Abstract: The paper deals with the estimation of amplitude and phase of an analogue multi-harmonic band-limited signal from irregularly spaced sampling values. To this end, assuming the signal fundamental frequency is known in advance (i.e., estimated at an independent stage), a complexity-reduced algorithm for signal reconstruction in time domain is proposed. The reduction in complexity is achieved owing to completely new analytical and summarized expressions that enable a quick estimation at a low numerical error. The proposed algorithm for the calculation of the unknown parameters requires O((2M+1)2) flops, while the straightforward solution of the obtained equations takes O((2M+1)3) flops (M is the number of the harmonic components). It is applied in signal reconstruction, spectral estimation, system identification, as well as in other important signal processing problems. The proposed method of processing can be used for precise RMS measurements (for power and energy) of a periodic signal based on the presented signal reconstruction. The paper investigates the errors related to the signal parameter estimation, and there is a computer simulation that demonstrates the accuracy of these algorithms.
Abstract: In this paper, two very different optimization
algorithms, Genetic and DIRECT algorithms, are used to history
match a bottomhole pressure response for a reservoir with wellbore
storage and skin with the best possible analytical model. No initial
guesses are available for reservoir parameters. The results show that
the matching process is much faster and more accurate for DIRECT
method in comparison with Genetic algorithm. It is furthermore
concluded that the DIRECT algorithm does not need any initial
guesses, whereas Genetic algorithm needs to be tuned according to
initial guesses.
Abstract: The technology usages of high speed Internet leads to
establish and start new era of online education. With the
advancement of the information technology and communication
systems new opportunities have been created. This leads universities
to have various online education channels to meet the demand of
different learners- needs. One of these channels is M-learning, which
can be used to improve the online education environment. With using
such mobile technology in learning both students and instructors can
easily access educational courses anytime from anywhere. The paper
first presents literature about mobile learning and to what extent this
approach can be utilized to enhance the overall learning system. It
provides a comparison between mobile learning and traditional elearning
showing the wide array of benefits of the new generation of
technology. The possible challenges and potential advantages of Mlearning
in the online education system are also discussed.
Abstract: This paper presents the modeling results of an
innovative system for the temperature control in the interior
compartment of a stationary automobile facing the solar energy from
the sun. A very thin layer of PCM inside a pouch placed in the
ceiling of the car in which the heating energy is absorbed and release
with melting and solidification of phase change materials. As a result
the temperature of the car interior is maintained in the comfort
condition. The amount of required PCM has been calculated to be
about 755 g. The PCM-temperature controlling system is simple and
has a potential to be implemented as a practical solution to prevent
undesirable heating of the automobile-s cabin.
Abstract: Trust management and Reputation models are
becoming integral part of Internet based applications such as CSCW,
E-commerce and Grid Computing. Also the trust dimension is a
significant social structure and key to social relations within a
collaborative community. Collaborative Decision Making (CDM) is
a difficult task in the context of distributed environment (information
across different geographical locations) and multidisciplinary
decisions are involved such as Virtual Organization (VO). To aid
team decision making in VO, Decision Support System and social
network analysis approaches are integrated. In such situations social
learning helps an organization in terms of relationship, team
formation, partner selection etc. In this paper we focus on trust
learning. Trust learning is an important activity in terms of
information exchange, negotiation, collaboration and trust
assessment for cooperation among virtual team members. In this
paper we have proposed a reinforcement learning which enhances the
trust decision making capability of interacting agents during
collaboration in problem solving activity. Trust computational model
with learning that we present is adapted for best alternate selection of
new project in the organization. We verify our model in a multi-agent
simulation where the agents in the community learn to identify
trustworthy members, inconsistent behavior and conflicting behavior
of agents.
Abstract: We have previously introduced an ultrasonic imaging
approach that combines harmonic-sensitive pulse sequences with a
post-beamforming quadratic kernel derived from a second-order
Volterra filter (SOVF). This approach is designed to produce images
with high sensitivity to nonlinear oscillations from microbubble
ultrasound contrast agents (UCA) while maintaining high levels of
noise rejection. In this paper, a two-step algorithm for computing the
coefficients of the quadratic kernel leading to reduction of tissue
component introduced by motion, maximizing the noise rejection and
increases the specificity while optimizing the sensitivity to the UCA
is presented. In the first step, quadratic kernels from individual
singular modes of the PI data matrix are compared in terms of their
ability of maximize the contrast to tissue ratio (CTR). In the second
step, quadratic kernels resulting in the highest CTR values are
convolved. The imaging results indicate that a signal processing
approach to this clinical challenge is feasible.
Abstract: A simple mobile engine-driven pneumatic paddy
collector made of locally available materials using local
manufacturing technology was designed, fabricated, and tested for
collecting and bagging of paddy dried on concrete pavement. The
pneumatic paddy collector had the following major components:
radial flat bladed type centrifugal fan, power transmission system,
bagging area, frame and the conveyance system. Results showed
significant differences on the collecting capacity, noise level, and fuel
consumption when rotational speed of the air mover shaft was varied.
