Scholarly

DACS3: Embedding Individual Ant Behavior in Ant Colony System

Year: 2008 Volume: 2 Issue: 8 2861 - 2866 Pages

Abstract: Ants are fascinating creatures that demonstrate the ability to find food and bring it back to their nest. Their ability as a colony, to find paths to food sources has inspired the development of algorithms known as Ant Colony Systems (ACS). The principle of cooperation forms the backbone of such algorithms, commonly used to find solutions to problems such as the Traveling Salesman Problem (TSP). Ants communicate to each other through chemical substances called pheromones. Modeling individual ants- ability to manipulate this substance can help an ACS find the best solution. This paper introduces a Dynamic Ant Colony System with threelevel updates (DACS3) that enhance an existing ACS. Experiments were conducted to observe single ant behavior in a colony of Malaysian House Red Ants. Such behavior was incorporated into the DACS3 algorithm. We benchmark the performance of DACS3 versus DACS on TSP instances ranging from 14 to 100 cities. The result shows that the DACS3 algorithm can achieve shorter distance in most cases and also performs considerably faster than DACS.

Application of Fuzzy Neural Network for Image Tumor Description

Year: 2008 Volume: 2 Issue: 8 2858 - 2860 Pages

Abstract: This paper used a fuzzy kohonen neural network for medical image segmentation. Image segmentation plays a important role in the many of medical imaging applications by automating or facilitating the diagnostic. The paper analyses the tumor by extraction of the features of (area, entropy, means and standard deviation).These measurements gives a description for a tumor.

Graph-based High Level Motion Segmentation using Normalized Cuts

Year: 2008 Volume: 2 Issue: 8 2852 - 2857 Pages

Abstract: Motion capture devices have been utilized in producing several contents, such as movies and video games. However, since motion capture devices are expensive and inconvenient to use, motions segmented from captured data was recycled and synthesized to utilize it in another contents, but the motions were generally segmented by contents producers in manual. Therefore, automatic motion segmentation is recently getting a lot of attentions. Previous approaches are divided into on-line and off-line, where on-line approaches segment motions based on similarities between neighboring frames and off-line approaches segment motions by capturing the global characteristics in feature space. In this paper, we propose a graph-based high-level motion segmentation method. Since high-level motions consist of several repeated frames within temporal distances, we consider all similarities among all frames within the temporal distance. This is achieved by constructing a graph, where each vertex represents a frame and the edges between the frames are weighted by their similarity. Then, normalized cuts algorithm is used to partition the constructed graph into several sub-graphs by globally finding minimum cuts. In the experiments, the results using the proposed method showed better performance than PCA-based method in on-line and GMM-based method in off-line, as the proposed method globally segment motions from the graph constructed based similarities between neighboring frames as well as similarities among all frames within temporal distances.

Mimicking Morphogenesis for Robust Behaviour of Cellular Architectures

Year: 2008 Volume: 2 Issue: 8 2849 - 2851 Pages

Abstract: Morphogenesis is the process that underpins the selforganised development and regeneration of biological systems. The ability to mimick morphogenesis in artificial systems has great potential for many engineering applications, including production of biological tissue, design of robust electronic systems and the co-ordination of parallel computing. Previous attempts to mimick these complex dynamics within artificial systems have relied upon the use of evolutionary algorithms that have limited their size and complexity. This paper will present some insight into the underlying dynamics of morphogenesis, then show how to, without the assistance of evolutionary algorithms, design cellular architectures that converge to complex patterns.

Data Embedding Based on Better Use of Bits in Image Pixels

Year: 2008 Volume: 2 Issue: 8 2845 - 2848 Pages

Abstract: In this study, a novel approach of image embedding is introduced. The proposed method consists of three main steps. First, the edge of the image is detected using Sobel mask filters. Second, the least significant bit LSB of each pixel is used. Finally, a gray level connectivity is applied using a fuzzy approach and the ASCII code is used for information hiding. The prior bit of the LSB represents the edged image after gray level connectivity, and the remaining six bits represent the original image with very little difference in contrast. The proposed method embeds three images in one image and includes, as a special case of data embedding, information hiding, identifying and authenticating text embedded within the digital images. Image embedding method is considered to be one of the good compression methods, in terms of reserving memory space. Moreover, information hiding within digital image can be used for security information transfer. The creation and extraction of three embedded images, and hiding text information is discussed and illustrated, in the following sections.

