Abstract: Load modeling is one of the central functions in
power systems operations. Electricity cannot be stored, which means
that for electric utility, the estimate of the future demand is necessary
in managing the production and purchasing in an economically
reasonable way. A majority of the recently reported approaches are
based on neural network. The attraction of the methods lies in the
assumption that neural networks are able to learn properties of the
load. However, the development of the methods is not finished, and
the lack of comparative results on different model variations is a
problem. This paper presents a new approach in order to predict the
Tunisia daily peak load. The proposed method employs a
computational intelligence scheme based on the Fuzzy neural
network (FNN) and support vector regression (SVR). Experimental
results obtained indicate that our proposed FNN-SVR technique gives
significantly good prediction accuracy compared to some classical
techniques.
Abstract: The aim of this paper is to perform experimental
modal analysis (EMA) of reinforced concrete (RC) square slabs.
EMA is the process of determining the modal parameters (Natural
Frequencies, damping factors, modal vectors) of a structure from a
set of frequency response functions FRFs (curve fitting). Although,
experimental modal analysis (or modal testing) has grown steadily in
popularity since the advent of the digital FFT spectrum analyzer in
the early 1970’s, studying all types of members and materials using
such method have not yet been well documented. Therefore, in this
work, experimental tests were conducted on RC square slab
specimens of dimensions 600mm x 600mmx 40mm. Experimental
analysis was based on freely supported boundary condition.
Moreover, impact testing as a fast and economical means of finding
the modes of vibration of a structure was used during the
experiments. In addition, Pico Scope 6 device and MATLAB
software were used to acquire data, analyze and plot Frequency
Response Function (FRF). The experimental natural frequencies
which were extracted from measurements exhibit good agreement
with analytical predictions. It is showed that EMA method can be
usefully employed to investigate the dynamic behavior of RC slabs.
Abstract: The 3D body movement signals captured during
human-human conversation include clues not only to the content of
people’s communication but also to their culture and personality.
This paper is concerned with automatic extraction of this information
from body movement signals. For the purpose of this research, we
collected a novel corpus from 27 subjects, arranged them into groups
according to their culture. We arranged each group into pairs and
each pair communicated with each other about different topics.
A state-of-art recognition system is applied to the problems of
person, culture, and topic recognition. We borrowed modeling,
classification, and normalization techniques from speech recognition.
We used Gaussian Mixture Modeling (GMM) as the main technique
for building our three systems, obtaining 77.78%, 55.47%, and
39.06% from the person, culture, and topic recognition systems
respectively. In addition, we combined the above GMM systems with
Support Vector Machines (SVM) to obtain 85.42%, 62.50%, and
40.63% accuracy for person, culture, and topic recognition
respectively.
Although direct comparison among these three recognition
systems is difficult, it seems that our person recognition system
performs best for both GMM and GMM-SVM, suggesting that intersubject
differences (i.e. subject’s personality traits) are a major
source of variation. When removing these traits from culture and
topic recognition systems using the Nuisance Attribute Projection
(NAP) and the Intersession Variability Compensation (ISVC)
techniques, we obtained 73.44% and 46.09% accuracy from culture
and topic recognition systems respectively.
Abstract: Recently, universities are increasingly consuming
energy to support various activities. A large population of staff and
students in Malaysian universities has led to excessive energy
consumption which directly gives an impact to the environment. The
key question then ascended “How well is an energy management
(EM) been practiced in universities without taking the Critical
Success Factors (CSFs) into consideration to ensure the management
of university achieves the goals in reducing energy consumption.
Review on past literature is carried out to establish CSFs for EM best
practices. Thus, this paper highlighted the CSFs which have to be
focused on by management of university to successfully measure the
EM implementation and its performance. At the end of this paper, a
theoretical framework is developed for EM success factors towards
sustainable university.
Abstract: Currently, there is excessively growing information
about places on Facebook, which is the largest social network but
such information is not explicitly organized and ranked. Therefore
users cannot exploit such data to recommend places conveniently and
quickly. This paper proposes a Facebook application and an Android
application that recommend places based on the number of check-ins
of those places, the distance of those places from the current location,
the number of people who like Facebook page of those places, and
the number of talking about of those places. Related Facebook data is
gathered via Facebook API requests. The experimental results of the
developed applications show that the applications can recommend
places and rank interesting places from the most to the least. We have
found that the average satisfied score of the proposed Facebook
application is 4.8 out of 5. The users’ satisfaction can increase by
adding the app features that support personalization in terms of
interests and preferences.
