Abstract: .Hardware realization of a Neural Network (NN), to a large extent depends on the efficient implementation of a single neuron. FPGA-based reconfigurable computing architectures are suitable for hardware implementation of neural networks. FPGA realization of ANNs with a large number of neurons is still a challenging task. This paper discusses the issues involved in implementation of a multi-input neuron with linear/nonlinear excitation functions using FPGA. Implementation method with resource/speed tradeoff is proposed to handle signed decimal numbers. The VHDL coding developed is tested using Xilinx XC V50hq240 Chip. To improve the speed of operation a lookup table method is used. The problems involved in using a lookup table (LUT) for a nonlinear function is discussed. The percentage saving in resource and the improvement in speed with an LUT for a neuron is reported. An attempt is also made to derive a generalized formula for a multi-input neuron that facilitates to estimate approximately the total resource requirement and speed achievable for a given multilayer neural network. This facilitates the designer to choose the FPGA capacity for a given application. Using the proposed method of implementation a neural network based application, namely, a Space vector modulator for a vector-controlled drive is presented
Abstract: Wireless mesh networks based on IEEE 802.11
technology are a scalable and efficient solution for next generation
wireless networking to provide wide-area wideband internet access to
a significant number of users. The deployment of these wireless mesh
networks may be within different authorities and without any
planning, they are potentially overlapped partially or completely in
the same service area. The aim of the proposed model is design a new
model to Enhancement Throughput of Unplanned Wireless Mesh
Networks Deployment Using Partitioning Hierarchical Cluster
(PHC), the unplanned deployment of WMNs are determinates there
performance. We use throughput optimization approach to model the
unplanned WMNs deployment problem based on partitioning
hierarchical cluster (PHC) based architecture, in this paper the
researcher used bridge node by allowing interworking traffic between
these WMNs as solution for performance degradation.
Abstract: With the exponential rise in the number of multimedia
applications available, the best-effort service provided by the Internet
today is insufficient. Researchers have been working on new
architectures like the Next Generation Network (NGN) which, by
definition, will ensure Quality of Service (QoS) in an all-IP based
network [1]. For this approach to become a reality, reservation of
bandwidth is required per application per user. WiMAX (Worldwide
Interoperability for Microwave Access) is a wireless communication
technology which has predefined levels of QoS which can be
provided to the user [4]. IPv6 has been created as the successor for
IPv4 and resolves issues like the availability of IP addresses and
QoS. This paper provides a design to use the power of WiMAX as an
NSP (Network Service Provider) for NGN using IPv6. The use of the
Traffic Class (TC) field and the Flow Label (FL) field of IPv6 has
been explained for making QoS requests and grants [6], [7]. Using
these fields, the processing time is reduced and routing is simplified.
Also, we define the functioning of the ASN gateway and the NGN
gateway (NGNG) which are edge node interfaces in the NGNWiMAX
design. These gateways ensure QoS management through
built in functions and by certain physical resources and networking
capabilities.
Abstract: Recently, web services to access from many type devices
are often used. We have developed the shortest path planning
system called "Bus-Net" in Tottori prefecture as a web application
to sustain the public transport. And it used the same user interface
for both devices. To support both devices, the interface cannot use
JavaScript and so on.
Thus, we developed the method that use individual user interface
for each device type to improve its convenience. To be concrete,
we defined formats of condition input to the path planning system
and result output from it and separate the system into the request
processing part and user interface parts that depend on device types.
By this method, we have also developed special device for Bus-Net
named "Intelligent-Bus-Stop".
Abstract: Worm propagation profiles have significantly changed
since 2003-2004: sudden world outbreaks like Blaster or Slammer
have progressively disappeared and slower but stealthier worms
appeared since, most of them for botnets dissemination. Decreased
worm virulence results in more difficult detection.
In this paper, we describe a stealth worm propagation model
which has been extensively simulated and analysed on a huge virtual
network. The main features of this model is its ability to infect any
Internet-like network in a few seconds, whatever may be its size while
greatly limiting the reinfection attempt overhead of already infected
hosts. The main simulation results shows that the combinatorial
topology of routing may have a huge impact on the worm propagation
and thus some servers play a more essential and significant role than
others. The real-time capability to identify them may be essential to
greatly hinder worm propagation.
