Abstract: Knowledge Discovery in Databases (KDD) has
evolved into an important and active area of research because of
theoretical challenges and practical applications associated with the
problem of discovering (or extracting) interesting and previously
unknown knowledge from very large real-world databases. Rough
Set Theory (RST) is a mathematical formalism for representing
uncertainty that can be considered an extension of the classical set
theory. It has been used in many different research areas, including
those related to inductive machine learning and reduction of
knowledge in knowledge-based systems. One important concept
related to RST is that of a rough relation. In this paper we presented
the current status of research on applying rough set theory to KDD,
which will be helpful for handle the characteristics of real-world
databases. The main aim is to show how rough set and rough set
analysis can be effectively used to extract knowledge from large
databases.
Abstract: Availability of high dimensional biological datasets such as from gene expression, proteomic, and metabolic experiments can be leveraged for the diagnosis and prognosis of diseases. Many classification methods in this area have been studied to predict disease states and separate between predefined classes such as patients with a special disease versus healthy controls. However, most of the existing research only focuses on a specific dataset. There is a lack of generic comparison between classifiers, which might provide a guideline for biologists or bioinformaticians to select the proper algorithm for new datasets. In this study, we compare the performance of popular classifiers, which are Support Vector Machine (SVM), Logistic Regression, k-Nearest Neighbor (k-NN), Naive Bayes, Decision Tree, and Random Forest based on mock datasets. We mimic common biological scenarios simulating various proportions of real discriminating biomarkers and different effect sizes thereof. The result shows that SVM performs quite stable and reaches a higher AUC compared to other methods. This may be explained due to the ability of SVM to minimize the probability of error. Moreover, Decision Tree with its good applicability for diagnosis and prognosis shows good performance in our experimental setup. Logistic Regression and Random Forest, however, strongly depend on the ratio of discriminators and perform better when having a higher number of discriminators.
Abstract: Continuation of an active call is one of the most important quality measurements in the cellular systems. Handoff process enables a cellular system to provide such a facility by transferring an active call from one cell to another. Different approaches are proposed and applied in order to achieve better handoff service. The principal parameters used to evaluate handoff techniques are: forced termination probability and call blocking probability. The mechanisms such as guard channels and queuing handoff calls decrease the forced termination probability while increasing the call blocking probability. In this paper we present an overview about the issues related to handoff initiation and decision and discuss about different types of handoff techniques available in the literature.
Abstract: Mathematical models can be used to describe the
transmission of disease. Dengue disease is the most significant
mosquito-borne viral disease of human. It now a leading cause of
childhood deaths and hospitalizations in many countries. Variations
in environmental conditions, especially seasonal climatic parameters,
effect to the transmission of dengue viruses the dengue viruses and
their principal mosquito vector, Aedes aegypti. A transmission model
for dengue disease is discussed in this paper. We assume that the
human and vector populations are constant. We showed that the local
stability is completely determined by the threshold parameter, 0 B . If
0 B is less than one, the disease free equilibrium state is stable. If
0 B is more than one, a unique endemic equilibrium state exists and
is stable. The numerical results are shown for the different values of
the transmission probability from vector to human populations.
Abstract: Dengue is a mosquito-borne infection that has peaked to an alarming rate in recent decades. It can be found in tropical and sub-tropical climate. In Malaysia, dengue has been declared as one of the national health threat to the public. This study aimed to map the spatial distributions of dengue cases in the district of Hulu Langat, Selangor via a combination of Geographic Information System (GIS) and spatial statistic tools. Data related to dengue was gathered from the various government health agencies. The location of dengue cases was geocoded using a handheld GPS Juno SB Trimble. A total of 197 dengue cases occurring in 2003 were used in this study. Those data then was aggregated into sub-district level and then converted into GIS format. The study also used population or demographic data as well as the boundary of Hulu Langat. To assess the spatial distribution of dengue cases three spatial statistics method (Moran-s I, average nearest neighborhood (ANN) and kernel density estimation) were applied together with spatial analysis in the GIS environment. Those three indices were used to analyze the spatial distribution and average distance of dengue incidence and to locate the hot spot of dengue cases. The results indicated that the dengue cases was clustered (p < 0.01) when analyze using Moran-s I with z scores 5.03. The results from ANN analysis showed that the average nearest neighbor ratio is less than 1 which is 0.518755 (p < 0.0001). From this result, we can expect the dengue cases pattern in Hulu Langat district is exhibiting a cluster pattern. The z-score for dengue incidence within the district is -13.0525 (p < 0.0001). It was also found that the significant spatial autocorrelation of dengue incidences occurs at an average distance of 380.81 meters (p < 0.0001). Several locations especially residential area also had been identified as the hot spots of dengue cases in the district.
