Abstract: The purpose of this paper is to investigate the
influence of a number of variables on the conditional mean and
conditional variance of credit spread changes. The empirical analysis
in this paper is conducted within the context of bivariate GARCH-in-
Mean models, using the so-called BEKK parameterization. We show
that credit spread changes are determined by interest-rate and equityreturn
variables, which is in line with theory as provided by the
structural models of default. We also identify the credit spread
change volatility as an important determinant of credit spread
changes, and provide evidence on the transmission of volatility
between the variables under study.
Abstract: This paper presents an assessment study conducted
among the distance learners in India. Open and distance learning
systems have traveled a long way since its inception and its journey
has witnessed the evolution and adoption of different generations of
technology. This study focuses on the distant learners in India.
Sampling for this study has been derived from the mass enrollment
from Tamil Nadu area, a southern state of India. Learners were
chosen from dual mode universities, private universities, Tamil Nadu
Open University and IGNOU. The main focus of the study is to
examine the coverage and appropriation of students support services
and learning aids. It explores two aspects: the facilities available and
the awareness and use of such services. It includes, self-learning
materials, face-to-face counseling, multimedia learning materials,
website, e-learning, radio and television services etc. While exploring
the student-s perspective on these learning aspects, it is important to
understand the perspectives of the teachers. Two different interests
are visible among the teachers. Majority of the teachers support faceto-
face counseling. However, the young teachers are in favour of
online learning and multimedia supports in teaching. Through the
awareness is somewhat high, the actual participation in online is very
low. This is due to the inadequate infrastructure as well as the
traditional attitudes of the teachers. Still the face-to-face sessions
remain popular than online.
Abstract: Recognizing human action from videos is an active
field of research in computer vision and pattern recognition. Human
activity recognition has many potential applications such as video
surveillance, human machine interaction, sport videos retrieval and
robot navigation. Actually, local descriptors and bag of visuals words
models achieve state-of-the-art performance for human action
recognition. The main challenge in features description is how to
represent efficiently the local motion information. Most of the
previous works focus on the extension of 2D local descriptors on 3D
ones to describe local information around every interest point. In this
paper, we propose a new spatio-temporal descriptor based on a spacetime
description of moving points. Our description is focused on an
Accordion representation of video which is well-suited to recognize
human action from 2D local descriptors without the need to 3D
extensions. We use the bag of words approach to represent videos.
We quantify 2D local descriptor describing both temporal and spatial
features with a good compromise between computational complexity
and action recognition rates. We have reached impressive results on
publicly available action data set
Abstract: The purpose of this study was to determine the most satisfying and frustrating aspects of ICT (Information and Communications Technologies) teaching in Turkish schools. Another aim was to compare these aspects based-on ICT teachers- selfefficacy. Participants were 119 ICT teachers from different geographical areas of Turkey. Participants were asked to list salient satisfying and frustrating aspects of ICT teaching, and to fill out the Self-Efficacy Scale for ICT Teachers. Results showed that the high self-efficacy teachers listed more positive and negative aspects of ICT teaching then did the low self-efficacy teachers. The satisfying aspects of ICT teaching were the dynamic nature of ICT subject, higher student interest, having opportunity to help other subject teachers, and lecturing in well-equipped labs, whereas the most frequently cited frustrating aspects of ICT teaching were ICT-related extra works of schools and colleagues, shortages of hardware and technical problems, indifferent students, insufficient teaching time, and the status of ICT subject in school curriculum. This information could be useful in redesigning ICT teachers- roles and responsibilities as well as job environment in schools.
Abstract: This paper introduces an isolated and unique ancient language Burushaski, spoken in Hunza, Nagar, Yasin and parts of Gilgit in the Northern Areas of Pakistan. It explains the working mechanism of Multi Language Text Editor for Urdu and Burushaski. It is developed under the use of ISO/IEC 10646 Unicode standards for Urdu and Burushaski open-type fonts. It gives an ample opportunity to this regional ancient language to have a modern Information technology for its promotion and preservation. The main objective of this research paper is to help preserve the heritage of such rare languages and give smart way of automation. It also facilitates to those who are interested in undertaking research on Burushaski or keen to trace fonatic relationship between the national Urdu language and Burushaski. Since this editor covers both Burushaski and Urdu so it can play an important role to introduce Burusho linguistic culture to the world at large. Precisely, as a result of this research paper, Burushaski publication through IT means would be possible.
