Abstract: This paper investigates how the use of machine learning techniques can significantly predict the three major dimensions of learner-s emotions (pleasure, arousal and dominance) from brainwaves. This study has adopted an experimentation in which participants were exposed to a set of pictures from the International Affective Picture System (IAPS) while their electrical brain activity was recorded with an electroencephalogram (EEG). The pictures were already rated in a previous study via the affective rating system Self-Assessment Manikin (SAM) to assess the three dimensions of pleasure, arousal, and dominance. For each picture, we took the mean of these values for all subjects used in this previous study and associated them to the recorded brainwaves of the participants in our study. Correlation and regression analyses confirmed the hypothesis that brainwave measures could significantly predict emotional dimensions. This can be very useful in the case of impassive, taciturn or disabled learners. Standard classification techniques were used to assess the reliability of the automatic detection of learners- three major dimensions from the brainwaves. We discuss the results and the pertinence of such a method to assess learner-s emotions and integrate it into a brainwavesensing Intelligent Tutoring System.
Abstract: Currently in many major cities, public transit schedules
are disseminated through lists of routes, grids of stop times and
static maps. This paper describes a web based geographic information
system which disseminates the same schedule information through
intuitive GIS techniques. Using data from Calgary, Canada, an map
based interface has been created to allow users to see routes, stops and
moving buses all at once. Zoom and pan controls as well as satellite
imagery allows users to apply their personal knowledge about the
local geography to achieve faster, and more pertinent transit results.
Using asynchronous requests to web services, users are immersed
in an application where buses and stops can be added and removed
interactively, without the need to wait for responses to HTTP requests.
Abstract: Hidden failure in a protection system has been
recognized as one of the main reasons which may cause to a power
system instability leading to a system cascading collapse. This paper
presents a computationally systematic approach used to obtain the
estimated average probability of a system cascading collapse by
considering the effect of probability hidden failure in a protection
system. The estimated average probability of a system cascading
collapse is then used to determine the severe loading condition
contributing to the higher risk of critical system cascading collapse.
This information is essential to the system utility since it will assist
the operator to determine the highest point of increased system
loading condition prior to the event of critical system cascading
collapse.
Abstract: In this paper, we study the multi-scenario knapsack problem, a variant of the well-known NP-Hard single knapsack problem. We investigate the use of an adaptive algorithm for solving heuristically the problem. The used method combines two complementary phases: a size reduction phase and a dynamic 2- opt procedure one. First, the reduction phase applies a polynomial reduction strategy; that is used for reducing the size problem. Second, the adaptive search procedure is applied in order to attain a feasible solution Finally, the performances of two versions of the proposed algorithm are evaluated on a set of randomly generated instances.
Abstract: Self-organizing map (SOM) is a well known data reduction technique used in data mining. Data visualization can reveal structure in data sets that is otherwise hard to detect from raw data alone. However, interpretation through visual inspection is prone to errors and can be very tedious. There are several techniques for the automatic detection of clusters of code vectors found by SOMs, but they generally do not take into account the distribution of code vectors; this may lead to unsatisfactory clustering and poor definition of cluster boundaries, particularly where the density of data points is low. In this paper, we propose the use of a generic particle swarm optimization (PSO) algorithm for finding cluster boundaries directly from the code vectors obtained from SOMs. The application of our method to unlabeled call data for a mobile phone operator demonstrates its feasibility. PSO algorithm utilizes U-matrix of SOMs to determine cluster boundaries; the results of this novel automatic method correspond well to boundary detection through visual inspection of code vectors and k-means algorithm.
Abstract: Tourism researchers have recently focused on repeat visitation as a part of destination loyalty. Different models have also considered satisfaction as the main determinant of revisit intention, while findings in many studies show it as a continuous issue. This conceptual paper attempts at evaluating recent empirical studies on satisfaction and revisit intention. Based on limitations and gaps in recent studies, the current paper suggests a new model that would be more comprehensive than those in previous studies. The new model offers new relationships between antecedents (destination image, perceived value, specific novelty seeking, and distance to destination) and both of satisfaction and revisit intention. Revisit intention in turn is suggested to be measured in a temporal approach.
