Abstract: In many industries, control charts is one of the most
frequently used tools for quality management. Hotelling-s T2 is used
widely in multivariate control chart. However, it has little defect when
detecting small or medium process shifts. The use of supplementary
sensitizing rules can improve the performance of detection. This study
applied sensitizing rules for Hotelling-s T2 control chart to improve the
performance of detection. Support vector machines (SVM) classifier
to identify the characteristic or group of characteristics that are
responsible for the signal and to classify the magnitude of the mean
shifts. The experimental results demonstrate that the support vector
machines (SVM) classifier can effectively identify the characteristic
or group of characteristics that caused the process mean shifts and the
magnitude of the shifts.
Abstract: The threshold voltage and capacitance voltage characteristics of ultra-thin Silicon-on-Insulator MOSFET are greatly influenced by the thickness and doping concentration of the silicon film. In this work, the capacitance voltage characteristics and threshold voltage of the device have been analyzed with quantum mechanical effects using the Self-Consistent model. Reduction of channel thickness and adding doping impurities cause an increase in the threshold voltage. Moreover, the temperature effects cause a significant amount of threshold voltage shift. The temperature dependence of threshold voltage has also been observed with Self- Consistent approach which are well supported from experimental performance of practical devices.
Abstract: Residues are produced in all stages of human activities
in terms of composition and volume which vary according to
consumption practices and to production methods. Forms of
significant harm to the environment are associated to volume of
generated material as well as to improper disposal of solid wastes,
whose negative effects are noticed more frequently in the long term.
The solution to this problem constitutes a challenge to the
government, industry and society, because they involve economic,
social, environmental and, especially, awareness of the population in
general. The main concerns are focused on the impact it can have on
human health and on the environment (soil, water, air and sights).
The hazardous waste produced mainly by industry, are particularly
worrisome because, when improperly managed, they become a
serious threat to the environment. In view of this issue, this study
aimed to evaluate the management system of solid waste of a coprocessing
industrial waste company, to propose improvements to the
rejects generation management in a specific step of the Blending
production process.
Abstract: SoftBoost is a recently presented boosting algorithm,
which trades off the size of achieved classification margin and
generalization performance. This paper presents a performance
evaluation of SoftBoost algorithm on the generic object recognition
problem. An appearance-based generic object recognition
model is used. The evaluation experiments are performed using
a difficult object recognition benchmark. An assessment with respect
to different degrees of label noise as well as a comparison to
the well known AdaBoost algorithm is performed. The obtained
results reveal that SoftBoost is encouraged to be used in cases
when the training data is known to have a high degree of noise.
Otherwise, using Adaboost can achieve better performance.
Abstract: Nowadays, people are going more and more mobile, both in terms of devices and associated applications. Moreover, services that these devices are offering are getting wider and much more complex. Even though actual handheld devices have considerable computing power, their contexts of utilization are different. These contexts are affected by the availability of connection, high latency of wireless networks, battery life, size of the screen, on-screen or hard keyboard, etc. Consequently, development of mobile applications and their associated mobile Web services, if any, should follow a concise methodology so they will provide a high Quality of Service. The aim of this paper is to highlight and discuss main issues to consider when developing mobile applications and mobile Web services and then propose a framework that leads developers through different steps and modules toward development of efficient and secure mobile applications. First, different challenges in developing such applications are elicited and deeply discussed. Second, a development framework is presented with different modules addressing each of these challenges. Third, the paper presents an example of a mobile application, Eivom Cinema Guide, which benefits from following our development framework.
Abstract: This paper presents a formant-tracking linear prediction
(FTLP) model for speech processing in noise. The main focus of this
work is the detection of formant trajectory based on Hidden Markov
Models (HMM), for improved formant estimation in noise. The
approach proposed in this paper provides a systematic framework for
modelling and utilization of a time- sequence of peaks which satisfies
continuity constraints on parameter; the within peaks are modelled
by the LP parameters. The formant tracking LP model estimation
is composed of three stages: (1) a pre-cleaning multi-band spectral
subtraction stage to reduce the effect of residue noise on formants
(2) estimation stage where an initial estimate of the LP model of
speech for each frame is obtained (3) a formant classification using
probability models of formants and Viterbi-decoders. The evaluation
results for the estimation of the formant tracking LP model tested
in Gaussian white noise background, demonstrate that the proposed
combination of the initial noise reduction stage with formant tracking
and LPC variable order analysis, results in a significant reduction in
errors and distortions. The performance was evaluated with noisy
natual vowels extracted from international french and English vocabulary
speech signals at SNR value of 10dB. In each case, the
estimated formants are compared to reference formants.
