Abstract: Adolescents in Northern Uganda are at risk of teenage
pregnancies, unsafe abortions and sexually transmitted infections
(STIs). There is silence on sex both at home and school. This cross
sectional descriptive analytical study interviews a random sample of
827 students and 13 teachers on knowledge, perception and
acceptability to a comprehensive adolescent sexual and reproductive
health education in “O” and “A” level secondary schools in Gulu
District. Quantitative data was analyzed using SPSS 16.0. Directed
content analysis of themes of transcribed qualitative data was
conducted manually for common codes, sub-categories and
categories. Of the 827 students; 54.3% (449) reported being in a
sexual relationship especially those aged 15-17 years. Majority
96.1% (807) supported the teaching of a comprehensive ASRHE,
citing no negative impact 71.5% (601). Majority 81.6% (686) agreed
that such education could help prevention of STIs, abortions and
teenage pregnancies, and that it should be taught by health workers
69.0% (580). Majority 76.6% (203) reported that ASRHE was not
currently being taught in their schools. Students had low knowledge
levels and misconceptions about ASRHE. ASRHE was highly
acceptable though not being emphasized; its success in school
settings requires multidisciplinary culturally sensitive approaches
amongst which health workers should be frontiers.
Abstract: If there exists a nonempty, proper subset S of the set of all (n+1)(n+2)/2 inertias such that S Ôèå i(A) is sufficient for any n×n zero-nonzero pattern A to be inertially arbitrary, then S is called a critical set of inertias for zero-nonzero patterns of order n. If no proper subset of S is a critical set, then S is called a minimal critical set of inertias. In [Kim, Olesky and Driessche, Critical sets of inertias for matrix patterns, Linear and Multilinear Algebra, 57 (3) (2009) 293-306], identifying all minimal critical sets of inertias for n×n zero-nonzero patterns with n ≥ 3 and the minimum cardinality of such a set are posed as two open questions by Kim, Olesky and Driessche. In this note, the minimum cardinality of all critical sets of inertias for 4 × 4 irreducible zero-nonzero patterns is identified.
Abstract: Service identification is one of the main activities in
the modeling of a service-oriented solution, and therefore errors
made during identification can flow down through detailed design
and implementation activities that may necessitate multiple
iterations, especially in building composite applications. Different
strategies exist for how to identify candidate services that each of
them has its own benefits and trade offs. The approach presented in
this paper proposes a selective identification of services approach,
based on in depth business process analysis coupled with use cases
and existing assets analysis and goal service modeling. This article
clearly emphasizes the key activities need for the analysis and
service identification to build a optimized service oriented
architecture. In contrast to other approaches this article mentions
some best practices and steps, wherever appropriate, to point out the
vagueness involved in service identification.
Abstract: This paper proposes an auto-classification algorithm
of Web pages using Data mining techniques. We consider the
problem of discovering association rules between terms in a set of
Web pages belonging to a category in a search engine database, and
present an auto-classification algorithm for solving this problem that
are fundamentally based on Apriori algorithm. The proposed
technique has two phases. The first phase is a training phase where
human experts determines the categories of different Web pages, and
the supervised Data mining algorithm will combine these categories
with appropriate weighted index terms according to the highest
supported rules among the most frequent words. The second phase is
the categorization phase where a web crawler will crawl through the
World Wide Web to build a database categorized according to the
result of the data mining approach. This database contains URLs and
their categories.
Abstract: Presented herein is an assessment of current nonlinear
static procedures (NSPs) for seismic evaluation of bucklingrestrained
braced frames (BRBFs) which have become a favorable
lateral-force resisting system for earthquake resistant buildings. The
bias and accuracy of modal, improved modal pushover analysis
(MPA, IMPA) and mass proportional pushover (MPP) procedures
are comparatively investigated when they are applied to BRBF
buildings subjected to two sets of strong ground motions. The
assessment is based on a comparison of seismic displacement
demands such as target roof displacements, peak floor/roof
displacements and inter-story drifts. The NSP estimates are compared
to 'exact' results from nonlinear response history analysis (NLRHA).