Abstract: In this paper, we present a cost-effective wireless
distributed load shedding system for non-emergency scenarios. In
power transformer locations where SCADA system cannot be used,
the proposed solution provides a reasonable alternative that combines
the use of microcontrollers and existing GSM infrastructure to send
early warning SMS messages to users advising them to proactively
reduce their power consumption before system capacity is reached
and systematic power shutdown takes place.
A novel communication protocol and message set have been
devised to handle the messaging between the transformer sites, where
the microcontrollers are located and where the measurements take
place, and the central processing site where the database server is
hosted. Moreover, the system sends warning messages to the endusers
mobile devices that are used as communication terminals. The
system has been implemented and tested via different experimental
results.
Abstract: Using Internet communication, new home electronics
have functions of monitoring and control from remote. However in
many case these electronics work as standalone, and old electronics
are not followed. Then, we developed the total remote system include
not only new electronics but olds. This systems node is a adapter of
electrical power plug that embed relay switch and some sensors, and
these nodes communicate with each other. the system server was build
on the Internet, and users access to this system from web browsers.
To reduce the cost to set up of this system, communication between
adapters are used ZigBee wireless network instead of wired LAN
cable[3]. From measured RSSI(received signal strength indicator)
information between each nodes, the system can estimate roughly
adapters were mounted on which room, and where in the room. So
also it reduces the cost of mapping nodes. Using this system, energy
saving and house monitoring are expected.
Abstract: Series of experimental tests were conducted on a
section of a 660 kW wind turbine blade to measure the pressure
distribution of this model oscillating in plunging motion. In order to
minimize the amount of data required to predict aerodynamic loads
of the airfoil, a General Regression Neural Network, GRNN, was
trained using the measured experimental data. The network once
proved to be accurate enough, was used to predict the flow behavior
of the airfoil for the desired conditions.
Results showed that with using a few of the acquired data, the
trained neural network was able to predict accurate results with
minimal errors when compared with the corresponding measured
values. Therefore with employing this trained network the
aerodynamic coefficients of the plunging airfoil, are predicted
accurately at different oscillation frequencies, amplitudes, and angles
of attack; hence reducing the cost of tests while achieving acceptable
accuracy.
Abstract: A novel idea presented in this paper is to combine
multihop routing with single-frequency networks (SFNs) for a
broadcasting scenario. An SFN is a set of multiple nodes that transmit
the same data simultaneously, resulting in transmitter macrodiversity.
Two of the most important performance factors of multihop
networks, node reachability and routing robustness, are analyzed.
Simulation results show that our proposed SFN-D routing algorithm
improves the node reachability by 37 percentage points as compared
to non-SFN multihop routing. It shows a diversity gain of 3.7 dB,
meaning that 3.7 dB lower transmission powers are required for the
same reachability. Even better results are possible for larger
networks. If an important node becomes inactive, this algorithm can
find new routes that a non-SFN scheme would not be able to find.
Thus, two of the major problems in multihopping are addressed;
achieving robust routing as well as improving node reachability or
reducing transmission power.
Abstract: In this paper, we propose a dynamic TDMA slot
reservation (DTSR) protocol for cognitive radio ad hoc networks.
Quality of Service (QoS) guarantee plays a critically important role
in such networks. We consider the problem of providing QoS
guarantee to users as well as to maintain the most efficient use of
scarce bandwidth resources. According to one hop neighboring
information and the bandwidth requirement, our proposed protocol
dynamically changes the frame length and the transmission schedule.