Abstract: This paper presents a design and prototype
implementation of new home automation system that uses WiFi
technology as a network infrastructure connecting its parts. The
proposed system consists of two main components; the first part is
the server (web server), which presents system core that manages,
controls, and monitors users- home. Users and system administrator
can locally (LAN) or remotely (internet) manage and control system
code. Second part is hardware interface module, which provides
appropriate interface to sensors and actuator of home automation
system. Unlike most of available home automation system in the
market the proposed system is scalable that one server can manage
many hardware interface modules as long as it exists on WiFi
network coverage. System supports a wide range of home
automation devices like power management components, and
security components. The proposed system is better from the
scalability and flexibility point of view than the commercially
available home automation systems.
Abstract: This paper introduces and studies new indexing techniques for content-based queries in images databases. Indexing is the key to providing sophisticated, accurate and fast searches for queries in image data. This research describes a new indexing approach, which depends on linear modeling of signals, using bases for modeling. A basis is a set of chosen images, and modeling an image is a least-squares approximation of the image as a linear combination of the basis images. The coefficients of the basis images are taken together to serve as index for that image. The paper describes the implementation of the indexing scheme, and presents the findings of our extensive evaluation that was conducted to optimize (1) the choice of the basis matrix (B), and (2) the size of the index A (N). Furthermore, we compare the performance of our indexing scheme with other schemes. Our results show that our scheme has significantly higher performance.
Abstract: Air emissions from waste treatment plants often
consist of a combination of Volatile Organic Compounds (VOCs)
and odors. Hydrogen sulfide is one of the major odorous gases
present in the waste emissions coming from municipal wastewater
treatment facilities. Hydrogen sulfide (H2S) is odorous, highly toxic
and flammable. Exposure to lower concentrations can result in eye
irritation, a sore throat and cough, shortness of breath, and fluid in
the lungs. Biofiltration has become a widely accepted technology for
treating air streams containing H2S. When compared with other nonbiological
technologies, biofilter is more cost-effective for treating large
volumes of air containing low concentrations of biodegradable compounds.
Optimization of biofilter media is essential for many reasons such as:
providing a higher surface area for biofilm growth, low pressure drop,
physical stability, and good moisture retention. In this work, a novel
biofilter media is developed and tested at a pumping station of a
municipality located in the United Arab Emirates (UAE). The
media is found to be very effective (>99%) in removing H2S
concentrations that are expected in pumping stations under steady
state and shock loading conditions.
Abstract: Society has grown to rely on Internet services, and the
number of Internet users increases every day. As more and more
users become connected to the network, the window of opportunity
for malicious users to do their damage becomes very great and
lucrative. The objective of this paper is to incorporate different
techniques into classier system to detect and classify intrusion from
normal network packet. Among several techniques, Steady State
Genetic-based Machine Leaning Algorithm (SSGBML) will be used
to detect intrusions. Where Steady State Genetic Algorithm (SSGA),
Simple Genetic Algorithm (SGA), Modified Genetic Algorithm and
Zeroth Level Classifier system are investigated in this research.
SSGA is used as a discovery mechanism instead of SGA. SGA
replaces all old rules with new produced rule preventing old good
rules from participating in the next rule generation. Zeroth Level
Classifier System is used to play the role of detector by matching
incoming environment message with classifiers to determine whether
the current message is normal or intrusion and receiving feedback
from environment. Finally, in order to attain the best results,
Modified SSGA will enhance our discovery engine by using Fuzzy
Logic to optimize crossover and mutation probability. The
experiments and evaluations of the proposed method were performed
with the KDD 99 intrusion detection dataset.
Abstract: In this paper we consider the issue of distributed adaptive estimation over sensor networks. To deal with more realistic scenario, different variance for observation noise is assumed for sensors in the network. To solve the problem of different variance of observation noise, the proposed method is divided into two phases: I) Estimating each sensor-s observation noise variance and II) using the estimated variances to obtain the desired parameter. Our proposed algorithm is based on a diffusion least mean square (LMS) implementation with linear combiner model. In the proposed algorithm, the step-size parameter the coefficients of linear combiner are adjusted according to estimated observation noise variances. As the simulation results show, the proposed algorithm considerably improves the diffusion LMS algorithm given in literature.