The response statistics presented show that the MPP
procedure tends to significantly overestimate seismic demands of
lower stories of tall buildings considered in this study while MPA
and IMPA procedures provide reasonably accurate results in
estimating maximum inter-story drift over all stories of studied BRBF
systems.
Abstract: In order to meet the limits imposed on automotive
emissions, engine control systems are required to constrain air/fuel
ratio (AFR) in a narrow band around the stoichiometric value, due to
the strong decay of catalyst efficiency in case of rich or lean mixture.
This paper presents a model of a sample spark ignition engine and
demonstrates Simulink-s capabilities to model an internal combustion
engine from the throttle to the crankshaft output. We used welldefined
physical principles supplemented, where appropriate, with
empirical relationships that describe the system-s dynamic behavior
without introducing unnecessary complexity. We also presents a PID
tuning method that uses an adaptive fuzzy system to model the
relationship between the controller gains and the target output
response, with the response specification set by desired percent
overshoot and settling time. The adaptive fuzzy based input-output
model is then used to tune on-line the PID gains for different
response specifications. Experimental results demonstrate that better
performance can be achieved with adaptive fuzzy tuning relative to
similar alternative control strategies. The actual response
specifications with adaptive fuzzy matched the desired response
specifications.
Abstract: Over the past few years, a number of efforts have
been exerted to build parallel processing systems that utilize the idle
power of LAN-s and PC-s available in many homes and corporations.
The main advantage of these approaches is that they provide cheap
parallel processing environments for those who cannot afford the
expenses of supercomputers and parallel processing hardware.
However, most of the solutions provided are not very flexible in the
use of available resources and very difficult to install and setup.
In this paper, a multi-level web-based parallel processing system
(MWPS) is designed (appendix). MWPS is based on the idea of
volunteer computing, very flexible, easy to setup and easy to use.
MWPS allows three types of subscribers: simple volunteers (single
computers), super volunteers (full networks) and end users. All of
these entities are coordinated transparently through a secure web site.
Volunteer nodes provide the required processing power needed by
the system end users. There is no limit on the number of volunteer
nodes, and accordingly the system can grow indefinitely. Both
volunteer and system users must register and subscribe. Once, they
subscribe, each entity is provided with the appropriate MWPS
components. These components are very easy to install.
Super volunteer nodes are provided with special components that
make it possible to delegate some of the load to their inner nodes.
These inner nodes may also delegate some of the load to some other
lower level inner nodes .... and so on. It is the responsibility of the
parent super nodes to coordinate the delegation process and deliver
the results back to the user.
MWPS uses a simple behavior-based scheduler that takes into
consideration the current load and previous behavior of processing
nodes. Nodes that fulfill their contracts within the expected time get a
high degree of trust. Nodes that fail to satisfy their contract get a
lower degree of trust.
MWPS is based on the .NET framework and provides the minimal
level of security expected in distributed processing environments.
Users and processing nodes are fully authenticated. Communications
and messages between nodes are very secure. The system has been
implemented using C#.
MWPS may be used by any group of people or companies to
establish a parallel processing or grid environment.
Abstract: This paper sets forth the possibility and importance about applying Data Mining in Web logs mining and shows some problems in the conventional searching engines. Then it offers an improved algorithm based on the original AprioriAll algorithm which has been used in Web logs mining widely. The new algorithm adds the property of the User ID during the every step of producing the candidate set and every step of scanning the database by which to decide whether an item in the candidate set should be put into the large set which will be used to produce next candidate set. At the meantime, in order to reduce the number of the database scanning, the new algorithm, by using the property of the Apriori algorithm, limits the size of the candidate set in time whenever it is produced. Test results show the improved algorithm has a more lower complexity of time and space, better restrain noise and fit the capacity of memory.
Abstract: Dioscorea species or commonly named as yam is
reported to be one of the major food sources worldwide. This
ethnobotanical study was conducted to document local knowledge
and potentials of DioscoreahispidaDennst. and to investigate and
record its distribution in three districts of Terengganu. Information
was gathered from 23 villagers from three districts of Besut, Marang
and Setiu by using semi-structured questionnaire. The villagers were
randomly selected and no appointment was made prior to the visits.