Abstract: Asiatic Houbara ( Chlamydotis macqueenii ) is a
flagship and vulnerable species. In-situ conservation of this
threatened species demands for knowledge of its habitat selection.
The aim of this study was to determine habitat variables influencing
birds wintering and breeding selection in semi- arid central Iran.
Habitat features of the detected nest and pellet sites were compared
with paired and random plots by quantifying a number of habitat
variables. In wintering habitat use at micro scale houbara selected
sites where vegetation cover was significantly lower compard to
control sites( p< 0.001). Areas with low number of larger plant
species (p=0.03) that were not too close to a vegetation
patch(p
Abstract: Urban road network traffic has become one of the
most studied research topics in the last decades. This is mainly due to
the enlargement of the cities and the growing number of motor
vehicles traveling in this road network. One of the most sensitive
problems is to verify if the network is congestion-free. Another
related problem is the automatic reconfiguration of the network
without building new roads to alleviate congestions. These problems
require an accurate model of the traffic to determine the steady state
of the system. An alternative is to simulate the traffic to see if there
are congestions and when and where they occur. One key issue is to
find an adequate model for road intersections. Once the model
established, either a large scale model is built or the intersection is
represented by its performance measures and simulation for analysis.
In both cases, it is important to seek the queueing model to represent
the road intersection. In this paper, we propose to model the road
intersection as a BCMP queueing network and we compare this
analytical model against a simulation model for validation.
Abstract: Weblog is an Internet tool that is believed to possess
great potential to facilitate learning in education. This study wants to
know if weblog can be used to promote students- critical thinking. It
used a group of secondary two students from a Singapore school to
write weblogs as a means of substitution for their traditional
handwritten assignments. The topics for the weblogging are taken
from History syllabus but modified to suit the purpose of this study.
Weblogs from the students were collected and analysed using a
known coding system for measuring critical thinking. Results show
that the topic for blogging is crucial in determining the types of
critical thinking employed by the students. Students are seen to
display critical thinking traits in the areas of information sourcing,
linking information to arguments and viewpoints justification.
Students- criticalness is more profound when the information for
writing a topic is readily available. Otherwise, they tend to be less
critical and subjective. The study also found that students lack the
ability to source for external information suggesting that students
may need to be taught information literacy in order to widen their use
of critical thinking skills.
Abstract: Routing places an important role in determining the
quality of service in wireless networks. The routing methods adopted
in wireless networks have many drawbacks. This paper aims to
review the current routing methods used in wireless networks. This
paper proposes an innovative solution to overcome the problems in
routing. This solution is aimed at improving the Quality of Service.
This solution is different from others as it involves the resuage of the
part of the virtual circuits. This improvement in quality of service is
important especially in propagation of multimedia applications like
video, animations etc. So it is the dire need to propose a new solution
to improve the quality of service in ATM wireless networks for
multimedia applications especially during this era of multimedia
based applications.
Abstract: Modeling and simulation of fixed bed three-phase
catalytic reactors are considered for wet air catalytic oxidation of
phenol to perform a comparative numerical analysis between tricklebed
and packed-bubble column reactors. The modeling involves
material balances both for the catalyst particle as well as for different
fluid phases. Catalyst deactivation is also considered in a transient
reactor model to investigate the effects of various parameters
including reactor temperature on catalyst deactivation. The
simulation results indicated that packed-bubble columns were
slightly superior in performance than trickle beds. It was also found
that reaction temperature was the most effective parameter in catalyst
deactivation.
