Abstract: In metal cutting industries, mathematical/statistical
models are typically used to predict tool replacement time. These
off-line methods usually result in less than optimum replacement
time thereby either wasting resources or causing quality problems.
The few online real-time methods proposed use indirect measurement
techniques and are prone to similar errors. Our idea is based on
identifying the optimal replacement time using an electronic nose to
detect the airborne compounds released when the tool wear reaches
to a chemical substrate doped into tool material during the
fabrication. The study investigates the feasibility of the idea, possible
doping materials and methods along with data stream mining
techniques for detection and monitoring different phases of tool
wear.
Abstract: The primary objective of this paper was to construct a
“kinematic parameter-independent modeling of three-axis machine
tools for geometric error measurement" technique. Improving the
accuracy of the geometric error for three-axis machine tools is one of
the machine tools- core techniques. This paper first applied the
traditional method of HTM to deduce the geometric error model for
three-axis machine tools. This geometric error model was related to the
three-axis kinematic parameters where the overall errors was relative
to the machine reference coordinate system. Given that the
measurement of the linear axis in this model should be on the ideal
motion axis, there were practical difficulties. Through a measurement
method consolidating translational errors and rotational errors in the
geometric error model, we simplified the three-axis geometric error
model to a kinematic parameter-independent model. Finally, based on
the new measurement method corresponding to this error model, we
established a truly practical and more accurate error measuring
technique for three-axis machine tools.
Abstract: Shadows add great amount of realism to a scene and
many algorithms exists to generate shadows. Recently, Shadow
volumes (SVs) have made great achievements to place a valuable
position in the gaming industries. Looking at this, we concentrate on
simple but valuable initial partial steps for further optimization in SV
generation, i.e.; model simplification and silhouette edge detection
and tracking. Shadow volumes (SVs) usually takes time in generating
boundary silhouettes of the object and if the object is complex then
the generation of edges become much harder and slower in process.
The challenge gets stiffer when real time shadow generation and
rendering is demanded. We investigated a way to use the real time
silhouette edge detection method, which takes the advantage of
spatial and temporal coherence, and exploit the level-of-details
(LOD) technique for reducing silhouette edges of the model to use
the simplified version of the model for shadow generation speeding
up the running time. These steps highly reduce the execution time of
shadow volume generations in real-time and are easily flexible to any
of the recently proposed SV techniques. Our main focus is to exploit
the LOD and silhouette edge detection technique, adopting them to
further enhance the shadow volume generations for real time
rendering.
Abstract: MRAM technology provides a combination of fast
access time, non-volatility, data retention and endurance. While a
growing interest is given to two-terminal Magnetic Tunnel Junctions
(MTJ) based on Spin-Transfer Torque (STT) switching as the
potential candidate for a universal memory, its reliability is
dramatically decreased because of the common writing/reading path.
Three-terminal MTJ based on Spin-Orbit Torque (SOT) approach
revitalizes the hope of an ideal MRAM. It can overcome the
reliability barrier encountered in current two-terminal MTJs by
separating the reading and the writing path. In this paper, we study
two possible writing schemes for the SOT-MTJ device based on
recently fabricated samples. While the first is based on precessional
switching, the second requires the presence of permanent magnetic
field. Based on an accurate Verilog-A model, we simulate the two
writing techniques and we highlight advantages and drawbacks of
each one. Using the second technique, pioneering logic circuits based
on the three-terminal architecture of the SOT-MTJ described in this
work are under development with preliminary attractive results.
Abstract: Opinion extraction about products from customer
reviews is becoming an interesting area of research. Customer
reviews about products are nowadays available from blogs and
review sites. Also tools are being developed for extraction of opinion
from these reviews to help the user as well merchants to track the
most suitable choice of product. Therefore efficient method and
techniques are needed to extract opinions from review and blogs. As
reviews of products mostly contains discussion about the features,
functions and services, therefore, efficient techniques are required to
extract user comments about the desired features, functions and
services. In this paper we have proposed a novel idea to find features
of product from user review in an efficient way. Our focus in this
paper is to get the features and opinion-oriented words about
products from text through auxiliary verbs (AV) {is, was, are, were,
has, have, had}. From the results of our experiments we found that
82% of features and 85% of opinion-oriented sentences include AVs.
