Abstract: Load Forecasting plays a key role in making today's
and future's Smart Energy Grids sustainable and reliable. Accurate
power consumption prediction allows utilities to organize in advance
their resources or to execute Demand Response strategies more
effectively, which enables several features such as higher
sustainability, better quality of service, and affordable electricity
tariffs. It is easy yet effective to apply Load Forecasting at larger
geographic scale, i.e. Smart Micro Grids, wherein the lower available
grid flexibility makes accurate prediction more critical in Demand
Response applications. This paper analyses the application of
short-term load forecasting in a concrete scenario, proposed within the
EU-funded GreenCom project, which collect load data from single
loads and households belonging to a Smart Micro Grid. Three
short-term load forecasting techniques, i.e. linear regression, artificial
neural networks, and radial basis function network, are considered,
compared, and evaluated through absolute forecast errors and training
time. The influence of weather conditions in Load Forecasting is also
evaluated. A new definition of Gain is introduced in this paper, which
innovatively serves as an indicator of short-term prediction
capabilities of time spam consistency. Two models, 24- and
1-hour-ahead forecasting, are built to comprehensively compare these
three techniques.
Abstract: Access control is one of the most challenging issues
facing information security. Access control is defined as, the ability to
permit or deny access to a particular computational resource or digital
information by an unauthorized user or subject. The concept of usage
control (UCON) has been introduced as a unified approach to capture a
number of extensions for access control models and systems. In
UCON, an access decision is determined by three factors:
authorizations, obligations and conditions. Attribute mutability and
decision continuity are two distinct characteristics introduced by
UCON for the first time. An observation of UCON components
indicates that, the components are predefined and static. In this paper,
we propose a new and flexible model of usage control for the creation
and elimination of some of these components; for example new
objects, subjects, attributes and integrate these with the original
UCON model. We also propose a model for concurrent usage
scenarios in UCON.
Abstract: One of the major goals of Spoken Dialog Systems
(SDS) is to understand what the user utters.
In the SDS domain, the Spoken Language Understanding (SLU)
Module classifies user utterances by means of a pre-definite
conceptual knowledge. The SLU module is able to recognize only the
meaning previously included in its knowledge base. Due the vastity
of that knowledge, the information storing is a very expensive
process.
Updating and managing the knowledge base are time-consuming
and error-prone processes because of the rapidly growing number of
entities like proper nouns and domain-specific nouns. This paper
proposes a solution to the problem of Name Entity Recognition
(NER) applied to a SDS domain. The proposed solution attempts to
automatically recognize the meaning associated with an utterance by
using the PANKOW (Pattern based Annotation through Knowledge
On the Web) method at runtime.
The method being proposed extracts information from the Web to
increase the SLU knowledge module and reduces the development
effort. In particular, the Google Search Engine is used to extract
information from the Facebook social network.
Abstract: This study aimed at designing and developing a
mechanical force gauge for the square watermelon mold for the first
time. It also tried to introduce the square watermelon characteristics
and its production limitations. The mechanical force gauge
performance and the product itself were also described. There are
three main designable gauge models: a. hydraulic gauge, b. strain
gauge, and c. mechanical gauge. The advantage of the hydraulic
model is that it instantly displays the pressure and thus the force
exerted by the melon. However, considering the inability to measure
forces at all directions, complicated development, high cost, possible
hydraulic fluid leak into the fruit chamber and the possible influence
of increased ambient temperature on the fluid pressure, the
development of this gauge was overruled. The second choice was to
calculate pressure using the direct force a strain gauge. The main
advantage of these strain gauges over spring types is their high
precision in measurements; but with regard to the lack of conformity
of strain gauge working range with water melon growth, calculations
were faced with problems. Finally the mechanical pressure gauge has
advantages, including the ability to measured forces and pressures on
the mold surface during melon growth; the ability to display the peak
forces; the ability to produce melon growth graph thanks to its
continuous force measurements; the conformity of its manufacturing
materials with the required physical conditions of melon growth; high
air conditioning capability; the ability to permit sunlight reaches the
melon rind (no yellowish skin and quality loss); fast and
straightforward calibration; no damages to the product during
assembling and disassembling; visual check capability of the product
within the mold; applicable to all growth environments (field,
greenhouses, etc.); simple process; low costs and so forth.