Abstract: The use OF adhesive anchors for wooden constructions is an efficient technology to connect and design timber members in new timber structures and to rehabilitate the damaged structural members of historical buildings. Due to the lack of standard regulation in this specific area of structural design, designers’ choices are still supported by test analysis that enables knowledge, and the prediction, of the structural behaviour of glued in rod joints. The paper outlines an experimental research activity aimed at identifying the tensile resistance capacity of several new adhesive joint prototypes made of epoxy resin, steel bar and timber, Oak and Douglas Fir species. The development of new adhesive connectors has been carried out by using epoxy to glue stainless steel bars into pre-drilled holes, characterised by smooth and rough internal surfaces, in timber samples. The realization of a threaded contact surface using a specific drill bit has led to an improved bond between wood and epoxy. The applied changes have also reduced the cost of the joints’ production. The paper presents the results of this parametric analysis and a Finite Element analysis that enables identification and study of the internal stress distribution in the proposed adhesive anchors.
Abstract: The study of the electrical signals produced by neural
activities of human brain is called Electroencephalography. In this
paper, we propose an automatic and efficient EEG signal
classification approach. The proposed approach is used to classify the
EEG signal into two classes: epileptic seizure or not. In the proposed
approach, we start with extracting the features by applying Discrete
Wavelet Transform (DWT) in order to decompose the EEG signals
into sub-bands. These features, extracted from details and
approximation coefficients of DWT sub-bands, are used as input to
Principal Component Analysis (PCA). The classification is based on
reducing the feature dimension using PCA and deriving the supportvectors
using Support Vector Machine (SVM). The experimental are
performed on real and standard dataset. A very high level of
classification accuracy is obtained in the result of classification.
Abstract: The design and plantwide control of an integrated
plant where the endothermic 1,4-butanediol dehydrogenation and the
exothermic furfural hydrogenation is simultaneously performed in a
single reactor is studied. The reactions can be carried out in an
adiabatic reactor using small hydrogen excess and with reduced
parameter sensitivity. The plant is robust and flexible enough to
allow different production rates of γ-butyrolactone and 2-methyl
furan, keeping high product purities. Rigorous steady state and
dynamic simulations performed in AspenPlus and AspenDynamics to
support the conclusions.
Abstract: Water contamination by toxic compound is one of the serious environmental problems today. These toxic compounds mostly originated from industrial effluents, agriculture, natural sources and human waste. These studies focus on modification of multiwalled carbon nanotube (MWCNTs) with nanoparticle of calixarene and explore the possibility of using this modification for the remediation of cadmium in water. The nanocomposites were prepared by dissolving calixarene in chloroform solution as solvent, followed by additional multiwalled carbon nanotube (MWCNTs) then sonication process for 3 hour and fabricated the nanocomposites on substrate by spin coating method. Finally, the nanocomposites were tested on cadmium ion (10 mg/ml). The morphology of nanocomposites was investigated by FESEM showing the formation of calixarene on the outer walls of carbon nanotube and cadmium ion also clearly seen from the micrograph. This formation was supported by using energy dispersive x-ray (EDX). The presence of cadmium ions in the films, leads to some changes in the surface potential and Fourier Transform Infrared spectroscopy (FTIR).The nanocomposites MWCNTs-calixarene have potential for development of sensor for pollutant monitoring and nanoelectronics devices applications.
Abstract: Reverse Logistics (RL) Network is considered as
complex and dynamic network that involves many stakeholders such
as: suppliers, manufactures, warehouse, retails and costumers, this
complexity is inherent in such process due to lack of perfect
knowledge or conflicting information. Ontologies on the other hand
can be considered as an approach to overcome the problem of sharing
knowledge and communication among the various reverse logistics
partners. In this paper we propose a semantic representation based on
hybrid architecture for building the Ontologies in ascendant way, this
method facilitates the semantic reconciliation between the
heterogeneous information systems that support reverse logistics
processes and product data.
Abstract: Given the dynamic nature of the higher education
landscape, induction programmes for new academics has become the
norm nowadays to support academics negotiate these rough terrain.