Thus these AVs are good indicators of features and opinion
orientation in customer reviews.
Abstract: During recent years, the traditional learning
approaches have undergone fundamental changes due to the
emergence of new technologies such as multimedia, hypermedia and
telecommunication. E-learning is a modern world phenomenon that
has come into existence in the information age and in a knowledgebased
society. E-learning has developed significantly within a short
period of time. Thus it is of a great significant to secure information,
allow a confident access and prevent unauthorized accesses. Making
use of individuals- physiologic or behavioral (biometric) properties is
a confident method to make the information secure. Among the
biometrics, fingerprint is more acceptable and most countries use it as
an efficient methods of identification. This article provides a new
method to compare the fingerprint comparison by pattern recognition
and image processing techniques. To verify fingerprint, the shortest
distance method is used together with perceptronic multilayer neural
network functioning based on minutiae. This method is highly
accurate in the extraction of minutiae and it accelerates comparisons
due to elimination of false minutiae and is more reliable compared
with methods that merely use directional images.
Abstract: The procurement and cost management approach adopted for mechanical and electrical (M&E) services in Malaysian construction industry have been criticized for its inefficiency. The study examined early cost estimating practices adopted for mechanical and electrical services (M&E) in Malaysia so as to understand the level of compliance of the current techniques with best practices. The methodology adopted for the study is a review of bidding documents used on both completed and on – going building projects awarded between 2008 – 2010 under 9th Malaysian Plan. The analysis revealed that, M&E services cost cannot be reliably estimated at pre-contract stage; the bidding techniques adopted for M&E services failed to provide uniform basis for contractors to submit tender; detailed measurement of items were not made which could complicate post contract cost control and financial management. The paper concluded that, there is need to follow a structured approach in determining the pre-contract cost estimate for M&E services which will serve as a virile tool for post contract cost control.
Abstract: Fundamental sensor-motor couplings form the backbone
of most mobile robot control tasks, and often need to be implemented
fast, efficiently and nevertheless reliably. Machine learning
techniques are therefore often used to obtain the desired sensor-motor
competences.
In this paper we present an alternative to established machine
learning methods such as artificial neural networks, that is very fast,
easy to implement, and has the distinct advantage that it generates
transparent, analysable sensor-motor couplings: system identification
through nonlinear polynomial mapping.
This work, which is part of the RobotMODIC project at the
universities of Essex and Sheffield, aims to develop a theoretical understanding
of the interaction between the robot and its environment.
One of the purposes of this research is to enable the principled design
of robot control programs.
As a first step towards this aim we model the behaviour of the
robot, as this emerges from its interaction with the environment, with
the NARMAX modelling method (Nonlinear, Auto-Regressive, Moving
Average models with eXogenous inputs). This method produces
explicit polynomial functions that can be subsequently analysed using
established mathematical methods.
In this paper we demonstrate the fidelity of the obtained NARMAX
models in the challenging task of robot route learning; we present a
set of experiments in which a Magellan Pro mobile robot was taught
to follow four different routes, always using the same mechanism to
obtain the required control law.
Abstract: This paper proposes and analyses the wireless
telecommunication system with multiple antennas to the emission
and reception MIMO (multiple input multiple output) with space
diversity in a OFDM context. In particular it analyses the
performance of a DTT (Digital Terrestrial Television) broadcasting
system that includes MIMO-OFDM techniques. Different
propagation channel models and configurations are considered for
each diversity scheme. This study has been carried out in the context
of development of the next generation DVB-T/H and WRAN.
Abstract: The clinical usefulness of heart rate variability is
limited to the range of Holter monitoring software available. These
software algorithms require a normal sinus rhythm to accurately
acquire heart rate variability (HRV) measures in the frequency
domain. Premature ventricular contractions (PVC) or more
commonly referred to as ectopic beats, frequent in heart failure,
hinder this analysis and introduce ambiguity. This investigation
demonstrates an algorithm to automatically detect ectopic beats by
analyzing discrete wavelet transform coefficients. Two techniques
for filtering and replacing the ectopic beats from the RR signal are
compared. One technique applies wavelet hard thresholding
techniques and another applies linear interpolation to replace ectopic
cycles. The results demonstrate through simulation, and signals
acquired from a 24hr ambulatory recorder, that these techniques can
accurately detect PVC-s and remove the noise and leakage effects
produced by ectopic cycles retaining smooth spectra with the
minimum of error.
