Abstract: Suppose KY and KX are large sets of observed and
reference signals, respectively, each containing N signals. Is it possible to construct a filter F : KY → KX that requires a priori
information only on few signals, p N, from KX but performs better than the known filters based on a priori information on every
reference signal from KX? It is shown that the positive answer is
achievable under quite unrestrictive assumptions. The device behind
the proposed method is based on a special extension of the piecewise
linear interpolation technique to the case of random signal sets. The proposed technique provides a single filter to process any signal from
the arbitrarily large signal set. The filter is determined in terms of pseudo-inverse matrices so that it always exists.
Abstract: In this work the characteristics of spatial signal detec¬tion from an antenna array in various sample cases are investigated. Cases for a various number of available prior information about the received signal and the background noise are considered. The spatial difference between a signal and noise is only used. The performance characteristics and detecting curves are presented. All test-statistics are obtained on the basis of the generalized likelihood ratio (GLR). The received results are correct for a short and long sample.
Abstract: A synchronous network-on-chip using wormhole packet switching
and supporting guaranteed-completion best-effort with low-priority (LP)
and high-priority (HP) wormhole packet delivery service is presented in
this paper. Both our proposed LP and HP message services deliver a good
quality of service in term of lossless packet completion and in-order message
data delivery. However, the LP message service does not guarantee minimal
completion bound. The HP packets will absolutely use 100% bandwidth of
their reserved links if the HP packets are injected from the source node with
maximum injection. Hence, the service are suitable for small size messages
(less than hundred bytes). Otherwise the other HP and LP messages, which
require also the links, will experience relatively high latency depending on the
size of the HP message. The LP packets are routed using a minimal adaptive
routing, while the HP packets are routed using a non-minimal adaptive routing
algorithm. Therefore, an additional 3-bit field, identifying the packet type,
is introduced in their packet headers to classify and to determine the type
of service committed to the packet. Our NoC prototypes have been also
synthesized using a 180-nm CMOS standard-cell technology to evaluate the
cost of implementing the combination of both services.
Abstract: This paper considers inference under progressive type II censoring with a compound Rayleigh failure time distribution. The maximum likelihood (ML), and Bayes methods are used for estimating the unknown parameters as well as some lifetime parameters, namely reliability and hazard functions. We obtained Bayes estimators using the conjugate priors for two shape and scale parameters. When the two parameters are unknown, the closed-form expressions of the Bayes estimators cannot be obtained. We use Lindley.s approximation to compute the Bayes estimates. Another Bayes estimator has been obtained based on continuous-discrete joint prior for the unknown parameters. An example with the real data is discussed to illustrate the proposed method. Finally, we made comparisons between these estimators and the maximum likelihood estimators using a Monte Carlo simulation study.
Abstract: The environmental impact caused by industries is an issue that, in the last 20 years, has become very important in terms of society, economics and politics in Colombia. Particularly, the tannery process is extremely polluting because of uneffective treatments and regulations given to the dumping process and atmospheric emissions. Considering that, this investigation is intended to propose a management model based on the integration of Lean Supply Chain, Green Supply Chain, Cleaner Production and ISO 14001-2004, that prioritizes the strategic components of the organizations. As a result, a management model will be obtained and it will provide a strategic perspective through a systemic approach to the tanning process. This will be achieved through the use of Multicriteria Decision tools, along with Quality Function Deployment and Fuzzy Logic. The strategic approach that embraces the management model using the alignment of Lean Supply Chain, Green Supply Chain, Cleaner Production and ISO 14001-2004, is an integrated perspective that allows a gradual frame of the tactical and operative elements through the correct setting of the information flow, improving the decision making process. In that way, Small Medium Enterprises (SMEs) could improve their productivity, competitiveness and as an added value, the minimization of the environmental impact. This improvement is expected to be controlled through a Dashboard that helps the Organization measure its performance along the implementation of the model in its productive process.
Abstract: Unlike the best effort service provided by the internet
today, next-generation wireless networks will support real-time
applications. This paper proposes an adaptive early packet discard
(AEPD) policy to improve the performance of the real time TCP
traffic over ATM networks and avoid the fragmentation problem.
