Abstract: Library management systems are commonly used in
all educational related institutes. Many commercial products are
available. However, many institutions may not be able to afford the
cost of using commercial products. Therefore, an alternative solution
in such situations would be open source software. This paper is
focusing on reviewing open source library management system
packages currently available. The review will focus on the abilities to
perform four basic components which are traditional services,
interlibrary load management, managing electronic materials and
basic common management system such as security, alert system and
statistical reports. In addition, environment, basic requirement and
supporting aspects of each open source package are also mentioned.
Abstract: Method of Parallel Joint Channel Coding and
Cryptography has been analyzed and simulated in this paper. The
method is an extension of Soft Input Decryption with feedback,
which is used for improvement of channel decoding of secured
messages. Parallel Joint Channel Coding and Cryptography results in
improved coding gain of channel decoding, which achieves more
than 2 dB. Such results are an implication of a combination of
receiver components and their interoperability.
Abstract: In this paper, the authors present architecture of a multi agent consultation system for obesity related problems, which hybrid the technology of an expert system (ES) and an intelligent agent (IA). The strength of the ES which is capable of pulling the expert knowledge is consulted and presented to the end user via the autonomous and friendly pushing environment of the intelligent agent.
Abstract: In this paper DJess is presented, a novel distributed production system that provides an infrastructure for factual and procedural knowledge sharing. DJess is a Java package that provides programmers with a lightweight middleware by which inference systems implemented in Jess and running on different nodes of a network can communicate. Communication and coordination among inference systems (agents) is achieved through the ability of each agent to transparently and asynchronously reason on inferred knowledge (facts) that might be collected and asserted by other agents on the basis of inference code (rules) that might be either local or transmitted by any node to any other node.
Abstract: The early diagnostic decision making in industrial processes is absolutely necessary to produce high quality final products. It helps to provide early warning for a special event in a process, and finding its assignable cause can be obtained. This work presents a hybrid diagnostic schmes for batch processes. Nonlinear representation of raw process data is combined with classification tree techniques. The nonlinear kernel-based dimension reduction is executed for nonlinear classification decision boundaries for fault classes. In order to enhance diagnosis performance for batch processes, filtering of the data is performed to get rid of the irrelevant information of the process data. For the diagnosis performance of several representation, filtering, and future observation estimation methods, four diagnostic schemes are evaluated. In this work, the performance of the presented diagnosis schemes is demonstrated using batch process data.
Abstract: Steganography, derived from Greek, literally means
“covered writing". It includes a vast array of secret communications
methods that conceal the message-s very existence. These methods
include invisible inks, microdots, character arrangement, digital
signatures, covert channels, and spread spectrum communications.
This paper proposes a new improved version of Least Significant Bit
(LSB) method. The approach proposed is simple for implementation
when compared to Pixel value Differencing (PVD) method and yet
achieves a High embedding capacity and imperceptibility. The
proposed method can also be applied to 24 bit color images and
achieve embedding capacity much higher than PVD.
Abstract: Motion control of flexible arms is more difficult than
that of rigid arms, however utilizing its dynamics enables improved
performance such as a fast motion in short operation time. This paper
investigates a ball throwing robot with one rigid link and one flexible
link. This robot throws a ball at a set speed with a proper control torque.
A mathematical model of this ball throwing robot is derived through
Hamilton’s principle. Several patterns of torque input are designed and
tested through the proposed simulation models. The parameters of
each torque input pattern is optimized and determined by chaos
embedded vector evaluated particle swarm optimization (CEVEPSO).
Then, the residual vibration of the manipulator after throwing is
suppressed with input shaping technique. Finally, a real experiment is
set up for the model checking.
Abstract: K-Modes is an extension of K-Means clustering algorithm, developed to cluster the categorical data, where the mean is replaced by the mode. The similarity measure proposed by Huang is the simple matching or mismatching measure. Weight of attribute values contribute much in clustering; thus in this paper we propose a new weighted dissimilarity measure for K-Modes, based on the ratio of frequency of attribute values in the cluster and in the data set. The new weighted measure is experimented with the data sets obtained from the UCI data repository. The results are compared with K-Modes and K-representative, which show that the new measure generates clusters with high purity.
