Abstract: It is important to give input information without other device in AR system. One solution is using hand for augmented reality application. Many researchers have proposed different solutions for hand interface in augmented reality. Analyze Histogram and connecting factor is can be example for that. Various Direction searching is one of robust way to recognition hand but it takes too much calculating time. And background should be distinguished with skin color. This paper proposes a hand tracking method to control the 3D object in augmented reality using depth device and skin color. Also in this work discussed relationship between several markers, which is based on relationship between camera and marker. One marker used for displaying virtual object and three markers for detecting hand gesture and manipulating the virtual object.
Abstract: Ventilation is a fundamental requirement for
occupant health and indoor air quality in buildings. Natural
ventilation can be used as a design strategy in free-running
buildings to:
• Renew indoor air with fresh outside air and lower room
temperatures at times when the outdoor air is cooler.
• Promote air flow to cool down the building structure
(structural cooling).
• Promote occupant physiological cooling processes
(comfort cooling).
This paper focuses on ways in which ventilation can
provide the mechanism for heat dissipation and cooling of the
building structure..It also discusses use of ventilation as a
means of increasing air movement to improve comfort when
indoor air temperatures are too high. The main influencing
factors and design considerations and quantitative guidelines
to help meet the design objectives are also discussed.
Abstract: We here propose improved version of elastic graph matching (EGM) as a face detector, called the multi-scale EGM (MS-EGM). In this improvement, Gabor wavelet-based pyramid reduces computational complexity for the feature representation often used in the conventional EGM, but preserving a critical amount of information about an image. The MS-EGM gives us higher detection performance than Viola-Jones object detection algorithm of the AdaBoost Haar-like feature cascade. We also show rapid detection speeds of the MS-EGM, comparable to the Viola-Jones method. We find fruitful benefits in the MS-EGM, in terms of topological feature representation for a face.
Abstract: As the Computed Tomography(CT) requires normally
hundreds of projections to reconstruct the image, patients are exposed
to more X-ray energy, which may cause side effects such as cancer.
Even when the variability of the particles in the object is very less,
Computed Tomography requires many projections for good quality
reconstruction. In this paper, less variability of the particles in an
object has been exploited to obtain good quality reconstruction.
Though the reconstructed image and the original image have same
projections, in general, they need not be the same. In addition
to projections, if a priori information about the image is known,
it is possible to obtain good quality reconstructed image. In this
paper, it has been shown by experimental results why conventional
algorithms fail to reconstruct from a few projections, and an efficient
polynomial time algorithm has been given to reconstruct a bi-level
image from its projections along row and column, and a known sub
image of unknown image with smoothness constraints by reducing the
reconstruction problem to integral max flow problem. This paper also
discusses the necessary and sufficient conditions for uniqueness and
extension of 2D-bi-level image reconstruction to 3D-bi-level image
reconstruction.
Abstract: In this paper we present a way of controlling the
concurrent access to data in a distributed application using the
Pessimistic Offline Lock design pattern. In our case, the application
processes a complex entity, which contains in a hierarchical structure
different other entities (objects). It will be shown how the complex
entity and the contained entities must be locked in order to control
the concurrent access to data.
Abstract: The objective of this research is parameters optimized
of the stair shape workpiece which is cut by CNC Wire-Cut EDM
(WEDW). The experiment material is SKD-11 steel of stair-shaped
with variable height workpiece 10, 20, 30 and 40 mm. with the same
10 mm. thickness are cut by Sodick's CNC Wire-Cut EDM model
AD325L.
The experiments are designed by 3k full factorial experimental
design at 3 level 2 factors and 9 experiments with 2 replicate. The
selected two factor are servo voltage (SV) and servo feed rate (SF)
and the response is cutting thickness error. The experiment is divided
in two experiments. The first experiment determines the significant
effective factor at confidential interval 95%. The SV factor is the
significant effective factor from first result. In order to result smallest
cutting thickness error of workpieces is 17 micron with the SV value
is 46 volt. Also show that the lower SV value, the smaller different
thickness error of workpiece. Then the second experiment is done to
reduce different cutting thickness error of workpiece as small as
possible by lower SV. The second experiment result show the
significant effective factor at confidential interval 95% is the SV
factor and the smallest cutting thickness error of workpieces reduce
to 11 micron with the experiment SV value is 36 volt.
