Abstract: Ability of accurate and reliable location estimation in
indoor environment is the key issue in developing great number of
context aware applications and Location Based Services (LBS).
Today, the most viable solution for localization is the Received
Signal Strength (RSS) fingerprinting based approach using wireless
local area network (WLAN). This paper presents two RSS
fingerprinting based approaches – first we employ widely used
WLAN based positioning as a reference system and then investigate
the possibility of using GSM signals for positioning. To compare
them, we developed a positioning system in real world environment,
where realistic RSS measurements were collected. Multi-Layer
Perceptron (MLP) neural network was used as the approximation
function that maps RSS fingerprints and locations. Experimental
results indicate advantage of WLAN based approach in the sense of
lower localization error compared to GSM based approach, but GSM
signal coverage by far outreaches WLAN coverage and for some
LBS services requiring less precise accuracy our results indicate that
GSM positioning can also be a viable solution.
Abstract: At the time where electronic books, or e-Books, offer
students a fun way of learning , teachers who are used to the paper
text books may find it as a new challenge to use it as a part of
learning process. Precisely, there are various types of e-Books
available to suit students- knowledge, characteristics, abilities, and
interests. The paper discusses teachers- perceptions on the use of ebooks
as a paper text book in the classroom. A survey was conducted
on 72 teachers who use e-books as textbooks. It was discovered that a
majority of these teachers had good perceptions on the use of ebooks.
However, they had little problems using the devices. It can be
overcome with some strategies and a suggested framework.
Abstract: Complaints today have the ability to retain
customer loyalty using state of the art systems and strategies
in customer relationship management to analyze and respond
to a plethora of customer perception. The Majority of
companies are not aware of the beneficiary utilization of
customer complaints for the sake of quality improvements.
Also, some companies have problems determining how
resolution of complaints can be profitable. In this study, we
will define the problems and ascertain the importance of
customer management system on the companies. Furthermore,
we will determine the impact of such a system on efficiency,
confidence, profitability and customer complaints. Eventually,
we will develop methods and address the issues. In this paper,
we used an open-ended questionnaire and distributed that to
30 randomly chosen respondents which were the passengers in
an airport. We also define three hypotheses for our study and
we will validate each of them. Then using frequency, Chi-
Square and quality control method we optimized the size of
customers- negative feedback and improved the process of
customer retention.
Abstract: The use of neural networks is popular in various
building applications such as prediction of heating load, ventilation
rate and indoor temperature. Significant is, that only few papers deal
with indoor carbon dioxide (CO2) prediction which is a very good
indicator of indoor air quality (IAQ). In this study, a data-driven
modelling method based on multilayer perceptron network for indoor
air carbon dioxide in an apartment building is developed.
Temperature and humidity measurements are used as input variables
to the network. Motivation for this study derives from the following
issues. First, measuring carbon dioxide is expensive and sensors
power consumptions is high and secondly, this leads to short
operating times of battery-powered sensors. The results show that
predicting CO2 concentration based on relative humidity and
temperature measurements, is difficult. Therefore, more additional
information is needed.
Abstract: Human perceives color in categories, which may be
identified using color name such as red, blue, etc. The categorization
is unique for each human being. However despite the individual
differences, the categorization is shared among members in society.
This allows communication among them, especially when using
color name. Sociable robot, to live coexist with human and become
part of human society, must also have the shared color
categorization, which can be achieved through learning. Many
works have been done to enable computer, as brain of robot, to learn
color categorization. Most of them rely on modeling of human color
perception and mathematical complexities. Differently, in this work,
the computer learns color categorization through interaction with
humans. This work aims at developing the innate ability of the
computer to learn the human-like color categorization. It focuses on
the representation of color categorization and how it is built and
developed without much mathematical complexity.
Abstract: A study of the obtainable watermark data rate for information hiding algorithms is presented in this paper. As the perceptual entropy for wideband monophonic audio signals is in the range of four to five bits per sample, a significant amount of additional information can be inserted into signal without causing any perceptual distortion. Experimental results showed that transform domain watermark embedding outperforms considerably watermark embedding in time domain and that signal decompositions with a high gain of transform coding, like the wavelet transform, are the most suitable for high data rate information hiding. Keywords?Digital watermarking, information hiding, audio watermarking, watermark data rate.
Abstract: Based on 276 responses from academic staff in an
evaluation of an online learning environment (OLE), this paper
identifies those elements of the OLE that were most used and valued
by staff, those elements of the OLE that staff most wanted to see
improved, and those factors that most contributed to staff perceptions
that the use of the OLE enhanced their teaching. The most used and
valued elements were core functions, including accessing unit
information, accessing lecture/tutorial/lab notes, and reading online
discussions. The elements identified as most needing attention related
to online assessment: submitting assignments, managing assessment
items, and receiving feedback on assignments. Staff felt that using the
OLE enhanced their teaching when they were satisfied that their
students were able to access and use their learning materials, and
when they were satisfied with the professional development they
received and were confident with their ability to teach with the OLE.