Abstract: This study was conducted to investigate the incidence
of pathogenic bacteria: Salmonella, Shigella, Escherichia coli O157
and Staphylococcus aureus in cakes and tarts collected from thirtyfive
confectionery producing and selling premises located within
Tripoli city, Libya. The results revealed an incidence of S. aureus
with 94.4 and 48.0 %, E. coli O157 with 14.7 and 4.0 % and Salmonella
sp. with 5.9 and 8.0 % in cakes and tarts samples respectively;
while Shigella was not detected in all samples. In order to determine
the source of these pathogenic bacteria, cotton swabs were taken
from the hands of workers on the production line, the surfaces of
preparation tables and cream whipping instruments. The results
showed that the cotton swabs obtained from the hands of workers
contained S. aureus and Salmonella sp. with an incidence of 42.9 and
2.9 %, the cotton swabs obtained from the surfaces of preparation
tables 22.9 and 2.9 % and the cotton swabs obtained from the cream
whipping instruments 14.3 and 0.0 % respectively; while E. coli
O157 and Shigella sp. were not detected in all swabs. Additionally,
other bacteria were isolated from the hands of workers and the Surfaces
of producing equipments included: Aeromonas sp., Pseudomonas
sp., E. coli, Klebsiella sp., Enterobacter sp., Citrobacter sp.,
Proteus sp., Serratia sp. and Acinetobacter sp. These results indicate
that some of the cakes and tarts might pose threat to consumer's
health. Meanwhile, occurrences of pathogenic bacteria on the hands
of those who are working in production line and the surfaces of
equipments reflect poor hygienic practices at most confectionery
premises examined in this study. Thus, firm and continuous surveillance
of these premises is needed to insure the consumer's health and
safety.
Abstract: Underpricing is one anomaly in initial public offerings
(IPO) literature that has been widely observed across different stock
markets with different trends emerging over different time periods.
This study seeks to determine how IPOs on the JSE performed on the
first day, first week and first month over the period of 1996-2011.
Underpricing trends are documented for both hot and cold market
periods in terms of four main sectors (cyclical, defensive, growth
stock and interest rate sensitive stocks). Using a sample of 360 listed
companies on the JSE, the empirical findings established that IPOs
on the JSE are significantly underpriced with an average market
adjusted first day return of 62.9%. It is also established that hot
market IPOs on the JSE are more underpriced than the cold market
IPOs. Also observed is the fact that as the offer price per share
increases above the median price for any given period, the level of
underpricing decreases substantially. While significant differences
exist in the level of underpricing of IPOs in the four different sectors
in the hot and cold market periods, interest rates sensitive stocks
showed a different trend from the other sectors and thus require
further investigation to uncover this pattern.
Abstract: Khao Yai National Park is the First National Park in
Thailand and approximately 800,000 tourists visited Khao Yai yearly.
This study aimed to identify the perception of tourists in Khao Yai
National Park according to the implementation of eco-friendly
cleansers along their leisure in the campsites. Due to tourist’s
activities in the park were affected on quality of environment;
especially on water resource. Therefore, eco-friendly cleansers were
used in campsites for tourists and restaurants during high tourist
season. The results indicated positive effects of environmental
friendly cleansers on water quality in Lam Ta Khong River, as well
as the tourist’s perception on eco-friendly cleansers.
Abstract: This is a survey research using quantitative and qualitative methodology. There were three objectives: 1) To study participatory level of community in water and waste environment management. 2) To study the affecting factors for community participation in water and waste environment management in Ampawa District, Samut Songkram Province. 3) To search for the participatory patterns in water and waste management. The population sample for the quantitative research was 1,364 people living in Ampawa District. The methodology was simple random sampling. Research instrument was a questionnaire and the qualitative research used purposive sampling in 6 Sub Districts which are Ta Ka, Suanluang, Bangkae, Muangmai, Kwae-om, and Bangnanglee Sub District Administration Organization. Total population is 63. For data analysis, the study used content analysis from quantitative research to synthesize and build question frame from the content for interview and conducting focus group interview. The study found that the community participatory in the issue of level in water and waste management are moderate of planning, operation, and evaluation. The issue of being beneficial is at low level. Therefore, the overall participatory level of community in water and waste environment management is at a medium level. The factors affecting the participatory of community in water and waste management are age, the period dwelling in the community and membership in which the mean difference is statistic significant at 0.05 in area of operation, being beneficial, and evaluation. For patterns of community participation, there is the correlation with water and waste management in 4 concerns which are 1) Participation in planning 2) Participation in operation 3) Participation in being beneficial both directly and indirectly benefited 4) Participation in evaluation and monitoring. The recommendation from this study is the need to create conscious awareness in order to increase participation level of people by organizing activities that promote participation with volunteer spirit. Government should open opportunities for people to participate in sharing ideas and create the culture of living together with equality which would build more concrete participation.