Abstract: Public parks are placed high on the research agenda, with many studies addressing their social, economic and environment influences in different countries around the world. They have been recognized as contributors to the physical quality of urban environments. Recently, a broader view of public parks has emerged. This view goes well beyond the traditional value of parks as places for more recreation and visual delight, to depict them as valuable contributors to broader strategic objectives, such as property values, place attractiveness, job opportunities, social belonging, public health, tourist development, and improving the overall quality of life. This research examines the role of public parks in enhancing the quality of human life in Egyptian environment. It measures 'quality of life' in terms of 'human needs' and 'well-being'. This should open ways for policymakers, practitioners, researchers and the public to realize the potentials of public parks towards improving the quality of life.
Abstract: A green design for assembly model is presented to
integrate design evaluation and assembly and disassembly sequence
planning by evaluating the three activities in one integrated model. For
an assembled product, an assembly sequence planning model is
required for assembling the product at the start of the product life cycle.
A disassembly sequence planning model is needed for disassembling
the product at the end. In a green product life cycle, it is important to
plan how a product can be disassembled, reused, or recycled, before
the product is actually assembled and produced. Given a product
requirement, there may be several design alternative cases to design
the same product. In the different design cases, the assembly and
disassembly sequences for producing the product can be different. In
this research, a new model is presented to concurrently evaluate the
design and plan the assembly and disassembly sequences. First, the
components are represented by using graph based models. Next, a
particle swarm optimization (PSO) method with a new encoding
scheme is developed. In the new PSO encoding scheme, a particle is
represented by a position matrix defining an assembly sequence and a
disassembly sequence. The assembly and disassembly sequences can
be simultaneously planned with an objective of minimizing the total of
assembly costs and disassembly costs. The test results show that the
presented method is feasible and efficient for solving the integrated
design evaluation and assembly and disassembly sequence planning
problem. An example product is implemented and illustrated in this
paper.
Abstract: This paper presents a highly efficient algorithm for detecting and tracking humans and objects in video surveillance sequences. Mean shift clustering is applied on backgrounddifferenced image sequences. For efficiency, all calculations are performed on integral images. Novel corresponding exponential integral kernels are introduced to allow the application of nonuniform kernels for clustering, which dramatically increases robustness without giving up the efficiency of the integral data structures. Experimental results demonstrating the power of this approach are presented.
Abstract: An important problem in speech research is the automatic extraction of information about the shape and dimensions of the vocal tract during real-time speech production. We have previously developed Southampton dynamic magnetic resonance imaging (SDMRI) as an approach to the solution of this problem.However, the SDMRI images are very noisy so that shape extraction is a major challenge. In this paper, we address the problem of tongue shape extraction, which poses difficulties because this is a highly deforming non-parametric shape. We show that combining active shape models with the dynamic Hough transform allows the tongue shape to be reliably tracked in the image sequence.
Abstract: RoboCup Rescue simulation as a large-scale Multi
agent system (MAS) is one of the challenging environments for
keeping coordination between agents to achieve the objectives
despite sensing and communication limitations. The dynamicity of
the environment and intensive dependency between actions of
different kinds of agents make the problem more complex. This point
encouraged us to use learning-based methods to adapt our decision
making to different situations. Our approach is utilizing
reinforcement leaning. Using learning in rescue simulation is one of
the current ways which has been the subject of several researches in
recent years. In this paper we present an innovative learning method
implemented for Police Force (PF) Agent. This method can cope
with the main difficulties that exist in other learning approaches.
Different methods used in the literature have been examined. Their
drawbacks and possible improvements have led us to the method
proposed in this paper which is fast and accurate. The Brain
Emotional Learning Based Intelligent Controller (BELBIC) is our
solution for learning in this environment. BELBIC is a
physiologically motivated approach based on a computational model
of amygdale and limbic system. The paper presents the results
obtained by the proposed approach, showing the power of BELBIC
as a decision making tool in complex and dynamic situation.
