Abstract: Traditionally, Internet has provided best-effort service to every user regardless of its requirements. However, as Internet becomes universally available, users demand more bandwidth and applications require more and more resources, and interest has developed in having the Internet provide some degree of Quality of Service. Although QoS is an important issue, the question of how it will be brought into the Internet has not been solved yet. Researches, due to the rapid advances in technology are proposing new and more desirable capabilities for the next generation of IP infrastructures. But neither all applications demand the same amount of resources, nor all users are service providers. In this way, this paper is the first of a series of papers that presents an architecture as a first step to the optimization of QoS in the Internet environment as a solution to a SMSE's problem whose objective is to provide public service to internet with certain Quality of Service expectations. The service provides new business opportunities, but also presents new challenges. We have designed and implemented a scalable service framework that supports adaptive bandwidth based on user demands, and the billing based on usage and on QoS. The developed application has been evaluated and the results show that traffic limiting works at optimum and so it does exceeding bandwidth distribution. However, some considerations are done and currently research is under way in two basic areas: (i) development and testing new transfer protocols, and (ii) developing new strategies for traffic improvements based on service differentiation.
Abstract: Design and implementation of a novel B-ACOSD CFAR algorithm is presented in this paper. It is proposed for detecting radar target in log-normal distribution environment. The BACOSD detector is capable to detect automatically the number interference target in the reference cells and detect the real target by an adaptive threshold. The detector is implemented as a System on Chip on FPGA Altera Stratix II using parallelism and pipelining technique. For a reference window of length 16 cells, the experimental results showed that the processor works properly with a processing speed up to 115.13MHz and processing time0.29 ┬Ás, thus meets real-time requirement for a typical radar system.
Abstract: The Application of e-health solutions has brought superb advancements in the health care industry. E-health solutions have already been embraced in the industrialized countries. In an effort to catch up with the growth, the developing countries have strived to revolutionize the healthcare industry by use of Information technology in different ways. Based on a technology assessment carried out in Kenya – one of the developing countries – and using multiple case studies in Nyanza Province, this work focuses on an investigation on how five rural hospitals are adapting to the technology shift. The issues examined include the ICT infrastructure and e-health technologies in place, the knowledge of participants in terms of benefits gained through the use of ICT and the challenges posing barriers to the use of ICT technologies in these hospitals. The results reveal that the ICT infrastructure in place is inadequate for e-health implementations as a result to various challenges that exist. Consequently, suggestions on how to tackle the various challenges have been addressed in this paper.
Abstract: In this paper we propose and examine an Adaptive
Neuro-Fuzzy Inference System (ANFIS) in Smoothing Transition
Autoregressive (STAR) modeling. Because STAR models follow
fuzzy logic approach, in the non-linear part fuzzy rules can be
incorporated or other training or computational methods can be
applied as the error backpropagation algorithm instead to nonlinear
squares. Furthermore, additional fuzzy membership functions can be
examined, beside the logistic and exponential, like the triangle,
Gaussian and Generalized Bell functions among others. We examine
two macroeconomic variables of US economy, the inflation rate and
the 6-monthly treasury bills interest rates.
Abstract: This paper deals with the design of a periodic output
feedback controller for a flexible beam structure modeled with
Timoshenko beam theory, Finite Element Method, State space
methods and embedded piezoelectrics concept. The first 3 modes are
considered in modeling the beam. The main objective of this work is
to control the vibrations of the beam when subjected to an external
force. Shear piezoelectric sensors and actuators are embedded into
the top and bottom layers of a flexible aluminum beam structure, thus
making it intelligent and self-adaptive. The composite beam is
divided into 5 finite elements and the control actuator is placed at
finite element position 1, whereas the sensor is varied from position 2
to 5, i.e., from the nearby fixed end to the free end. 4 state space
SISO models are thus developed. Periodic Output Feedback (POF)
Controllers are designed for the 4 SISO models of the same plant to
control the flexural vibrations. The effect of placing the sensor at
different locations on the beam is observed and the performance of
the controller is evaluated for vibration control. Conclusions are
finally drawn.
Abstract: Decision feedback equalizers are commonly employed to reduce the error caused by intersymbol interference. Here, an adaptive decision feedback equalizer is presented with a new adaptation algorithm. The algorithm follows a block-based approach of normalized least mean square (NLMS) algorithm with set-membership filtering and achieves a significantly less computational complexity over its conventional NLMS counterpart with set-membership filtering. It is shown in the results that the proposed algorithm yields similar type of bit error rate performance over a reasonable signal to noise ratio in comparison with the latter one.
Abstract: Technology transfer is a common method for
companies to acquire new technology and presents both challenges
and substantial benefits. In some cases especially in developing
countries, the mere possession of technology does not guarantee a
competitive advantage if the appropriate infrastructure is not in place.