A dynamic frame length expansion and shrinking scheme that
controls the excessive increase of unassigned slots has been
proposed. This method efficiently utilizes the channel bandwidth by
assigning unused slots to new neighboring nodes and increasing the
frame length when the number of slots in the frame is insufficient to
support the neighboring nodes. It also shrinks the frame length when
half of the slots in the frame of a node are empty. An efficient slot
reservation protocol not only guarantees successful data
transmissions without collisions but also enhance channel spatial
reuse to maximize the system throughput. Our proposed scheme,
which provides both QoS guarantee and efficient resource utilization,
be employed to optimize the channel spatial reuse and maximize the
system throughput. Extensive simulation results show that the
proposed mechanism achieves desirable performance in multichannel
multi-rate cognitive radio ad hoc networks.
Abstract: In this paper sensitivity analysis is performed for
reliability evaluation of power systems. When examining the
reliability of a system, it is useful to recognize how results
change as component parameters are varied. This knowledge
helps engineers to understand the impact of poor data, and
gives insight on how reliability can be improved. For these
reasons, a sensitivity analysis can be performed. Finally, a real
network was used for testing the presented method.
Abstract: Naïve Bayes classifiers are simple probabilistic
classifiers. Classification extracts patterns by using data file with a set
of labeled training examples and is currently one of the most
significant areas in data mining. However, Naïve Bayes assumes the
independence among the features. Structural learning among the
features thus helps in the classification problem. In this study, the use
of structural learning in Bayesian Network is proposed to be applied
where there are relationships between the features when using the
Naïve Bayes. The improvement in the classification using structural
learning is shown if there exist relationship between the features or
when they are not independent.
Abstract: Microstrip lines, widely used for good reason, are
broadband in frequency and provide circuits that are compact and
light in weight. They are generally economical to produce since they
are readily adaptable to hybrid and monolithic integrated circuit (IC)
fabrication technologies at RF and microwave frequencies. Although,
the existing EM simulation models used for the synthesis and
analysis of microstrip lines are reasonably accurate, they are
computationally intensive and time consuming. Neural networks
recently gained attention as fast and flexible vehicles to microwave
modeling, simulation and optimization. After learning and
abstracting from microwave data, through a process called training,
neural network models are used during microwave design to provide
instant answers to the task learned.This paper presents simple and
accurate ANN models for the synthesis and analysis of Microstrip
lines to more accurately compute the characteristic parameters and
the physical dimensions respectively for the required design
specifications.
Abstract: Several studies have been carried out, using various techniques, including neural networks, to discriminate vigilance states in humans from electroencephalographic (EEG) signals, but we are still far from results satisfactorily useable results. The work presented in this paper aims at improving this status with regards to 2 aspects. Firstly, we introduce an original procedure made of the association of two neural networks, a self organizing map (SOM) and a learning vector quantization (LVQ), that allows to automatically detect artefacted states and to separate the different levels of vigilance which is a major breakthrough in the field of vigilance. Lastly and more importantly, our study has been oriented toward real-worked situation and the resulting model can be easily implemented as a wearable device. It benefits from restricted computational and memory requirements and data access is very limited in time. Furthermore, some ongoing works demonstrate that this work should shortly results in the design and conception of a non invasive electronic wearable device.
Abstract: In this paper, application of artificial neural networks
in typical disease diagnosis has been investigated. The real procedure
of medical diagnosis which usually is employed by physicians was
analyzed and converted to a machine implementable format. Then
after selecting some symptoms of eight different diseases, a data set
contains the information of a few hundreds cases was configured and
applied to a MLP neural network. The results of the experiments and
also the advantages of using a fuzzy approach were discussed as
well. Outcomes suggest the role of effective symptoms selection and
the advantages of data fuzzificaton on a neural networks-based
automatic medical diagnosis system.
Abstract: This paper presents the development of a wavelet
based algorithm, for distinguishing between magnetizing inrush
currents and power system fault currents, which is quite adequate,
reliable, fast and computationally efficient tool. The proposed
technique consists of a preprocessing unit based on discrete wavelet
transform (DWT) in combination with an artificial neural network
(ANN) for detecting and classifying fault currents. The DWT acts as
an extractor of distinctive features in the input signals at the relay
location. This information is then fed into an ANN for classifying
fault and magnetizing inrush conditions. A 220/55/55 V, 50Hz
laboratory transformer connected to a 380 V power system were
simulated using ATP-EMTP. The DWT was implemented by using
Matlab and Coiflet mother wavelet was used to analyze primary
currents and generate training data. The simulated results presented
clearly show that the proposed technique can accurately discriminate
between magnetizing inrush and fault currents in transformer
protection.