For distribution, the location of Dioscoreahispida was recorded by
using the Global Positioning System (GPS). The villagers identified
Dioscoreahispida or locally named ubigadong by looking at the
physical characteristics that include its leaf shape, stem and the color
of the tuber-s flesh. The villagers used Dioscoreahispida in many
ways in their life such as for food, medicinal purposes and fish
poison.
Abstract: Various intelligences and inspirations have been
adopted into the iterative searching process called as meta-heuristics.
They intelligently perform the exploration and exploitation in the
solution domain space aiming to efficiently seek near optimal
solutions. In this work, the bee algorithm, inspired by the natural
foraging behaviour of honey bees, was adapted to find the near
optimal solutions of the transportation management system, dynamic
multi-zone dispatching. This problem prepares for an uncertainty and
changing customers- demand. In striving to remain competitive,
transportation system should therefore be flexible in order to cope
with the changes of customers- demand in terms of in-bound and outbound
goods and technological innovations. To remain higher service
level but lower cost management via the minimal imbalance scenario,
the rearrangement penalty of the area, in each zone, including time
periods are also included. However, the performance of the algorithm
depends on the appropriate parameters- setting and need to be
determined and analysed before its implementation. BEE parameters
are determined through the linear constrained response surface
optimisation or LCRSOM and weighted centroid modified simplex
methods or WCMSM. Experimental results were analysed in terms
of best solutions found so far, mean and standard deviation on the
imbalance values including the convergence of the solutions
obtained. It was found that the results obtained from the LCRSOM
were better than those using the WCMSM. However, the average
execution time of experimental run using the LCRSOM was longer
than those using the WCMSM. Finally a recommendation of proper
level settings of BEE parameters for some selected problem sizes is
given as a guideline for future applications.
Abstract: In general fuzzy sets are used to analyze the fuzzy
system reliability. Here intuitionistic fuzzy set theory for analyzing
the fuzzy system reliability has been used. To analyze the fuzzy
system reliability, the reliability of each component of the system as
a triangular intuitionistic fuzzy number is considered. Triangular
intuitionistic fuzzy number and their arithmetic operations are
introduced. Expressions for computing the fuzzy reliability of a
series system and a parallel system following triangular intuitionistic
fuzzy numbers have been described. Here an imprecise reliability
model of an electric network model of dark room is taken. To
compute the imprecise reliability of the above said system, reliability
of each component of the systems is represented by triangular
intuitionistic fuzzy numbers. Respective numerical example is
presented.
Abstract: In this paper, a Web-based e-Training platform that is dedicated to multimodal breast imaging is presented. The assets of this platform are summarised in (i) the efficient representation of the curriculum flow that will permit efficient training; (ii) efficient tagging of multimodal content appropriate for the completion of realistic cases and (iii) ubiquitous accessibility and platform independence via a web-based approach.
Abstract: In this paper an extensive verification of the extraction
method (published earlier) that consistently accounts for self-heating
and Early effect to accurately extract both base and thermal resistance
of bipolar junction transistors is presented. The method verification is
demonstrated on advanced RF SiGe HBTs were the extracted results
for the thermal resistance are compared with those from another
published method that ignores the effect of Early effect on internal
base-emitter voltage and the extracted results of the base resistance
are compared with those determined from noise measurements. A
self-consistency of our method in the extracted base resistance and
thermal resistance using compact model simulation results is also
carried out in order to study the level of accuracy of the method.
Abstract: New generalization of the new class matrix polynomial set have been obtained. An explicit representation and an expansion of the matrix exponential in a series of these matrix are given for these matrix polynomials.
Abstract: The Ant Colony Optimization (ACO) is a metaheuristic inspired by the behavior of real ants in their search for the shortest paths to food sources. It has recently attracted a lot of attention and has been successfully applied to a number of different optimization problems. Due to the importance of the feature selection problem and the potential of ACO, this paper presents a novel method that utilizes the ACO algorithm to implement a feature subset search procedure. Initial results obtained using the classification of speech segments are very promising.