Abstract: The Multi-Layered Perceptron (MLP) Neural
networks have been very successful in a number of signal processing
applications. In this work we have studied the possibilities and the
met difficulties in the application of the MLP neural networks for the
prediction of daily solar radiation data. We have used the Polack-Ribière algorithm for training the neural networks. A comparison, in
term of the statistical indicators, with a linear model most used in
literature, is also performed, and the obtained results show that the
neural networks are more efficient and gave the best results.
Abstract: This paper presents the study of parameters affecting
the environment protection in the printing industry. The paper has
also compared LCA studies performed within the printing industry in
order to identify common practices, limitations, areas for
improvement, and opportunities for standardization. This comparison
is focused on the data sources and methodologies used in the printing
pollutants register. The presented concepts, methodology and results
represent the contribution to the sustainable development
management. Furthermore, the paper analyzes the result of the
quantitative identification of hazardous substances emitted in printing
industry of Novi Sad.
Abstract: The present paper presents a finite element model and
analysis for the interaction between a piezoresistive tactile sensor and
biological tissues. The tactile sensor is proposed for use in minimally
invasive surgery to deliver tactile information of biological tissues to
surgeons. The proposed sensor measures the relative hardness of soft
contact objects as well as the contact force. Silicone rubbers were
used as the phantom of biological tissues. Finite element analysis of
the silicone rubbers and the mechanical structure of the sensor were
performed using COMSOL Multiphysics (v3.4) environment. The
simulation results verify the capability of the sensor to be used to
differentiate between different kinds of silicone rubber materials.
Abstract: Complexity, as a theoretical background has made it
easier to understand and explain the features and dynamic behavior
of various complex systems. As the common theoretical background
has confirmed, borrowing the terminology for design from the
natural sciences has helped to control and understand urban
complexity. Phenomena like self-organization, evolution and
adaptation are appropriate to describe the formerly inaccessible
characteristics of the complex environment in unpredictable bottomup
systems. Increased computing capacity has been a key element in
capturing the chaotic nature of these systems.
A paradigm shift in urban planning and architectural design has
forced us to give up the illusion of total control in urban
environment, and consequently to seek for novel methods for
steering the development. New methods using dynamic modeling
have offered a real option for more thorough understanding of
complexity and urban processes. At best new approaches may renew
the design processes so that we get a better grip on the complex
world via more flexible processes, support urban environmental
diversity and respond to our needs beyond basic welfare by liberating
ourselves from the standardized minimalism.
A complex system and its features are as such beyond human
ethics. Self-organization or evolution is either good or bad. Their
mechanisms are by nature devoid of reason. They are common in
urban dynamics in both natural processes and gas. They are features
of a complex system, and they cannot be prevented. Yet their
dynamics can be studied and supported.
The paradigm of complexity and new design approaches has been
criticized for a lack of humanity and morality, but the ethical
implications of scientific or computational design processes have not
been much discussed. It is important to distinguish the (unexciting)
ethics of the theory and tools from the ethics of computer aided
processes based on ethical decisions. Urban planning and architecture
cannot be based on the survival of the fittest; however, the natural
dynamics of the system cannot be impeded on grounds of being
“non-human".
In this paper the ethical challenges of using the dynamic models
are contemplated in light of a few examples of new architecture and
dynamic urban models and literature. It is suggested that ethical
challenges in computational design processes could be reframed
under the concepts of responsibility and transparency.
Abstract: The segmentation of endovascular tools in fluoroscopy images can be accurately performed automatically or by minimum user intervention, using known modern techniques. It has been proven in literature, but no clinical implementation exists so far because the computational time requirements of such technology have not yet been met. A classical segmentation scheme is composed of edge enhancement filtering, line detection, and segmentation. A new method is presented that consists of a vector that propagates in the image to track an edge as it advances. The filtering is performed progressively in the projected path of the vector, whose orientation allows for oriented edge detection, and a minimal image area is globally filtered. Such an algorithm is rapidly computed and can be implemented in real-time applications. It was tested on medical fluoroscopy images from an endovascular cerebral intervention. Ex- periments showed that the 2D tracking was limited to guidewires without intersection crosspoints, while the 3D implementation was able to cope with such planar difficulties.