Abstract: Human skin detection recognized as the primary step in most of the applications such as face detection, illicit image filtering, hand recognition and video surveillance. The performance of any skin detection applications greatly relies on the two components: feature extraction and classification method. Skin color is the most vital information used for skin detection purpose. However, color feature alone sometimes could not handle images with having same color distribution with skin color. A color feature of pixel-based does not eliminate the skin-like color due to the intensity of skin and skin-like color fall under the same distribution. Hence, the statistical color analysis will be exploited such mean and standard deviation as an additional feature to increase the reliability of skin detector. In this paper, we studied the effectiveness of statistical color feature for human skin detection. Furthermore, the paper analyzed the integrated color and texture using eight classifiers with three color spaces of RGB, YCbCr, and HSV. The experimental results show that the integrating statistical feature using Random Forest classifier achieved a significant performance with an F1-score 0.969.
Abstract: Urbanization, population growth, climate change and the current increase in water demand have made the adoption of innovative demand management strategies crucial to the water industry. Water conservation in urban areas has to be improved by encouraging consumers to adopt more sustainable habits and behaviours. This includes informing and educating them about their households’ water consumption and advising them about ways to achieve significant savings on a daily basis. This paper presents a study conducted in the context of the European FP7 WISDOM Project. By integrating innovative Information and Communication Technologies (ICT) frameworks, this project aims at achieving a change in water savings. More specifically, behavioural change will be attempted by implementing smart meters and in-home displays in a trial group of selected households within Cardiff (UK). Using this device, consumers will be able to receive feedback and information about their consumption but will also have the opportunity to compare their consumption to the consumption of other consumers and similar households. Following an initial survey, it appeared necessary to implement these in-home displays in a way that matches consumer's motivations to save water. The results demonstrated the importance of various factors influencing people’s daily water consumption. Both the relevant literature on the subject and the results of our survey therefore led us to include within the in-home device a variety of elements. It first appeared crucial to make consumers aware of the economic aspect of water conservation and especially of the significant financial savings that can be achieved by reducing their household’s water consumption on the long term. Likewise, reminding participants of the impact of their consumption on the environment by making them more aware of water scarcity issues around the world will help increasing their motivation to save water. Additionally, peer pressure and social comparisons with neighbours and other consumers, accentuated by the use of online social networks such as Facebook or Twitter, will likely encourage consumers to reduce their consumption. Participants will also be able to compare their current consumption to their past consumption and to observe the consequences of their efforts to save water through diverse graphs and charts. Finally, including a virtual water game within the display will help the whole household, children and adults, to achieve significant reductions by providing them with simple tips and advice to save water on a daily basis. Moreover, by setting daily and weekly goals for them to reach, the game will expectantly generate cooperation between family members. Members of each household will indeed be encouraged to work together to reduce their water consumption within different rooms of the house, such as the bathroom, the kitchen, or the toilets. Overall, this study will allow us to understand the elements that attract consumers the most and the features that are most commonly used by the participants. In this way, we intend to determine the main factors influencing water consumption in order to identify the measures that will most encourage water conservation in both the long and short term.
Abstract: This paper compares the findings of two studies conducted to determine the effectiveness of simulation-based, hands-on and feedback mechanism on students learning by answering the following questions: 1). Does the use of simulation improve students’ learning outcomes? 2). How do students perceive the instructional design features embedded in the simulation program such as exploration and scaffolding support in learning new concepts? 3.) What is the effect of feedback mechanisms on students’ learning in the use of simulation-based labs? The paper also discusses the other aspects of findings which reveal that simulation by itself is not very effective in promoting student learning. Simulation becomes effective when it is followed by hands-on activity and feedback mechanisms. Furthermore, the paper presents recommendations for improving student learning through the use of simulation-based, hands-on, and feedback-based teaching methodologies.