Three main aspects are incorporated in the proposed policy. First,
providing quality-of-service (QoS) guaranteed for real-time
applications by implementing a priority scheduling. Second,
resolving the partially corrupted packets problem by differentiating
the buffered cells of one packet from another. Third, adapting a
threshold dynamically using Fuzzy logic based on the traffic
behavior to maintain a high throughput under a variety of load
conditions. The simulation is run for two priority classes of the input
traffic: real time and non-real time classes. Simulation results show
that the proposed AEPD policy improves throughput and fairness
over that using static threshold under the same traffic conditions.
Abstract: Development of levels of service in municipal context
is a flexible vehicle to assist in performing quality-cost trade-off
analysis for municipal services. This trade-off depends on the
willingness of a community to pay as well as on the condition of the
assets. Community perspective of the performance of an asset from
service point of view may be quite different from the municipality
perspective of the performance of the same asset from condition
point of view. This paper presents a three phased level of service
based methodology for water mains that consists of :1)development
of an Analytical Hierarchy model of level of service 2) development
of Fuzzy Weighted Sum model of water main condition index and 3)
deriving a Fuzzy logic based function that maps level of service to
asset condition index. This mapping will assist asset managers in
quantifying condition improvement requirement to meet service
goals and to make more informed decisions on interventions and
relayed priorities.
Abstract: This study investigated possible ways to improve the
efficiency of the platinum precipitation process using ammonium
chloride by reducing the platinum content reporting to the effluent.
The ore treated consist of five platinum group metals namely,
ruthenium, rhodium, iridium, platinum, palladium and a precious
metal gold. Gold, ruthenium, rhodium and iridium were extracted
prior the platinum precipitation process. Temperature, reducing
agent, flow rate and potential difference were the variables controlled
to determine the operation conditions for optimum platinum
precipitation efficiency. Hydrogen peroxide was added as the
oxidizing agent at the temperature of 85-90oC and potential
difference of 700-850mV was the variable used to check the
oxidizing state of platinum. The platinum was further purified at
temperature between 60-65oC, potential difference above 700 mV,
ammonium chloride of 200 l, and at these conditions the platinum
content reporting to the effluent was reduced to less than 300ppm,
resulting in optimum platinum precipitation efficiency and purity of
99.9%.
Abstract: This paper presents an online method that learns the
corresponding points of an object from un-annotated grayscale images
containing instances of the object. In the first image being
processed, an ensemble of node points is automatically selected
which is matched in the subsequent images. A Bayesian posterior
distribution for the locations of the nodes in the images is formed.
The likelihood is formed from Gabor responses and the prior assumes
the mean shape of the node ensemble to be similar in a translation
and scale free space. An association model is applied for separating
the object nodes and background nodes. The posterior distribution is
sampled with Sequential Monte Carlo method. The matched object
nodes are inferred to be the corresponding points of the object
instances. The results show that our system matches the object nodes
as accurately as other methods that train the model with annotated
training images.
Abstract: The increasing divorce and fertility rates outside of marriage, the changing values in the last decades have led to a high prevalence of single parent families. Currently, worldwide, singleparent families represent about a quarter of all families. Recent changes occurring in the structure of single-parent families and also the multitude of factors that influence the quality of life of these families require the development of new research tools in order to provide foundations for social policies addressed to this type of family. The purpose of this paper is to present an analysis concerning the quality of life for single parent families in Romania, based on data collected through a research methodology developed by the authors within a scientific research project funded by a national grant called Partnerships in priority areas.
Abstract: In this paper a special kind of buffer management policy is studied where the packet are preempted even when sufficient space is available in the buffer for incoming packets. This is done to congestion for future incoming packets to improve QoS for certain type of packets. This type of study has been done in past for ATM type of scenario. We extend the same for heterogeneous traffic where data rate and size of the packets are very versatile in nature. Typical example of this scenario is the buffer management in Differentiated Service Router. There are two aspects that are of interest. First is the packet size: whether all packets have same or different sizes. Second aspect is the value or space priority of the packets, do all packets have the same space priority or different packets have different space priorities. We present two types of policies to achieve QoS goals for packets with different priorities: the push out scheme and the expelling scheme. For this work the scenario of packets of variable length is considered with two space priorities and main goal is to minimize the total weighted packet loss. Simulation and analytical studies show that, expelling policies can outperform the push out policies when it comes to offering variable QoS for packets of two different priorities and expelling policies also help improve the amount of admissible load. Some other comparisons of push out and expelling policies are also presented using simulations.
