Abstract: A prototype of an anomaly detection system was
developed to automate process of recognizing an anomaly of
roentgen image by utilizing fuzzy histogram hyperbolization image
enhancement and back propagation artificial neural network.
The system consists of image acquisition, pre-processor, feature
extractor, response selector and output. Fuzzy Histogram
Hyperbolization is chosen to improve the quality of the roentgen
image. The fuzzy histogram hyperbolization steps consist of
fuzzyfication, modification of values of membership functions and
defuzzyfication. Image features are extracted after the the quality of
the image is improved. The extracted image features are input to the
artificial neural network for detecting anomaly. The number of nodes
in the proposed ANN layers was made small.
Experimental results indicate that the fuzzy histogram
hyperbolization method can be used to improve the quality of the
image. The system is capable to detect the anomaly in the roentgen
image.
Abstract: Trust and Energy consumption is the most challenging
issue in routing protocol design for Mobile ad hoc networks
(MANETs), since mobile nodes are battery powered and nodes
behaviour are unpredictable. Furthermore replacing and recharging
batteries and making nodes co-operative is often impossible in
critical environments like military applications. In this paper, we
propose a trust based energy aware routing model in MANET.
During route discovery, node with more trust and maximum energy
capacity is selected as a router based on a parameter called
'Reliability'. Route request from the source is accepted by a node
only if its reliability is high. Otherwise, the route request is
discarded. This approach forms a reliable route from source to
destination thus increasing network life time, improving energy
utilization and decreasing number of packet loss during transmission.
Abstract: Resource Discovery in Grids is critical for efficient
resource allocation and management. Heterogeneous nature and
dynamic availability of resources make resource discovery a
challenging task. As numbers of nodes are increasing from tens to
thousands, scalability is essentially desired. Peer-to-Peer (P2P)
techniques, on the other hand, provide effective implementation of
scalable services and applications. In this paper we propose a model
for resource discovery in Condor Middleware by using the four axis
framework defined in P2P approach. The proposed model enhances
Condor to incorporate functionality of a P2P system, thus aim to
make Condor more scalable, flexible, reliable and robust.
Abstract: This paper deals with dynamic load balancing using PVM. In distributed environment Load Balancing and Heterogeneity are very critical issues and needed to drill down in order to achieve the optimal results and efficiency. Various techniques are being used in order to distribute the load dynamically among different nodes and to deal with heterogeneity. These techniques are using different approaches where Process Migration is basic concept with different optimal flavors. But Process Migration is not an easy job, it impose lot of burden and processing effort in order to track each process in nodes. We will propose a dynamic load balancing technique in which application will intelligently balance the load among different nodes, resulting in efficient use of system and have no overheads of process migration. It would also provide a simple solution to problem of load balancing in heterogeneous environment.
Abstract: Over the past few years, a number of efforts have
been exerted to build parallel processing systems that utilize the idle
power of LAN-s and PC-s available in many homes and corporations.
The main advantage of these approaches is that they provide cheap
parallel processing environments for those who cannot afford the
expenses of supercomputers and parallel processing hardware.
However, most of the solutions provided are not very flexible in the
use of available resources and very difficult to install and setup.
In this paper, a multi-level web-based parallel processing system
(MWPS) is designed (appendix). MWPS is based on the idea of
volunteer computing, very flexible, easy to setup and easy to use.
MWPS allows three types of subscribers: simple volunteers (single
computers), super volunteers (full networks) and end users. All of
these entities are coordinated transparently through a secure web site.
Volunteer nodes provide the required processing power needed by
the system end users. There is no limit on the number of volunteer
nodes, and accordingly the system can grow indefinitely. Both
volunteer and system users must register and subscribe. Once, they
subscribe, each entity is provided with the appropriate MWPS
components. These components are very easy to install.
Super volunteer nodes are provided with special components that
make it possible to delegate some of the load to their inner nodes.
These inner nodes may also delegate some of the load to some other
lower level inner nodes .... and so on. It is the responsibility of the
parent super nodes to coordinate the delegation process and deliver
the results back to the user.
MWPS uses a simple behavior-based scheduler that takes into
consideration the current load and previous behavior of processing
nodes. Nodes that fulfill their contracts within the expected time get a
high degree of trust. Nodes that fail to satisfy their contract get a
lower degree of trust.
MWPS is based on the .NET framework and provides the minimal
level of security expected in distributed processing environments.
Users and processing nodes are fully authenticated. Communications
and messages between nodes are very secure. The system has been
implemented using C#.