Abstract: In blended learning environments, the Internet can be combined with other technologies. The aim of this research was to design, introduce and validate a model to support synchronous and asynchronous activities by managing content domains in an Adaptive Hypermedia System (AHS). The application is based on information recovery techniques, clustering algorithms and adaptation rules to adjust the user's model to contents and objects of study. This system was applied to blended learning in higher education. The research strategy used was the case study method. Empirical studies were carried out on courses at two universities to validate the model. The results of this research show that the model had a positive effect on the learning process. The students indicated that the synchronous and asynchronous scenario is a good option, as it involves a combination of work with the lecturer and the AHS. In addition, they gave positive ratings to the system and stated that the contents were adapted to each user profile.
Abstract: Knowledge bases are basic components of expert
systems or intelligent computational programs. Knowledge bases
provide knowledge, events that serve deduction activity,
computation and control. Therefore, researching and developing of
models for knowledge representation play an important role in
computer science, especially in Artificial Intelligence Science and
intelligent educational software. In this paper, the extensive
deduction computational model is proposed to design knowledge
bases whose attributes are able to be real values or functional values.
The system can also solve problems based on knowledge bases.
Moreover, the models and algorithms are applied to produce the
educational software for solving alternating current problems or
solving set of equations automatically.
Abstract: Expression data analysis is based mostly on the
statistical approaches that are indispensable for the study of
biological systems. Large amounts of multidimensional data resulting
from the high-throughput technologies are not completely served by
biostatistical techniques and are usually complemented with visual,
knowledge discovery and other computational tools. In many cases,
in biological systems we only speculate on the processes that are
causing the changes, and it is the visual explorative analysis of data
during which a hypothesis is formed. We would like to show the
usability of multidimensional visualization tools and promote their
use in life sciences. We survey and show some of the
multidimensional visualization tools in the process of data
exploration, such as parallel coordinates and radviz and we extend
them by combining them with the self-organizing map algorithm. We
use a time course data set of transitional cell carcinoma of the bladder
in our examples. Analysis of data with these tools has the potential to
uncover additional relationships and non-trivial structures.
Abstract: Biometric measures of one kind or another have been
used to identify people since ancient times, with handwritten
signatures, facial features, and fingerprints being the traditional
methods. Of late, Systems have been built that automate the task of
recognition, using these methods and newer ones, such as hand
geometry, voiceprints and iris patterns. These systems have different
strengths and weaknesses. This work is a two-section composition. In
the starting section, we present an analytical and comparative study
of common biometric techniques. The performance of each of them
has been viewed and then tabularized as a result. The latter section
involves the actual implementation of the techniques under
consideration that has been done using a state of the art tool called,
MATLAB. This tool aids to effectively portray the corresponding
results and effects.
Abstract: There are many sources trough which the soil get
enriched and contaminated with REEs. The determination of REEs in
environmental samples has been limited because of the lack of
sensitive analytical techniques. Soil samples were collected from
four sites including open cast coal mine, natural coal burning, coal
washery and control in the coal field located in Dhanbad, India.
Total concentrations of rare earth elements (REEs) were determined
using the inductively coupled plasma atomic absorption spectrometry
in order to assess enrichment status in the coal field. Results showed
that the mean concentrations of La, Pr, Eu, Tb, Ho, and Tm in open
cast mine and natural coal burning sites were elevated compared to
the reference concentrations, while Ce, Nd, Sm, and Gd were
elevated in coal washery site. When compared to reference soil,
heavy REEs (HREEs) were enriched in open cast mines and natural
coal burning affected soils, however, the HREEs were depleted in the
coal washery sites. But, the Chondrite-normalization diagram showed
significant enrichment for light REEs (LREEs) in all the soils. High
concentration of Pr, Eu, Tb, Ho, Tm, and Lu in coal mining and coal
burning sites may pose human health risks. Factor analysis showed
that distribution and relative abundance of REEs of the coal washery
site is comparable with the control. Eventually washing or cleaning
of coal could significantly decrease the emission of REEs from coal
into the environment.