Abstract: Texture is an important characteristic in real and
synthetic scenes. Texture analysis plays a critical role in inspecting
surfaces and provides important techniques in a variety of
applications. Although several descriptors have been presented to
extract texture features, the development of object recognition is still a
difficult task due to the complex aspects of texture. Recently, many
robust and scaling-invariant image features such as SIFT, SURF and
ORB have been successfully used in image retrieval and object
recognition. In this paper, we have tried to compare the performance
for texture classification using these feature descriptors with k-means
clustering. Different classifiers including K-NN, Naive Bayes, Back
Propagation Neural Network , Decision Tree and Kstar were applied in
three texture image sets － UIUCTex, KTH-TIPS and Brodatz,
respectively. Experimental results reveal SIFTS as the best average
accuracy rate holder in UIUCTex, KTH-TIPS and SURF is
advantaged in Brodatz texture set. BP neuro network works best in the
test set classification among all used classifiers.
Abstract: Health diseases have a vital significance affecting human being's life and life quality. Sudden death events can be prevented owing to early diagnosis and treatment methods. Electrical signals, taken from the human being's body using non-invasive methods and showing the heart activity is called Electrocardiogram (ECG). The ECG signal is used for following daily activity of the heart by clinicians. Heart Rate Variability (HRV) is a physiological parameter giving the variation between the heart beats. ECG data taken from MITBIH Arrhythmia Database is used in the model employed in this study. The detection of arrhythmic heart beats is aimed utilizing the features extracted from the HRV time domain parameters. The developed model provides a satisfactory performance with ~89% accuracy, 91.7 % sensitivity and 85% specificity rates for the detection of arrhythmic beats.
Abstract: Liver cancer is one of the common diseases that cause the death. Early detection is important to diagnose and reduce the incidence of death. Improvements in medical imaging and image processing techniques have significantly enhanced interpretation of medical images. Computer-Aided Diagnosis (CAD) systems based on these techniques play a vital role in the early detection of liver disease and hence reduce liver cancer death rate. This paper presents an automated CAD system consists of three stages; firstly, automatic liver segmentation and lesion’s detection. Secondly, extracting features. Finally, classifying liver lesions into benign and malignant by using the novel contrasting feature-difference approach. Several types of intensity, texture features are extracted from both; the lesion area and its surrounding normal liver tissue. The difference between the features of both areas is then used as the new lesion descriptors. Machine learning classifiers are then trained on the new descriptors to automatically classify liver lesions into benign or malignant. The experimental results show promising improvements. Moreover, the proposed approach can overcome the problems of varying ranges of intensity and textures between patients, demographics, and imaging devices and settings.
Abstract: In this paper, we analyze NEtwork MObility (NEMO) supporting problems in Content-Centric Networking (CCN), and propose the CCN-NEMO which can well support the deployment of the content-centric paradigm in large-scale mobile Internet. The CCN-NEMO extends the signaling message of the basic CCN protocol, to support the mobility discovery and fast trigger of Interest re-issuing during the network mobility. Besides, the Mobile Router (MR) is extended to optimize the content searching and relaying in the local subnet. These features can be employed by the nested NEMO to maximize the advantages of content retrieving with CCN. Based on the analysis, we compare the performance on handover latency between the basic CCN and our proposed CCN-NEMO. The results show that our scheme can facilitate the content-retrieving in the NEMO scenario with improved performance.
Abstract: In this paper, a single phase soft switched Zero Voltage Transition and Zero Current Transition (ZVT-ZCT) Power Factor Correction (PFC) boost converter is proposed. In the proposed PFC converter, the main switch turns on with ZVT and turns off with ZCT without any additional voltage or current stresses. Auxiliary switch turns on and off with zero current switching (ZCS). Also, the main diode turns on with zero voltage switching (ZVS) and turns off with ZCS. The proposed converter has features like low cost, simple control and structure. The output current and voltage are controlled by the proposed PFC converter in wide line and load range. The theoretical analysis of converter is clarified and the operating steps are given in detail. The simulation results of converter are obtained for 500 W and 100 kHz. It is observed that the semiconductor devices operate with soft switching (SS) perfectly. So, the switching power losses are minimum. Also, the proposed converter has 0.99 power factor with sinusoidal current shape.