Abstract: The cost of developing the software from scratch can
be saved by identifying and extracting the reusable components from
already developed and existing software systems or legacy systems
[6]. But the issue of how to identify reusable components from
existing systems has remained relatively unexplored. We have used
metric based approach for characterizing a software module. In this
present work, the metrics McCabe-s Cyclometric Complexity
Measure for Complexity measurement, Regularity Metric, Halstead
Software Science Indicator for Volume indication, Reuse Frequency
metric and Coupling Metric values of the software component are
used as input attributes to the different types of Neural Network
system and reusability of the software component is calculated. The
results are recorded in terms of Accuracy, Mean Absolute Error
(MAE) and Root Mean Squared Error (RMSE).
Abstract: This paper presents a modified version of the
maximum urgency first scheduling algorithm. The maximum
urgency algorithm combines the advantages of fixed and dynamic
scheduling to provide the dynamically changing systems with
flexible scheduling. This algorithm, however, has a major
shortcoming due to its scheduling mechanism which may cause a
critical task to fail. The modified maximum urgency first scheduling
algorithm resolves the mentioned problem. In this paper, we propose
two possible implementations for this algorithm by using either
earliest deadline first or modified least laxity first algorithms for
calculating the dynamic priorities. These two approaches are
compared together by simulating the two algorithms. The earliest
deadline first algorithm as the preferred implementation is then
recommended. Afterwards, we make a comparison between our
proposed algorithm and maximum urgency first algorithm using
simulation and results are presented. It is shown that modified
maximum urgency first is superior to maximum urgency first, since it
usually has less task preemption and hence, less related overhead. It
also leads to less failed non-critical tasks in overloaded situations.
Abstract: The survey and classification of the different security
attacks in structured peer-to-peer (P2P) overlay networks can be
useful to computer system designers, programmers, administrators,
and users. In this paper, we attempt to provide a taxonomy of
structured P2P overlay networks security attacks. We have specially
focused on the way these attacks can arise at each level of the
network. Moreover, we observed that most of the existing systems
such as Content Addressable Network (CAN), Chord, Pastry,
Tapestry, Kademlia, and Viceroy suffer from threats and vulnerability
which lead to disrupt and corrupt their functioning. We hope that our
survey constitutes a good help for who-s working on this area of
research.
Abstract: The paper presents a set of guidelines for analysis of industrial embedded distributed systems and introduces a mathematical model derived from these guidelines. In this study, the author examines a set of modern communication technologies that are or possibly can be used to build communication links between the subsystems of a distributed embedded system. An investigation of these guidelines results in a algorithm for analysis of specific use cases of target technologies. A goal of the paper acts as an important base for ongoing research on comparison of communication technologies. The author describes the principles of the model and presents results of the test calculations. Practical implementation of target technologies and empirical experiment data are based on a practical experience during the design and test of specific distributed systems in Latvian market.
Abstract: A new blind symbol by symbol equalizer is proposed.
The operation of the proposed equalizer is based on the geometric
properties of the two dimensional data constellation. An unsupervised
clustering technique is used to locate the clusters formed by the
received data. The symmetric properties of the clusters labels are
subsequently utilized in order to label the clusters. Following this
step, the received data are compared to clusters and decisions are
made on a symbol by symbol basis, by assigning to each data
the label of the nearest cluster. The operation of the equalizer is
investigated both in linear and nonlinear channels. The performance
of the proposed equalizer is compared to the performance of a CMAbased
blind equalizer.
Abstract: In this paper a real-time trajectory generation algorithm for computing 2-D optimal paths for autonomous aerial vehicles has been discussed. A dynamic programming approach is adopted to compute k-best paths by minimizing a cost function. Collision detection is implemented to detect intersection of the paths with obstacles. Our contribution is a novel approach to the problem of trajectory generation that is computationally efficient and offers considerable gain over existing techniques.
