Abstract: The intrusion detection problem has been frequently studied, but intrusion detection methods are often based on a single point of view, which always limits the results. In this paper, we introduce a new intrusion detection model based on the combination of different current methods. First we use a notion of distance to unify the different methods. Second we combine these methods using the Pearson correlation coefficients, which measure the relationship between two methods, and we obtain a combined distance. If the combined distance is greater than a predetermined threshold, an intrusion is detected. We have implemented and tested the combination model with two different public data sets: the data set of masquerade detection collected by Schonlau & al., and the data set of program behaviors from the University of New Mexico. The results of the experiments prove that the combination model has better performances.
Abstract: This paper proposed high level feature for online Lao handwritten recognition. This feature must be high level enough so that the feature is not change when characters are written by different persons at different speed and different proportion (shorter or longer stroke, head, tail, loop, curve). In this high level feature, a character is divided in to sequence of curve segments where a segment start where curve reverse rotation (counter clockwise and clockwise). In each segment, following features are gathered cumulative change in direction of curve (- for clockwise), cumulative curve length, cumulative length of left to right, right to left, top to bottom and bottom to top ( cumulative change in X and Y axis of segment). This feature is simple yet robust for high accuracy recognition. The feature can be gather from parsing the original time sampling sequence X, Y point of the pen location without re-sampling. We also experiment on other segmentation point such as the maximum curvature point which was widely used by other researcher. Experiments results show that the recognition rates are at 94.62% in comparing to using maximum curvature point 75.07%. This is due to a lot of variations of turning points in handwritten.
Abstract: This paper is a review on the aspects and approaches of design an image cryptosystem. First a general introduction given for cryptography and images encryption and followed by different techniques in image encryption and related works for each technique surveyed. Finally, general security analysis methods for encrypted images are mentioned.
Abstract: The success of IT-projects concerning the
implementation of business application Software is strongly
depending upon the application of an efficient requirements
management, to understand the business requirements and to realize
them in the IT. But in fact, the Potentials of the requirements
management are not fully exhausted by small and medium sized
enterprises (SME) of the IT sector. To work out recommendations for
action and furthermore a possible solution, allowing a better exhaust
of potentials, it shall be examined in a scientific research project,
which problems occur out of which causes. In the same place, the
storage of knowledge from the requirements management, and its
later reuse are important, to achieve sustainable improvements of the
competitive of the IT-SMEs. Requirements Engineering is one of the
most important topics in Product Management for Software to
achieve the goal of optimizing the success of the software product.
Abstract: Developed tool is one of system tools for easier access to various scientific areas and real time interactive learning between
lecturer and for hearing impaired students. There is no demand for the lecturer to know Sign Language (SL). Instead, the new software
tools will perform the translation of the regular speech into SL, after
which it will be transferred to the student. On the other side, the
questions of the student (in SL) will be translated and transferred to
the lecturer in text or speech. One of those tools is presented tool. It-s
too for developing the correct Speech Visemes as a root of total communication method for hearing impared students.
Abstract: Data security in u-Health system can be an important
issue because wireless network is vulnerable to hacking. However, it is
not easy to implement a proper security algorithm in an embedded
u-health monitoring because of hardware constraints such as low
performance, power consumption and limited memory size and etc. To
secure data that contain personal and biosignal information, we
implemented several security algorithms such as Blowfish, data
encryption standard (DES), advanced encryption standard (AES) and
Rivest Cipher 4 (RC4) for our u-Health monitoring system and the
results were successful. Under the same experimental conditions, we
compared these algorithms. RC4 had the fastest execution time.
Memory usage was the most efficient for DES. However, considering
performance and safety capability, however, we concluded that AES
was the most appropriate algorithm for a personal u-Health monitoring
system.
Abstract: In this paper, a Bayesian Network (BN) based system
is presented for providing clinical decision support to healthcare
practitioners in rural or remote areas of India for young infants or
children up to the age of 5 years. The government is unable to
appoint child specialists in rural areas because of inadequate number
of available pediatricians. It leads to a high Infant Mortality Rate
(IMR). In such a scenario, Intelligent Pediatric System provides a
realistic solution. The prototype of an intelligent system has been
developed that involves a knowledge component called an Intelligent
Pediatric Assistant (IPA); and User Agents (UA) along with their
Graphical User Interfaces (GUI). The GUI of UA provides the
interface to the healthcare practitioner for submitting sign-symptoms
and displaying the expert opinion as suggested by IPA. Depending
upon the observations, the IPA decides the diagnosis and the
treatment plan. The UA and IPA form client-server architecture for
knowledge sharing.