Abstract: It-s known that incorporating prior knowledge into support
vector regression (SVR) can help to improve the approximation
performance. Most of researches are concerned with the incorporation
of knowledge in form of numerical relationships. Little work,
however, has been done to incorporate the prior knowledge on the
structural relationships among the variables (referred as to Structural
Prior Knowledge, SPK). This paper explores the incorporation of SPK
in SVR by constructing appropriate admissible support vector kernel
(SV kernel) based on the properties of reproducing kernel (R.K).
Three-levels specifications of SPK are studies with the corresponding
sub-levels of prior knowledge that can be considered for the method.
These include Hierarchical SPK (HSPK), Interactional SPK (ISPK)
consisting of independence, global and local interaction, Functional
SPK (FSPK) composed of exterior-FSPK and interior-FSPK. A
convenient tool for describing the SPK, namely Description Matrix
of SPK is introduced. Subsequently, a new SVR, namely Motivated
Support Vector Regression (MSVR) whose structure is motivated
in part by SPK, is proposed. Synthetic examples show that it is
possible to incorporate a wide variety of SPK and helpful to improve
the approximation performance in complex cases. The benefits of
MSVR are finally shown on a real-life military application, Air-toground
battle simulation, which shows great potential for MSVR to
the complex military applications.
Abstract: The copper flotation tailings from Konkola Copper
mine in Nchanga, Zambia were used in the study. The purpose of this
study was to determine the leaching characteristics of the tailings
material prior and after the physical beneficiation process is
employed. The Knelson gravity concentrator (KC-MD3) was used for
the beneficiation process. The copper leaching efficiencies and
impurity co-extraction percentages in both the upgraded and the raw
feed material were determined at different pH levels and temperature.
It was observed that the copper extraction increased with an increase
in temperature and a decrease in pH levels. In comparison to the raw
feed sample, the upgraded sample reported a maximum copper
extraction of 69% which was 9%, higher than raw feed % extractions.
The impurity carry over was reduced from 18% to 4 % on the
upgraded sample. The reduction in impurity co-extraction was as a
result of the removal of the reactive gangue elements during the
upgrading process, this minimized the number of side reaction
occurring during leaching.
Abstract: School experiences, family bonding and self-concept
had always been a crucial factor in influencing all aspects of a
student-s development. The purpose of this study is to develop and to
validate a priori model of self-concept among students. The study
was tested empirically using Structural Equation Modeling (SEM)
and Confirmatory Factor Analysis (CFA) to validate the structural
model. To address these concerns, 1167 students were randomly
selected and utilized the Cognitive Psycho-Social University of
Malaya instrument (2009).Resulted demonstrated there is indirect
effect from family bonding to self-concept through school
experiences among secondary school students as a mediator. Besides
school experiences, there is a direct effect from family bonding to
self-concept and family bonding to school experiences among
students.
Abstract: The Neuro-Fuzzy hybridization scheme has become
of research interest in pattern classification over the past decade. The
present paper proposes a novel Modified Adaptive Fuzzy Inference
Engine (MAFIE) for pattern classification. A modified Apriori
algorithm technique is utilized to reduce a minimal set of decision
rules based on input output data sets. A TSK type fuzzy inference
system is constructed by the automatic generation of membership
functions and rules by the fuzzy c-means clustering and Apriori
algorithm technique, respectively. The generated adaptive fuzzy
inference engine is adjusted by the least-squares fit and a conjugate
gradient descent algorithm towards better performance with a
minimal set of rules. The proposed MAFIE is able to reduce the
number of rules which increases exponentially when more input
variables are involved. The performance of the proposed MAFIE is
compared with other existing applications of pattern classification
schemes using Fisher-s Iris and Wisconsin breast cancer data sets and
shown to be very competitive.