Abstract: A novel typical day prediction model have been built and validated by the measured data of a grid-connected solar photovoltaic (PV) system in Macau. Unlike conventional statistical method used by previous study on PV systems which get results by averaging nearby continuous points, the present typical day statistical method obtain the value at every minute in a typical day by averaging discontinuous points at the same minute in different days. This typical day statistical method based on discontinuous point averaging makes it possible for us to obtain the Gaussian shape dynamical distributions for solar irradiance and output power in a yearly or monthly typical day. Based on the yearly typical day statistical analysis results, the maximum possible accumulated output energy in a year with on site climate conditions and the corresponding optimal PV system running time are obtained. Periodic Gaussian shape prediction models for solar irradiance, output energy and system energy efficiency have been built and their coefficients have been determined based on the yearly, maximum and minimum monthly typical day Gaussian distribution parameters, which are obtained from iterations for minimum Root Mean Squared Deviation (RMSD). With the present model, the dynamical effects due to time difference in a day are kept and the day to day uncertainty due to weather changing are smoothed but still included. The periodic Gaussian shape correlations for solar irradiance, output power and system energy efficiency have been compared favorably with data of the PV system in Macau and proved to be an improvement than previous models.
Abstract: The increasing interest on processing data created by
sensor networks has evolved into approaches to implement sensor
networks as databases. The aggregation operator, which calculates a
value from a large group of data such as computing averages or sums,
etc. is an essential function that needs to be provided when
implementing such sensor network databases. This work proposes to
add the DURING clause into TinySQL to calculate values during a
specific long period and suggests a way to implement the aggregation
service in sensor networks by applying materialized view and
incremental view maintenance techniques that is used in data
warehouses. In sensor networks, data values are passed from child
nodes to parent nodes and an aggregation value is computed at the root
node. As such root nodes need to be memory efficient and low
powered, it becomes a problem to recompute aggregate values from all
past and current data. Therefore, applying incremental view
maintenance techniques can reduce the memory consumption and
support fast computation of aggregate values.
Abstract: The objective of the present communication is to
develop new genuine exponentiated mean codeword lengths and to
study deeply the problem of correspondence between well known
measures of entropy and mean codeword lengths. With the help of
some standard measures of entropy, we have illustrated such a
correspondence. In literature, we usually come across many
inequalities which are frequently used in information theory.
Keeping this idea in mind, we have developed such inequalities via
coding theory approach.
Abstract: With the exponential progress of technological
development comes a strong sense that events are moving too quickly
for our schools and that teachers may be losing control of them in the
process. This paper examines the impact of e-learning and e-teaching
in universities, from both the student and teacher perspective. In
particular, it is shown that e-teachers should focus not only on the
technical capacities and functions of IT materials and activities, but
must attempt to more fully understand how their e-learners perceive
the learning environment. From the e-learner perspective, this paper
indicates that simply having IT tools available does not automatically
translate into all students becoming effective learners. More
evidence-based evaluative research is needed to allow e-learning and
e-teaching to reach full potential.
Abstract: According as the Architecture, Engineering and Construction (AEC) Industry projects have grown more complex and larger, the number of utilization of BIM for 3D design and simulation is increasing significantly. Therefore, typical applications of BIM such as clash detection and alternative measures based on 3-dimenstional planning are expanded to process management, cost and quantity management, structural analysis, check for regulation, and various domains for virtual design and construction. Presently, commercial BIM software is operated on single-user environment, so initial cost is so high and the investment may be wasted frequently. Cloud computing that is a next-generation internet technology enables simple internet devices (such as PC, Tablet, Smart phone etc) to use services and resources of BIM software. In this paper, we suggested developing method of the BIM software based on cloud computing environment in order to expand utilization of BIM and reduce cost of BIM software. First, for the benchmarking, we surveyed successful case of BIM and cloud computing. And we analyzed needs and opportunities of BIM and cloud computing in AEC Industry. Finally, we suggested main functions of BIM software based on cloud computing environment and developed a simple prototype of cloud computing BIM software for basic BIM model viewing.