MWPS may be used by any group of people or companies to
establish a parallel processing or grid environment.
Abstract: Multiparty voice over IP (MVoIP) systems allows a group of people to freely communicate each other via the internet, which have many applications such as online gaming, teleconferencing, online stock trading etc. Peertalk is a peer to peer multiparty voice over IP system (MVoIP) which is more feasible than existing approaches such as p2p overlay multicast and coupled distributed processing. Since the stream mixing and distribution are done by the peers, it is vulnerable to major security threats like nodes misbehavior, eavesdropping, Sybil attacks, Denial of Service (DoS), call tampering, Man in the Middle attacks etc. To thwart the security threats, a security framework called PEERTS (PEEred Reputed Trustworthy System for peertalk) is implemented so that efficient and secure communication can be carried out between peers.
Abstract: The mitigation of crop loss due to damaging freezes
requires accurate air temperature prediction models. Previous work
established that the Ward-style artificial neural network (ANN) is a
suitable tool for developing such models. The current research
focused on developing ANN models with reduced average prediction
error by increasing the number of distinct observations used in
training, adding additional input terms that describe the date of an
observation, increasing the duration of prior weather data included in
each observation, and reexamining the number of hidden nodes used
in the network. Models were created to predict air temperature at
hourly intervals from one to 12 hours ahead. Each ANN model,
consisting of a network architecture and set of associated parameters,
was evaluated by instantiating and training 30 networks and
calculating the mean absolute error (MAE) of the resulting networks
for some set of input patterns. The inclusion of seasonal input terms,
up to 24 hours of prior weather information, and a larger number of
processing nodes were some of the improvements that reduced
average prediction error compared to previous research across all
horizons. For example, the four-hour MAE of 1.40°C was 0.20°C, or
12.5%, less than the previous model. Prediction MAEs eight and 12
hours ahead improved by 0.17°C and 0.16°C, respectively,
improvements of 7.4% and 5.9% over the existing model at these
horizons. Networks instantiating the same model but with different
initial random weights often led to different prediction errors. These
results strongly suggest that ANN model developers should consider
instantiating and training multiple networks with different initial
weights to establish preferred model parameters.
Abstract: This paper deals with wireless relay communication
systems in which multiple sources transmit information to the
destination node by the help of multiple relays. We consider a
signal forwarding technique based on the minimum mean-square
error (MMSE) approach with multiple antennas for each relay. A
source-relay-destination joint design strategy is proposed with power
constraints at the destination and the source nodes. Simulation results
confirm that the proposed joint design method improves the average
MSE performance compared with that of conventional MMSE relaying
schemes.
Abstract: We propose an enhanced key management scheme
based on Key Infection, which is lightweight scheme for tiny sensors.
The basic scheme, Key Infection, is perfectly secure against node
capture and eavesdropping if initial communications after node
deployment is secure. If, however, an attacker can eavesdrop on
the initial communications, they can take the session key. We use
common neighbors for each node to generate the session key. Each
node has own secret key and shares it with its neighbor nodes. Then
each node can establish the session key using common neighbors-
secret keys and a random number. Our scheme needs only a few
communications even if it uses neighbor nodes- information. Without
losing the lightness of basic scheme, it improves the resistance against
eavesdropping on the initial communications more than 30%.
Abstract: Task of object localization is one of the major
challenges in creating intelligent transportation. Unfortunately, in
densely built-up urban areas, localization based on GPS only
produces a large error, or simply becomes impossible. New
opportunities arise for the localization due to the rapidly emerging
concept of a wireless ad-hoc network. Such network, allows
estimating potential distance between these objects measuring
received signal level and construct a graph of distances in which
nodes are the localization objects, and edges - estimates of the
distances between pairs of nodes. Due to the known coordinates of
individual nodes (anchors), it is possible to determine the location of
all (or part) of the remaining nodes of the graph. Moreover, road
map, available in digital format can provide localization routines
with valuable additional information to narrow node location search.
However, despite abundance of well-known algorithms for solving
the problem of localization and significant research efforts, there are
still many issues that currently are addressed only partially. In this
paper, we propose localization approach based on the graph mapped
distances on the digital road map data basis. In fact, problem is
reduced to distance graph embedding into the graph representing area
geo location data. It makes possible to localize objects, in some cases
even if only one reference point is available. We propose simple
embedding algorithm and sample implementation as spatial queries
over sensor network data stored in spatial database, allowing
employing effectively spatial indexing, optimized spatial search
routines and geometry functions.