This study investigates an induction programme for new academics
in a higher education institution to establish what difference it has
made to participants. The findings revealed that the benefits ranged
from creating safe spaces for collaboration and networking to
fostering reflective practice and contributing to the scholarship of
teaching and learning. The study also revealed that some of the
intentions of the programme may not have been achieved, for
example transformative learning. This led to questioning whether this
intention is an appropriate one given the short duration of the
programme and the long, drawn out process of transformation. It may
be concluded that the academic induction programme in this study
serves to sow the seeds for transformative learning through fostering
critically reflective practice. Recommendations for further study
could include long term impact of the programme on student learning
and success, these being the core business of higher education. It is
also recommended that in addition to an induction programme, the
university invests in a mentoring programme for new staff and extend
the support for academics in order to sustain critical reflection and
which may contribute to transformative educational practice.
Abstract: The final energy use can be divided mainly in four sectors: commercial, industrial, residential, and transportation. The trend in final energy consumption by sector plays as a most straightforward way to provide a wide indication of progress for reducing energy consumption and associated environmental impacts by different end use sectors. The average share of end use energy for residential sector in the world was nearly 20% until 2011, in Germany a higher proportion is between 25% and 30%. However, it remains less studied than energy use in other three sectors as well its impacts on climate and environment. The reason for this involves a wide range of fields, including the diversity of residential construction like different housing building design and materials, living or energy using behavioral patterns, climatic condition and variation as well other social obstacles, market trend potential and financial support from government.
This paper presents an extensive and in-depth analysis of the manner by which projects researched and operated by authors in the fields of energy efficiency primarily from the perspectives of both technical potential and initiative energy saving consciousness in the residential sectors especially in social housing buildings.
Abstract: In this study, data loss tolerance of Support Vector Machines (SVM) based activity recognition model and multi activity classification performance when data are received over a lossy wireless sensor network is examined. Initially, the classification algorithm we use is evaluated in terms of resilience to random data loss with 3D acceleration sensor data for sitting, lying, walking and standing actions. The results show that the proposed classification method can recognize these activities successfully despite high data loss. Secondly, the effect of differentiated quality of service performance on activity recognition success is measured with activity data acquired from a multi hop wireless sensor network, which introduces high data loss. The effect of number of nodes on the reliability and multi activity classification success is demonstrated in simulation environment. To the best of our knowledge, the effect of data loss in a wireless sensor network on activity detection success rate of an SVM based classification algorithm has not been studied before.
Abstract: Proof of controlling crack width is a basic condition
for securing suitable performance in serviceability limit state. The
cracking in concrete can occur at any time from the casting of time to
the years after the concrete has been set in place. Most codes struggle
with offering procedure for crack width calculation. There is lack in
availability of design charts for designers to compute crack width
with ease. The focus of the study is to utilize design charts and
parametric equations in calculating crack width with minimum error.
The paper contains a simplified procedure to calculate crack width
for reinforced concrete (RC) sections subjected to bending with axial
tensile force following the guidelines of Euro code [DS EN-1992-1-1
& DS EN-1992-1-2]. Numerical examples demonstrate the
application of the suggested procedure. Comparison with parallel
analytical tools supports the validity of result and show the
percentage deviation of crack width in both the procedures. The
technique is simple, user friendly and ready to evolve for a greater
spectrum of section sizes and materials.
Abstract: The purpose of this study is to examine the possible
link between employee and customer satisfaction. The service
provided by employees, help to build a good relationship with
customers and can help at increasing their loyalty. Published data for
job satisfaction and indicators of customer services of banks were
gathered from relevant published works which included data from
five different countries. The scores of customers and employees
satisfaction of the different published works were transformed and
normalized to the scale of 1 to 100. The data were analyzed and a
regression analysis of the two parameters was used to describe the
link between employee’s satisfaction and customer’s satisfaction.