Abstract: Changing in consumers lifestyles and food
consumption patterns provide a great opportunity in developing the
functional food sector in Malaysia. There is only a little knowledge
about whether Malaysian consumers are aware of functional food and
if so what image consumers have of this product. The objective of
this research is to determine the extent to which selected socioeconomic
characteristics and attitudes influence consumers-
awareness of functional food. A survey was conducted in the Klang
Valley, Malaysia where 439 respondents were interviewed using a
structured questionnaire. The result shows that most respondents
have a positive attitude towards functional food. For the binary
logistic estimation, the results indicate that age, income and other
factors such as concern about food safety, subscribing to cooking or
health magazines, being a vegetarian and consumers who have been
involved in a food production company significantly influence
Malaysian consumers- awareness towards functional food.
Abstract: This paper presents dynamic voltage collapse prediction on an actual power system using support vector machines.
Dynamic voltage collapse prediction is first determined based on the PTSI calculated from information in dynamic simulation output. Simulations were carried out on a practical 87 bus test system by considering load increase as the contingency. The data collected from the time domain simulation is then used as input to the SVM in which support vector regression is used as a predictor to determine the
dynamic voltage collapse indices of the power system. To reduce training time and improve accuracy of the SVM, the Kernel function type and Kernel parameter are considered. To verify the
effectiveness of the proposed SVM method, its performance is compared with the multi layer perceptron neural network (MLPNN). Studies show that the SVM gives faster and more accurate results for dynamic voltage collapse prediction compared with the MLPNN.
Abstract: The main aim of this study was to examine whether
people understand indicative conditionals on the basis of syntactic
factors or on the basis of subjective conditional probability. The
second aim was to investigate whether the conditional probability of
q given p depends on the antecedent and consequent sizes or derives
from inductive processes leading to establish a link of plausible cooccurrence
between events semantically or experientially associated.
These competing hypotheses have been tested through a 3 x 2 x 2 x 2
mixed design involving the manipulation of four variables: type of
instructions (“Consider the following statement to be true", “Read the
following statement" and condition with no conditional statement);
antecedent size (high/low); consequent size (high/low); statement
probability (high/low). The first variable was between-subjects, the
others were within-subjects. The inferences investigated were Modus
Ponens and Modus Tollens. Ninety undergraduates of the Second
University of Naples, without any prior knowledge of logic or
conditional reasoning, participated in this study.
Results suggest that people understand conditionals in a syntactic
way rather than in a probabilistic way, even though the perception of
the conditional probability of q given p is at least partially involved in
the conditionals- comprehension. They also showed that, in presence
of a conditional syllogism, inferences are not affected by the
antecedent or consequent sizes. From a theoretical point of view these
findings suggest that it would be inappropriate to abandon the idea
that conditionals are naturally understood in a syntactic way for the
idea that they are understood in a probabilistic way.
Abstract: This study proposes and tests a rescapturing elements of perceived gain and loss that, by perceived value of medical tourism products, influencintention of potential customers. Data from 301 usable qwere tested against the research model using the structmodeling approach. The results indicated that perceivedkey predictor of customer intentions. As for benefimedical quality, service quality and enjoyment wcomponents that significantly influenced the perceptiRegarding sacrifice, the effects of perceived risk on pewere significant. The findings can provide insights intohow destination countries can make medical tourism a wfor themselves and international patients.KeywordsMedical tourism, perceived valueintention.
Abstract: Emotion recognition is an important research field that finds lots of applications nowadays. This work emphasizes on recognizing different emotions from speech signal. The extracted features are related to statistics of pitch, formants, and energy contours, as well as spectral, perceptual and temporal features, jitter, and shimmer. The Artificial Neural Networks (ANN) was chosen as the classifier. Working on finding a robust and fast ANN classifier suitable for different real life application is our concern. Several experiments were carried out on different ANN to investigate the different factors that impact the classification success rate. Using a database containing 7 different emotions, it will be shown that with a proper and careful adjustment of features format, training data sorting, number of features selected and even the ANN type and architecture used, a success rate of 85% or even more can be achieved without increasing the system complicity and the computation time
Abstract: Predict daily global solar radiation (GSR) based on meteorological variables, using Multi-layer perceptron (MLP) neural networks is the main objective of this study. Daily mean air temperature, relative humidity, sunshine hours, evaporation, wind speed, and soil temperature values between 2002 and 2006 for Dezful city in Iran (32° 16' N, 48° 25' E), are used in this study. The measured data between 2002 and 2005 are used to train the neural networks while the data for 214 days from 2006 are used as testing data.