Using Dempster-Shafer Theory in XML Information Retrieval

Year: 2008 Volume: 2 Issue: 8 2841 - 2844 Pages

Abstract: XML is a markup language which is becoming the standard format for information representation and data exchange. A major purpose of XML is the explicit representation of the logical structure of a document. Much research has been performed to exploit logical structure of documents in information retrieval in order to precisely extract user information need from large collections of XML documents. In this paper, we describe an XML information retrieval weighting scheme that tries to find the most relevant elements in XML documents in response to a user query. We present this weighting model for information retrieval systems that utilize plausible inferences to infer the relevance of elements in XML documents. We also add to this model the Dempster-Shafer theory of evidence to express the uncertainty in plausible inferences and Dempster-Shafer rule of combination to combine evidences derived from different inferences.

Novel Approach for Promoting the Generalization Ability of Neural Networks

Year: 2008 Volume: 2 Issue: 8 2836 - 2840 Pages

Abstract: A new approach to promote the generalization ability of neural networks is presented. It is based on the point of view of fuzzy theory. This approach is implemented through shrinking or magnifying the input vector, thereby reducing the difference between training set and testing set. It is called “shrinking-magnifying approach" (SMA). At the same time, a new algorithm; α-algorithm is presented to find out the appropriate shrinking-magnifying-factor (SMF) α and obtain better generalization ability of neural networks. Quite a few simulation experiments serve to study the effect of SMA and α-algorithm. The experiment results are discussed in detail, and the function principle of SMA is analyzed in theory. The results of experiments and analyses show that the new approach is not only simpler and easier, but also is very effective to many neural networks and many classification problems. In our experiments, the proportions promoting the generalization ability of neural networks have even reached 90%.

HSV Image Watermarking Scheme Based on Visual Cryptography

Year: 2008 Volume: 2 Issue: 8 2832 - 2835 Pages

Abstract: In this paper a simple watermarking method for color images is proposed. The proposed method is based on watermark embedding for the histograms of the HSV planes using visual cryptography watermarking. The method has been proved to be robust for various image processing operations such as filtering, compression, additive noise, and various geometrical attacks such as rotation, scaling, cropping, flipping, and shearing.

Glass Bottle Inspector Based on Machine Vision

Year: 2008 Volume: 2 Issue: 8 2826 - 2831 Pages

Abstract: This text studies glass bottle intelligent inspector based machine vision instead of manual inspection. The system structure is illustrated in detail in this paper. The text presents the method based on watershed transform methods to segment the possible defective regions and extract features of bottle wall by rules. Then wavelet transform are used to exact features of bottle finish from images. After extracting features, the fuzzy support vector machine ensemble is putted forward as classifier. For ensuring that the fuzzy support vector machines have good classification ability, the GA based ensemble method is used to combining the several fuzzy support vector machines. The experiments demonstrate that using this inspector to inspect glass bottles, the accuracy rate may reach above 97.5%.

A New Approach to Steganography using Sinc-Convolution Method

Year: 2008 Volume: 2 Issue: 8 2820 - 2825 Pages

Abstract: Both image steganography and image encryption have advantages and disadvantages. Steganograhy allows us to hide a desired image containing confidential information in a covered or host image while image encryption is decomposing the desired image to a non-readable, non-comprehended manner. The encryption methods are usually much more robust than the steganographic ones. However, they have a high visibility and would provoke the attackers easily since it usually is obvious from an encrypted image that something is hidden! The combination of steganography and encryption will cover both of their weaknesses and therefore, it increases the security. In this paper an image encryption method based on sinc-convolution along with using an encryption key of 128 bit length is introduced. Then, the encrypted image is covered by a host image using a modified version of JSteg steganography algorithm. This method could be applied to almost all image formats including TIF, BMP, GIF and JPEG. The experiment results show that our method is able to hide a desired image with high security and low visibility.

Enabling Integration across Heterogeneous Care Networks

Year: 2008 Volume: 2 Issue: 8 2815 - 2819 Pages

Abstract: The paper shows how the CASMAS modeling language, and its associated pervasive computing architecture, can be used to facilitate continuity of care by providing members of patientcentered communities of care with a support to cooperation and knowledge sharing through the usage of electronic documents and digital devices. We consider a scenario of clearly fragmented care to show how proper mechanisms can be defined to facilitate a better integration of practices and information across heterogeneous care networks. The scenario is declined in terms of architectural components and cooperation-oriented mechanisms that make the support reactive to the evolution of the context where these communities operate.