In this paper, we identify the localization factors needed to provide a
better understanding of the conditions necessary for localization in
order to benefit from future technology developments. Our
theoretical and empirical analyses allow us to identify several factors
in the technology transfer process that affect localization and provide
leverage in enhancing capabilities and absorptive capacity.The
impact factors are categorized within different groups of government,
firms, institutes and market, and are verified through the empirical
survey of a technology transfer experience. Moreover, statistical
analysis has allowed a deeper understanding of the importance of
each factor and has enabled each group to prioritize their
organizational policies to effectively localize their technology.
Abstract: Purpose: To develop a method for automatic segmentation of adipose and muscular tissue in thighs from magnetic resonance images. Materials and methods: Thirty obese women were scanned on a Siemens Impact Expert 1T resonance machine. 1500 images were finally used in the tests. The developed segmentation method is a recursive and multilevel process that makes use of several concepts such as shaped histograms, adaptative thresholding and connectivity. The segmentation process was implemented in Matlab and operates without the need of any user interaction. The whole set of images were segmented with the developed method. An expert radiologist segmented the same set of images following a manual procedure with the aid of the SliceOmatic software (Tomovision). These constituted our 'goal standard'. Results: The number of coincidental pixels of the automatic and manual segmentation procedures was measured. The average results were above 90 % of success in most of the images. Conclusions: The proposed approach allows effective automatic segmentation of MRIs from thighs, comparable to expert manual performance.
Abstract: Adapting wireless devices to communicate within grid
networks empowers us by providing range of possibilities.. These
devices create a mechanism for consumers and publishers to create
modern networks with or without peer device utilization. Emerging
mobile networks creates new challenges in the areas of reliability,
security, and adaptability. In this paper, we propose a system
encompassing mobility management using AAA context transfer for
mobile grid networks. This system ultimately results in seamless task
processing and reduced packet loss, communication delays,
bandwidth, and errors.
Abstract: Efficient storage, transmission and use of video information are key requirements in many multimedia applications currently being addressed by MPEG-4. To fulfill these requirements, a new approach for representing video information which relies on an object-based representation, has been adopted. Therefore, objectbased watermarking schemes are needed for copyright protection. This paper proposes a novel blind object watermarking scheme for images and video using the in place lifting shape adaptive-discrete wavelet transform (SA-DWT). In order to make the watermark robust and transparent, the watermark is embedded in the average of wavelet blocks using the visual model based on the human visual system. Wavelet coefficients n least significant bits (LSBs) are adjusted in concert with the average. Simulation results shows that the proposed watermarking scheme is perceptually invisible and robust against many attacks such as lossy image/video compression (e.g. JPEG, JPEG2000 and MPEG-4), scaling, adding noise, filtering, etc.
Abstract: The African Diaspora in Singapore (and larger Asia)
is a topic that has received little scholarly attention and research. This
exploratory study will analyze the changing identity of Africans
throughout the process of cultural adaptation in Singapore. For the
focus of this study, “black Africans" will be defined as any black
Africans from sub-Saharan Africa who have lived in Singapore for at
least six months. The dialectic relationship between Singaporean
conceptions of black African identity and African self-consciousness
will be analyzed from the perspective of black Africans so as to
evaluate the impact of intercultural discourse on the evolution of the
African identity in Singapore.
Abstract: to simulate the phenomenon of electronic transport in semiconductors, we try to adapt a numerical method, often and most frequently it’s that of Monte Carlo. In our work, we applied this method in the case of a ternary alloy semiconductor GaInP in its cubic form; The Calculations are made using a non-parabolic effective-mass energy band model. We consider a band of conduction to three valleys (ΓLX), major of the scattering mechanisms are taken into account in this modeling, as the interactions with the acoustic phonons (elastic collisions) and optics (inelastic collisions). The polar optical phonons cause anisotropic collisions, intra-valleys, very probable in the III-V semiconductors. Other optical phonons, no polar, allow transitions inter-valleys. Initially, we present the full results obtained by the simulation of Monte Carlo in GaInP in stationary regime. We consider thereafter the effects related to the application of an electric field varying according to time, we thus study the transient phenomenon which make their appearance in ternary material
Abstract: This paper presents a novel approach for the design of
microwave circuits using Adaptive Network Fuzzy Inference
Optimizer (ANFIO). The method takes advantage of direct synthesis
of subsections of the amplifier using very fast and accurate ANFIO
models based on exact simulations using ADS. A mapping from
course space to fine space known as space mapping is also used. The
proposed synthesis approach takes into account the noise and
scattering parameters due to parasitic elements to achieve optimal
results. The overall ANFIO system is capable of designing different
LNAs at different noise and scattering criteria. This approach offers
significantly reduced time in the design of microwave amplifiers
within the validity range of the ANFIO system. The method has been
proven to work efficiently for a 2.4GHz LNA example. The S21 of
10.1 dB and noise figure (NF) of 2.7 dB achieved for ANFIO while
S21 of 9.05 dB and NF of 2.6 dB achieved for ANN.
Abstract: We developed a multi-camera control system that a (one) cameraman can operate several cameras at a compact studio. we analyzed a workflow of a cameraman of some program shootings with two cameras and clarified their heavy tasks. The system based on a dynamic workflow which adapts a program progressing and recommends of cameraman. we perform the automation of multicamera controls by modeling of studio environment and perform automatic camera adjustment for suitable angle of view with face detection. Our experiment at a real program shooting showed that one cameraman can carry out the task of shooting sufficiently.