Abstract: The growth of wireless devices affects the availability
of limited frequencies or spectrum bands as it has been known that
spectrum bands are a natural resource that cannot be added.
Meanwhile, the licensed frequencies are idle most of the time.
Cognitive radio is one of the solutions to solve those problems.
Cognitive radio is a promising technology that allows the unlicensed
users known as secondary users (SUs) to access licensed bands
without making interference to licensed users or primary users (PUs).
As cloud computing has become popular in recent years, cognitive
radio networks (CRNs) can be integrated with cloud platform. One of
the important issues in CRNs is security. It becomes a problem since
CRNs use radio frequencies as a medium for transmitting and CRNs
share the same issues with wireless communication systems. Another
critical issue in CRNs is performance. Security has adverse effect to
performance and there are trade-offs between them. The goal of this
paper is to investigate the performance related to security trade-off in
CRNs with supporting cloud platforms. Furthermore, Queuing
Network Models with preemptive resume and preemptive repeat
identical priority are applied in this project to measure the impact of
security to performance in CRNs with or without cloud platform. The
generalized exponential (GE) type distribution is used to reflect the
bursty inter-arrival and service times at the servers. The results show
that the best performance is obtained when security is disabled and
cloud platform is enabled.
Abstract: Consumer-to-Consumer (C2C) E-commerce has been
growing at a very high speed in recent years. Since identical or
nearly-same kinds of products compete one another by relying on
keyword search in C2C E-commerce, some sellers describe their
products with spam keywords that are popular but are not related to
their products. Though such products get more chances to be retrieved
and selected by consumers than those without spam keywords,
the spam keywords mislead the consumers and waste their time.
This problem has been reported in many commercial services like
ebay and taobao, but there have been little research to solve this
problem. As a solution to this problem, this paper proposes a method
to classify whether keywords of a product are spam or not. The
proposed method assumes that a keyword for a given product is
more reliable if the keyword is observed commonly in specifications
of products which are the same or the same kind as the given
product. This is because that a hierarchical category of a product
in general determined precisely by a seller of the product and so is
the specification of the product. Since higher layers of the hierarchical
category represent more general kinds of products, a reliable degree
is differently determined according to the layers. Hence, reliable
degrees from different layers of a hierarchical category become
features for keywords and they are used together with features only
from specifications for classification of the keywords. Support Vector
Machines are adopted as a basic classifier using the features, since
it is powerful, and widely used in many classification tasks. In
the experiments, the proposed method is evaluated with a golden
standard dataset from Yi-han-wang, a Chinese C2C E-commerce,
and is compared with a baseline method that does not consider
the hierarchical category. The experimental results show that the
proposed method outperforms the baseline in F1-measure, which
proves that spam keywords are effectively identified by a hierarchical
category in C2C E-commerce.
Abstract: The emergence of the Semantic Web technology
increases day by day due to the rapid growth of multiple web pages.
Many standard formats are available to store the semantic web data.
The most popular format is the Resource Description Framework
(RDF). Querying large RDF graphs becomes a tedious procedure
with a vast increase in the amount of data. The problem of query
optimization becomes an issue in querying large RDF graphs.
Choosing the best query plan reduces the amount of query execution
time. To address this problem, nature inspired algorithms can be used
as an alternative to the traditional query optimization techniques. In
this research, the optimal query plan is generated by the proposed
SAPSO algorithm which is a hybrid of Simulated Annealing (SA)
and Particle Swarm Optimization (PSO) algorithms. The proposed
SAPSO algorithm has the ability to find the local optimistic result
and it avoids the problem of local minimum. Experiments were
performed on different datasets by changing the number of predicates
and the amount of data. The proposed algorithm gives improved
results compared to existing algorithms in terms of query execution
time.
