Abstract: At present, dictionary attack has been the basic tool for
recovering key passwords. In order to avoid dictionary attack, users
purposely choose another character strings as passwords. According to
statistics, about 14% of users choose keys on a keyboard (Kkey, for
short) as passwords. This paper develops a framework system to attack
the password chosen from Kkeys and analyzes its efficiency. Within
this system, we build up keyboard rules using the adjacent and parallel
relationship among Kkeys and then use these Kkey rules to generate
password databases by depth-first search method. According to the
experiment results, we find the key space of databases derived from
these Kkey rules that could be far smaller than the password databases
generated within brute-force attack, thus effectively narrowing down
the scope of attack research. Taking one general Kkey rule, the
combinations in all printable characters (94 types) with Kkey adjacent
and parallel relationship, as an example, the derived key space is about
240 smaller than those in brute-force attack. In addition, we
demonstrate the method's practicality and value by successfully
cracking the access password to UNIX and PC using the password
databases created
Abstract: The steady state response of bond graphs representing
passive and active suspension is presented. A bond graph with
preferred derivative causality assignment to get the steady state
is proposed. A general junction structure of this bond graph
is proposed. The proposed methodology to passive and active
suspensions is applied.
Abstract: Forecasting the values of the indicators, which
characterize the effectiveness of performance of organizations is of
great importance for their successful development. Such forecasting
is necessary in order to assess the current state and to foresee future
developments, so that measures to improve the organization-s
activity could be undertaken in time. The article presents an
overview of the applied mathematical and statistical methods for
developing forecasts. Special attention is paid to artificial neural
networks as a forecasting tool. Their strengths and weaknesses are
analyzed and a synopsis is made of the application of artificial neural
networks in the field of forecasting of the values of different
education efficiency indicators. A method of evaluation of the
activity of universities using the Balanced Scorecard is proposed and
Key Performance Indicators for assessment of e-learning are
selected. Resulting indicators for the evaluation of efficiency of the
activity are proposed. An artificial neural network is constructed and
applied in the forecasting of the values of indicators for e-learning
efficiency on the basis of the KPI values.
Abstract: The electronically available Urdu data is in image form
which is very difficult to process. Printed Urdu data is the root cause
of problem. So for the rapid progress of Urdu language we need an
OCR systems, which can help us to make Urdu data available for the
common person. Research has been carried out for years to automata
Arabic and Urdu script. But the biggest hurdle in the development of
Urdu OCR is the challenge to recognize Nastalique Script which is
taken as standard for writing Urdu language. Nastalique script is
written diagonally with no fixed baseline which makes the script
somewhat complex. Overlap is present not only in characters but in
the ligatures as well. This paper proposes a method which allows
successful recognition of Nastalique Script.
Abstract: Probability-based identity disclosure risk
measurement may give the same overall risk for different
anonymization strategy of the same dataset. Some entities in the
anonymous dataset may have higher identification risks than the
others. Individuals are more concerned about higher risks than the
average and are more interested to know if they have a possibility of
being under higher risk. A notation of overall risk in the above
measurement method doesn-t indicate whether some of the involved
entities have higher identity disclosure risk than the others. In this
paper, we have introduced an identity disclosure risk measurement
method that not only implies overall risk, but also indicates whether
some of the members have higher risk than the others. The proposed
method quantifies the overall risk based on the individual risk values,
the percentage of the records that have a risk value higher than the
average and how larger the higher risk values are compared to the
average. We have analyzed the disclosure risks for different
disclosure control techniques applied to original microdata and
present the results.
Abstract: The efficient use of available licensed spectrum is
becoming more and more critical with increasing demand and usage
of the radio spectrum. This paper shows how the use of spectrum as
well as dynamic spectrum management can be effectively managed
and spectrum allocation schemes in the wireless communication
systems be implemented and used, in future. This paper would be an
attempt towards better utilization of the spectrum. This research will
focus on the decision-making process mainly, with an
assumption that the radio environment has already been sensed and
the QoS requirements for the application have been specified either
by the sensed radio environment or by the secondary user itself. We
identify and study the characteristic parameters of Cognitive Radio
and use Genetic Algorithm for spectrum allocation. Performance
evaluation is done using MATLAB toolboxes.
Abstract: Scalability poses a severe threat to the existing
DRAM technology. The capacitors that are used for storing and
sensing charge in DRAM are generally not scaled beyond 42nm.