Abstract: Enterprises need a strategic plan to retain their skillful employees and provide their career management, sustain their existence, to have growth and leadership qualities, to reach the objectives to increase the value of the enterprise and to not to be affected from changing demographic structure. In the cases when the long term career expectations of skillful employees are in integrity with the enterprise’s interests, skill management process is directly related to the career management. With a long term plan, the enterprises should cover the labor force need that may arise in the future by using systematic career development programs and be prepared against developments for all times. Skill management is considered as a practice with which career mobility is planned for the skillful employee to be prepared for high level positions. Career planning is the planning of an employee’s progress or promotion within an organization for which he works by developing his knowledge, skills, abilities and motives. Career planning is considered as an individual’s planning his future and the position which he wants to have, the area which he want to work in, the objectives which he want to reach. With the aim of contributing the abovementioned discussion process, career management concept and its perception manner are examined in this study in a comparative manner.
Abstract: To motivate users to adopt and use information
systems effectively, the nature of motivation should be carefully
investigated. People are usually motivated within ongoing processes
which include a chain of states such as perception, stimulation,
motivation, actions and reactions and finally, satisfaction. This study
assumes that the relevant motivation processes should be executed in
a proper and continuous manner to be able to persistently motivate
and re-motivate people in organizational settings and towards
information systems. On this basis, the study attempts to propose
possible relationships between this process-nature view of
motivation in terms of the common chain of states and the nearly
unique properties of information systems as is perceived by users in
the sense of a knowledgeable and authoritative entity. In the
conclusion section, some guidelines for practitioners are suggested to
ease their tasks for motivating people to adopt and use information
systems.
Abstract: The main purpose of this research aimed to create tactile texture designed media for the blind used for extra learning outside classrooms in order to enhance imagination of the blind about Himmapan creatures, furthermore, the main objective of the research focused on improving the visual disabled perception to be equal to normal people. The target group of the research is blinded students studying in The Bangkok school for the blind between grade 4-6 in the second semester of 2011 who are able to read the braille language. The research methodology consisted of the field study and the documentary study related to the blind, tactile texture designed media and Himmapan creatures. 10 pictures of tactile texture designed media were created in the designing process which began after the analysis had conducted based the primary and secondary data. The works had presented to experts in the visual disabled field who evaluated the works. After approval, the works used as prototype to teach the blind. KeywordsBlind, Himmapan Creatures, Tactile Texture.
Abstract: Effective estimation of just noticeable distortion (JND) for images is helpful to increase the efficiency of a compression algorithm in which both the statistical redundancy and the perceptual redundancy should be accurately removed. In this paper, we design a DCT-based model for estimating JND profiles of color images. Based on a mathematical model of measuring the base detection threshold for each DCT coefficient in the color component of color images, the luminance masking adjustment, the contrast masking adjustment, and the cross masking adjustment are utilized for luminance component, and the variance-based masking adjustment based on the coefficient variation in the block is proposed for chrominance components. In order to verify the proposed model, the JND estimator is incorporated into the conventional JPEG coder to improve the compression performance. A subjective and fair viewing test is designed to evaluate the visual quality of the coding image under the specified viewing condition. The simulation results show that the JPEG coder integrated with the proposed DCT-based JND model gives better coding bit rates at visually lossless quality for a variety of color images.
Abstract: This article presents the development of a neural
network cognitive model for the classification and detection of
different frequency signals. The basic structure of the implemented
neural network was inspired on the perception process that humans
generally make in order to visually distinguish between high and low
frequency signals. It is based on the dynamic neural network concept,
with delays. A special two-layer feedforward neural net structure was
successfully implemented, trained and validated, to achieve
minimum target error. Training confirmed that this neural net
structure descents and converges to a human perception classification
solution, even when far away from the target.
Abstract: The binary phase-only filter digital watermarking
embeds the phase information of the discrete Fourier transform of the
image into the corresponding magnitudes for better image authentication.
The paper proposed an approach of how to implement watermark
embedding by quantizing the magnitude, with discussing how to
regulate the quantization steps based on the frequencies of the magnitude
coefficients of the embedded watermark, and how to embed the
watermark at low frequency quantization. The theoretical analysis and
simulation results show that algorithm flexibility, security, watermark
imperceptibility and detection performance of the binary phase-only
filter digital watermarking can be effectively improved with quantization
based watermark embedding, and the robustness against JPEG
compression will also be increased to some extent.
Abstract: The objective of this paper is to develop a neural
network-based residual generator to detect the fault in the actuators
for a specific communication satellite in its attitude control system
(ACS). First, a dynamic multilayer perceptron network with dynamic
neurons is used, those neurons correspond a second order linear
Infinite Impulse Response (IIR) filter and a nonlinear activation
function with adjustable parameters. Second, the parameters from the
network are adjusted to minimize a performance index specified by
the output estimated error, with the given input-output data collected
from the specific ACS. Then, the proposed dynamic neural network
is trained and applied for detecting the faults injected to the wheel,
which is the main actuator in the normal mode for the communication
satellite. Then the performance and capabilities of the proposed
network were tested and compared with a conventional model-based
observer residual, showing the differences between these two
methods, and indicating the benefit of the proposed algorithm to
know the real status of the momentum wheel. Finally, the application
of the methods in a satellite ground station is discussed.