Abstract: In this paper we present the design of a new encryption scheme. The scheme we propose is a very exible encryption and authentication primitive. We build this scheme on two relatively new design principles: t-functions and fast pseudo hadamard transforms. We recapitulate the theory behind these principles and analyze their security properties and efficiency. In more detail we propose a streamcipher which outputs a message authentication tag along with theencrypted data stream with only little overhead. Moreover we proposesecurity-speed tradeoffs. Our scheme is faster than other comparablet-function based designs while offering the same security level.
Abstract: This paper proposes a new approach for image encryption
using a combination of different permutation techniques.
The main idea behind the present work is that an image can be
viewed as an arrangement of bits, pixels and blocks. The intelligible
information present in an image is due to the correlations among the
bits, pixels and blocks in a given arrangement. This perceivable information
can be reduced by decreasing the correlation among the bits,
pixels and blocks using certain permutation techniques. This paper
presents an approach for a random combination of the aforementioned
permutations for image encryption. From the results, it is observed
that the permutation of bits is effective in significantly reducing the
correlation thereby decreasing the perceptual information, whereas
the permutation of pixels and blocks are good at producing higher
level security compared to bit permutation. A random combination
method employing all the three techniques thus is observed to be
useful for tactical security applications, where protection is needed
only against a casual observer.
Abstract: Automatic currency note recognition invariably
depends on the currency note characteristics of a particular country
and the extraction of features directly affects the recognition ability.
Sri Lanka has not been involved in any kind of research or
implementation of this kind. The proposed system “SLCRec" comes
up with a solution focusing on minimizing false rejection of notes.
Sri Lankan currency notes undergo severe changes in image quality
in usage. Hence a special linear transformation function is adapted to
wipe out noise patterns from backgrounds without affecting the
notes- characteristic images and re-appear images of interest. The
transformation maps the original gray scale range into a smaller
range of 0 to 125. Applying Edge detection after the transformation
provided better robustness for noise and fair representation of edges
for new and old damaged notes. A three layer back propagation
neural network is presented with the number of edges detected in row
order of the notes and classification is accepted in four classes of
interest which are 100, 500, 1000 and 2000 rupee notes. The
experiments showed good classification results and proved that the
proposed methodology has the capability of separating classes
properly in varying image conditions.
Abstract: The necessity of ever-increasing use of distributed
data in computer networks is obvious for all. One technique that is
performed on the distributed data for increasing of efficiency and
reliablity is data rplication. In this paper, after introducing this
technique and its advantages, we will examine some dynamic data
replication. We will examine their characteristies for some overus
scenario and the we will propose some suggestion for their
improvement.
Abstract: In this study, a new criterion for determining the number of classes an image should be segmented is proposed. This criterion is based on discriminant analysis for measuring the separability among the segmented classes of pixels. Based on the new discriminant criterion, two algorithms for recursively segmenting the image into determined number of classes are proposed. The proposed methods can automatically and correctly segment objects with various illuminations into separated images for further processing. Experiments on the extraction of text strings from complex document images demonstrate the effectiveness of the proposed methods.1
Abstract: The goal of the study reported in the paper was to
determine whether Ambient Occlusion Shading (AOS) has a significant effect on users' perception of American Sign Language (ASL) finger spelling animations. Seventy-one (71) subjects
participated in the study; all subjects were fluent in ASL. The participants were asked to watch forty (40) sign language animation
clips representing twenty (20) finger spelled words. Twenty (20) clips did not show ambient occlusion, whereas the other twenty (20) were
rendered using ambient occlusion shading. After viewing each animation, subjects were asked to type the word being finger-spelled and rate its legibility. Findings show that the presence of AOS had a significant effect on the subjects perception of the signed words.