This is because; the capacitors must be sufficiently large for reliable
sensing and charge storage mechanism. This leaves DRAM memory
scaling in jeopardy, as charge sensing and storage mechanisms
become extremely difficult. In this paper we provide an overview of
the potential and the possibilities of using Phase Change Memory
(PCM) as an alternative for the existing DRAM technology. The
main challenges that we encounter in using PCM are, the limited
endurance, high access latencies, and higher dynamic energy
consumption than that of the conventional DRAM. We then provide
an overview of various methods, which can be employed to
overcome these drawbacks. Hybrid memories involving both PCM
and DRAM can be used, to achieve good tradeoffs in access latency
and storage density. We conclude by presenting, the results of these
methods that makes PCM a potential replacement for the current
DRAM technology.
Abstract: Adaptive control involves modifying the control law
used by the controller to cope with the fact that the parameters of the
system being controlled change drastically due to change in
environmental conditions or in system itself. This technique is based
on the fundamental characteristic of adaptation of living organism.
The adaptive control process is one that continuously and
automatically measures the dynamic behavior of plant, compares it
with the desired output and uses the difference to vary adjustable
system parameters or to generate an actuating signal in such a way so
that optimal performance can be maintained regardless of system
changes. This paper deals with application of model reference
adaptive control scheme in first order system. The rule which is used
for this application is MIT rule. This paper also shows the effect of
adaptation gain on the system performance. Simulation is done in
MATLAB and results are discussed in detail.
Abstract: Classifying data hierarchically is an efficient approach
to analyze data. Data is usually classified into multiple categories, or
annotated with a set of labels. To analyze multi-labeled data, such
data must be specified by giving a set of labels as a semantic range.
There are some certain purposes to analyze data. This paper shows
which multi-labeled data should be the target to be analyzed for
those purposes, and discusses the role of a label against a set of
labels by investigating the change when a label is added to the set of
labels. These discussions give the methods for the advanced analysis
of multi-labeled data, which are based on the role of a label against
a semantic range.
Abstract: In this paper, we present a method named Signal Level
Matrix (SLM) which can improve the accuracy and stability of active
RFID indoor positioning system. Considering the accuracy and cost,
we use uniform distribution mode to set up and separate the
overlapped signal covering areas, in order to achieve preliminary
location setting. Then, based on the proposed SLM concept and the
characteristic of the signal strength value that attenuates as the
distance increases, this system cross-examines the distribution of
adjacent signals to locate the users more accurately. The experimental
results indicate that the adaptive positioning method proposed in this
paper could improve the accuracy and stability of the positioning
system effectively and satisfyingly.
Abstract: Internet is largely composed of textual contents and a
huge volume of digital contents gets floated over the Internet daily.
The ease of information sharing and re-production has made it
difficult to preserve author-s copyright. Digital watermarking came
up as a solution for copyright protection of plain text problem after
1993. In this paper, we propose a zero text watermarking algorithm
based on occurrence frequency of non-vowel ASCII characters and
words for copyright protection of plain text. The embedding
algorithm makes use of frequency non-vowel ASCII characters and
words to generate a specialized author key. The extraction algorithm
uses this key to extract watermark, hence identify the original
copyright owner. Experimental results illustrate the effectiveness of
the proposed algorithm on text encountering meaning preserving
attacks performed by five independent attackers.
Abstract: This paper proposes the analysis and design of robust
fuzzy control to Stochastic Parametrics Uncertaint Linear systems.
This system type to be controlled is partitioned into several linear
sub-models, in terms of transfer function, forming a convex polytope,
similar to LPV (Linear Parameters Varying) system. Once defined the
linear sub-models of the plant, these are organized into fuzzy Takagi-
Sugeno (TS) structure. From the Parallel Distributed Compensation
(PDC) strategy, a mathematical formulation is defined in the frequency
domain, based on the gain and phase margins specifications,
to obtain robust PI sub-controllers in accordance to the Takagi-
Sugeno fuzzy model of the plant. The main results of the paper are
based on the robust stability conditions with the proposal of one
Axiom and two Theorems.
Abstract: The stem cells have ability to differentiated
themselves through mitotic cell division and various range of
specialized cell types. Cellular differentiation is a way by which few
specialized cell develops into more specialized.This paper studies the
fundamental problem of computational schema for an artificial neural
network based on chemical, physical and biological variables of
state. By doing this type of study system could be model for a viable
propagation of various economically important stem cells
differentiation. This paper proposes various differentiation outcomes
of artificial neural network into variety of potential specialized cells
on implementing MATLAB version 2009. A feed-forward back
propagation kind of network was created to input vector (five input
elements) with single hidden layer and one output unit in output
layer. The efficiency of neural network was done by the assessment
of results achieved from this study with that of experimental data
input and chosen target data. The propose solution for the efficiency
of artificial neural network assessed by the comparatative analysis of
“Mean Square Error" at zero epochs. There are different variables of
data in order to test the targeted results.