Abstract: To increase the quality of learning, teacher and learner need mutual effort for realization of educational value. For this purpose, we need to manage the co-creational education among teacher and learners. In this research, we try to find a feature of co-creational education. To be more precise, we analyzed learners’ reports by natural language processing, and extract some features that describe the state of the co-creational education.
Abstract: In order to understand whether there is a better than the
learning function of learning methods and improve the CAD Courses
for enterprise’s design human resource development, this research is
applied in learning practical learning computer graphics software. In
this study, Revit building information model for learning content,
design of two different modes of learning curriculum to learning,
learning functions, respectively, and project learning. Via a post-test,
questionnaires and student interviews, etc., to study the effectiveness
of a comparative analysis of two different modes of learning. Students
participate in a period of three weeks after a total of nine-hour course,
and finally written and hands-on test. In addition, fill in the
questionnaire response by the student learning, a total of fifteen
questionnaire title, problem type into the base operating software,
application software and software-based concept features three
directions. In addition to the questionnaire, and participants were
invited to two different learning methods to conduct interviews to
learn more about learning students the idea of two different modes.
The study found that the ad hoc short-term courses in learning, better
learning outcomes. On the other hand, functional style for the whole
course students are more satisfied, and the ad hoc style student is
difficult to accept the ad hoc style of learning.
Abstract: The effectiveness of microchannels in enhancing heat
transfer has been demonstrated in the semiconductor industry. In
order to tap the microscale heat transfer effects into macro
geometries, overcoming the cost and technological constraints,
microscale passages were created in macro geometries machined
using conventional fabrication methods. A cylindrical insert was
placed within a pipe, and geometrical profiles were created on the
outer surface of the insert to enhance heat transfer under steady-state
single-phase liquid flow conditions. However, while heat transfer
coefficient values of above 10 kW/m2·K were achieved, the heat
transfer enhancement was accompanied by undesirable pressure drop
increment. Therefore, this study aims to address the high pressure
drop issue using Constructal theory, a universal design law for both
animate and inanimate systems. Two designs based on Constructal theory were developed to study
the effectiveness of Constructal features in reducing the pressure drop
increment as compared to parallel channels, which are commonly
found in microchannel fabrication. The hydrodynamic and heat
transfer performance for the Tree insert and Constructal fin (Cfin)
insert were studied using experimental methods, and the underlying
mechanisms were substantiated by numerical results. In technical
terms, the objective is to achieve at least comparable increment in
both heat transfer coefficient and pressure drop, if not higher
increment in the former parameter. Results show that the Tree insert improved the heat transfer
performance by more than 16 percent at low flow rates, as compared
to the Tree-parallel insert. However, the heat transfer enhancement
reduced to less than 5 percent at high Reynolds numbers. On the
other hand, the pressure drop increment stayed almost constant at 20
percent. This suggests that the Tree insert has better heat transfer
performance in the low Reynolds number region. More importantly,
the Cfin insert displayed improved heat transfer performance along
with favourable hydrodynamic performance, as compared to Cfinparallel
insert, at all flow rates in this study. At 2 L/min, the
enhancement of heat transfer was more than 30 percent, with 20
percent pressure drop increment, as compared to Cfin-parallel insert.
Furthermore, comparable increment in both heat transfer coefficient
and pressure drop was observed at 8 L/min. In other words, the Cfin
insert successfully achieved the objective of this study. Analysis of the results suggests that bifurcation of flows is
effective in reducing the increment in pressure drop relative to heat
transfer enhancement. Optimising the geometries of the Constructal
fins is therefore the potential future study in achieving a bigger stride
in energy efficiency at much lower costs.