Other parameters such as collecting efficiency, air velocity,
augmented cracked grain percentage, and germination rate were not
significantly affected by varying rotational speed of the air mover
shaft. The pneumatic paddy collector had a collecting efficiency of
99.33 % with a collecting capacity of 2685.00 kg/h at maximum
rotational speed of centrifugal fan shaft of about 4200 rpm. The
machine entailed an investment cost of P 62,829.25. The break-even
weight of paddy was 510,606.75 kg/yr at a collecting cost of 0.11
P/kg of paddy. Utilizing the machine for 400 hours per year
generated an income of P 23,887.73. The projected time needed to
recover cost of the machine based on 2685 kg/h collecting capacity
was 2.63 year.
Abstract: This paper discusses the designing of knowledge
integration of clinical information extracted from distributed medical
ontologies in order to ameliorate a machine learning-based multilabel
coding assignment system. The proposed approach is
implemented using a decision tree technique of the machine learning
on the university hospital data for patients with Coronary Heart
Disease (CHD). The preliminary results obtained show a satisfactory
finding that the use of medical ontologies improves the overall
system performance.
Abstract: Fungal infections are becoming more common and the
range of susceptible individuals has expanded. While Candida
albicans remains the most common infective species, other Candida
spp. are becoming increasingly significant. In a range of large-scale
studies of candidaemia between 1999 and 2006, about 52% of 9717
cases involved C. albicans, about 30% involved either C. glabrata or
C. parapsilosis and less than 15% involved C. tropicalis, C. krusei or
C. guilliermondii. However, the probability of mortality within 30
days of infection with a particular species was at least 40% for C.
tropicalis, C. albicans, C. glabrata and C. krusei and only 22% for
C. parapsilopsis. Clinical isolates of Candida spp. grew at rates
ranging from 1.65 h-1 to 4.9 h-1. Three species (C. krusei, C. albicans
and C. glabrata) had relatively high growth rates (μm > 4 h-1), C.
tropicalis and C. dubliniensis grew moderately quickly (Ôëê 3 h-1) and
C. parapsilosis and C. guilliermondii grew slowly (< 2 h-1). Based
on these data, the log of the odds of mortality within 30 days of
diagnosis was linearly related to μm. From this the underlying
probability of mortality is 0.13 (95% CI: 0.10-0.17) and it increases
by about 0.09 ± 0.02 for each unit increase in μm. Given that the
overall crude mortality is about 0.36, the growth of Candida spp.
approximately doubles the rate, consistent with the results of larger
case-matched studies of candidaemia.
Abstract: Finding effective ways of improving university quality assurance requires, as well, a retraining of the staff. This article illustrates an Online Programme of Excellence Model (OPEM), based on the European quality assurance model, for improving participants- formative programme standards. The results of applying this OPEM indicate the necessity of quality policies that support the evaluators- competencies to improve formative programmes. The study concludes by outlining how faculty and agency staff can use OPEM for the internal and external quality assurance of formative programmes.
Abstract: The main objective of this paper is to analyse the influence of preparation and control of orders on performance. The focused activities explored in this research are: procurement, production and distribution. These changes in performance were obtained through improvement of the supply chain. It is proved using all the company activities that it is possible to increase de efficiency and do services in an adequate way, placing the products in the market efficiently. For that, it was explored the importance of the supply chain, with privilege to the practical environment and the quantification of the obtained results.
Abstract: In this paper we present a method of abrupt cut detection with a novel logic of frames- comparison. Actual frame is compared with its motion estimated prediction instead of comparison with successive frame. Four different similarity metrics were employed to estimate the resemblance of compared frames. Obtained results were evaluated by standard used measures of test accuracy and compared with existing approach. Based on the results, we claim the proposed method is more effective and Pearson correlation coefficient obtained the best results among chosen similarity metrics.
Abstract: Information sharing and exchange, rather than
information processing, is what characterizes information
technology in the 21st century. Ontologies, as shared common
understanding, gain increasing attention, as they appear as the
most promising solution to enable information sharing both at
a semantic level and in a machine-processable way. Domain
Ontology-based modeling has been exploited to provide
shareability and information exchange among diversified,
heterogeneous applications of enterprises.
Contextual ontologies are “an explicit specification of
contextual conceptualization". That is: ontology is
characterized by concepts that have multiple representations
and they may exist in several contexts. Hence, contextual
ontologies are a set of concepts and relationships, which are
seen from different perspectives. Contextualization is to allow
for ontologies to be partitioned according to their contexts.
The need for contextual ontologies in enterprise modeling
has become crucial due to the nature of today's competitive
market. Information resources in enterprise is distributed and
diversified and is in need to be shared and communicated
locally through the intranet and globally though the internet.
This paper discusses the roles that ontologies play in an
enterprise modeling, and how ontologies assist in building a
conceptual model in order to provide communicative and
interoperable information systems. The issue of enterprise
modeling based on contextual domain ontology is also
investigated, and a framework is proposed for an enterprise
model that consists of various applications.