An Efficient Biometric Cryptosystem using Autocorrelators

Year: 2008 Volume: 2 Issue: 8 2808 - 2814 Pages

Abstract: Cryptography provides the secure manner of information transmission over the insecure channel. It authenticates messages based on the key but not on the user. It requires a lengthy key to encrypt and decrypt the sending and receiving the messages, respectively. But these keys can be guessed or cracked. Moreover, Maintaining and sharing lengthy, random keys in enciphering and deciphering process is the critical problem in the cryptography system. A new approach is described for generating a crypto key, which is acquired from a person-s iris pattern. In the biometric field, template created by the biometric algorithm can only be authenticated with the same person. Among the biometric templates, iris features can efficiently be distinguished with individuals and produces less false positives in the larger population. This type of iris code distribution provides merely less intra-class variability that aids the cryptosystem to confidently decrypt messages with an exact matching of iris pattern. In this proposed approach, the iris features are extracted using multi resolution wavelets. It produces 135-bit iris codes from each subject and is used for encrypting/decrypting the messages. The autocorrelators are used to recall original messages from the partially corrupted data produced by the decryption process. It intends to resolve the repudiation and key management problems. Results were analyzed in both conventional iris cryptography system (CIC) and non-repudiation iris cryptography system (NRIC). It shows that this new approach provides considerably high authentication in enciphering and deciphering processes.

3D Rendering of American Sign Language Finger-Spelling: A Comparative Study of Two Animation Techniques

Year: 2008 Volume: 2 Issue: 8 2802 - 2807 Pages

Authors:
Nicoletta Adamo-Villani

Abstract: In this paper we report a study aimed at determining the most effective animation technique for representing ASL (American Sign Language) finger-spelling. Specifically, in the study we compare two commonly used 3D computer animation methods (keyframe animation and motion capture) in order to ascertain which technique produces the most 'accurate', 'readable', and 'close to actual signing' (i.e. realistic) rendering of ASL finger-spelling. To accomplish this goal we have developed 20 animated clips of fingerspelled words and we have designed an experiment consisting of a web survey with rating questions. 71 subjects ages 19-45 participated in the study. Results showed that recognition of the words was correlated with the method used to animate the signs. In particular, keyframe technique produced the most accurate representation of the signs (i.e., participants were more likely to identify the words correctly in keyframed sequences rather than in motion captured ones). Further, findings showed that the animation method had an effect on the reported scores for readability and closeness to actual signing; the estimated marginal mean readability and closeness was greater for keyframed signs than for motion captured signs. To our knowledge, this is the first study aimed at measuring and comparing accuracy, readability and realism of ASL animations produced with different techniques.

RBF modeling of Incipient Motion of Plane Sand Bed Channels

Year: 2008 Volume: 2 Issue: 8 2796 - 2801 Pages

Abstract: To define or predict incipient motion in an alluvial channel, most of the investigators use a standard or modified form of Shields- diagram. Shields- diagram does give a process to determine the incipient motion parameters but an iterative one. To design properly (without iteration), one should have another equation for resistance. Absence of a universal resistance equation also magnifies the difficulties in defining the model. Neural network technique, which is particularly useful in modeling a complex processes, is presented as a tool complimentary to modeling incipient motion. Present work develops a neural network model employing the RBF network to predict the average velocity u and water depth y based on the experimental data on incipient condition. Based on the model, design curves have been presented for the field application.

A New High Speed Neural Model for Fast Character Recognition Using Cross Correlation and Matrix Decomposition

Year: 2008 Volume: 2 Issue: 8 2776 - 2795 Pages

Authors:
Hazem M. El-Bakry

Abstract: Neural processors have shown good results for detecting a certain character in a given input matrix. In this paper, a new idead to speed up the operation of neural processors for character detection is presented. Such processors are designed based on cross correlation in the frequency domain between the input matrix and the weights of neural networks. This approach is developed to reduce the computation steps required by these faster neural networks for the searching process. The principle of divide and conquer strategy is applied through image decomposition. Each image is divided into small in size sub-images and then each one is tested separately by using a single faster neural processor. Furthermore, faster character detection is obtained by using parallel processing techniques to test the resulting sub-images at the same time using the same number of faster neural networks. In contrast to using only faster neural processors, the speed up ratio is increased with the size of the input image when using faster neural processors and image decomposition. Moreover, the problem of local subimage normalization in the frequency domain is solved. The effect of image normalization on the speed up ratio of character detection is discussed. Simulation results show that local subimage normalization through weight normalization is faster than subimage normalization in the spatial domain. The overall speed up ratio of the detection process is increased as the normalization of weights is done off line.