Abstract: Academics and researchers are interested in the effects of social media on college students, with a specific focus on the most popular social media website; Facebook. Previous studied have found contradictory result on the relationship between Facebook usage and the student engagement with positive, detrimental and no significant relationships. However, these studies were limited to western higher education system. This paper fills a gap in the literature by using a sample (300) of Sri Lankan management undergraduates to examine the relationship between Facebook usage and student engagement. Student engagement was measured 35 item scale based on the National Survey of Student Engagement and Facebook usage by Facebook intensity scale. Descriptive statistics, path analysis and structural equation modeling were applied as statistical tools and techniques. Results indicate that student engagement scale was significantly negatively related with the Facebook usage with the influence from student engagement on Facebook usage.
Abstract: Nowadays, precipitation prediction is required for proper planning and management of water resources. Prediction with neural network models has received increasing interest in various research and application domains. However, it is difficult to determine the best neural network architecture for prediction since it is not immediately obvious how many input or hidden nodes are used in the model. In this paper, neural network model is used as a forecasting tool. The major aim is to evaluate a suitable neural network model for monthly precipitation mapping of Myanmar. Using 3-layerd neural network models, 100 cases are tested by changing the number of input and hidden nodes from 1 to 10 nodes, respectively, and only one outputnode used. The optimum model with the suitable number of nodes is selected in accordance with the minimum forecast error. In measuring network performance using Root Mean Square Error (RMSE), experimental results significantly show that 3 inputs-10 hiddens-1 output architecture model gives the best prediction result for monthly precipitation in Myanmar.
Abstract: This study was a part of the three-year longitudinal
research on setting up an math learning model for the disadvantaged
students in Taiwan. A target 2nd grade class with 10 regular students
and 6 disadvantaged students at a disadvantaged area in Taipei
participated in this study. Two units of a market basal math textbook
concerning fractions, three-dimensional figures, weight and capacity
were adapted to enhance their math learning motivations, confidences
and effects. The findings were (1) curriculum adaptation was effective
on enhancing students- learning motivations, confidences and effects;
(2) story-type problems and illustrations decreased difficulties on
understanding math language for students from new immigrant
families and students with special needs; (3) “concrete –
semiconcrete – abstract" teaching strategies and hands-on activities
were essential to raise students learning interests and effects; and (4)
curriculum adaptation knowledge and skills needed to be included in
the pre- and in-service teacher training programs.
Abstract: A higher order spline interpolated contour obtained
with up-sampling of homogenously distributed coordinates for
segmentation of kidney region in different classes of ultrasound
kidney images has been developed and presented in this paper. The
performance of the proposed method is measured and compared with
modified snake model contour, Markov random field contour and
expert outlined contour. The validation of the method is made in
correspondence with expert outlined contour using maximum coordinate
distance, Hausdorff distance and mean radial distance
metrics. The results obtained reveal that proposed scheme provides
optimum contour that agrees well with expert outlined contour.
Moreover this technique helps to preserve the pixels-of-interest
which in specific defines the functional characteristic of kidney. This
explores various possibilities in implementing computer-aided
diagnosis system exclusively for US kidney images.
Abstract: The paper investigates downtrend algorithm and
trading strategy based on chart pattern recognition and technical
analysis in futures market. The proposed chart formation is a pattern
with the lowest low in the middle and one higher low on each side.
The contribution of this paper lies in the reinforcement of statements
about the profitability of momentum trend trading strategies.
Practical benefit of the research is a trading algorithm in falling
markets and back-test analysis in futures markets. When based on
daily data, the algorithm has generated positive results, especially
when the market had downtrend period. Downtrend algorithm can be
applied as a hedge strategy against possible sudden market crashes.
The proposed strategy can be interesting for futures traders, hedge
funds or scientific researchers performing technical or algorithmic
market analysis based on momentum trend trading.