Abstract: This paper argues that fostering mutual understanding in landscape planning is as much about the planners educating stakeholder groups as the stakeholders educating the planners. In other words it is an epistemological agreement as to the meaning and nature of place, especially where an effort is made to go beyond the quantitative aspects, which can be achieved by the phenomenological experience of the Virtual Reality (VR) environment. This education needs to be a bi-directional process in which distance can be both temporal as well as spatial separation of participants, that there needs to be a common framework of understanding in which neither 'side' is disadvantaged during the process of information exchange and it follows that a medium such as VR offers an effective way of overcoming some of the shortcomings of traditional media by taking advantage of continuing technological advances in Information, Technology and Communications (ITC). In this paper we make particular reference to this as an extension to Geographical Information Systems (GIS). VR as a two-way communication tool offers considerable potential particularly in the area of Public Participation GIS (PPGIS). Information rich virtual environments that can operate over broadband networks are now possible and thus allow for the representation of large amounts of qualitative and quantitative information 'side-by-side'. Therefore, with broadband access becoming standard for households and enterprises alike, distributed virtual reality environments have great potential to contribute to enabling stakeholder participation and mutual learning within the planning context.
Abstract: On one hand, SNMP (Simple Network Management
Protocol) allows integrating different enterprise elements connected
through Internet into a standardized remote management. On the
other hand, as a consequence of the success of Intelligent Houses
they can be connected through Internet now by means of a residential
gateway according to a common standard called OSGi (Open
Services Gateway initiative). Due to the specifics of OSGi Service
Platforms and their dynamic nature, specific design criterions should
be defined to implement SNMP Agents for OSGi in order to integrate
them into the SNMP remote management. Based on the analysis of
the relation between both standards (SNMP and OSGi), this paper
shows how OSGi Service Platforms can be included into the SNMP
management of a global enterprise, giving implementation details
about an SNMP Agent solution and the definition of a new MIB
(Management Information Base) for managing OSGi platforms that
takes into account the specifics and dynamic nature of OSGi.
Abstract: A direct adaptive controller for a class of unknown nonlinear discrete-time systems is presented in this article. The proposed controller is constructed by fuzzy rules emulated network (FREN). With its simple structure, the human knowledge about the plant is transferred to be if-then rules for setting the network. These adjustable parameters inside FREN are tuned by the learning mechanism with time varying step size or learning rate. The variation of learning rate is introduced by main theorem to improve the system performance and stabilization. Furthermore, the boundary of adjustable parameters is guaranteed through the on-line learning and membership functions properties. The validation of the theoretical findings is represented by some illustrated examples.
Abstract: In this paper a new fast simplification method is
presented. Such method realizes Karnough map with large
number of variables. In order to accelerate the operation of the
proposed method, a new approach for fast detection of group
of ones is presented. Such approach implemented in the
frequency domain. The search operation relies on performing
cross correlation in the frequency domain rather than time one.
It is proved mathematically and practically that the number of
computation steps required for the presented method is less
than that needed by conventional cross correlation. Simulation
results using MATLAB confirm the theoretical computations.
Furthermore, a powerful solution for realization of complex
functions is given. The simplified functions are implemented
by using a new desigen for neural networks. Neural networks
are used because they are fault tolerance and as a result they
can recognize signals even with noise or distortion. This is
very useful for logic functions used in data and computer
communications. Moreover, the implemented functions are
realized with minimum amount of components. This is done
by using modular neural nets (MNNs) that divide the input
space into several homogenous regions. Such approach is
applied to implement XOR function, 16 logic functions on one
bit level, and 2-bit digital multiplier. Compared to previous
non- modular designs, a clear reduction in the order of
computations and hardware requirements is achieved.