Abstract: Disasters are quite experienced in our days. They are
caused by floods, landslides, and building fires that is the main
objective of this study. To cope with these unexpected events,
precautions must be taken to protect human lives. The emphasis on
disposal work focuses on the resolution of the evacuation problem in
case of no-notice disaster. The problem of evacuation is listed as a
dynamic network flow problem. Particularly, we model the
evacuation problem as an earliest arrival flow problem with load
dependent transit time. This problem is classified as NP-Hard. Our
challenge here is to propose a metaheuristic solution for solving the
evacuation problem. We define our objective as the maximization of
evacuees during earliest periods of a time horizon T. The objective
provides the evacuation of persons as soon as possible. We
performed an experimental study on emergency evacuation from the
tunisian children’s hospital. This work prompts us to look for
evacuation plans corresponding to several situations where the
network dynamically changes.
Abstract: Second line antiretroviral therapy (ART) regimen is
used when patients fail their first line regimen. There are many
factors such as non-adherence, drug resistance as well as virological
and immunological failure that lead to second line highly active
antiretroviral therapy (HAART) regimen treatment failure. This study
was aimed at determining predictor factors to treatment failure with
second line HAART and analyzing median survival time.
An observational, retrospective study was conducted in Sungai
Buloh Hospital (HSB) to assess current status of HIV patients treated
with second line HAART regimen. Convenience sampling was used
and 104 patients were included based on the study’s inclusion and
exclusion criteria. Data was collected for six months i.e. from July
until December 2013. Data was then analysed using SPSS version 18.
Kaplan-Meier and Cox regression analyses were used to measure
median survival times and predictor factors for treatment failure.
The study population consisted mainly of male subjects, aged 30-
45 years, who were heterosexual, and had HIV infection for less than
6 years. The most common second line HAART regimen given was
lopinavir/ritonavir (LPV/r)-based combination. Kaplan-Meier
analysis showed that patients on LPV/r demonstrated longer median
survival times than patients on indinavir/ritonavir (IDV/r) based
combination (p
Abstract: The purpose of this work is to optimize a Switched Reluctance Motor (SRM) for an automotive application, specifically for a fully electric car. A new optimization approach is proposed. This unique approach transforms automotive customer requirements into an optimization problem, based on sound knowledge of a SRM theory. The approach combines an analytical and a finite element analysis of the motor to quantify static nonlinear and dynamic performance parameters, as phase currents and motor torque maps, an output power and power losses in order to find the optimal motor as close to the reality as possible, within reasonable time. The new approach yields the optimal motor which is competitive with other types of already proposed motors for automotive applications. This distinctive approach can also be used to optimize other types of electrical motors, when parts specifically related to the SRM are adjusted accordingly.
Abstract: The aim of this paper is to create a proposal for determining the costs of logistics processes by using process-oriented calculation methods. The traditional approach is that logistics costs are part of manufacturing overhead which is usually calculated as a percentage surcharge. Therefore in the traditional approach it is not obvious where and in which activities costs were incurred. So it is impossible to trace logistics costs to products. Our point of view is trying to fix or at least improve this issue. Another benefit of applying the process approach is identification of logistics processes which are otherwise part of manufacturing overhead. In the first part this paper describes the development of process-oriented methods over time. The next part shows the possibility of implementing the process-oriented method called Prozesskostenrechnung to logistics processes. The conclusion summarizes advantages and disadvantages of using this method in logistics.
Abstract: Partial shadowing is one of the problems that are always faced in terrestrial applications of solar photovoltaic (PV). The effects of partial shadow on the energy yield of conventional mono-crystalline and multi-crystalline PV modules have been researched for a long time. With deployment of new thin-film solar PV modules in the market, it is important to understand the performance of new PV modules operating under the partial shadow in the tropical zone. This paper addresses the impacts of different partial shadowing on the operating characteristics of four different types of solar PV modules that include multi-crystalline, amorphous thin-film, CdTe thin-film and CIGS thin-film PV modules.