Abstract: This paper proposes improved delay-dependent stability conditions of the linear time-delay systems of neutral type. The proposed methods employ a suitable Lyapunov-Krasovskii’s functional and a new form of the augmented system. New delay-dependent stability criteria for the systems are established in terms of Linear matrix inequalities (LMIs) which can be easily solved by various effective optimization algorithms. Numerical examples showed that the proposed method is effective and can provide less conservative results.
Abstract: To solve the problem of multisensor data fusion under
non-Gaussian channel noise. The advanced M-estimates are known
to be robust solution while trading off some accuracy. In order to
improve the estimation accuracy while still maintaining the equivalent
robustness, a two-stage robust fusion algorithm is proposed using
preliminary rejection of outliers then an optimal linear fusion. The
numerical experiments show that the proposed algorithm is equivalent
to the M-estimates in the case of uncorrelated local estimates and
significantly outperforms the M-estimates when local estimates are
correlated.
Abstract: The aim of this article is to explain how features of attacks could be extracted from the packets. It also explains how vectors could be built and then applied to the input of any analysis stage. For analyzing, the work deploys the Feedforward-Back propagation neural network to act as misuse intrusion detection system. It uses ten types if attacks as example for training and testing the neural network. It explains how the packets are analyzed to extract features. The work shows how selecting the right features, building correct vectors and how correct identification of the training methods with nodes- number in hidden layer of any neural network affecting the accuracy of system. In addition, the work shows how to get values of optimal weights and use them to initialize the Artificial Neural Network.
Abstract: We developed a GPS-based navigation device for the
blind, with audio guidance in Thai language. The device is composed
of simple and inexpensive hardware components. Its user interface is
quite simple. It determines optimal routes to various landmarks in our
university campus by using heuristic search for the next waypoints.
We tested the device and made note of its limitations and possible
extensions.
Abstract: Global competitiveness has recently become the
biggest concern of both manufacturing and service companies.
Electronic commerce, as a key technology enables the firms to reach
all the potential consumers from all over the world. In this study, we
have presented commonly used electronic payment systems, and then
we have shown the evaluation of these systems in respect to different
criteria. The payment systems which are included in this research are
the credit card, the virtual credit card, the electronic money, the
mobile payment, the credit transfer and the debit instruments. We
have realized a systematic comparison of these systems in respect to
three main criteria: Technical, economical and social. We have
conducted a fuzzy multi-criteria decision making procedure to deal
with the multi-attribute nature of the problem. The subjectiveness
and imprecision of the evaluation process are modeled using
triangular fuzzy numbers.
Abstract: The necessity of accurate and timely field data is
shared among organizations engaged in fundamentally different
activities, public services or commercial operations. Basically, there
are three major components in the process of the qualitative research:
data collection, interpretation and organization of data, and analytic
process. Representative technological advancements in terms of
innovation have been made in mobile devices (mobile phone, PDA-s,
tablets, laptops, etc). Resources that can be potentially applied on the
data collection activity for field researches in order to improve this
process.
This paper presents and discuss the main features of a mobile
phone based solution for field data collection, composed of basically
three modules: a survey editor, a server web application and a client
mobile application. The data gathering process begins with the
survey creation module, which enables the production of tailored
questionnaires. The field workforce receives the questionnaire(s) on
their mobile phones to collect the interviews responses and sending
them back to a server for immediate analysis.
Abstract: With the increasing number of on-chip components and the critical requirement for processing power, Chip Multiprocessor (CMP) has gained wide acceptance in both academia and industry during the last decade. However, the conventional bus-based onchip communication schemes suffer from very high communication delay and low scalability in large scale systems. Network-on-Chip (NoC) has been proposed to solve the bottleneck of parallel onchip communications by applying different network topologies which separate the communication phase from the computation phase. Observing that the memory bandwidth of the communication between on-chip components and off-chip memory has become a critical problem even in NoC based systems, in this paper, we propose a novel 3D NoC with on-chip Dynamic Random Access Memory (DRAM) in which different layers are dedicated to different functionalities such as processors, cache or memory. Results show that, by using our proposed architecture, average link utilization has reduced by 10.25% for SPLASH-2 workloads. Our proposed design costs 1.12% less execution cycles than the traditional design on average.