Abstract: Many Wireless Sensor Network (WSN) applications necessitate secure multicast services for the purpose of broadcasting delay sensitive data like video files and live telecast at fixed time-slot. This work provides a novel method to deal with end-to-end delay and drop rate of packets. Opportunistic Routing chooses a link based on the maximum probability of packet delivery ratio. Null Key Generation helps in authenticating packets to the receiver. Markov Decision Process based Adaptive Scheduling algorithm determines the time slot for packet transmission. Both theoretical analysis and simulation results show that the proposed protocol ensures better performance in terms of packet delivery ratio, average end-to-end delay and normalized routing overhead.
Abstract: Graph has become increasingly important in modeling
complicated structures and schemaless data such as proteins, chemical
compounds, and XML documents. Given a graph query, it is desirable
to retrieve graphs quickly from a large database via graph-based
indices. Different from the existing methods, our approach, called
VFM (Vertex to Frequent Feature Mapping), makes use of vertices
and decision features as the basic indexing feature. VFM constructs
two mappings between vertices and frequent features to answer graph
queries. The VFM approach not only provides an elegant solution to
the graph indexing problem, but also demonstrates how database
indexing and query processing can benefit from data mining,
especially frequent pattern mining. The results show that the proposed
method not only avoids the enumeration method of getting subgraphs
of query graph, but also effectively reduces the subgraph isomorphism
tests between the query graph and graphs in candidate answer set in
verification stage.
Abstract: In this work, we propose a hybrid heuristic in order to
solve the Team Orienteering Problem (TOP). Given a set of points (or
customers), each with associated score (profit or benefit), and a team
that has a fixed number of members, the problem to solve is to visit a
subset of points in order to maximize the total collected score. Each
member performs a tour starting at the start point, visiting distinct
customers and the tour terminates at the arrival point. In addition,
each point is visited at most once, and the total time in each tour
cannot be greater than a given value. The proposed heuristic combines
beam search and a local optimization strategy. The algorithm was
tested on several sets of instances and encouraging results were
obtained.
Abstract: Human activities are increasingly based on the use of remote resources and services, and on the interaction between
remotely located parties that may know little about each other. Mobile agents must be prepared to execute on different hosts with
various environmental security conditions. The aim of this paper is to
propose a trust based mechanism to improve the security of mobile
agents and allow their execution in various environments. Thus, an
adaptive trust mechanism is proposed. It is based on the dynamic interaction between the agent and the environment. Information
collected during the interaction enables generation of an environment
key. This key informs on the host-s trust degree and permits the mobile agent to adapt its execution. Trust estimation is based on
concrete parameters values. Thus, in case of distrust, the source of problem can be located and a mobile agent appropriate behavior can
be selected.
Abstract: Sequences of execution of algorithms in an interactive
manner using multimedia tools are employed in this paper. It helps to
realize the concept of fundamentals of algorithms such as searching
and sorting method in a simple manner. Visualization gains more
attention than theoretical study and it is an easy way of learning
process. We propose methods for finding runtime sequence of each
algorithm in an interactive way and aims to overcome the drawbacks
of the existing character systems. System illustrates each and every
step clearly using text and animation. Comparisons of its time
complexity have been carried out and results show that our approach
provides better perceptive of algorithms.
Abstract: The anti-lock braking systems installed on vehicles
for safe and effective braking, are high-order nonlinear and timevariant.
Using fuzzy logic controllers increase efficiency of such
systems, but impose a high computational complexity as well. The
main concept introduced by this paper is reducing computational
complexity of fuzzy controllers by deploying problem-solution data
structure. Unlike conventional methods that are based on
calculations, this approach is based on data oriented modeling.
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: This paper presents the design and implementation of CASTE, a Cloud-based automatic software test environment. We first present the architecture of CASTE, then the main packages and classes of it are described in detail. CASTE is built upon a private Infrastructure as a Service platform. Through concentrated resource management of virtualized testing environment and automatic execution control of test scripts, we get a better solution to the testing resource utilization and test automation problem. Experiments on CASTE give very appealing results.
Abstract: Keystroke authentication is a new access control system
to identify legitimate users via their typing behavior. In this paper,
machine learning techniques are adapted for keystroke authentication.
Seven learning methods are used to build models to differentiate user
keystroke patterns. The selected classification methods are Decision
Tree, Naive Bayesian, Instance Based Learning, Decision Table, One
Rule, Random Tree and K-star. Among these methods, three of them
are studied in more details. The results show that machine learning
is a feasible alternative for keystroke authentication. Compared to
the conventional Nearest Neighbour method in the recent research,
learning methods especially Decision Tree can be more accurate. In
addition, the experiment results reveal that 3-Grams is more accurate
than 2-Grams and 4-Grams for feature extraction. Also, combination
of attributes tend to result higher accuracy.
Abstract: Computer game industry has experienced exponential
growth in recent years. A game is a recreational activity involving
one or more players. Game input is information such as data,
commands, etc., which is passed to the game system at run time from
an external source. Conversely, game outputs are information which
are generated by the game system and passed to an external target,
but which is not used internally by the game. This paper identifies a
new classification scheme for game input and output, which is based
on player-s input and output. Using this, relationship table for game
input classifier and output classifier is developed.
Abstract: In most rule-induction algorithms, the only operator used against nominal attributes is the equality operator =. In this paper, we first propose the use of the inequality operator, ≠, in addition to the equality operator, to increase the expressiveness of induced rules. Then, we present a new method, Binary Coding, which can be used along with an arbitrary rule-induction algorithm to make use of the inequality operator without any need to change the algorithm. Experimental results suggest that the Binary Coding method is promising enough for further investigation, especially in cases where the minimum number of rules is desirable.