Abstract: The challenge in the case of image authentication is that in many cases images need to be subjected to non malicious operations like compression, so the authentication techniques need to be compression tolerant. In this paper we propose an image authentication system that is tolerant to JPEG lossy compression operations. A scheme for JPEG grey scale images is proposed based on a data embedding method that is based on a secret key and a secret mapping vector in the frequency domain. An encrypted feature vector extracted from the image DCT coefficients, is embedded redundantly, and invisibly in the marked image. On the receiver side, the feature vector from the received image is derived again and compared against the extracted watermark to verify the image authenticity. The proposed scheme is robust against JPEG compression up to a maximum compression of approximately 80%,, but sensitive to malicious attacks such as cutting and pasting.
Abstract: Due to the dynamic nature of the Cloud, continuous monitoring of QoS requirements is necessary to manage the Cloud computing environment. The process of QoS monitoring and SLA violation detection consists of: collecting low and high level information pertinent to the service, analyzing the collected information, and taking corrective actions when SLA violations are detected. In this paper, we detail the architecture and the implementation of the first step of this process. More specifically, we propose an event-based approach to obtain run time information of services developed as BPEL processes. By catching particular events (i.e., the low level information), our approach recognizes the run-time execution path of a monitored service and uses the BPEL execution patterns to compute QoS of the composite service (i.e., the high level information).
Abstract: The main goal of data mining is to extract accurate, comprehensible and interesting knowledge from databases that may be considered as large search spaces. In this paper, a new, efficient type of Genetic Algorithm (GA) called uniform two-level GA is proposed as a search strategy to discover truly interesting, high-level prediction rules, a difficult problem and relatively little researched, rather than discovering classification knowledge as usual in the literatures. The proposed method uses the advantage of uniform population method and addresses the task of generalized rule induction that can be regarded as a generalization of the task of classification. Although the task of generalized rule induction requires a lot of computations, which is usually not satisfied with the normal algorithms, it was demonstrated that this method increased the performance of GAs and rapidly found interesting rules.
Abstract: Computer technology and the Internet have made a
breakthrough in the existence of data communication. This has
opened a whole new way of implementing steganography to ensure
secure data transfer. Steganography is the fine art of hiding the
information. Hiding the message in the carrier file enables the
deniability of the existence of any message at all. This paper designs
a stego machine to develop a steganographic application to hide data
containing text in a computer video file and to retrieve the hidden
information. This can be designed by embedding text file in a video
file in such away that the video does not loose its functionality using
Least Significant Bit (LSB) modification method. This method
applies imperceptible modifications. This proposed method strives
for high security to an eavesdropper-s inability to detect hidden
information.
Abstract: This paper presents three new methodologies for the
basic operations, which aim at finding new ways of computing union
(maximum) and intersection (minimum) membership values by
taking into effect the entire membership values in a fuzzy set. The
new methodologies are conceptually simple and easy from the
application point of view and are illustrated with a variety of
problems such as Cartesian product of two fuzzy sets, max –min
composition of two fuzzy sets in different product spaces and an
application of an inverted pendulum to determine the impact of the
new methodologies. The results clearly indicate a difference based on
the nature of the fuzzy sets under consideration and hence will be
highly useful in quite a few applications where different values have
significant impact on the behavior of the system.
Abstract: This paper describes the results of an extensive study
and comparison of popular hash functions SHA-1, SHA-256,
RIPEMD-160 and RIPEMD-320 with JERIM-320, a 320-bit hash
function. The compression functions of hash functions like SHA-1
and SHA-256 are designed using serial successive iteration whereas
those like RIPEMD-160 and RIPEMD-320 are designed using two
parallel lines of message processing. JERIM-320 uses four parallel
lines of message processing resulting in higher level of security than
other hash functions at comparable speed and memory requirement.
The performance evaluation of these methods has been done by using
practical implementation and also by using step computation
methods. JERIM-320 proves to be secure and ensures the integrity of
messages at a higher degree. The focus of this work is to establish
JERIM-320 as an alternative of the present day hash functions for the
fast growing internet applications.