Abstract: This paper discusses on the use of Spline Interpolation
and Mean Square Error (MSE) as tools to process data acquired from
the developed simulator that shall replicate sea bed logging environment.
Sea bed logging (SBL) is a new technique that uses marine
controlled source electromagnetic (CSEM) sounding technique and is
proven to be very successful in detecting and characterizing hydrocarbon
reservoirs in deep water area by using resistivity contrasts. It uses
very low frequency of 0.1Hz to 10 Hz to obtain greater wavelength.
In this work the in house built simulator was used and was provided
with predefined parameters and the transmitted frequency was varied
for sediment thickness of 1000m to 4000m for environment with and
without hydrocarbon. From series of simulations, synthetics data were
generated. These data were interpolated using Spline interpolation
technique (degree of three) and mean square error (MSE) were
calculated between original data and interpolated data. Comparisons
were made by studying the trends and relationship between frequency
and sediment thickness based on the MSE calculated. It was found
that the MSE was on increasing trends in the set up that has the
presence of hydrocarbon in the setting than the one without. The MSE
was also on decreasing trends as sediment thickness was increased
and with higher transmitted frequency.
Abstract: The mitigation of crop loss due to damaging freezes
requires accurate air temperature prediction models. Previous work
established that the Ward-style artificial neural network (ANN) is a
suitable tool for developing such models. The current research
focused on developing ANN models with reduced average prediction
error by increasing the number of distinct observations used in
training, adding additional input terms that describe the date of an
observation, increasing the duration of prior weather data included in
each observation, and reexamining the number of hidden nodes used
in the network. Models were created to predict air temperature at
hourly intervals from one to 12 hours ahead. Each ANN model,
consisting of a network architecture and set of associated parameters,
was evaluated by instantiating and training 30 networks and
calculating the mean absolute error (MAE) of the resulting networks
for some set of input patterns. The inclusion of seasonal input terms,
up to 24 hours of prior weather information, and a larger number of
processing nodes were some of the improvements that reduced
average prediction error compared to previous research across all
horizons. For example, the four-hour MAE of 1.40°C was 0.20°C, or
12.5%, less than the previous model. Prediction MAEs eight and 12
hours ahead improved by 0.17°C and 0.16°C, respectively,
improvements of 7.4% and 5.9% over the existing model at these
horizons. Networks instantiating the same model but with different
initial random weights often led to different prediction errors. These
results strongly suggest that ANN model developers should consider
instantiating and training multiple networks with different initial
weights to establish preferred model parameters.
Abstract: More and more natural disasters are happening every
year: floods, earthquakes, volcanic eruptions, etc. In order to reduce
the risk of possible damages, governments all around the world are
investing into development of Early Warning Systems (EWS) for
environmental applications. The most important task of the EWS is
identification of the onset of critical situations affecting environment
and population, early enough to inform the authorities and general
public. This paper describes an approach for monitoring of flood
protections systems based on machine learning methods. An
Artificial Intelligence (AI) component has been developed for
detection of abnormal dike behaviour. The AI module has been
integrated into an EWS platform of the UrbanFlood project (EU
Seventh Framework Programme) and validated on real-time
measurements from the sensors installed in a dike.
Abstract: In this study, two new classes of generalized homeomorphisms are introduced and shown that one of these classes has a group structure. Moreover, some properties of these two homeomorphisms are obtained.
Abstract: A renewable energy system discussed in this paper is
a stand-alone wind-hydrogen system for a remote island in Australia.
The analysis of an existing wind-diesel power system was performed.
Simulation technique was used to model the power system currently
employed on the island, and simulated different configurations of
additional hydrogen energy system. This study aims to determine the
suitable hydrogen integrated configuration to setting up the prototype
system for the island, which helps to reduce the diesel consumption
on the island. A set of configurations for the hydrogen system and
associated parameters that consists of wind turbines, electrolysers,
hydrogen internal combustion engines, and storage tanks has been
purposed. The simulation analyses various configurations that
perfectly balances the system to meet the demand on the island.