Abstract: In recent years image watermarking has become an
important research area in data security, confidentiality and image
integrity. Many watermarking techniques were proposed for medical
images. However, medical images, unlike most of images, require
extreme care when embedding additional data within them because
the additional information must not affect the image quality and
readability. Also the medical records, electronic or not, are linked to
the medical secrecy, for that reason, the records must be confidential.
To fulfill those requirements, this paper presents a lossless
watermarking scheme for DICOM images. The proposed a fragile
scheme combines two reversible techniques based on difference
expansion for patient's data hiding and protecting the region of
interest (ROI) with tamper detection and recovery capability.
Patient's data are embedded into ROI, while recovery data are
embedded into region of non-interest (RONI). The experimental
results show that the original image can be exactly extracted from the
watermarked one in case of no tampering. In case of tampered ROI,
tampered area can be localized and recovered with a high quality
version of the original area.
Abstract: Case based reasoning (CBR) methodology presents a foundation for a new technology of building intelligent computeraided diagnoses systems. This Technology directly addresses the problems found in the traditional Artificial Intelligence (AI) techniques, e.g. the problems of knowledge acquisition, remembering, robust and maintenance. This paper discusses the CBR methodology, the research issues and technical aspects of implementing intelligent medical diagnoses systems. Successful applications in cancer and heart diseases developed by Medical Informatics Research Group at Ain Shams University are also discussed.
Abstract: We investigate efficient spreading codes for transmitter based techniques of code division multiple access (CDMA) systems. The channel is considered to be known at the transmitter which is usual in a time division duplex (TDD) system where the channel is assumed to be the same on uplink and downlink. For such a TDD/CDMA system, both bitwise and blockwise multiuser transmission schemes are taken up where complexity is transferred to the transmitter side so that the receiver has minimum complexity. Different spreading codes are considered at the transmitter to spread the signal efficiently over the entire spectrum. The bit error rate (BER) curves portray the efficiency of the codes in presence of multiple access interference (MAI) as well as inter symbol interference (ISI).
Abstract: CTMA-bentonite and BTEA-Bentonite prepared by Na-bentonite cation exchanged with cetyltrimethylammonium(CTMA) and benzyltriethylammonium (BTEA). Products were characterized by XRD and IR techniques.The d001 spacing value of CTMA-bentonite and BTEA-bentonite are 7.54Å and 3.50Å larger than that of Na-bentonite at 100% cation exchange capacity, respectively. The IR spectrum showed that the intensities of OH stretching and bending vibrations of the two organoclays decreased greatly comparing to untreated Na-bentonite. Batch experiments were carried out at 303 K, 318 K and 333 K to obtain the sorption isotherms of Crystal violet onto the two organoclays. The results show that the sorption isothermal data could be well described by Freundlich model. The dynamical data for the two organoclays fit well with pseudo-second-order kinetic model. The adsorption capacity of CTMA-bentonite was found higher than that of BTEA-Bentonite. Thermodynamic parameters such as changes in the free energy (ΔG°), the enthalpy (ΔH°) and the entropy (ΔS°) were also evaluated. The overall adsorption process of Crystal violet onto the two organoclays were spontaneous, endothermic physisorption. The CTMA-bentonite and BTEA-Bentonite could be employed as low-cost alternatives to activated carbon in wastewater treatment for the removal of color which comes from textile dyes.
Abstract: Fine-grained data replication over the Internet allows duplication of frequently accessed data objects, as opposed to entire sites, to certain locations so as to improve the performance of largescale content distribution systems. In a distributed system, agents representing their sites try to maximize their own benefit since they are driven by different goals such as to minimize their communication costs, latency, etc. In this paper, we will use game theoretical techniques and in particular auctions to identify a bidding mechanism that encapsulates the selfishness of the agents, while having a controlling hand over them. In essence, the proposed game theory based mechanism is the study of what happens when independent agents act selfishly and how to control them to maximize the overall performance. A bidding mechanism asks how one can design systems so that agents- selfish behavior results in the desired system-wide goals. Experimental results reveal that this mechanism provides excellent solution quality, while maintaining fast execution time. The comparisons are recorded against some well known techniques such as greedy, branch and bound, game theoretical auctions and genetic algorithms.