From logic programming towards multi‐agent systems

In this paper we present an extension of logic programming (LP) that is suitable not only for the “rational” component of a single agent but also for the “reactive” component and that can encompass multi‐agent systems. We modify an earlier abductive proof procedure and embed it within an agent cycle. The proof procedure incorporates abduction, definitions and integrity constraints within a dynamic environment, where changes can be observed as inputs. The definitions allow rational planning behaviour and the integrity constraints allow reactive, condition‐action type behaviour. The agent cycle provides a resource‐bounded mechanism that allows the agent’s thinking to be interrupted for the agent to record and assimilate observations as input and execute actions as output, before resuming further thinking. We argue that these extensions of LP, accommodating multi‐theories embedded in a shared environment, provide the necessary multi‐agent functionality. We argue also that our work extends Shoham’s Agent0 and the BDI architecture. This revised version was published online in June 2006 with corrections to the Cover Date.     

Speech emotion recognition based on multi‐feature and multi‐lingual fusion

Multimedia Tools and Applications - A speech emotion recognition algorithm based on multi-feature and Multi-lingual fusion is proposed in order to resolve low recognition accuracy caused bylack of...     

Sequential masking classification of multi‐temporal Landsat7 ETM+ images for field‐based crop mapping in Karacabey,Turkey

Three Landsat7 ETM+ images acquired in May, July and August during the 2000 crop growing season were used for field‐based mapping of summer crops in Karacabey, Turkey. First, the classification of each image date was performed on a standard per pixel basis. The results of per pixel classification were integrated with digital agricultural field boundaries and a crop type was determined for each field based on the modal class calculated within the field. The classification accuracy was computed by comparing the reference data, field‐by‐field, to each classified image. The individual crop accuracies were examined on each classified data and those crops whose accuracy exceeds a preset threshold level were determined. A sequential masking classification procedure was then performed using the three image dates, excluding after each classification the class properly classified. The final classified data were analysed on a field basis to assign each field a class label. An immediate update of the database was provided by directly entering the results of the analysis into the database. The sequential masking procedure for field‐based crop mapping improved the overall accuracies of the classifications of the July and August images alone by more than 10%.     

Optimization in multi‐scale segmentation of high‐resolution satellite images for artificial feature recognition

Multi‐resolution segmentation, as one of the most popular approaches in object‐oriented image segmentation, has been greatly enabled by the advent of the commercial software, eCognition. However, the application of multi‐resolution segmentation still poses problems, especially in its operational aspects. This paper addresses the issue of optimization of the algorithm‐associated parameters in multi‐resolution segmentation. A framework starting with the definition of meaningful objects is proposed to find optimal segmentations for a given feature type. The proposed framework was tested to segment three exemplary artificial feature types (sports fields, roads, and residential buildings) in IKONOS multi‐spectral images, based on a sampling scheme of all the parameters required by the algorithm. Results show that the feature‐type‐oriented segmentation evaluation provides an insight to the decision‐making process in choosing appropriate parameters towards a high‐quality segmentation. By adopting these feature‐type‐based optimal parameters, multi‐resolution segmentation is able to produce objects of desired form to represent artificial features.     

An agent based system for activity monitoring on network – ABSAMN

Computer network as a force drags its customers to share more and more resources while on the other hand managing such network recourses is a challenging job for an IT professional and perhaps becoming difficult humanly. In this paper, we have proposed an agent based system for activity monitoring on network (ABSAMN) for the monitoring of resources over a network, suitable for network of networks; commonly known as CAN (campus area network). Multi-agent system is a system composed of several agents, collectively capable of achieving goals that are difficult to achieve by an individual agent or monolithic system. We propose the use of multi-agent system to ensure proper system operation by watching for inconsistencies in user activities, node level activity, internet monitoring, and system configuration. The system is fully autonomous and once initialized with the given rules and domain knowledge ABSAMN manages resources on its own with the help of mobile agents. We have evaluated this architecture on the university campus having seven labs equipped with 20–300 number of PCs in various labs. Results were very promising and support the implementation of the solution.     

A multi‐scale segmentation approach to filling gaps in Landsat ETM+ SLC‐off images

On 31 May 2003, the Landsat Enhanced Thematic Plus (ETM+) Scan Line Corrector (SLC) failed, causing the scanning pattern to exhibit wedge‐shaped scan‐to‐scan gaps. We developed a method that uses coincident spectral data to fill the image gaps. This method uses a multi‐scale segment model, derived from a previous Landsat SLC‐on image (image acquired prior to the SLC failure), to guide the spectral interpolation across the gaps in SLC‐off images (images acquired after the SLC failure). This paper describes the process used to generate the segment model, provides details of the gap‐fill algorithm used in deriving the segment‐based gap‐fill product, and presents the results of the gap‐fill process applied to grassland, cropland, and forest landscapes. Our results indicate this product will be useful for a wide variety of applications, including regional‐scale studies, general land cover mapping (e.g. forest, urban, and grass), crop‐specific mapping and monitoring, and visual assessments. Applications that need to be cautious when using pixels in the gap areas include any applications that require per‐pixel accuracy, such as urban characterization or impervious surface mapping, applications that use texture to characterize landscape features, and applications that require accurate measurements of small or narrow landscape features such as roads, farmsteads, and riparian areas.     

