Abstract: Studies in neuroscience suggest that both global and
local feature information are crucial for perception and recognition of
faces. It is widely believed that local feature is less sensitive to
variations caused by illumination, expression and illumination. In
this paper, we target at designing and learning local features for face
recognition. We designed three types of local features. They are
semi-global feature, local patch feature and tangent shape feature.
The designing of semi-global feature aims at taking advantage of
global-like feature and meanwhile avoiding suppressing AdaBoost
algorithm in boosting weak classifies established from small local
patches. The designing of local patch feature targets at automatically
selecting discriminative features, and is thus different with traditional
ways, in which local patches are usually selected manually to cover
the salient facial components. Also, shape feature is considered in
this paper for frontal view face recognition. These features are
selected and combined under the framework of boosting algorithm
and cascade structure. The experimental results demonstrate that the
proposed approach outperforms the standard eigenface method and
Bayesian method. Moreover, the selected local features and
observations in the experiments are enlightening to researches in
local feature design in face recognition.
Abstract: Quality control charts indicate out of control
conditions if any nonrandom pattern of the points is observed or any
point is plotted beyond the control limits. Nonrandom patterns of
Shewhart control charts are tested with sensitizing rules. When the
processes are defined with fuzzy set theory, traditional sensitizing
rules are insufficient for defining all out of control conditions. This is
due to the fact that fuzzy numbers increase the number of out of
control conditions. The purpose of the study is to develop a set of
fuzzy sensitizing rules, which increase the flexibility and sensitivity
of fuzzy control charts. Fuzzy sensitizing rules simplify the
identification of out of control situations that results in a decrease in
the calculation time and number of evaluations in fuzzy control chart
approach.
Abstract: All practical real-time scheduling algorithms in multiprocessor systems present a trade-off between their computational complexity and performance. In real-time systems, tasks have to be performed correctly and timely. Finding minimal schedule in multiprocessor systems with real-time constraints is shown to be NP-hard. Although some optimal algorithms have been employed in uni-processor systems, they fail when they are applied in multiprocessor systems. The practical scheduling algorithms in real-time systems have not deterministic response time. Deterministic timing behavior is an important parameter for system robustness analysis. The intrinsic uncertainty in dynamic real-time systems increases the difficulties of scheduling problem. To alleviate these difficulties, we have proposed a fuzzy scheduling approach to arrange real-time periodic and non-periodic tasks in multiprocessor systems. Static and dynamic optimal scheduling algorithms fail with non-critical overload. In contrast, our approach balances task loads of the processors successfully while consider starvation prevention and fairness which cause higher priority tasks have higher running probability. A simulation is conducted to evaluate the performance of the proposed approach. Experimental results have shown that the proposed fuzzy scheduler creates feasible schedules for homogeneous and heterogeneous tasks. It also and considers tasks priorities which cause higher system utilization and lowers deadline miss time. According to the results, it performs very close to optimal schedule of uni-processor systems.
Abstract: Today we tend to go back to the past to our root
relation to nature. Therefore in search of friendly spaces there are
elements of natural environment introduced as elements of spatial
composition. Though reinvented through the use of the new
substance such as greenery, water etc. made possible by state of the
art technologies, still, in principal, they remain the same. As a result,
sustainable design, based upon the recognized means of composition
in addition to the relation of architecture and urbanism vs. nature
introduces a new aesthetical values into architectural and urban
space.
Abstract: This paper presents a novel two-phase hybrid optimization algorithm with hybrid genetic operators to solve the optimal control problem of a single stage hybrid manufacturing system. The proposed hybrid real coded genetic algorithm (HRCGA) is developed in such a way that a simple real coded GA acts as a base level search, which makes a quick decision to direct the search towards the optimal region, and a local search method is next employed to do fine tuning. The hybrid genetic operators involved in the proposed algorithm improve both the quality of the solution and convergence speed. The phase–1 uses conventional real coded genetic algorithm (RCGA), while optimisation by direct search and systematic reduction of the size of search region is employed in the phase – 2. A typical numerical example of an optimal control problem with the number of jobs varying from 10 to 50 is included to illustrate the efficacy of the proposed algorithm. Several statistical analyses are done to compare the validity of the proposed algorithm with the conventional RCGA and PSO techniques. Hypothesis t – test and analysis of variance (ANOVA) test are also carried out to validate the effectiveness of the proposed algorithm. The results clearly demonstrate that the proposed algorithm not only improves the quality but also is more efficient in converging to the optimal value faster. They can outperform the conventional real coded GA (RCGA) and the efficient particle swarm optimisation (PSO) algorithm in quality of the optimal solution and also in terms of convergence to the actual optimum value.