Abstract: This study describes the methodology for the development of a validated in-vitro in-vivo correlation (IVIVC) for metoprolol tartrate modified release dosage forms with distinctive release rate characteristics. Modified release dosage forms were formulated by microencapsulation of metoprolol tartrate into different amounts of ethylcellulose by non-solvent addition technique. Then in-vitro and in-vivo studies were conducted to develop and validate level A IVIVC for metoprolol tartrate. The values of regression co-efficient (R2-values) for IVIVC of T2 and T3 formulations were not significantly (p
Abstract: The burst of Web 2.0 technology and social
networking tools manifest different styles of learning and managing
knowledge among both knowledge workers and adult learners. In the
Western countries, open-learning concept has been made popular due
to the ease of use and the reach that the technology provides. In
Malaysia, there are still some gaps between the learners- acceptance
of technology and the full implementation of the technology in the
education system. There is a need to understand how adult learners,
who are knowledge workers, manage their personal knowledge via
social networking tools, especially in their learning process. Four
processes of personal knowledge management (PKM) and four
cognitive enablers are proposed supported by analysed data on adult
learners in a university. The model derived from these processes and
enablers is tested and presented, with recommendations on features to be included in adult learners- learning environment.
Abstract: In this paper a new Genetic Algorithm based on a heuristic operator and Centre of Mass selection operator (CMGA) is designed for the unbounded knapsack problem(UKP), which is NP-Hard combinatorial optimization problem. The proposed genetic algorithm is based on a heuristic operator, which utilizes problem specific knowledge. This center of mass operator when combined with other Genetic Operators forms a competitive algorithm to the existing ones. Computational results show that the proposed algorithm is capable of obtaining high quality solutions for problems of standard randomly generated knapsack instances. Comparative study of CMGA with simple GA in terms of results for unbounded knapsack instances of size up to 200 show the superiority of CMGA. Thus CMGA is an efficient tool of solving UKP and this algorithm is competitive with other Genetic Algorithms also.
Abstract: Amphawa is the most popular weekend destination for
both domestic and international tourists in Thailand. More than 112
homestays and resorts have been developed along the water
resources. This research aims to initiate appropriate environmental
management system for riverside tourist accommodations in
Amphawa by investigating current environmental characteristics.
Eighty-eight riverside tourist accommodations were survey from
specific questionnaire, GPS data were also gathered for spatial
analysis. The results revealed that the accommodations are welled
manage in regards to some environmental aspects. In order to reduce
economic costs, energy efficiency equipment is utilized. A substantial
number of tourist accommodations encouraged waste separation,
followed by transfer to local administration organization. Grease
traps also utilized in order to decrease chemical discharged, grease
and oil from canteen and restaurants on natural environment. The
most notable mitigation is to initiate environmental friendly cleansers
for tourist accommodation along the riverside in tourism destinations.
Abstract: In this paper, a solution is presented for a robotic
manipulation problem in industrial settings. The problem is sensing
objects on a conveyor belt, identifying the target, planning and
tracking an interception trajectory between end effector and the
target. Such a problem could be formulated as combining object
recognition, tracking and interception. For this purpose, we integrated
a vision system to the manipulation system and employed tracking
algorithms. The control approach is implemented on a real industrial
manipulation setting, which consists of a conveyor belt, objects
moving on it, a robotic manipulator, and a visual sensor above the
conveyor. The trjectory for robotic interception at a rendezvous point
on the conveyor belt is analytically calculated. Test results show that
tracking the raget along this trajectory results in interception and
grabbing of the target object.
Abstract: An iterative algorithm is proposed and tested in Cournot Game models, which is based on the convergence of sequential best responses and the utilization of a genetic algorithm for determining each player-s best response to a given strategy profile of its opponents. An extra outer loop is used, to address the problem of finite accuracy, which is inherent in genetic algorithms, since the set of feasible values in such an algorithm is finite. The algorithm is tested in five Cournot models, three of which have convergent best replies sequence, one with divergent sequential best replies and one with “local NE traps"[14], where classical local search algorithms fail to identify the Nash Equilibrium. After a series of simulations, we conclude that the algorithm proposed converges to the Nash Equilibrium, with any level of accuracy needed, in all but the case where the sequential best replies process diverges.
Abstract: People nowadays love to travel around the world.
Regardless of their location and time, they especially Muslims still need to perform their five times prayer. Normally for travelers, they
need to bring maps, compass and for Muslim, they even have to bring Qibla pointer when they travel. It is slightly difficult to
determine the Qibla direction and to know the time for each prayer. In this paper we present a new electronic device called Universal Qibla and Prayer Time Finder to locate the Qibla direction and to determine each prayer time based on the current user-s location. This device use PIC microcontroller equipped with digital compass and
Global Positioning System (GPS) where it will display the exact Qibla direction and prayer time automatically at any place in the world. This device is reliable, user friendly and accurate in
determining the Qibla direction and prayer time.
Abstract: The use of a Geographic Information System (GIS) in
roadway lighting to show the state of street-lighting and nighttime
accident is demonstrated. Geographical maps were generated
showing colored streets based on how much of the street's length is
illuminated. The night to daytime accidents ratio at intersections
were found along with the state of lighting at those intersections.
