which input parameters affect the variation of the
outputs the most. Moreover, a probabilistic verification methodology
of calibration process, which equates the observed and calculated
production, has been proposed. The model chosen as an application is
the model of the city of Grenoble, France. For sensitivity analysis and
uncertainty propagation, Monte Carlo method was employed, and a
statistical hypothesis test was used for verification. The parameters of
the induced demand function in TRANUS, were assumed as uncertain
in the present case. It was found that, if during calibration, TRANUS
converges, then with a high probability the calibration process is
verified. Moreover, a weak correlation was found between the inputs
and the outputs of the calibration process. The total effect of the
inputs on outputs was investigated, and the output variation was found
to be dictated by only a few input parameters.
Abstract: The purposes of this paper are to (1) promote
excellence in computer science by suggesting a cohesive innovative
approach to fill well documented deficiencies in current computer
science education, (2) justify (using the authors- and others anecdotal
evidence from both the classroom and the real world) why this
approach holds great potential to successfully eliminate the
deficiencies, (3) invite other professionals to join the authors in proof
of concept research. The authors- experiences, though anecdotal,
strongly suggest that a new approach involving visual modeling
technologies should allow computer science programs to retain a
greater percentage of prospective and declared majors as students
become more engaged learners, more successful problem-solvers,
and better prepared as programmers. In addition, the graduates of
such computer science programs will make greater contributions to
the profession as skilled problem-solvers. Instead of wearily
rememorizing code as they move to the next course, students will
have the problem-solving skills to think and work in more
sophisticated and creative ways.
Abstract: Surveillance system is widely used in the traffic
monitoring. The deployment of cameras is moving toward a
ubiquitous camera (UbiCam) environment. In our previous study, a
novel service, called GPS-VT, was firstly proposed by incorporating
global positioning system (GPS) and visual tracking techniques for
the UbiCam environment. The first prototype is called GODTA
(GPS-based Moving Object Detection and Tracking Approach). For a
moving person carried GPS-enabled mobile device, he can be
tracking when he enters the field-of-view (FOV) of a camera
according to his real-time GPS coordinate. In this paper, GPS-VT
service is applied to the tracking of vehicles. The moving speed of a
vehicle is much faster than a person. It means that the time passing
through the FOV is much shorter than that of a person. Besides, the
update interval of GPS coordinate is once per second, it is
asynchronous with the frame rate of the real-time image. The above
asynchronous is worsen by the network transmission delay. These
factors are the main challenging to fulfill GPS-VT service on a
vehicle.In order to overcome the influence of the above factors, a
back-propagation neural network (BPNN) is used to predict the
possible lane before the vehicle enters the FOV of a camera. Then, a
template matching technique is used for the visual tracking of a target
vehicle. The experimental result shows that the target vehicle can be
located and tracking successfully. The success location rate of the
implemented prototype is higher than that of the previous GODTA.
Abstract: The recent trend has been using hybrid approach rather than using a single intelligent technique to solve the problems. In this paper, we describe and discuss a framework to develop enterprise solutions that are backed by intelligent techniques. The framework not only uses intelligent techniques themselves but it is a complete environment that includes various interfaces and components to develop the intelligent solutions. The framework is completely Web-based and uses XML extensively. It can work like shared plat-form to be accessed by multiple developers, users and decision makers.
Abstract: In this study, we are interested in the economic lot
scheduling problem (ELSP) that considers manufacturing of the
serviceable products and remanufacturing of the reworked products. In
this paper, we formulate a mathematical model for the ELSP with
reworks using the basic period approach. In order to solve this
problem, we propose a search algorithm to find the cyclic multiplier ki
of each product that can be cyclically produced for every ki basic
periods. This research also uses two heuristics to search for the optimal
production sequence of all lots and the optimal time length of the basic
period so as to minimize the average total cost. This research uses a
numerical example to show the effectiveness of our approach.
Abstract: The groundwater is one of the main sources for
sustainability in the United Arab Emirates (UAE). Intensive
developments in Al-Ain area lead to increase water demand, which
consequently reduced the overall groundwater quantity in major
aquifers. However, in certain residential areas within Al-Ain, it has
been noticed that the groundwater level is rising, for example in
Sha-ab Al Askher area. The reasons for the groundwater rising
phenomenon are yet to be investigated. In this work, twenty four
seismic refraction profiles have been carried out along the study
pilot area; as well as field measurement of the groundwater level in
a number of available water wells in the area. The processed
seismic data indicated the deepest and shallowest groundwater
levels are 15m and 2.3 meters respectively. This result is greatly
consistent with the proper field measurement of the groundwater
level. The minimum detected value may be referred to perched
subsurface water which may be associated to the infiltration from
the surrounding water bodies such as lakes, and elevated farms. The
maximum values indicate the accurate groundwater level within the
study area. The findings of this work may be considered as a
preliminary help to the decision makers.
Abstract: We propose a low-cost uniform analysis framework
allowing comparison of the strengths and weaknesses of the
bicycling experience within and between cities. A primary
component is an expedient, one-page mobility survey from which
mode share is calculated. The bicycle mode share of many cities
remains unknown, creating a serious barrier for both scientists and
policy makers aiming to understand and increase rates of bicycling.
Because of its low cost and expedience, this framework could be
replicated widely, uniformly filling the data gap. The framework has
been applied to 13 Central European cities with success. Data is
collected on multiple modes with specific questions regarding both
behavior and quality of travel experience. Individual preferences are
also collected, examining the conditions under which respondents
would change behavior to adopt more sustainable modes (bicycling
or public transportation). A broad analysis opportunity results,
intended to inform policy choices.