Abstract: C-control chart assumes that process nonconformities follow a Poisson distribution. In actuality, however, this Poisson distribution does not always occur. A process control for semiconductor based on a Poisson distribution always underestimates the true average amount of nonconformities and the process variance. Quality is described more accurately if a compound Poisson process is used for process control at this time. A cumulative sum (CUSUM) control chart is much better than a C control chart when a small shift will be detected. This study calculates one-sided CUSUM ARLs using a Markov chain approach to construct a CUSUM control chart with an underlying Poisson-Gamma compound distribution for the failure mechanism. Moreover, an actual data set from a wafer plant is used to demonstrate the operation of the proposed model. The results show that a CUSUM control chart realizes significantly better performance than EWMA.
Abstract: Control chart pattern recognition is one of the most important tools to identify the process state in statistical process control. The abnormal process state could be classified by the recognition of unnatural patterns that arise from assignable causes. In this study, a wavelet based neural network approach is proposed for the recognition of control chart patterns that have various characteristics. The procedure of proposed control chart pattern recognizer comprises three stages. First, multi-resolution wavelet analysis is used to generate time-shape and time-frequency coefficients that have detail information about the patterns. Second, distance based features are extracted by a bi-directional Kohonen network to make reduced and robust information. Third, a back-propagation network classifier is trained by these features. The accuracy of the proposed method is shown by the performance evaluation with numerical results.
Abstract: The two-stage compensator designs of linear system are
investigated in the framework of the factorization approach. First, we
give “full feedback" two-stage compensator design. Based on this
result, various types of the two-stage compensator designs with partial
feedbacks are derived.
Abstract: In this paper an effective approach for segmenting
human skin regions in images taken at different environment is
proposed. The proposed method uses a color distance map that is
flexible enough to reliably detect the skin regions even if the
illumination conditions of the image vary. Local image conditions is
also focused, which help the technique to adaptively detect differently
illuminated skin regions of an image. Moreover, usage of local
information also helps the skin detection process to get rid of picking
up much noisy pixels.
Abstract: Versatile dual-mode class-AB CMOS four-quadrant
analog multiplier circuit is presented. The dual translinear loops and
current mirrors are the basic building blocks in realization scheme.
This technique provides; wide dynamic range, wide-bandwidth response
and low power consumption. The major advantages of this
approach are; its has single ended inputs; since its input is dual translinear
loop operate in class-AB mode which make this multiplier
configuration interesting for low-power applications; current multiplying,
voltage multiplying, or current and voltage multiplying can
be obtainable with balanced input. The simulation results of versatile
analog multiplier demonstrate a linearity error of 1.2 %, a -3dB bandwidth
of about 19MHz, a maximum power consumption of 0.46mW,
and temperature compensated. Operation of versatile analog multiplier
was also confirmed through an experiment using CMOS transistor
array.
Abstract: Web usage mining has become a popular research
area, as a huge amount of data is available online. These data can be
used for several purposes, such as web personalization, web structure
enhancement, web navigation prediction etc. However, the raw log
files are not directly usable; they have to be preprocessed in order to
transform them into a suitable format for different data mining tasks.
One of the key issues in the preprocessing phase is to identify web
users. Identifying users based on web log files is not a
straightforward problem, thus various methods have been developed.