Abstract: In this study, too, an attempt was made to reveal the
place and effects of information technologies on the lives and
education of gifted children based on the views of gifted. To this end,
the effects of information technologies on gifted are general skills,
technology use, academic and social skills, and cooperative and
personal skills were investigated. These skills were explored
depending on whether or not gifted had their own computers, had
internet connection at home, or how often they use the internet,
average time period they spent at the computer, how often they
played computer games and their use of social media.
The study was conducted using the screening model with a
quantitative approach. The sample of the study consisted of 129
gifted attending 5-12th classes in 12 provinces in different regions of
Turkey. 64 of the participants were female while 65 were male. The
research data were collected using the using computer of gifted and
information technologies (UCIT) questionnaire which was developed
by the researchers and given its final form after receiving expert
view.
As a result of the study, it was found that UCIT use improved
foreign language speaking skills of gifted, enabled them to get to
know and understand different cultures, and made use of computer
and information technologies while they study. At the end of the
study these result were obtained: Gifted have positive idea using
computer and communication technology. There are differences
whether using the internet about the ideas UCIT. But there are not
differences whether having computer, inhabited city, grade level,
having internet at home, daily and weekly internet usage durations,
playing the computer and internet game, having Facebook and
Twitter account about the UCIT.
UCIT contribute to the development of gifted vocabulary, allows
knowing and understand different cultures, developing foreign
language speaking skills, gifted do not give up computer when they
do their homework, improve their reading, listening, understanding
and writing skills in a foreign language.
Gifted children want to have transition to the use of tablets in
education. They think UCIT facilitates doing their homework,
contributes learning more information in a shorter time. They'd like
to use computer-assisted instruction programs at courses. They think
they will be more successful in the future if their computer skills are
good. But gifted students prefer teacher instead of teaching with
computers and they said that learning can be run from home without
going to school.
Abstract: In this paper, a backward semi-Lagrangian scheme
combined with the second-order backward difference formula
is designed to calculate the numerical solutions of nonlinear
advection-diffusion equations. The primary aims of this paper are
to remove any iteration process and to get an efficient algorithm
with the convergence order of accuracy 2 in time. In order to achieve
these objects, we use the second-order central finite difference and the
B-spline approximations of degree 2 and 3 in order to approximate
the diffusion term and the spatial discretization, respectively. For the
temporal discretization, the second order backward difference formula
is applied. To calculate the numerical solution of the starting point
of the characteristic curves, we use the error correction methodology
developed by the authors recently. The proposed algorithm turns out
to be completely iteration free, which resolves the main weakness
of the conventional backward semi-Lagrangian method. Also, the
adaptability of the proposed method is indicated by numerical
simulations for Burgers’ equations. Throughout these numerical
simulations, it is shown that the numerical results is in good
agreement with the analytic solution and the present scheme offer
better accuracy in comparison with other existing numerical schemes.
Abstract: This paper proposes a linear mixed model (LMM) with spatial effects to forecast rice and cassava yields in Thailand at the same time. A multivariate conditional autoregressive (MCAR) model is assumed to present the spatial effects. A Bayesian method is used for parameter estimation via Gibbs sampling Markov Chain Monte Carlo (MCMC). The model is applied to the rice and cassava yields monthly data which have been extracted from the Office of Agricultural Economics, Ministry of Agriculture and Cooperatives of Thailand. The results show that the proposed model has better performance in most provinces in both fitting part and validation part compared to the simple exponential smoothing and conditional auto regressive models (CAR) from our previous study.