Abstract: The objectives of this research were to compare the success of SME registered in Nakorn Pathom Province divided in personal data also to study the relations between the innovation knowledge and capability and the success of SME registered in Nakorn Pathom Province and to study the relations between the work efficiency and the success of SME registered in Nakorn Pathom Province. A questionnaire was utilized as a tool to collect data. Statistics utilized in this research included frequency, percentage, mean, standard deviation, and multiple regression analysis. Data were analyzed by using Statistical Package for the Social Sciences.The findings revealed that the majority of respondents were male with the age between 25-34 years old, hold undergraduate degree, married and stay together. The average income of respondents was between 10,001-20,000 baht. It also found that in terms of innovation knowledge and capability, there were two variables had an influence on the amount of innovation knowledge and capability, innovation evaluation which were physical characteristic and innovation process.
Abstract: Existing image-based virtual reality applications
allow users to view image-based 3D virtual environment in a more
interactive manner. User could “walkthrough"; looks left, right, up
and down and even zoom into objects in these virtual worlds of
images. However what the user sees during a “zoom in" is just a
close-up view of the same image which was taken from a distant.
Thus, this does not give the user an accurate view of the object from
the actual distance. In this paper, a simple technique for zooming in
an object in a virtual scene is presented. The technique is based on
the 'hotspot' concept in existing application. Instead of navigation
between two different locations, the hotspots are used to focus into
an object in the scene. For each object, several hotspots are created.
A different picture is taken for each hotspot. Each consecutive
hotspot created will take the user closer to the object. This will
provide the user with a correct of view of the object based on his
proximity to the object. Implementation issues and the relevance of
this technique in potential application areas are highlighted.
Abstract: The mathematical modeling of different biological
processes is usually used to predict or assess behavior of systems in
which these processes take place. This study deals with mathematical
and computer modeling of bi-substrate enzymatic reactions with
ping-pong mechanism, which play an important role in different
biochemical pathways. Besides that, three models of competitive
inhibition were designed using different software packages. The main
objective of this study is to represent the results from in silico
investigation of bi-substrate enzymatic reactions with ordered pingpong
mechanism in the presence of competitive inhibitors, as well as
to describe in details the inhibition effects. The simulation of the
models with certain kinetic parameters allowed investigating the
behavior of reactions as well as determined some interesting aspects
concerning influence of different cases of competitive inhibition.
Simultaneous presence of two inhibitors, competitive to the S1 and S2
substrates have been studied. Moreover, we have found the pattern of
simultaneous influence of both inhibitors.
Abstract: This research presents a fuzzy multi-objective model
for a machine selection problem in a flexible manufacturing system
of a tire company. Two main objectives are minimization of an
average machine error and minimization of the total setup time.
Conventionally, the working team uses trial and error in selecting a
pressing machine for each task due to the complexity and constraints
of the problem. So, both objectives may not satisfy. Moreover, trial
and error takes a lot of time to get the final decision. Therefore, in
this research preemptive fuzzy goal programming model is developed
for solving this multi-objective problem. The proposed model can
obtain the appropriate results that the Decision Making (DM) is
satisfied for both objectives. Besides, alternative choice can be easily
generated by varying the satisfaction level. Additionally, decision
time can be reduced by using the model, which includes all
constraints of the system to generate the solutions. A numerical
example is also illustrated to show the effectiveness of the proposed
model.
Abstract: Background Contact lens (CL) wear can cause
changes in blinking and corneal staining. Aims and Objectives To
determine the effects of CL materials (HEMA and SiHy) on
spontaneous blink rate, blinking patterns and corneal staining after 2
months of wear. Methods Ninety subjects in 3 groups (control,
HEMA and SiHy) were assessed at baseline and 2-months. Blink rate
was recorded using a video camera. Blinking patterns were assessed
with digital camera and slit lamp biomicroscope. Corneal staining
was graded using IER grading scale Results There were no significant
differences in all parameters at baseline. At 2 months, CL wearers
showed significant increment in average blink rate (F1.626, 47.141 =
7.250, p = 0.003; F2,58 = 6.240, p = 0.004) and corneal staining (χ2
2,
n=30 = 31.921, p < 0.001; χ2
2, n=30 = 26.909, p < 0.001). Conclusion
Blinking characteristics and corneal staining were not influence by
soft CL materials.