There are several difficulties that have to be overcome, such as client
side caching, changing and shared IP addresses and so on. This paper
presents three different methods for identifying web users. Two of
them are the most commonly used methods in web log mining
systems, whereas the third on is our novel approach that uses a
complex cookie-based method to identify web users. Furthermore we
also take steps towards identifying the individuals behind the
impersonal web users. To demonstrate the efficiency of the new
method we developed an implementation called Web Activity
Tracking (WAT) system that aims at a more precise distinction of
web users based on log data. We present some statistical analysis
created by the WAT on real data about the behavior of the Hungarian
web users and a comprehensive analysis and comparison of the three
methods
Abstract: Innovation, technology and knowledge are the trilogy
of impact to support the challenges arising from uncertainty.
Evidence showed an opportunity to ask how to manage in this
environment under constant innovation. In an attempt to get a
response from the field of Management Sciences, based in the
Contingency Theory, a research was conducted, with
phenomenological and descriptive approaches, using the Case Study
Method and the usual procedures for this task involving a focus
group composed of managers and employees working in the
pharmaceutical field. The problem situation was raised; the state of
the art was interpreted and dissected the facts. In this tasks were
involved four establishments. The result indicates that these focused
ventures have been managed by its founder empirically and is
experimenting agility described in this work. The expectation of this
study is to improve concepts for stakeholders on creativity in
business.
Abstract: In this article, we propose an Intelligent Medical
Diagnostic System (IMDS) accessible through common
web-based interface, to on-line perform initial screening for
osteoporosis. The fundamental approaches which construct the
proposed system are mainly based on the fuzzy-neural theory,
which can exhibit superiority over other conventional technologies
in many fields. In diagnosis process, users simply answer
a series of directed questions to the system, and then they
will immediately receive a list of results which represents the
risk degrees of osteoporosis. According to clinical testing results,
it is shown that the proposed system can provide the general
public or even health care providers with a convenient, reliable,
inexpensive approach to osteoporosis risk assessment.
Abstract: Researchers of drug-drug interaction alert systems
have often suggested that there were high overridden rate for alerts and
also too false alerts. However, research about decreasing false alerts is
scant. Therefore, the aim of this article attempts to proactive
identification of false alert for drug-drug interaction and provide
solution to decrease false alerts. This research involved retrospective
analysis prescribing database and calculated false alert rate by using
MYSQL and JAVA. Results of this study showed 17% of false alerts
and the false alert rate in the hospitals (37%) was more than in the
clinics. To conclude, this study described the importance that
drug-drug interaction alert system should not only detect drug name
but also detect frequency or route, as well as in providing solution to
decrease false alerts.
Abstract: Parsing is important in Linguistics and Natural
Language Processing to understand the syntax and semantics of a
natural language grammar. Parsing natural language text is
challenging because of the problems like ambiguity and inefficiency.
Also the interpretation of natural language text depends on context
based techniques. A probabilistic component is essential to resolve
ambiguity in both syntax and semantics thereby increasing accuracy
and efficiency of the parser. Tamil language has some inherent
features which are more challenging. In order to obtain the solutions,
lexicalized and statistical approach is to be applied in the parsing
with the aid of a language model. Statistical models mainly focus on
semantics of the language which are suitable for large vocabulary
tasks where as structural methods focus on syntax which models
small vocabulary tasks. A statistical language model based on Trigram
for Tamil language with medium vocabulary of 5000 words has
been built. Though statistical parsing gives better performance
through tri-gram probabilities and large vocabulary size, it has some
disadvantages like focus on semantics rather than syntax, lack of
support in free ordering of words and long term relationship. To
overcome the disadvantages a structural component is to be
incorporated in statistical language models which leads to the
implementation of hybrid language models. This paper has attempted
to build phrase structured hybrid language model which resolves
above mentioned disadvantages. In the development of hybrid
language model, new part of speech tag set for Tamil language has
been developed with more than 500 tags which have the wider
coverage. A phrase structured Treebank has been developed with 326
Tamil sentences which covers more than 5000 words. A hybrid
language model has been trained with the phrase structured Treebank
using immediate head parsing technique. Lexicalized and statistical
parser which employs this hybrid language model and immediate
head parsing technique gives better results than pure grammar and
trigram based model.