Abstract: One of the most important applications of
wireless sensor networks is data collection. This paper
proposes as efficient approach for data collection in wireless
sensor networks by introducing Member Forward List. This list
includes the nodes with highest priority for forwarding the data.
When a node fails or dies, this list is used to select the next node
with higher priority. The benefit of this node is that it prevents
the algorithm from repeating when a node fails or dies. The
results show that Member Forward List decreases power
consumption and latency in wireless sensor networks.
Abstract: Sequential pattern mining is a challenging task in data mining area with large applications. One among those applications is mining patterns from weblog. Recent times, weblog is highly dynamic and some of them may become absolute over time. In addition, users may frequently change the threshold value during the data mining process until acquiring required output or mining interesting rules. Some of the recently proposed algorithms for mining weblog, build the tree with two scans and always consume large time and space. In this paper, we build Revised PLWAP with Non-frequent Items (RePLNI-tree) with single scan for all items. While mining sequential patterns, the links related to the nonfrequent items are not considered. Hence, it is not required to delete or maintain the information of nodes while revising the tree for mining updated transactions. The algorithm supports both incremental and interactive mining. It is not required to re-compute the patterns each time, while weblog is updated or minimum support changed. The performance of the proposed tree is better, even the size of incremental database is more than 50% of existing one. For evaluation purpose, we have used the benchmark weblog dataset and found that the performance of proposed tree is encouraging compared to some of the recently proposed approaches.
Abstract: Wireless Sensor Networks (WSN) are emerging
because of the developments in wireless communication technology and miniaturization of the hardware. WSN consists of a large number of low-cost, low-power, multifunctional sensor nodes to monitor physical conditions, such as temperature, sound, vibration, pressure,
motion, etc. The MAC protocol to be used in the sensor networks must be energy efficient and this should aim at conserving the energy during its operation. In this paper, with the focus of analyzing the
MAC protocols used in wireless Adhoc networks to WSN, simulation
experiments were conducted in Global Mobile Simulator
(GloMoSim) software. Number of packets sent by regular nodes, and received by sink node in different deployment strategies, total energy
spent, and the network life time have been chosen as the metric for comparison. From the results of simulation, it is evident that the IEEE 802.11 protocol performs better compared to CSMA and MACA protocols.
Abstract: Environment both endowed and built are essential for
tourism. However tourism and environment maintains a complex
relationship, where in most cases environment is at the receiving end.
Many tourism development activities have adverse environmental
effects, mainly emanating from construction of general infrastructure
and tourism facilities. These negative impacts of tourism can lead to
the destruction of precious natural resources on which it depends.
These effects vary between locations; and its effect on a hill
destination is highly critical. This study aims at developing a
Sustainable Tourism Planning Model for an environmentally
sensitive tourism destination in Kerala, India. Being part of the
Nilgiri mountain ranges, Munnar falls in the Western Ghats, one of
the biological hotspots in the world. Endowed with a unique high
altitude environment Munnar inherits highly significant ecological
wealth. Giving prime importance to the protection of this ecological
heritage, the study proposes a tourism planning model with resource
conservation and sustainability as the paramount focus. Conceiving a
novel approach towards sustainable tourism planning, the study
proposes to assess tourism attractions using Ecological Sensitivity
Index (ESI) and Tourism Attractiveness Index (TAI). Integration of
these two indices will form the Ecology – Tourism Matrix (ETM),
outlining the base for tourism planning in an environmentally
sensitive destination. The ETM Matrix leads to a classification of
tourism nodes according to its Conservation Significance and
Tourism Significance. The spatial integration of such nodes based on
the Hub & Spoke Principle constitutes sub – regions within the STZ.
Ensuing analyses lead to specific guidelines for the STZ as a whole,
specific tourism nodes, hubs and sub-regions. The study results in a
multi – dimensional output, viz., (1) Classification system for tourism
nodes in an environmentally sensitive region/ destination (2)
Conservation / Tourism Development Strategies and Guidelines for
the micro and macro regions and (3) A Sustainable Tourism Planning
Tool particularly for Ecologically Sensitive Destinations, which can
be adapted for other destinations as well.