The result is a method to show the state of street-lighting at roads and
intersections and a quick guide for decision makers to implement
strategies for better street-lighting to reduce night time traffic
accidents in a particular district.
Abstract: In this paper, the phase control antenna array synthesis
is presented. The problem is formulated as a constrained optimization
problem that imposes nulls with prescribed level while maintaining
the sidelobe at a prescribed level. For efficient use of the algorithm
memory, compared to the well known Particle Swarm Optimization
(PSO), the Accelerated Particle Swarm Optimization (APSO) is used
to estimate the phase parameters of the synthesized array. The
objective function is formed using a main objective and set of
constraints with penalty factors that measure the violation of each
feasible solution in the search space to each constraint. In this case
the obtained feasible solution is guaranteed to satisfy all the
constraints. Simulation results have shown significant performance
increases and a decreased randomness in the parameter search space
compared to a single objective conventional particle swarm
optimization.
Abstract: Random Access Memory (RAM) is an important
device in computer system. It can represent the snapshot on how the
computer has been used by the user. With the growth of its
importance, the computer memory has been an issue that has been
discussed in digital forensics. A number of tools have been developed
to retrieve the information from the memory. However, most of the
tools have their limitation in the ability of retrieving the important
information from the computer memory. Hence, this paper is aimed
to discuss the limitation and the setback for two main techniques such
as process signature search and process enumeration. Then, a new
hybrid approach will be presented to minimize the setback in both
individual techniques. This new approach combines both techniques
with the purpose to retrieve the information from the process block
and other objects in the computer memory. Nevertheless, the basic
theory in address translation for x86 platforms will be demonstrated
in this paper.
Abstract: Large full frequency band gaps of surface and bulk
acoustic waves in two-dimensional phononic band structures with
hollow cylinders are addressed in this paper. It is well-known that
absolute frequency band gaps are difficultly obtained in a band
structure consisted of low-acoustic-impedance cylinders in
high-acoustic-impedance host materials such as PMMA/Ni band
structures. Phononic band structures with hollow cylinders are
analyzed and discussed to obtain large full frequency band gaps not
only for bulk modes but also for surface modes. The tendency of
absolute frequency band gaps of surface and bulk acoustic waves is
also addressed by changing the inner radius of hollow cylinders in this
paper. The technique and this kind of band structure are useful for
tuning the frequency band gaps and the design of acoustic waveguides.
Abstract: In this paper, the deformation modes of a compact impact absorption member subjected to axial compression are investigated using finite element method and experiments. A multiple combination compact impact absorption member, referred to as a 'compress-expand member', is proposed to substitute the conventional thin-walled circular tube. This study found that the proposed compact impact absorption member has stable load increase characteristics and a wider range of high load efficiency (Pave/Pmax) than the thin-walled circular tube. Moreover, the proposed compact impact absorption member can absorb larger loads in a smaller radius than the thin-walled cylindrical tube, as it can maintain its stable deformation in increased wall thicknesses.
Abstract: This paper presents design and characterization of a
microaccelerometer designated for integration into cataract surgical
probe to detect hardness of different eye tissues during cataract
surgery. Soft posterior lens capsule of eye can be easily damaged in
comparison with hard opaque lens since the surgeon can not see
directly behind cutting needle during the surgery. Presence of
microsensor helps the surgeon to avoid rupturing posterior lens
capsule which if occurs leads to severe complications such as
glaucoma, infection, or even blindness. The microsensor having
overall dimensions of 480 μm x 395 μm is able to deliver significant
capacitance variations during encountered vibration situations which
makes it capable to distinguish between different types of tissue.
Integration of electronic components on chip ensures high level of
reliability and noise immunity while minimizes space and power
requirements. Physical characteristics and results on performance
testing, proves integration of microsensor as an effective tool to aid
the surgeon during this procedure.
Abstract: Malaria is transmitted to the human by biting of
infected Anopheles mosquitoes. This disease is a serious, acute and
chronic relapsing infection to humans. Fever, nausea, vomiting, back
pain, increased sweating anemia and splenomegaly (enlargement of
the spleen) are the symptoms of the patients who infected with this
disease. It is caused by the multiplication of protozoa parasite of the
genus Plasmodium. Plasmodium falciparum, Plasmodium vivax,
Plasmodium malariae and Plasmodium ovale are the four types of
Plasmodium malaria. A mathematical model for the transmission of
Plasmodium Malaria is developed in which the human and vector
population are divided into two classes, the susceptible and the
infectious classes. In this paper, we formulate the dynamical model
of Plasmodium falciparum and Plasmodium vivax malaria. The
standard dynamical analysis is used for analyzing the behavior for
the transmission of this disease. The Threshold condition is found
and numerical results are shown to confirm the analytical results.