RVM‐based multi‐class classification of remotely sensed data

The relevance vector machine (RVM), a Bayesian extension of the support vector machine (SVM), has considerable potential for the analysis of remotely sensed data. Here, the RVM is introduced and used to derive a multi‐class classification of land cover with an accuracy of 91.25%, a level comparable to that achieved by a suite of popular image classifiers including the SVM. Critically, however, the output of the RVM includes an estimate of the posterior probability of class membership. This output may be used to illustrate the uncertainty of the class allocations on a per‐case basis and help to identify possible routes to further enhance classification accuracy.     

Web‐based testing: A study in insecurity

Much has been written about the distinct ideas of online testing, in which students take tests and receive immediate feedback on their performance; distance learning, in which telecommunication technology extends the traditional classroom beyond the classroom walls; and multimedia, in which text, sound and graphics are integrated within an application. By using the World Wide Web (WWW) as a medium for administering online tests, immediate feedback can be provided, tests can be administered at a distance, and multimedia resources can be conveniently incorporated into questions. This paper describes Eval, an undergraduate research software prototype in which we explore security issues related to using WWW as a testing medium.     

Intelligent agent based artificial immune system for computer security—a review

Since its introduction in the 1990s the internet has proliferated in the life of human kind in many numbers of ways. The two by-products of the internet are intelligent agents and intrusions which are far away from each other in the intention of their creation while similar in their characteristics. With automated code roaming the network intruding the users on one side as worms, viruses, and Trojans and autonomous agents tending to help the users on the other side, the internet has given great research challenges to the computer scientists. The greatest challenge of the internet is intrusion, which has increased and never decreased. There are various security systems for the internet. As the Human Immune System protects human body from external attacks, these security systems tend to protect the internet from intruders. Thus the internet security systems are comparable with human immune systems in which autonomous cells move throughout the body to protect it while learning to tackle new threats and keeping them in their memory for the future. These properties are comparable with that of autonomous agents in the internet. Thus intelligent agent technology combined with ideas from human immune system is a great area of research which is still in its developing phase. In this paper, state of the art of security systems which use both these technologies of intelligent agents and artificial immune system i.e., Agent Based Artificial Immune System (ABAIS) for security are reviewed, paying special attention to features of human immune system used in the system, the role of the agents in the ABAIS and the security mechanisms provided against intrusions.     

A resource limited artificial immune system algorithm for supervised classification of multi/hyper‐spectral remote sensing imagery

The resource limited artificial immune system (RLAIS), a new computational intelligence approach, is being increasingly recognized as one of the most competitive methods for data clustering and analysis. Nevertheless, owing to the inherent complexity of the conventional RLAIS algorithm, its application to multi/hyper‐class remote sensing image classification has been considerably limited. This paper explores a novel artificial immune algorithm based on the resource limited principles for supervised multi/hyper‐spectral image classification. Three experiments with different types of images were performed to evaluate the performance of the proposed algorithm in comparison with other traditional image classification algorithms: parallelepiped, minimum distance, maximum likelihood, K‐nearest neighbour and back‐propagation neural network. The results show that the proposed algorithm consistently outperforms the traditional algorithms in all the experiments and hence provides an effective new option for processing multi/hyper spectral remote sensing images.     

A WWW‐assisted fax system for Internet fax‐to‐fax communication

This paper describes a WWWassisted fax system (WAX) that is developed to provide reliable and enhanced Internet faxtofax communication. It integrates the easytouse WWW interface with conventional faxing procedures, resulting in an Internet fax system which not only circumvents the cost of long distance fax charges but also adds enhanced functionality not otherwise possible. The WAX system comprises two gateways, namely, the FaxIn and the FaxOut Gateways. The FaxIn Gateway accepts fax messages over Public Switched Telephone Network (PSTN) and stores them in a transit database. The system interfaces with the user over the WWW to provide access to his stored faxes, with the basic ability to send them out over the Internet to recipients. The FaxOut Gateway receives fax files from the FaxIn Gateway through the Internet and transmits them out to the intended recipients via the local PSTN. WAX users do not require any additional hardware except for a fax machine and a personal computer with Internet connectivity to gain access to WAX via any WWW browser. In addition, WAX provides a host of other enhanced features such as the ability to construct minifaxes from a single incoming fax as well as dynamically attach cover notes to outgoing faxes.     