Abstract: As business environments are rapidly changing,
the manufacturing system must be reconfigured to adapt to
various customer needs. In order to cope with this challenge, it
is quintessential to test industrial control logic rapidly and
easily in the design time, and monitor operational behavior in
the run time of automated manufacturing system. Proposed
integrated model for virtual prototyping and operational
monitoring of industrial control logic is to improve limitations
of current ladder programming practices and general discrete
event simulation method. Each plant layout model using HMI
package and object-oriented control logic model is designed
independently and is executed simultaneously in integrated
manner to reflect design practices of automation system in the
design time. Control logic is designed and executed using UML
activity diagram without considering complicated control
behavior to deal with current trend of reconfigurable
manufacturing. After the physical installation, layout model of
virtual prototype constructed in the design time is reused for
operational monitoring of system behavior during run time.
Abstract: System-level design based on high-level abstractions
is becoming increasingly important in hardware and embedded
system design. This paper analyzes meta-design techniques oriented
at developing meta-programs and meta-models for well-understood
domains. Meta-design techniques include meta-programming and
meta-modeling. At the programming level of design process, metadesign
means developing generic components that are usable in a
wider context of application than original domain components. At the
modeling level, meta-design means developing design patterns that
describe general solutions to the common recurring design problems,
and meta-models that describe the relationship between different
types of design models and abstractions. The paper describes and
evaluates the implementation of meta-design in hardware design
domain using object-oriented and meta-programming techniques.
The presented ideas are illustrated with a case study.
Abstract: Biodiesel as an alternative fuel for diesel engines has been developed for some three decades now. While it is gaining wide acceptance in Europe, USA and some parts of Asia, the same cannot be said of Africa. With more than 35 countries in the continent depending on imported crude oil, it is necessary to look for alternative fuels which can be produced from resources available locally within any country. Hence this study presents performance of single cylinder diesel engine using blends of shea butter biodiesel. Shea butter was transformed into biodiesel by transesterification process. Tests are conducted to compare the biodiesel with baseline diesel fuel in terms of engine performance and exhaust emission characteristics. The results obtained showed that the addition of biodiesel to diesel fuel decreases the brake thermal efficiency (BTE) and increases the brake specific fuel consumption (BSFC). These results are expected due to the lower energy content of biodiesel fuel. On the other hand while the NOx emissions increased with increase in biodiesel content in the fuel blends, the emissions of carbon monoxide (CO), un-burnt hydrocarbon (UHC) and smoke opacity decreased. The engine performance which indicates that the biodiesel has properties and characteristics similar to diesel fuel and the reductions in exhaust emissions make shea butter biodiesel a viable additive or substitute to diesel fuel.
Abstract: A new technique based on Pattern search optimization is proposed for estimating different solar cell parameters in this paper. The estimated parameters are the generated photocurrent, saturation current, series resistance, shunt resistance, and ideality factor. The proposed approach is tested and validated using double diode model to show its potential. Performance of the developed approach is quite interesting which signifies its potential as a promising estimation tool.
Abstract: Today, cancer remains one of the major diseases that
lead to death. The main obstacle in chemotherapy as a main cancer
treatment is the toxicity to normal cells due to Multidrug Resistance
(MDR) after the use of anticancer drugs. Proposed solution to
overcome this problem is the use of MDR efflux inhibitor of cinchona
alkaloids which is delivered together with anticancer drugs
encapsulated in the form of polymeric nanoparticles. The particles
were prepared by the hydration method. The characterization of
nanoparticles was particle size, zeta potential, entrapment efficiency
and in vitro drug release. Combination nanoparticle size ranged 29-45
nm with a neutral surface charge. Entrapment efficiency was above
87% for the use quinine, quinidine or cinchonidine in combination
with etoposide. The release test results exhibited that the cinchona
alkaloids release released faster than that of etoposide. Collectively,
cinchona alkaloids can be packaged along with etoposide in
nanomicelles for better cancer therapy.