Identification of Flexographic-printed Newspapers with NIR Spectral Imaging

Year: 2008 Volume: 2 Issue: 8 2770 - 2775 Pages

Abstract: Near-infrared (NIR) spectroscopy is a widely used method for material identification for laboratory and industrial applications. While standard spectrometers only allow measurements at one sampling point at a time, NIR Spectral Imaging techniques can measure, in real-time, both the size and shape of an object as well as identify the material the object is made of. The online classification and sorting of recovered paper with NIR Spectral Imaging (SI) is used with success in the paper recycling industry throughout Europe. Recently, the globalisation of the recycling material streams caused that water-based flexographic-printed newspapers mainly from UK and Italy appear also in central Europe. These flexo-printed newspapers are not sufficiently de-inkable with the standard de-inking process originally developed for offset-printed paper. This de-inking process removes the ink from recovered paper and is the fundamental processing step to produce high-quality paper from recovered paper. Thus, the flexo-printed newspapers are a growing problem for the recycling industry as they reduce the quality of the produced paper if their amount exceeds a certain limit within the recovered paper material. This paper presents the results of a research project for the development of an automated entry inspection system for recovered paper that was jointly conducted by CTR AG (Austria) and PTS Papiertechnische Stiftung (Germany). Within the project an NIR SI prototype for the identification of flexo-printed newspaper has been developed. The prototype can identify and sort out flexoprinted newspapers in real-time and achieves a detection accuracy for flexo-printed newspaper of over 95%. NIR SI, the technology the prototype is based on, allows the development of inspection systems for incoming goods in a paper production facility as well as industrial sorting systems for recovered paper in the recycling industry in the near future.

Design and Implementation of Optimal Winner Determination Algorithm in Combinatorial e- Auctions

Year: 2008 Volume: 2 Issue: 8 2766 - 2769 Pages

Abstract: The one of best robust search technique on large scale search area is heuristic and meta heuristic approaches. Especially in issue that the exploitation of combinatorial status in the large scale search area prevents the solution of the problem via classical calculating methods, so such problems is NP-complete. in this research, the problem of winner determination in combinatorial auctions have been formulated and by assessing older heuristic functions, we solve the problem by using of genetic algorithm and would show that this new method would result in better performance in comparison to other heuristic function such as simulated annealing greedy approach.

Time-Derivative Estimation of Noisy Movie Data using Adaptive Control Theory

Year: 2008 Volume: 2 Issue: 8 2758 - 2765 Pages

Abstract: This paper presents an adaptive differentiator of sequential data based on the adaptive control theory. The algorithm is applied to detect moving objects by estimating a temporal gradient of sequential data at a specified pixel. We adopt two nonlinear intensity functions to reduce the influence of noises. The derivatives of the nonlinear intensity functions are estimated by an adaptive observer with σ-modification update law.

A Stereo Image Processing System for Visually Impaired

Year: 2008 Volume: 2 Issue: 8 2748 - 2757 Pages

Abstract: This paper presents a review on vision aided systems and proposes an approach for visual rehabilitation using stereo vision technology. The proposed system utilizes stereo vision, image processing methodology and a sonification procedure to support blind navigation. The developed system includes a wearable computer, stereo cameras as vision sensor and stereo earphones, all moulded in a helmet. The image of the scene infront of visually handicapped is captured by the vision sensors. The captured images are processed to enhance the important features in the scene in front, for navigation assistance. The image processing is designed as model of human vision by identifying the obstacles and their depth information. The processed image is mapped on to musical stereo sound for the blind-s understanding of the scene infront. The developed method has been tested in the indoor and outdoor environments and the proposed image processing methodology is found to be effective for object identification.

A Graphical Environment for Petri Nets INA Tool Based on Meta-Modelling and Graph Grammars

Year: 2008 Volume: 2 Issue: 8 2743 - 2747 Pages

Abstract: The Petri net tool INA is a well known tool by the Petri net community. However, it lacks a graphical environment to cerate and analyse INA models. Building a modelling tool for the design and analysis from scratch (for INA tool for example) is generally a prohibitive task. Meta-Modelling approach is useful to deal with such problems since it allows the modelling of the formalisms themselves. In this paper, we propose an approach based on the combined use of Meta-modelling and Graph Grammars to automatically generate a visual modelling tool for INA for analysis purposes. In our approach, the UML Class diagram formalism is used to define a meta-model of INA models. The meta-modelling tool ATOM3 is used to generate a visual modelling tool according to the proposed INA meta-model. We have also proposed a graph grammar to automatically generate INA description of the graphically specified Petri net models. This allows the user to avoid the errors when this description is done manually. Then the INA tool is used to perform the simulation and the analysis of the resulted INA description. Our environment is illustrated through an example.

International Journal of Information, Control and Computer Sciences

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