Abstract: An alternative approach is proposed to develop the analytic solution for one dimensional heat conduction with one mixed type boundary condition and general time-dependent heat transfer coefficient. In this study, the physic meaning of the solution procedure is revealed. It is shown that the shifting function takes the physic meaning of the reciprocal of Biot function in the initial time. Numerical results show the accuracy of this study. Comparing with those given in the existing literature, the difference is less than 0.3%.
Abstract: Object detection using Wavelet Neural Network (WNN) plays a major contribution in the analysis of image processing. Existing cluster-based algorithm for co-saliency object detection performs the work on the multiple images. The co-saliency detection results are not desirable to handle the multi scale image objects in WNN. Existing Super Resolution (SR) scheme for landmark images identifies the corresponding regions in the images and reduces the mismatching rate. But the Structure-aware matching criterion is not paying attention to detect multiple regions in SR images and fail to enhance the result percentage of object detection. To detect the objects in the high-resolution remote sensing images, Tagged Grid Matching (TGM) technique is proposed in this paper. TGM technique consists of the three main components such as object determination, object searching and object verification in WNN. Initially, object determination in TGM technique specifies the position and size of objects in the current image. The specification of the position and size using the hierarchical grid easily determines the multiple objects. Second component, object searching in TGM technique is carried out using the cross-point searching. The cross out searching point of the objects is selected to faster the searching process and reduces the detection time. Final component performs the object verification process in TGM technique for identifying (i.e.,) detecting the dissimilarity of objects in the current frame. The verification process matches the search result grid points with the stored grid points to easily detect the objects using the Gabor wavelet Transform. The implementation of TGM technique offers a significant improvement on the multi-object detection rate, processing time, precision factor and detection accuracy level.
Abstract: The purposes of this research are to investigate Thai teens’ attitude toward prostitution on the internet, to discover the causes of teenage prostitution and to study the relationship between teenage promiscuity and the causes of teenage prostitution. This study is a mixed research which utilized both qualitative and quantitative approach. The population of this study included teenagers and early adults between 14-21 years old who were studying in high schools, colleges, or universities. A total of 600 respondents was sampled for interviews using a questionnaire, and 48 samples were chosen for an in-depth interview.
The findings revealed that the majority of respondents recognized that teenage prostitution on line was real. The reasons for choosing the internet to contact with customers included easy, convenient, safe, and anonymous. Moreover, the internet allowed teen prostitutes to contact customers anywhere and anytime. The correlation showed that promiscuity was related to the trend of teen prostitution. Other factors that contributed to increasing widespread teen prostitution online included their need for quick money to buy luxurious products and to support their extravagant behavior.
Abstract: Mobile communication provides access to the outside world without borders everywhere and at any time. The learning method that related to mobile communication technology is known as mobile learning (M-learning). It is a method that communicates learning materials with mobile device technology. The purpose of this method is to increase the interest in learning among students and assist them in obtaining learning materials at Kolej Poly-Tech MARA (KPTM) in order to improve the student’s performance in their study and to encourage educators to diversify the teaching practices. This paper discusses the student’s awareness for enhancement of learning style using mobile technologies and their readiness to apply the elements of mobile learning in learning to improve performance and interest in learning among students. An application called Mobile EEF Learning System (MEEFLS) has been developed as a tool to be used as a pilot test in KPTM.
Abstract: Lawsone is a pigment that occurs naturally in plants.
It has been used as a skin and hair dye for a long time. Moreover, its
different biological activities have been reported. The present study
focused on the effect of lawsone on a plant cell model represented by
tobacco BY-2 cell suspension culture, which is used as a model
comparable with the HeLa cells. It has been shown that lawsone
inhibits the cell growth in the concentration-dependent manner. In
addition, changes in DNA methylation level have been determined.
We observed decreasing level of DNA methylation in the presence of
increasing concentrations of lawsone. These results were
accompanied with overproduction of reactive oxygen species (ROS).
Since epigenetic modifications can be caused by different stress
factors, there could be a connection between the changes in the level
of DNA methylation and ROS production caused by lawsone.