Subjects were able to recognize the animated words rendered with AOS with higher level of accuracy, and the legibility ratings of the animations showing AOS were consistently higher across subjects.
Abstract: This paper presents a new version of the SVM mixture algorithm initially proposed by Kwok for classification and regression problems. For both cases, a slight modification of the mixture model leads to a standard SVM training problem, to the existence of an exact solution and allows the direct use of well known decomposition and working set selection algorithms. Only the regression case is considered in this paper but classification has been addressed in a very similar way. This method has been successfully applied to engine pollutants emission modeling.
Abstract: In this paper we proposed comparison of four content based objective metrics with results of subjective tests from 80 video sequences. We also include two objective metrics VQM and SSIM to our comparison to serve as “reference” objective metrics because their pros and cons have already been published. Each of the video sequence was preprocessed by the region recognition algorithm and then the particular objective video quality metric were calculated i.e. mutual information, angular distance, moment of angle and normalized cross-correlation measure. The Pearson coefficient was calculated to express metrics relationship to accuracy of the model and the Spearman rank order correlation coefficient to represent the metrics relationship to monotonicity. The results show that model with the mutual information as objective metric provides best result and it is suitable for evaluating quality of video sequences.
Abstract: In order to guarantee secure communication for wireless sensor networks (WSNs), many user authentication schemes have successfully drawn researchers- attention and been studied widely. In 2012, He et al. proposed a robust biometric-based user authentication scheme for WSNs. However, this paper demonstrates that He et al.-s scheme has some drawbacks: poor reparability problem, user impersonation attack, and sensor node impersonate attack.
Abstract: Application-Specific Instruction (ASI ) set Processors
(ASIP) have become an important design choice for embedded
systems due to runtime flexibility, which cannot be provided by
custom ASIC solutions. One major bottleneck in maximizing ASIP
performance is the limitation on the data bandwidth between the
General Purpose Register File (GPRF) and ASIs. This paper presents
the Implicit Registers (IRs) to provide the desirable data bandwidth.
An ASI Input/Output model is proposed to formulate the overheads of
the additional data transfer between the GPRF and IRs, therefore,
an IRs allocation algorithm is used to achieve the better performance
by minimizing the number of extra data transfer instructions. The
experiment results show an up to 3.33x speedup compared to the
results without using IRs.
Abstract: The design of distributed systems involves the
partitioning of the system into components or partitions and the
allocation of these components to physical nodes. Techniques have
been proposed for both the partitioning and allocation process.
However these techniques suffer from a number of limitations. For
instance object replication has the potential to greatly improve the
performance of an object orientated distributed system but can be
difficult to use effectively and there are few techniques that support
the developer in harnessing object replication.
This paper presents a methodological technique that helps
developers decide how objects should be allocated in order to
improve performance in a distributed system that supports
replication. The performance of the proposed technique is
demonstrated and tested on an example system.
Abstract: The stereophotogrammetry modality is gaining more widespread use in the clinical setting. Registration and visualization of this data, in conjunction with conventional 3D volumetric image modalities, provides virtual human data with textured soft tissue and internal anatomical and structural information. In this investigation computed tomography (CT) and stereophotogrammetry data is acquired from 4 anatomical phantoms and registered using the trimmed iterative closest point (TrICP) algorithm. This paper fully addresses the issue of imaging artifacts around the stereophotogrammetry surface edge using the registered CT data as a reference. Several iterative algorithms are implemented to automatically identify and remove stereophotogrammetry surface edge outliers, improving the overall visualization of the combined stereophotogrammetry and CT data. This paper shows that outliers at the surface edge of stereophotogrammetry data can be successfully removed automatically.
Abstract: Character segmentation is an important preprocessing step for text recognition. In degraded documents, existence of touching characters decreases recognition rate drastically, for any optical character recognition (OCR) system. In this paper a study of touching Gurmukhi characters is carried out and these characters have been divided into various categories after a careful analysis.Structural properties of the Gurmukhi characters are used for defining the categories. New algorithms have been proposed to segment the touching characters in middle zone. These algorithms have shown a reasonable improvement in segmenting the touching characters in degraded Gurmukhi script. The algorithms proposed in this paper are applicable only to machine printed text.