Abstract: The study explored the question of who am I? As a (re)construction of cultural identity by delving into globalization, communication, and social change in Malta during a historical moment when Malta became a European Union Member State. Three objectives guided this qualitative study. Firstly the study reviewed European Union (EU) policies that regulate broadcasting and their implementation in Member States, whilst meeting the challenges of globalization and new media technology. Secondly the research investigated the changes of the media landscape via organizational structures, programs and television (TV) content. Finally the study explored the impact of these transformations taking place in the way Maltese live as they (re)construct their cultural identity. Despite the choices available to the Maltese audience, old local traditions and new foreign customs coexist as informants continue to (re)construct their cultural identity and define who they are.
Abstract: This paper provides an analysis of corporate income
tax (CIT) incentives in the Western Balkan countries: Slovenia,
Croatia, Serbia, Montenegro, Macedonia and Albania. Western
Balkan countries, as other transition and developing countries, use
large number of the corporate income tax incentives (CIT) to attract
foreign investments and to stimulate economic activity. The main
goal of this paper is to investigate how often these countries use CIT
incentives and provide review of existing tax incentives in Western
Balkan countries. Paper will focus on reduced CIT rates, tax
holidays, and other investment incentives which imply incentives
like accelerated depreciation, tax allowances and tax credits.
Abstract: Proactive coping directed at an upcoming as opposed
to an ongoing stressor, is a new focus in positive psychology. The
present study explored the proactive coping-s effect on the workplace
adaptation after transition from college to workplace. In order to
demonstrate the influence process between them, we constructed the
model of proactive coping style effecting the actual positive coping
efforts and outcomes by mediating proactive competence during one
year after the transition. Participants (n = 100) started to work right
after graduating from college completed all the four time-s surveys
--one month before (Time 0), one month after (Time 1), three months
after (Time 2), and one year after (Time 3) the transition. Time 0
survey included the measurement of proactive coping style and
competence. Time 1, 2, 3 surveys included the measurement of the
challenge cognitive appraisal, problem solving coping strategy, and
subjective workplace adaptation. The result indicated that proactive
coping style effected newcomers- actual coping efforts and outcomes
by mediating proactive coping competence. The result also showed
that proactive coping competence directly promoted Time1-s actual
positive coping efforts and outcomes, and indirectly promoted Time
2-s and Time 3-s.
Abstract: This paper presents a new approach for image
segmentation by applying Pillar-Kmeans algorithm. This
segmentation process includes a new mechanism for clustering the
elements of high-resolution images in order to improve precision and
reduce computation time. The system applies K-means clustering to
the image segmentation after optimized by Pillar Algorithm. The
Pillar algorithm considers the pillars- placement which should be
located as far as possible from each other to withstand against the
pressure distribution of a roof, as identical to the number of centroids
amongst the data distribution. This algorithm is able to optimize the
K-means clustering for image segmentation in aspects of precision
and computation time. It designates the initial centroids- positions
by calculating the accumulated distance metric between each data
point and all previous centroids, and then selects data points which
have the maximum distance as new initial centroids. This algorithm
distributes all initial centroids according to the maximum
accumulated distance metric. This paper evaluates the proposed
approach for image segmentation by comparing with K-means and
Gaussian Mixture Model algorithm and involving RGB, HSV, HSL
and CIELAB color spaces. The experimental results clarify the
effectiveness of our approach to improve the segmentation quality in
aspects of precision and computational time.
Abstract: Financial literacy is one of the key factors needed in making informed financial decisions. As businesses continue to be more profit driven, more financial and economic intrigues arise that continue to put individuals at the risk of spending more and more without considering the short term and long term effects. We conducted a study to assess financial literacy and financial decision making among Emiratis. Our results show that financial literacy is lacking among Emiratis. Also, almost half of respondents owe loans to other peoples and 1/5 of them have bank loans. We expect that the outcome of this research will be useful for designing educational programs and policies to promote financial planning and security among Emiratis. We also posit that deeper and more informed understanding of this problem is a precursor for developing effective financial education programs with the aim of improving financial decision- making among Emiratis.