A view‐dependent method for the multi‐resolution representation of terrains with roads embedded

Generating multi‐resolution terrain models dynamically is necessary for rapid visualization because of the huge volume of data and the limited memory of computers. However, it is difficult to generate dynamic multi‐resolution terrain models with the roads embedded. This paper proposes a new method for generating these models. In contrast to previous approaches, our method divides the integrated terrains into multiple levels with a ‘?’ shape, and dynamically generates multi‐resolution terrain models with the roads embedded. Moreover, our method efficiently overcomes thin, long‐shaped triangles in multi‐resolution terrain models. On the other hand, the number of triangles in adjacent frames is efficiently updated during walking/flying through visualization. The experimental results demonstrate that the proposed method acquires better performance in terms of accuracy for the multi‐resolution representation of terrains with the roads embedded.     

Envisat multi‐polarized ASAR data for flood mapping

During the August 2002 Elbe river flood, different satellite sensor data were acquired, and especially Envisat Advanced Synthetic Aperture Radar (ASAR) data. The ASAR instrument was activated in Alternating Polarization (AP) and Image (IM) modes, providing high resolution datasets. Thus, the comparison with a quasi‐simultaneous ERS‐2 scene enables the evaluation of the contribution of polarization configurations to flood boundary delineation. This study highlights the increased capabilities of the Envisat ASAR instrument in flood mapping, especially the benefit of combining like‐ and cross‐polarizations for rapid mapping within a crisis context.     

Ontology‐based documentation of land degradation assessment from satellite images

In this paper, we introduce the idea of documenting operational chains for land degradation assessment using ontologies. We believe that this process will help end users better understand the application domain characteristics and evaluate the results of the assessment process. Since the application domain is wide, various operational chains for land degradation assessment and their associated documentation exist, according to different options. This parameterization process causes the development of different ontologies, which nonetheless are, to a certain extent, linked because of the common software components of the corresponding operational chains. We therefore propose a hierarchical structure of these ontologies; so that several requirements such as understanding of expert knowledge interconnections and of application domain variety, documentation and assimilation of new expert knowledge, and reusability of software components become feasible.     

Left‐handed scrolling for pen‐based devices

The effectiveness of interaction with mobile devices can be impacted by handedness; however, support for handedness in the interface is rarely provided. The goal of this article is to demonstrate that handedness is a significant interface consideration that should not be overlooked. Four studies were conducted to explore left‐handed user interaction with right‐ or left‐aligned scrollbars on personal digital assistants. Analysis of the data shows that left‐handed users are able to select targets significantly faster using a left‐aligned scrollbar when compared to a right‐aligned scrollbar. User feedback also indicated that a left‐aligned scrollbar was preferred by left‐handed users and provided more natural interaction.     

The use of multi‐temporal Landsat images for the change detection of the coastal zone near Hurghada,Egypt

A Landsat 5 Thematic Mapper (TM) image of 1987 and a Landsat 7 Enhanced Thematic Mapper Plus (ETM+) image of 2000 were used to examine changes in land use/land cover (LULC) around Hurghada, Egypt, and changes in the composition of coral reefs offshore. Prior to coral reef bottom‐type classification, the radiance values were transformed to depth‐invariant bottom indices to reduce the effect of the water column. Subsequently, a multi‐component change detection procedure was applied to these indices to define changes. Preliminary results showed significant changes in LULC during the period 1987–2000 as well as changes in coral reef composition. Direct impacts along the coastline were clearly shown, but it was more difficult to link offshore changes in coral reef composition to indirect impacts of the changing LULC. Further research is needed to explore the effects of the different image‐processing steps, and to discover possible links between indirect impacts of LULC changes and changes in the coral reef composition.     

A theory of command language dialogue for a knowledge‐based human‐computer interaction

The flexibility and usability of graphic‐based HCIs can be increased by adding a natural language interface with command menus. Among the several other advantages, such embellishment offers the user an opportunity for direct expression of his or her behaviors, goals, intentions, and objectives along the continuum of the task knowledge. The existing graphic‐based HCIs that operate on active symbologies and icons assume the user's mental models to correlate with perceptual and cognitive levels of the task understanding. This obviously increases mental loads and the frustration of the human adapting to the system. In reality, the system should be designed to adapt to the user's behavior and skill level. In order to improve the current design of graphic‐based HCIs, we have formulated theories of command production language that will enhance the user's ability to interact with the system. The methods developed combine the theory of expert database with formal grammar to develop command‐production rules using a natural language dictionary prototype. We show that the commands are linear, regular, and symmetric, although conforming to the formal rules of grammar.     

A semi‐automated line tracing technique for monitoring ice margins in Antarctic images

The current shape and rate of change of the margins of the Antarctic ice sheet are poorly known. Since polar regions are inhospitable, remotely sensed images provide an invaluable data source for studying the ice margin. These images can be examined by a human expert or processed automatically by a computer. This paper describes the design and implementation of a semi‐automated technique to trace ice margins in Synthetic Aperture Radar images. The technique is based on a deformable contour model derived from the Kass et al. active contour model and Lobregt and Viergever's discrete dynamic contour. The contour is initialized by the user, to approximate the margin, and the deformation process causes the contour to accurately mould itself to the shape of the margin. The technique has been tested on a number of different images, with acceptable results in most cases.