Abstract: This paper proposes a novel architecture for developing decision support systems. Unlike conventional decision support systems, the proposed architecture endeavors to reveal the decision-making process such that humans' subjectivity can be incorporated into a computerized system and, at the same time, to preserve the capability of the computerized system in processing information objectively. A number of techniques used in developing the decision support system are elaborated to make the decisionmarking process transparent. These include procedures for high dimensional data visualization, pattern classification, prediction, and evolutionary computational search. An artificial data set is first employed to compare the proposed approach with other methods. A simulated handwritten data set and a real data set on liver disease diagnosis are then employed to evaluate the efficacy of the proposed approach. The results are analyzed and discussed. The potentials of the proposed architecture as a useful decision support system are demonstrated.
Abstract: In the research field of Rough Set, few papers concern the significance of attribute set. However, there is important relation between the significance of single attribute and that of attribute set, which should not be ignored. In this paper, we draw conclusions by case analysis that (1) the attribute set including single attributes with high significance is certainly significant, while, (2)the attribute set which consists of single attributes with low significance possibly has high significance. We validate the conclusions on discernibility matrix and the results demonstrate the contribution of our conclusions.
Abstract: This paper may be considered as combination of both pervasive computing and Differential GPS (global positioning satellite) which relates to control automatic traffic signals in such a
way as to pre-empt normal signal operation and permit lifesaving vehicles. Before knowing the arrival of the lifesaving vehicles from
the signal there is a chance of clearing the traffic. Traffic signal
preemption system includes a vehicle equipped with onboard computer system capable of capturing diagnostic information and
estimated location of the lifesaving vehicle using the information provided by GPS receiver connected to the onboard computer system
and transmitting the information-s using a wireless transmitter via a
wireless network. The fleet management system connected to a
wireless receiver is capable of receiving the information transmitted
by the lifesaving vehicle .A computer is also located at the
intersection uses corrected vehicle position, speed & direction
measurements, in conjunction with previously recorded data defining
approach routes to the intersection, to determine the optimum time to
switch a traffic light controller to preemption mode so that lifesaving
vehicles can pass safely. In case when the ambulance need to take a
“U" turn in a heavy traffic area we suggest a solution. Now we are
going to make use of computerized median which uses LINKED
BLOCKS (removable) to solve the above problem.
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: Agriculture products are being more demanding in
market today. To increase its productivity, automation to produce
these products will be very helpful. The purpose of this work is to
measure and determine the ripeness and quality of watermelon. The
textures on watermelon skin will be captured using digital camera.
These images will be filtered using image processing technique. All
these information gathered will be trained using ANN to determine
the watermelon ripeness accuracy. Initial results showed that the best
model has produced percentage accuracy of 86.51%, when measured
at 32 hidden units with a balanced percentage rate of training dataset.
Abstract: This paper presents an overview of the design and
implementation of an online rule-based Expert Systems for Islamic
medication. T his Online Islamic Medication Expert System (OIMES)
focuses on physical illnesses only. Knowledge base of this Expert
System contains exhaustively the types of illness together with their
related cures or treatments/therapies, obtained exclusively from the
Quran and Hadith. Extensive research and study are conducted to
ensure that the Expert System is able to provide the most suitable
treatment with reference to the relevant verses cited in Quran or
Hadith. These verses come together with their related 'actions'
(bodily actions/gestures or some acts) to be performed by the patient
to treat a particular illness/sickness. These verses and the instructions
for the 'actions' are to be displayed unambiguously on the computer
screen. The online platform provides the advantage for patient getting
treatment practically anytime and anywhere as long as the computer
and Internet facility exist. Patient does not need to make appointment
to see an expert for a therapy.
Abstract: Efforts to secure supervisory control and data acquisition
(SCADA) systems must be supported under the guidance of
sound security policies and mechanisms to enforce them. Critical
elements of the policy must be systematically translated into a format
that can be used by policy enforcement components. Ideally, the
goal is to ensure that the enforced policy is a close reflection of
the specified policy. However, security controls commonly used to
enforce policies in the IT environment were not designed to satisfy
the specific needs of the SCADA environment. This paper presents
a language, based on the well-known XACML framework, for the
expression of authorization policies for SCADA systems.
Abstract: To support mobility in ATM networks, a number of
technical challenges need to be resolved. The impact of handoff
schemes in terms of service disruption, handoff latency, cost
implications and excess resources required during handoffs needs to
be addressed. In this paper, a one phase handoff and route
optimization solution using reserved PVCs between adjacent ATM
switches to reroute connections during inter-switch handoff is
studied. In the second phase, a distributed optimization process is
initiated to optimally reroute handoff connections. The main
objective is to find the optimal operating point at which to perform
optimization subject to cost constraint with the purpose of reducing
blocking probability of inter-switch handoff calls for delay tolerant
traffic. We examine the relation between the required bandwidth
resources and optimization rate. Also we calculate and study the
handoff blocking probability due to lack of bandwidth for resources
reserved to facilitate the rapid rerouting.
Abstract: CloudSim is a useful tool to simulate the cloud
environment. It shows the service availability, the power consumption,
and the network traffic of services on the cloud environment.
Moreover, it supports to calculate a network communication delay
through a network topology data easily. CloudSim allows inputting a
file of topology data, but it does not provide any generating process.
Thus, it needs the file of topology data generated from some other
tools. The BRITE is typical network topology generator. Also, it
supports various type of topology generating algorithms. If CloudSim
can include the BRITE, network simulation for clouds is easier than
existing version. This paper shows the potential of connection between
BRITE and CloudSim. Also, it proposes the direction to link between
them.