Abstract: Community living adjacent to forests and Protected
Areas, especially in South Asian countries, have a common practice
in extracting resources for their living and livelihoods. This
extraction of resources, because the way it is done, destroys the biophysical
features of the area. Deforestation, wildlife poaching, illegal
logging, unauthorized hill cutting etc. are some of the serious issues
of concern for the sustainability of the natural resources that has a
direct impact on environment and climate as a whole. To ensure
community involvement in conservation initiatives of the state,
community based forest management, commonly known as Comanagement,
has been in practice in 6 South Asian countries. These
are -India, Nepal, Sri Lanka, Pakistan, Bhutan and Bangladesh.
Involving community in forestry management was initiated first in
Bangladesh in 1979 and reached as an effective co-management
approach through a several paradigm shifts. This idea of Comanagement
has been institutionalized through a Government Order
(GO) by the Ministry of Environment and Forests, Government of
Bangladesh on November 23, 2009. This GO clearly defines the
structure and functions of Co-management and its different bodies.
Bangladesh Forest Department has been working in association with
community to conserve and manage the Forests and Protected areas
of Bangladesh following this legal document. Demographically
young people constitute the largest segment of population in
Bangladesh. This group, if properly sensitized, can produce valuable
impacts on the conservation initiatives, both by community and
government. This study traced the major factors that motivate
community youths to work effectively with different tiers of comanagement
organizations in conservation of forests and Protected
Areas of Bangladesh. For the purpose of this study, 3 FGDs were
conducted with 30 youths from the community living around the
Protected Areas of Cox’s bazar, South East corner of Bangladesh,
who are actively involved in Co-management organizations. KII were
conducted with 5 key officials of Forest Department stationed at
Cox’s Bazar. 2 FGDs were conducted with the representatives of 7
Co-management organizations working in Cox’s Bazar region and
approaches of different community outreach activities conducted for
forest conservation by 3 private organizations and Projects have been
reviewed. Also secondary literatures were reviewed for the history
and evolution of Co-management in Bangladesh and six South Asian
countries. This study found that innovative community outreach
activities that are financed by public and private sectors involving
youths and community as a whole have played a pivotal role in
conservation of forests and Protected Areas of the region. This
approach can be replicated in other regions of Bangladesh as well as
other countries of South Asia where Co-Management exists in
practice.
Abstract: Seeking and sharing knowledge on online forums
have made them popular in recent years. Although online forums are
valuable sources of information, due to variety of sources of
messages, retrieving reliable threads with high quality content is an
issue. Majority of the existing information retrieval systems ignore
the quality of retrieved documents, particularly, in the field of thread
retrieval. In this research, we present an approach that employs
various quality features in order to investigate the quality of retrieved
threads. Different aspects of content quality, including completeness,
comprehensiveness, and politeness, are assessed using these features,
which lead to finding not only textual, but also conceptual relevant
threads for a user query within a forum. To analyse the influence of
the features, we used an adopted version of voting model thread
search as a retrieval system. We equipped it with each feature solely
and also various combinations of features in turn during multiple
runs. The results show that incorporating the quality features
enhances the effectiveness of the utilised retrieval system
significantly.
Abstract: Patient-specific models are instance-based learning
algorithms that take advantage of the particular features of the patient
case at hand to predict an outcome. We introduce two patient-specific
algorithms based on decision tree paradigm that use AUC as a
metric to select an attribute. We apply the patient specific algorithms
to predict outcomes in several datasets, including medical datasets.
Compared to the patient-specific decision path (PSDP) entropy-based
and CART methods, the AUC-based patient-specific decision path
models performed equivalently on area under the ROC curve (AUC).
Our results provide support for patient-specific methods being a
promising approach for making clinical predictions.
Abstract: Recently, traffic monitoring has attracted the attention
of computer vision researchers. Many algorithms have been
developed to detect and track moving vehicles. In fact, vehicle
tracking in daytime and in nighttime cannot be approached with the
same techniques, due to the extreme different illumination conditions.