Abstract: An adaptive fuzzy PID controller with gain scheduling is proposed in this paper. The structure of the proposed gain scheduled fuzzy PID (GS_FPID) controller consists of both fuzzy PI-like controller and fuzzy PD-like controller. Both of fuzzy PI-like and PD-like controllers are weighted through adaptive gain scheduling, which are also determined by fuzzy logic inference. A modified genetic algorithm called accumulated genetic algorithm is designed to learn the parameters of fuzzy inference system. In order to learn the number of fuzzy rules required for the TSK model, the fuzzy rules are learned in an accumulated way. In other words, the parameters learned in the previous rules are accumulated and updated along with the parameters in the current rule. It will be shown that the proposed GS_FPID controllers learned by the accumulated GA perform well for not only the regular linear systems but also the higher order and time-delayed systems.
Abstract: Currently, most of distance learning courses can only
deliver standard material to students. Students receive course content
passively which leads to the neglect of the goal of education – “to suit
the teaching to the ability of students". Providing appropriate course
content according to students- ability is the main goal of this paper.
Except offering a series of conventional learning services, abundant
information available, and instant message delivery, a complete online
learning environment should be able to distinguish between students-
ability and provide learning courses that best suit their ability.
However, if a distance learning site contains well-designed course
content and design but fails to provide adaptive courses, students will
gradually loss their interests and confidence in learning and result in
ineffective learning or discontinued learning. In this paper, an
intelligent tutoring system is proposed and it consists of several
modules working cooperatively in order to build an adaptive learning
environment for distance education. The operation of the system is
based on the result of Self-Organizing Map (SOM) to divide students
into different groups according to their learning ability and learning
interests and then provide them with suitable course content.
Accordingly, the problem of information overload and internet traffic
problem can be solved because the amount of traffic accessing the
same content is reduced.
Abstract: In the end of the day, meteorological data and environmental data becomes widely used such as plant varieties selection system. Variety plant selection for planted area is of almost importance for all crops, including varieties of sugarcane. Since sugarcane have many varieties. Variety plant non selection for planting may not be adapted to the climate or soil conditions for planted area. Poor growth, bloom drop, poor fruit, and low price are to be from varieties which were not recommended for those planted area. This paper presents plant varieties selection system for planted areas in Thailand from meteorological data and environmental data by the use of decision tree techniques. With this software developed as an environmental data analysis tool, it can analyze resulting easier and faster. Our software is a front end of WEKA that provides fundamental data mining functions such as classify, clustering, and analysis functions. It also supports pre-processing, analysis, and decision tree output with exporting result. After that, our software can export and display data result to Google maps API in order to display result and plot plant icons effectively.
Abstract: A new Feed-Forward/Feedback Generalized
Minimum Variance Pole-placement Controller to incorporate the
robustness of classical pole-placement into the flexibility of
generalized minimum variance self-tuning controller for Single-Input
Single-Output (SISO) has been proposed in this paper. The design,
which provides the user with an adaptive mechanism, which ensures
that the closed loop poles are, located at their pre-specified positions.
In addition, the controller design which has a feed-forward/feedback
structure overcomes the certain limitations existing in similar poleplacement
control designs whilst retaining the simplicity of
adaptation mechanisms used in other designs. It tracks set-point
changes with the desired speed of response, penalizes excessive
control action, and can be applied to non-minimum phase systems.
Besides, at steady state, the controller has the ability to regulate the
constant load disturbance to zero. Example simulation results using
both simulated and real plant models demonstrate the effectiveness of
the proposed controller.
Abstract: In this paper, we demonstrate the adaptive
least-mean-square (LMS) filter modeling using SystemC. SystemC is
a modeling language that allows designer to model both hardware and
software component and makes it possible to design from high level
system of abstraction to low level system of abstraction. We produced
five adaptive least-mean-square filter models that are classed as five
abstraction levels using SystemC proceeding from the abstract model
to the more concrete model.
Abstract: One of the most important parameters to develop and
manage urban areas is appropriate selection of land surface to
develop green spaces in these areas. In this study, in order to identify
the most appropriate sites and areas cultivated for ornamental species
in Jiroft, Landsat Enhanced Thematic Mapper Plus (ETM+) images
due to extract the most important effective climatic and adaphic
parameters for growth ornamental species were used. After geometric
and atmospheric corrections applied, to enhance accuracy of multi
spectral (XS) bands, the fusion of Landsat XS bands by IRS-1D
panchromatic band (PAN) was performed. After field sampling to
evaluate the correlation between different factors in surface soil
sampling location and different bands digital number (DN) of ETM+
sensor on the same points, correlation tables formed using the best
computational model and the map of physical and chemical
parameters of soil was produced. Then the accuracy of them was
investigated by using kappa coefficient. Finally, according to
produced maps, the best areas for cultivation of recommended
species were introduced.