Abstract: This paper explores the scalability issues associated
with solving the Named Entity Recognition (NER) problem using
Support Vector Machines (SVM) and high-dimensional features. The
performance results of a set of experiments conducted using binary
and multi-class SVM with increasing training data sizes are
examined. The NER domain chosen for these experiments is the
biomedical publications domain, especially selected due to its
importance and inherent challenges. A simple machine learning
approach is used that eliminates prior language knowledge such as
part-of-speech or noun phrase tagging thereby allowing for its
applicability across languages. No domain-specific knowledge is
included. The accuracy measures achieved are comparable to those
obtained using more complex approaches, which constitutes a
motivation to investigate ways to improve the scalability of multiclass
SVM in order to make the solution more practical and useable.
Improving training time of multi-class SVM would make support
vector machines a more viable and practical machine learning
solution for real-world problems with large datasets. An initial
prototype results in great improvement of the training time at the
expense of memory requirements.
Abstract: The shortest path routing problem is a multiobjective nonlinear optimization problem with constraints. This problem has been addressed by considering Quality of service parameters, delay and cost objectives separately or as a weighted sum of both objectives. Multiobjective evolutionary algorithms can find multiple pareto-optimal solutions in one single run and this ability makes them attractive for solving problems with multiple and conflicting objectives. This paper uses an elitist multiobjective evolutionary algorithm based on the Non-dominated Sorting Genetic Algorithm (NSGA), for solving the dynamic shortest path routing problem in computer networks. A priority-based encoding scheme is proposed for population initialization. Elitism ensures that the best solution does not deteriorate in the next generations. Results for a sample test network have been presented to demonstrate the capabilities of the proposed approach to generate well-distributed pareto-optimal solutions of dynamic routing problem in one single run. The results obtained by NSGA are compared with single objective weighting factor method for which Genetic Algorithm (GA) was applied.
Abstract: For a long time as a result of accommodating car
traffic, planning ideologies in the past put a low priority on public
space, pedestrianism and the role of city space as a meeting place for
urban dwellers. In addition, according to authors such as Jan Gehl,
market forces and changing architectural perceptions began to shift
the focus of planning practice from the integration of public space in
various pockets around the contemporary city to individual buildings.
Eventually, these buildings have become increasingly more isolated
and introverted and have turned their backs to the realm of the public
space adjoining them. As a result of this practice, the traditional
function of public space as a social forum for city dwellers has in
many cases been reduced or even phased out. Author Jane Jacobs
published her seminal book “The Death and Life of Great American
Cities" more than fifty years ago, but her observations and
predictions at the time still ring true today, where she pointed out
how the dramatic increase in car traffic and its accommodation by the
urban planning ideology that was brought about by the Modern
movement has prompted a separation of the uses of the city. At the
same time it emphasizes free standing buildings that threaten urban
space and city life and result in underutilized and lifeless urban cores.
In this discussion context, the aim of this paper is to showcase a
reversal of just such a situation in the case of the Dasoupolis
neighborhood in Strovolos, Cyprus, where enlightened urban design
practice has see the reclamation of pedestrian space in a car
dominated area.
Abstract: This work has been conducted to study on comfort level of drivers of suspended cabin tractor semitrailer. Some drivers suffer from low back pain caused by vibration. The practical significance of applying suspended cabin type of tractor semi trailer was tested at different road conditions, different speed as well as different load conditions for comfortable driver seat interface (x, y, z ) and the process parameters have been prioritized using Taguchi-s L27 orthogonal array. Genetic Algorithm (GA) is used to optimize the human comfort vibration of suspended cabin tractor semitrailer drivers. The practical significance of applying GA to human comfort to reaction of suspended cabin tractor semitrailer has been validated by means of computing the deviation between predicted and experimentally obtained human comfort to vibration. The optimized acceleration data indicate a little uncomfortable ride for suspended cabin tractor semitrailer.
Abstract: Non-stationary trend in R-R interval series is
considered as a main factor that could highly influence the evaluation
of spectral analysis. It is suggested to remove trends in order to obtain
reliable results. In this study, three detrending methods, the
smoothness prior approach, the wavelet and the empirical mode
decomposition, were compared on artificial R-R interval series with
four types of simulated trends. The Lomb-Scargle periodogram was
used for spectral analysis of R-R interval series. Results indicated that
the wavelet method showed a better overall performance than the other
two methods, and more time-saving, too. Therefore it was selected for
spectral analysis of real R-R interval series of thirty-seven healthy
subjects. Significant decreases (19.94±5.87% in the low frequency
band and 18.97±5.78% in the ratio (p