Assuming that employee satisfaction has a significant influence on
customer’s service and the resulting customer satisfaction, the
reviewed data indicate that employee’s satisfaction contributes
significantly on the level of customer satisfaction in the Banking
sector. There was a significant correlation between the two
parameters (Pearson correlation R2=0.52 P
Abstract: Web-based Cognitive Writing Instruction (WeCWI)’s
contribution towards language development can be divided into
linguistic and non-linguistic perspectives. In linguistic perspective,
WeCWI focuses on the literacy and language discoveries, while the
cognitive and psychological discoveries are the hubs in non-linguistic
perspective. In linguistic perspective, WeCWI draws attention to free
reading and enterprises, which are supported by the language
acquisition theories. Besides, the adoption of process genre approach
as a hybrid guided writing approach fosters literacy development.
Literacy and language developments are interconnected in the
communication process; hence, WeCWI encourages meaningful
discussion based on the interactionist theory that involves input,
negotiation, output, and interactional feedback. Rooted in the elearning
interaction-based model, WeCWI promotes online
discussion via synchronous and asynchronous communications,
which allows interactions happened among the learners, instructor,
and digital content. In non-linguistic perspective, WeCWI highlights
on the contribution of reading, discussion, and writing towards
cognitive development. Based on the inquiry models, learners’
critical thinking is fostered during information exploration process
through interaction and questioning. Lastly, to lower writing anxiety,
WeCWI develops the instructional tool with supportive features to
facilitate the writing process. To bring a positive user experience to
the learner, WeCWI aims to create the instructional tool with
different interface designs based on two different types of perceptual
learning style.
Abstract: Operations research science (OR) deals with good
success in developing and applying scientific methods for problem
solving and decision-making. However, by using OR techniques, we
can enhance the use of computer decision support systems to achieve
optimal management for institutions. OR applies comprehensive
analysis including all factors that effect on it and builds mathematical
modeling to solve business or organizational problems. In addition, it
improves decision-making and uses available resources efficiently.
The adoption of OR by universities would definitely contributes to
the development and enhancement of the performance of OR
techniques. This paper provides an understanding of the structures,
approaches and models of OR in problem solving and decisionmaking.
Abstract: This study examines the credibility of the signaling as
explanation for IPO initial underpricing. Findings reveal the initial
underpricing and the long-term underperformance of IPOs in Taiwan.
However, we only find weak support for signaling as explanation of
IPO underpricing.
Abstract: Nowadays social media information, such as news,
links, images, or VDOs, is shared extensively. However, the
effectiveness of disseminating information through social media
lacks in quality: less fact checking, more biases, and several rumors.
Many researchers have investigated about credibility on Twitter, but
there is no the research report about credibility information on
Facebook. This paper proposes features for measuring credibility on
Facebook information. We developed the system for credibility on
Facebook. First, we have developed FB credibility evaluator for
measuring credibility of each post by manual human’s labelling. We
then collected the training data for creating a model using Support
Vector Machine (SVM). Secondly, we developed a chrome extension
of FB credibility for Facebook users to evaluate the credibility of
each post. Based on the usage analysis of our FB credibility chrome
extension, about 81% of users’ responses agree with suggested
credibility automatically computed by the proposed system.
Abstract: Background: Taiwan now is an aging society. Research
on the elderly should not be confined to caring for seniors, but should
also be focused on ways to improve health and the quality of life.
Senior citizens who participate in volunteer services could become
less lonely, have new growth opportunities, and regain a sense of
accomplishment. Thus, the question of how to get the elderly to
participate in volunteer service is worth exploring. Objective: Apply
the Transtheoretical Model to understand stages of change in regular
volunteer service and voluntary service behaviour among the seniors.
Methods: 1525 adults over the age of 65 from the Renai district of
Keelung City were interviewed. The research tool was a
self-constructed questionnaire, and individual interviews were
conducted to collect data. Then the data was processed and analyzed
using the IBM SPSS Statistics 20 (Windows version) statistical
software program. Results: In the past six months, research subjects
averaged 9.92 days of volunteer services. A majority of these elderly
individuals had no intention to change their regular volunteer services.
We discovered that during the maintenance stage, the self-efficacy for
volunteer services was higher than during all other stages, but
self-perceived barriers were less during the preparation stage and
action stage. Self-perceived benefits were found to have an important
predictive power for those with regular volunteer service behaviors in
the previous stage, and self-efficacy was found to have an important
predictive power for those with regular volunteer service behaviors in
later stages. Conclusions/Implications for Practice: The research
results support the conclusion that community nursing staff should
group elders based on their regular volunteer services change stages
and design appropriate behavioral change strategies.