Abstract: There has been a growing interest in implementing humanoid avatars in networked virtual environment. However, most existing avatar communication systems do not take avatars- social backgrounds into consideration. This paper proposes a novel humanoid avatar animation system to represent personalities and facial emotions of avatars based on culture, profession, mood, age, taste, and so forth. We extract semantic keywords from the input text through natural language processing, and then the animations of personalized avatars are retrieved and displayed according to the order of the keywords. Our primary work is focused on giving avatars runtime instruction from multiple natural languages. Experiments with Chinese, Japanese and English input based on the prototype show that interactive avatar animations can be displayed in real time and be made available online. This system provides a more natural and interesting means of human communication, and therefore is expected to be used for cross-cultural communication, multiuser online games, and other entertainment applications.
Abstract: In this paper three basic approaches and different
methods under each of them for extracting region of interest (ROI)
from stationary images are explored. The results obtained for each of
the proposed methods are shown, and it is demonstrated where each
method outperforms the other. Two main problems in ROI
extraction: the channel selection problem and the saliency reversal
problem are discussed and how best these two are addressed by
various methods is also seen. The basic approaches are 1) Saliency
based approach 2) Wavelet based approach 3) Clustering based
approach. The saliency approach performs well on images containing
objects of high saturation and brightness. The wavelet based
approach performs well on natural scene images that contain regions
of distinct textures. The mean shift clustering approach partitions the
image into regions according to the density distribution of pixel
intensities. The experimental results of various methodologies show
that each technique performs at different acceptable levels for
various types of images.
Abstract: As a vital activity for companies, new product
development (NPD) is also a very risky process due to the high
uncertainty degree encountered at every development stage and the
inevitable dependence on how previous steps are successfully
accomplished. Hence, there is an apparent need to evaluate new
product initiatives systematically and make accurate decisions under
uncertainty. Another major concern is the time pressure to launch a
significant number of new products to preserve and increase the
competitive power of the company. In this work, we propose an
integrated decision-making framework based on neural networks and
fuzzy logic to make appropriate decisions and accelerate the
evaluation process. We are especially interested in the two initial
stages where new product ideas are selected (go/no go decision) and
the implementation order of the corresponding projects are
determined. We show that this two-staged intelligent approach allows
practitioners to roughly and quickly separate good and bad product
ideas by making use of previous experiences, and then, analyze a
more shortened list rigorously.
Abstract: Today, people are more interested in the foods
beneficial on their health. However, there are still lacks of accurate
knowledge in the field of biological properties, functional properties,
including the application of legume in foods. This study focused on
antioxidant activity of soybean (SB) and fermented soybean (FSB)
crude extracts evaluating to have more information in fortification SB
and FSB crude extracts in food products and/or dietary supplement.
SB and FSB crude extracts were prepared by infusion with water and
ethanol. The antioxidant activity of crude extracts was studied with
DPPH and ABTS assay including commercial standard. From both
DPPH and ABTS assay, the antioxidant activity of SB and FSB water
crude extract showed higher antioxidant activity than ethanol crude
extract, and FSB crude extract showed higher antioxidant activity
than SB crude extract. In DPPH assay, BHT and vitamin C showed
IC50 values at 0.241, 0.039 mg/ml, in ABTS assay. In addition,
Trolox showed IC50 at 0.058 mg/ml respectively. FSB water crude
extract showed high antioxidant activity. Finally, the functional
properties study of both water and ethanol crude extracts should be
done for beneficial in application of these extracts in food products
and dietary supplement in the near future.
Abstract: One very interesting field of research in Pattern Recognition that has gained much attention in recent times is Gesture Recognition. In this paper, we consider a form of dynamic hand gestures that are characterized by total movement of the hand (arm) in space. For these types of gestures, the shape of the hand (palm) during gesturing does not bear any significance. In our work, we propose a model-based method for tracking hand motion in space, thereby estimating the hand motion trajectory. We employ the dynamic time warping (DTW) algorithm for time alignment and normalization of spatio-temporal variations that exist among samples belonging to the same gesture class. During training, one template trajectory and one prototype feature vector are generated for every gesture class. Features used in our work include some static and dynamic motion trajectory features. Recognition is accomplished in two stages. In the first stage, all unlikely gesture classes are eliminated by comparing the input gesture trajectory to all the template trajectories. In the next stage, feature vector extracted from the input gesture is compared to all the class prototype feature vectors using a distance classifier. Experimental results demonstrate that our proposed trajectory estimator and classifier is suitable for Human Computer Interaction (HCI) platform.