Abstract: Least Development Countries (LDC) like
Bangladesh, whose 25% revenue earning is achieved from Textile
export, requires producing less defective textile for minimizing
production cost and time. Inspection processes done on these
industries are mostly manual and time consuming. To reduce error
on identifying fabric defects requires more automotive and
accurate inspection process. Considering this lacking, this research
implements a Textile Defect Recognizer which uses computer
vision methodology with the combination of multi-layer neural
networks to identify four classifications of textile defects. The
recognizer, suitable for LDC countries, identifies the fabric defects
within economical cost and produces less error prone inspection
system in real time. In order to generate input set for the neural
network, primarily the recognizer captures digital fabric images by
image acquisition device and converts the RGB images into binary
images by restoration process and local threshold techniques.
Later, the output of the processed image, the area of the faulty
portion, the number of objects of the image and the sharp factor of
the image, are feed backed as an input layer to the neural network
which uses back propagation algorithm to compute the weighted
factors and generates the desired classifications of defects as an
output.
Abstract: The vehicle fleet of public transportation companies is often equipped with intelligent on-board passenger information systems. A frequently used but time and labor-intensive way for keeping the on-board controllers up-to-date is the manual update using different memory cards (e.g. flash cards) or portable computers. This paper describes a compression algorithm that enables data transmission using low bandwidth wireless radio networks (e.g. GPRS) by minimizing the amount of data traffic. In typical cases it reaches a compression rate of an order of magnitude better than that of the general purpose compressors. Compressed data can be easily expanded by the low-performance controllers, too.
Abstract: The resource-based view of the firm regards
knowledge as one of the most important organizational assets and a
key strategic resource that contributes unique value to organizations.
The acquisition, absorption and internalization of external
knowledge are central to an organization-s innovative capabilities.
This ability to evaluate, acquire and integrate new knowledge from
its environment is referred to as a firm-s absorptive capacity (AC).
This research in progress paper explores the link between interorganizational
Social Networks (SNs) and a firm-s Absorptive
Capacity (AC). Based on an in-depth literature survey of both
concepts, four propositions are proposed that explain the link
between AC and SNs. These propositions suggest that SNs are key
to a firm-s AC. A qualitative research method is proposed to test the
set of propositions in the next stage of this research.
Abstract: Studying alternative raw materials for biodiesel production is of major importance. The use of mixtures with incorporation of wastes is an environmental friendly alternative and might reduce biodiesel production costs. The objective of the present work was: (i) to study biodiesel production using waste frying oil mixed with pork lard and (ii) to understand how mixture composition influences biodiesel quality. Biodiesel was produced by transesterification and quality was evaluated through determination of several parameters according to EN 14214. The weight fraction of lard in the mixture varied from 0 to 1 in 0.2 intervals. Biodiesel production yields varied from 81.7 to 88.0 (wt%), the lowest yields being the ones obtained using waste frying oil and lard alone as raw materials. The obtained products fulfilled most of the determined quality specifications according to European biodiesel quality standard EN 14214. Minimum purity (96.5 wt%) was closely obtained when waste frying oil was used alone and when 0.2% of lard was incorporated in the raw material (96.3 wt%); however, it ranged from 93.9 to 96.3 (wt%) being always close to the limit. From the evaluation of the influence of mixture composition in biodiesel quality, it was possible to establish a model to be used for predicting some parameters of biodiesel resulting from mixtures of waste frying oil with lard when different lard contents are used.
Abstract: Home Automation is a field that, among other
subjects, is concerned with the comfort, security and energy
requirements of private homes. The configuration of automatic
functions in this type of houses is not always simple to its inhabitants
requiring the initial setup and regular adjustments. In this work, the
ubiquitous computing system vision is used, where the users- action
patterns are captured, recorded and used to create the contextawareness
that allows the self-configuration of the home automation
system. The system will try to free the users from setup adjustments
as the home tries to adapt to its inhabitants- real habits. In this paper
it is described a completely automated process to determine the light
state and act on them, taking in account the users- daily habits.
Artificial Neural Network (ANN) is used as a pattern recognition
method, classifying for each moment the light state. The work
presented uses data from a real house where a family is actually
living.
Abstract: This work presents the first results from the long-term experiment, which is focused on the impact of intensive rainfall and long period of drought on microbial activities in soil. Fifteen lysimeters were prepared in the area of our interest. This area is a protection zone of underground source of drinking water. These lysimeters were filed with topsoil and subsoil collected in this area and divided into two groups. These groups differ in fertilization and amount of water received during the growing season. Amount of microbial biomass and leaching of mineral nitrogen and phosphates were chosen as main indicators of microbial activities in soil. Content of mineral nitrogen and phosphates was measured in soil solution, which was collected from each lysimeters. Amount of microbial biomass was determined in soil samples that were taken from the lysimeters before and after the long period of drought and intensive rainfall.
Abstract: Beta-spline is built on G2 continuity which guarantees
smoothness of generated curves and surfaces using it. This curve is
preferred to be used in object design rather than reconstruction. This
study however, employs the Beta-spline in reconstructing a 3-
dimensional G2 image of the Stanford Rabbit. The original data
consists of multi-slice binary images of the rabbit. The result is then
compared with related works using other techniques.
Abstract: The aim of this paper is to experimentally discover the workability coefficient of the Inconel 718 material by using a slide turning machining. Two different types of cutting inserts, one made of carbide and the other one made of ceramic, are being used. The purpose is to compare measured results and recommend the appropriate materials and cutting parameters for a machining of the Inconel 718. Furthermore, the durability of inserts with the chosen wear criterion is being compared for different cutting speeds. Machinability of these materials is a crucial characteristic as it allows us to shorten the technological cycle time and increase the machining productivity. And this is of great importance from an economic point of view.