Abstract: This paper presents a experiment to estimate the
influences of cutting conditions in microstructure changes of
machining austenitic 304 stainless steel, especially for wear insert. The
wear insert were prefabricated with a width of 0.5 mm. And the forces,
temperature distribution, RS, and microstructure changes were
measured by force dynamometer, infrared thermal camera, X-ray
diffraction, XRD, SEM, respectively. The results told that the different
combinations of machining condition have a significant influence on
machined surface microstructure changes. In addition to that, the
ANOVA and AOMwere used to tell the different influences of cutting
speed, feed rate, and wear insert.
Abstract: The extraction of meaningful information from image
could be an alternative method for time series analysis. In this paper,
we propose a graphical analysis of time series grouped into table
with adjusted colour scale for numerical values. The advantages of
this method are also discussed. The proposed method is easy to
understand and is flexible to implement the standard methods of
pattern recognition and verification, especially for noisy
environmental data.
Abstract: This study examines the possibility to apply the theory of multidimensional accounting (momentum accounting) in a Brazilian Navy-s Services Provider Military Organization (Organização Militar Prestadora de Serviços - OMPS). In general, the core of the said theory is the fact that Accounting does not recognize the inertia of transactions occurring in an entity, and that occur repeatedly in some cases, regardless of the implementation of new actions by its managers. The study evaluates the possibility of greater use of information recorded in the financial statements of the unit of analysis, within the strategic decisions of the organization. As a research strategy, we adopted the case study. The results infer that it is possible to use the theory in the context of a multidimensional OMPS, promoting useful information for decision-making and thereby contributing to the strengthening of the necessary alignment of its administration with the current desires of the Brazilian society.
Abstract: Recent theorizations on the cognitive process of moral
judgment have focused on the role of intuitions and emotions, marking
a departure from previous emphasis on conscious, step-by-step
reasoning. My study investigated how being in a disgusted mood state
affects moral judgment.
Participants were induced to enter a disgusted mood state through
listening to disgusting sounds and reading disgusting descriptions.
Results shows that they, when compared to control who have not been
induced to feel disgust, are more likely to endorse actions that are
emotionally aversive but maximizes utilitarian return
The result is analyzed using the 'emotion-as-information' approach
to decision making. The result is consistent with the view that
emotions play an important role in determining moral judgment.
Abstract: The proposed system identifies the species of the wood
using the textural features present in its barks. Each species of a wood
has its own unique patterns in its bark, which enabled the proposed
system to identify it accurately. Automatic wood recognition system
has not yet been well established mainly due to lack of research in this
area and the difficulty in obtaining the wood database. In our work, a
wood recognition system has been designed based on pre-processing
techniques, feature extraction and by correlating the features of those
wood species for their classification. Texture classification is a problem
that has been studied and tested using different methods due to its
valuable usage in various pattern recognition problems, such as wood
recognition, rock classification. The most popular technique used
for the textural classification is Gray-level Co-occurrence Matrices
(GLCM). The features from the enhanced images are thus extracted
using the GLCM is correlated, which determines the classification
between the various wood species. The result thus obtained shows a
high rate of recognition accuracy proving that the techniques used in
suitable to be implemented for commercial purposes.
Abstract: High quality requirements analysis is one of the most
crucial activities to ensure the success of a software project, so that
requirements verification for software system becomes more and more
important in Requirements Engineering (RE) and it is one of the most
helpful strategies for improving the quality of software system.
Related works show that requirement elicitation and analysis can be
facilitated by ontological approaches and semantic web technologies.
In this paper, we proposed a hybrid method which aims to verify
requirements with structural and formal semantics to detect
interactions. The proposed method is twofold: one is for modeling
requirements with the semantic web language OWL, to construct a
semantic context; the other is a set of interaction detection rules which
are derived from scenario-based analysis and represented with
semantic web rule language (SWRL). SWRL based rules are working
with rule engines like Jess to reason in semantic context for
requirements thus to detect interactions. The benefits of the proposed
method lie in three aspects: the method (i) provides systematic steps
for modeling requirements with an ontological approach, (ii) offers
synergy of requirements elicitation and domain engineering for
knowledge sharing, and (3)the proposed rules can systematically assist
in requirements interaction detection.
Abstract: Work stress causes the organizational work-life
imbalance of employees. Because of this imbalance, workers perform
with lower effort to finish assignments and thus an organization will
experience reduced productivity. In order to investigate the problem
of an organizational work-life imbalance, this qualitative case study
focuses on an organizational work-life imbalance among Thai
software developers in a German-owned company in Chiang Mai,
Thailand. In terms of knowledge management, fishbone diagram is
useful analysis tool to investigate the root causes of an organizational
work-life imbalance systematically in focus-group discussions.
Furthermore, fishbone diagram shows the relationship between
causes and effects clearly. It was found that an organizational worklife
imbalance among Thai software developers is influenced by
management team, work environment, and information tools used in
the company over time.