Abstract: Classification is an interesting problem in functional
data analysis (FDA), because many science and application problems
end up with classification problems, such as recognition, prediction,
control, decision making, management, etc. As the high dimension
and high correlation in functional data (FD), it is a key problem to
extract features from FD whereas keeping its global characters, which
relates to the classification efficiency and precision to heavens. In this
paper, a novel automatic method which combined Genetic Algorithm
(GA) and classification algorithm to extract classification features is
proposed. In this method, the optimal features and classification model
are approached via evolutional study step by step. It is proved by
theory analysis and experiment test that this method has advantages in
improving classification efficiency, precision and robustness whereas
using less features and the dimension of extracted classification
features can be controlled.
Abstract: New software protection product called “Obfuscation
Studio" is presented in the paper. Several obfuscating modules that
are already implemented are described. Some theoretical data is
presented, that shows the potency and effectiveness of described
obfuscation methods. “Obfuscation Studio" is being implemented for
protecting programs written for .NET platform, but the described
methods can also be interesting for other applications.
Abstract: Bringing change to the housing industry requires
multiple efforts from various angles especially to overcome any
resistances in the form of technology, human aspects, financial and
resources. The transition from conventional to sustainable approach
consumes time as it requires changes from different facets in the
industry ranging from individual, organisational to industry level. In
Malaysia, there are various efforts to bring green into the industry but
the progress is low-moderate. Will the current efforts bear larger
fruits in the near future? This study examines the perceptions of the
developers in Malaysia on the future of the green housing sector for
the next 5 years. The introduction of GBI rating system, improvement
of awareness and knowledge among the stakeholders, support from
the government and local industry and the effect of competitive
advantage would support brighter future. Meanwhile, the status quo
in rules and regulation, lack of public interest and demand,
organization disinterest, local authority enforcement and project cost
escalation would hinder a faster progress.
Abstract: In Thailand, both the 1997 and the current 2007 Thai Constitutions have mentioned the establishment of independent organizations as a new mechanism to play a key role in proposing policy recommendations to national decision-makers in the interest of collective consumers. Over the last ten years, no independent organizations have yet been set up. Evidently, nobody could point out who should be key players in establishing provincial independent consumer bodies. The purpose of this study was to find definitive stakeholders in establishing and developing independent consumer bodies in a Thai context. This was a cross-sectional study between August and September 2007, using a postal questionnaire with telephone follow-up. The questionnaire was designed and used to obtain multiple stakeholder assessment of three key attributes (power, interest and influence). Study population was 153 stakeholders associated with policy decision-making, formulation and implementation processes of civil-based consumer protection in pilot provinces. The population covered key representatives from five sectors (academics, government officers, business traders, mass media and consumer networks) who participated in the deliberative forums at 10 provinces. A 49.7% response rate was achieved. Data were analyzed, comparing means of three stakeholder attributes and classification of stakeholder typology. The results showed that the provincial health officers were the definitive stakeholders as they had legal power, influence and interest in establishing and sustaining the independent consumer bodies. However, only a few key representatives of the provincial health officers expressed their own paradigm on the civil-based consumer protection. Most provincial health officers put their own standpoint of building civic participation at only a plan-implementation level. For effective policy implementation by the independent consumer bodies, the Thai government should provide budgetary support for the operation of the provincial health officers with their paradigm shift as well as their own clarified standpoint on corporate governance.
Abstract: The neural stimulation has been gaining much interest in neuromodulation research and clinical trials. For efficiency, there is a need for variable electrical stimulation such as current and voltage stimuli as well as wireless framework. In this regard, we develop the wireless neural stimulator capable of voltage and current stimuli. The system consists of ZigBee which is a wireless communication module and stimulus generator. The stimulus generator with 8-bits resolution enable both mono-polar and bi-polar waveform in voltage (-3.3~3.3V) and current(-330~330µA) stimulus mode which is controllable. The experimental results suggest that the proposed neural stimulator can play a role as an effective approach for neuromodulation.