Abstract: This research uses computational linguistics, an area of study that employs a computer to process natural language, and aims at discerning the patterns that exist in declarative sentences used in technical texts. The approach is mathematical, and the focus is on instructional texts found on web pages. The technique developed by the author and named the MAYA Semantic Technique is used here and organized into four stages. In the first stage, the parts of speech in each sentence are identified. In the second stage, the subject of the sentence is determined. In the third stage, MAYA performs a frequency analysis on the remaining words to determine the verb and its object. In the fourth stage, MAYA does statistical analysis to determine the content of the web page. The advantage of the MAYA Semantic Technique lies in its use of mathematical principles to represent grammatical operations which assist processing and accuracy if performed on unambiguous text. The MAYA Semantic Technique is part of a proposed architecture for an entire web-based intelligent tutoring system. On a sample set of sentences, partial semantics derived using the MAYA Semantic Technique were approximately 80% accurate. The system currently processes technical text in one domain, namely Cµ programming. In this domain all the keywords and programming concepts are known and understood.
Abstract: The modern world is experiencing fundamental and dynamic changes. The transformation of international relations; the end of confrontation and successive overcoming of the Cold War consequences have expanded possible international cooperation. The global nuclear conflict threat has been minimized, while a tendency to establish a unipolar world structure with the U.S. economic and power domination is growing. The current world system of international relations, apparently is secular. However, the religious beliefs of one or another nations play a certain (sometimes a key) role, both in the domestic affairs of the individual countries and in the development of bilateral ties. Political situation in Central Asia has been characterized by new factors such as international terrorism; religious extremism and radicalism; narcotrafficking and illicit arms trade of a global character immediately threaten to peace and political stability in Central Asia. The role and influence of Islamic fundamentalism is increasing; political ethnocentrism and the associated aggravation of inter-ethnic relations, the ambiguity of national interests and objectives of major geo-political groups in the Central Asian region regarding the division the political influence, emerge. This article approaches the following issues: the role of Islam in Central Asia; destabilizing factors in Central Asia; Islamic movements in Central Asia, Western Europe and the United States; the United States, Western Europe and Central Asia: religion, politics, ideology, and the US-Central Asia antiterrorism and religious extremism cooperation.
Abstract: Wireless capsule endoscopy provides real-time images in the digestive tract. Capsule images are usually low resolution and are diverse images due to travel through various regions of human body. Color information has been a primary reference in predicting abnormalities such as bleeding. Often color is not sufficient for this purpose. In this study, we took morphological shapes into account as additional, but important criterion. First, we processed gastric images in order to indentify various objects in the image. Then, we analyzed color information in the object. In this way, we could remove unnecessary information and increase the accuracy. Compared to our previous investigations, we could handle images of various degrees of brightness and improve our diagnostic algorithm.
Abstract: Recent scientific investigations indicate that
multimodal biometrics overcome the technical limitations of
unimodal biometrics, making them ideally suited for everyday life
applications that require a reliable authentication system. However,
for a successful adoption of multimodal biometrics, such systems
would require large heterogeneous datasets with complex multimodal
fusion and privacy schemes spanning various distributed
environments. From experimental investigations of current
multimodal systems, this paper reports the various issues related to
speed, error-recovery and privacy that impede the diffusion of such
systems in real-life. This calls for a robust mechanism that caters to
the desired real-time performance, robust fusion schemes,
interoperability and adaptable privacy policies.
The main objective of this paper is to present a framework that
addresses the abovementioned issues by leveraging on the
heterogeneous resource sharing capacities of Grid services and the
efficient machine learning capabilities of artificial neural networks
(ANN). Hence, this paper proposes a Grid-based neural network
framework for adopting multimodal biometrics with the view of
overcoming the barriers of performance, privacy and risk issues that
are associated with shared heterogeneous multimodal data centres.
The framework combines the concept of Grid services for reliable
brokering and privacy policy management of shared biometric
resources along with a momentum back propagation ANN (MBPANN)
model of machine learning for efficient multimodal fusion and
authentication schemes. Real-life applications would be able to adopt
the proposed framework to cater to the varying business requirements
and user privacies for a successful diffusion of multimodal
biometrics in various day-to-day transactions.