Consequently, traffic-monitoring systems are in need of having a
component to differentiate between daytime and nighttime scenes. In
this paper, a HSV-based day/night detector is proposed for traffic
monitoring scenes. The detector employs the hue-histogram and the
value-histogram on the top half of the image frame. Experimental
results show that the extraction of the brightness features along with
the color features within the top region of the image is effective for
classifying traffic scenes. In addition, the detector achieves high
precision and recall rates along with it is feasible for real time
applications.
Abstract: Data fusion technology can be the best way to extract
useful information from multiple sources of data. It has been widely
applied in various applications. This paper presents a data fusion
approach in multimedia data for event detection in twitter by using
Dempster-Shafer evidence theory. The methodology applies a mining
algorithm to detect the event. There are two types of data in the
fusion. The first is features extracted from text by using the bag-ofwords
method which is calculated using the term frequency-inverse
document frequency (TF-IDF). The second is the visual features
extracted by applying scale-invariant feature transform (SIFT). The
Dempster - Shafer theory of evidence is applied in order to fuse the
information from these two sources. Our experiments have indicated
that comparing to the approaches using individual data source, the
proposed data fusion approach can increase the prediction accuracy
for event detection. The experimental result showed that the proposed
method achieved a high accuracy of 0.97, comparing with 0.93 with
texts only, and 0.86 with images only.
Abstract: In the deep south of Thailand, checkpoints for people
verification are necessary for the security management of risk zones,
such as official buildings in the conflict area. In this paper, we
propose an automatic checkpoint system that verifies persons using
information from ID cards and facial features. The methods for a
person’s information abstraction and verification are introduced
based on useful information such as ID number and name, extracted
from official cards, and facial images from videos. The proposed
system shows promising results and has a real impact on the local
society.
Abstract: Torrefaction of biomass pellets is considered as a
useful pretreatment technology in order to convert them into a high
quality solid biofuel that is more suitable for pyrolysis, gasification,
combustion, and co-firing applications. In the course of torrefaction,
the temperature varies across the pellet, and therefore chemical
reactions proceed unevenly within the pellet. However, the
uniformity of the thermal distribution along the pellet is generally
assumed. The torrefaction process of a single cylindrical pellet is
modeled here, accounting for heat transfer coupled with chemical
kinetics. The drying sub-model was also introduced. The nonstationary
process of wood pellet decomposition is described by the
system of non-linear partial differential equations over the
temperature and mass. The model captures well the main features of
the experimental data.
Abstract: Ambient Computing or Ambient Intelligence (AmI) is
emerging area in computer science aiming to create intelligently
connected environments and Internet of Things. In this paper, we
propose communication middleware architecture for AmI. This
middleware architecture addresses problems of communication,
networking, and abstraction of applications, although there are other
aspects (e.g. HCI and Security) within general AmI framework.
Within this middleware architecture, any application developer might
address HCI and Security issues with extensibility features of this
platform.
Abstract: In order to retrieve images efficiently from a large
database, a unique method integrating color and texture features
using genetic programming has been proposed. Opponent color
histogram which gives shadow, shade, and light intensity invariant
property is employed in the proposed framework for extracting color
features. For texture feature extraction, fast discrete curvelet
transform which captures more orientation information at different
scales is incorporated to represent curved like edges. The recent
scenario in the issues of image retrieval is to reduce the semantic gap
between user’s preference and low level features. To address this
concern, genetic algorithm combined with relevance feedback is
embedded to reduce semantic gap and retrieve user’s preference
images. Extensive and comparative experiments have been conducted
to evaluate proposed framework for content based image retrieval on
two databases, i.e., COIL-100 and Corel-1000. Experimental results
clearly show that the proposed system surpassed other existing
systems in terms of precision and recall. The proposed work achieves
highest performance with average precision of 88.2% on COIL-100
and 76.3% on Corel, the average recall of 69.9% on COIL and 76.3%
on Corel. Thus, the experimental results confirm that the proposed
content based image retrieval system architecture attains better
solution for image retrieval.