Abstract: In the context of channel coding, the Generalized Belief Propagation (GBP) is an iterative algorithm used to recover the transmission bits sent through a noisy channel. To ensure a reliable transmission, we apply a map on the bits, that is called a code. This code induces artificial correlations between the bits to send, and it can be modeled by a graph whose nodes are the bits and the edges are the correlations. This graph, called Tanner graph, is used for most of the decoding algorithms like Belief Propagation or Gallager-B. The GBP is based on a non unic transformation of the Tanner graph into a so called region-graph. A clear advantage of the GBP over the other algorithms is the freedom in the construction of this graph. In this article, we explain a particular construction for specific graph topologies that involves relevant performance of the GBP. Moreover, we investigate the behavior of the GBP considered as a dynamic system in order to understand the way it evolves in terms of the time and in terms of the noise power of the channel. To this end we make use of classical measures and we introduce a new measure called the hyperspheres method that enables to know the size of the attractors.
Abstract: Movable power sources of proton exchange
membrane fuel cells (PEMFC) are the important research done in the
current fuel cells (FC) field. The PEMFC system control influences
the cell performance greatly and it is a control system for industrial
complex problems, due to the imprecision, uncertainty and partial
truth and intrinsic nonlinear characteristics of PEMFCs. In this paper
an adaptive PI control strategy using neural network adaptive Morlet
wavelet for control is proposed. It is based on a single layer feed
forward neural networks with hidden nodes of adaptive morlet
wavelet functions controller and an infinite impulse response (IIR)
recurrent structure. The IIR is combined by cascading to the network
to provide double local structure resulting in improving speed of
learning. The proposed method is applied to a typical 1 KW PEMFC
system and the results show the proposed method has more accuracy
against to MLP (Multi Layer Perceptron) method.
Abstract: In this paper, Land Marks for Unique Addressing( LMUA) algorithm is develped to generate unique ID for each and every node which leads to the formation of overlapping/Non overlapping clusters based on unique ID. To overcome the draw back of the developed LMUA algorithm, the concept of clustering is introduced. Based on the clustering concept a Land Marks for Unique Addressing and Clustering(LMUAC) Algorithm is developed to construct strictly non-overlapping clusters and classify those nodes in to Cluster Heads, Member Nodes, Gate way nodes and generating the Hierarchical code for the cluster heads to operate in the level one hierarchy for wireless communication switching. The expansion of the existing network can be performed or not without modifying the cost of adding the clusterhead is shown. The developed algorithm shows one way of efficiently constructing the
Abstract: To meet the demands of wireless sensor networks
(WSNs) where data are usually aggregated at a single source prior to
transmitting to any distant user, there is a need to establish a tree
structure inside any given event region. In this paper , a novel
technique to create one such tree is proposed .This tree preserves the
energy and maximizes the lifetime of event sources while they are
constantly transmitting for data aggregation. The term Decentralized
Lifetime Maximizing Tree (DLMT) is used to denote this tree.
DLMT features in nodes with higher energy tend to be chosen as data
aggregating parents so that the time to detect the first broken tree link
can be extended and less energy is involved in tree maintenance. By
constructing the tree in such a way, the protocol is able to reduce the
frequency of tree reconstruction, minimize the amount of data loss
,minimize the delay during data collection and preserves the energy.
Abstract: In this document, we have proposed a robust
conceptual strategy, in order to improve the robustness against the manufacturing defects and thus the reliability of logic CMOS circuits. However, in order to enable the use of future CMOS
technology nodes this strategy combines various types of design:
DFR (Design for Reliability), techniques of tolerance: hardware
redundancy TMR (Triple Modular Redundancy) for hard error
tolerance, the DFT (Design for Testability. The Results on largest ISCAS and ITC benchmark circuits show that our approach improves
considerably the reliability, by reducing the key factors, the area costs and fault tolerance probability.
Abstract: The vertex connectivity of a graph is the smallest number of vertices whose deletion separates the graph or makes it trivial. This work is devoted to the problem of vertex connectivity test of graphs in a distributed environment based on a general and a constructive approach. The contribution of this paper is threefold. First, using a preconstructed spanning tree of the considered graph, we present a protocol to test whether a given graph is 2-connected using only local knowledge. Second, we present an encoding of this protocol using graph relabeling systems. The last contribution is the implementation of this protocol in the message passing model. For a given graph G, where M is the number of its edges, N the number of its nodes and Δ is its degree, our algorithms need the following requirements: The first one uses O(Δ×N2) steps and O(Δ×logΔ) bits per node. The second one uses O(Δ×N2) messages, O(N2) time and O(Δ × logΔ) bits per node. Furthermore, the studied network is semi-anonymous: Only the root of the pre-constructed spanning tree needs to be identified.