The Infona portal uses cookies, i.e. strings of text saved by a browser on the user's device. The portal can access those files and use them to remember the user's data, such as their chosen settings (screen view, interface language, etc.), or their login data. By using the Infona portal the user accepts automatic saving and using this information for portal operation purposes. More information on the subject can be found in the Privacy Policy and Terms of Service. By closing this window the user confirms that they have read the information on cookie usage, and they accept the privacy policy and the way cookies are used by the portal. You can change the cookie settings in your browser.
Complex engineering applications demand powerful computing resources. An object based distributed system is suitable for such applications due to the inherent parallelism nature in the object based computing model. As the model is based on message passing, which in turns relies on location transparent object names, an efficient name translation system is therefore required to map the object names...
In this paper, we examine the readability of the human- machine conversation transcripts in the instant messaging environment based on the Gunning-fog Index. The study is based on an embodied conversational agent (ECA) called Artificial Intelligent Natural-language Identity (AINI) which was designed to mimic human conversation. The ECA is also expected to supply answers with a sense of humour. We...
This paper presents an innovative approach to solve the problem of multiclass classification. One-against-one neural networks are applied to interval neutrosophic sets (INS). INS associates a set of truth, false and indeterminacy membership values with an output. Multiple pairs of the truth binary neural network and the false binary neural network are trained to predict multiple pairs of the truth...
This paper presents an approach to the problem of binary classification using ensemble neural networks based on interval neutrosophic sets and bagging technique. Each component in the ensemble consists of a pair of neural networks trained to predict the degree of truth and false membership values. Uncertainties in the prediction are also estimated and represented using the indeterminacy membership...
This paper describes an integrated system based on open-domain and domain-specific knowledge for the purpose of providing query-based intelligent web interaction. It is understood that general purpose conversational agents are not able to answer questions on specific domain subject. On the other hand, domain specific systems lack the flexibility to handle common sense questions. To overcome the above...
As the increasing reliance on electronic mail (email) continues, unsolicited bulk email (SPAM) also continues to grow because it is a very cheap way for advertising. These unwanted emails are now causing a serious problem in clogging the Internet traffic and filling up the email inboxes thereby leaving no space for legitimate emails to pass through. In addition, dealing with SPAM messages is costly...
This paper describes the integration of neural network ensembles and interval neutrosophic sets using bagging technique for predicting regional-scale potential for mineral deposits as well as quantifying uncertainty in the predictions. Uncertainty in the types of error and vagueness are considered in this paper. Each component in the ensemble consists of a pair of neural networks trained for predicting...
Quantification of uncertainty in mineral prospectivity prediction is an important process to support decision making in mineral exploration. Degree of uncertainly can identify level of quality in the prediction. This paper proposes an approach to predict degrees of favourability for gold deposits together with quantification of uncertainty in the prediction. Geographic information systems (GIS) data...
Content-based image retrieval (CBIR) systems have drawn intense interest from many researchers in recent years. Over this period, certain degree of success has been achieved in domain-oriented systems for applications such as facial recognition and medical diagnosis. However, the machine learning techniques used in these systems mostly assume that all the targeted images belong to a single group....
In mining industry, accurate identification of new geographic locations that are favourable for mineral exploration is very important. However, definitive prediction of such locations is not an easy task. In recent years, the use of neural networks ensemble approach to the classification problem has gained much attention. This paper discusses the results obtained from using different neural network...
Customer relationship management using Web personalisation initiatives have gained much attention. The most important strategy of Web personalisation is to provide the customers with correct information or services based on the knowledge about the customers' preferences. With the help of data mining technologies, the above strategy can be implemented. Computational intelligence technologies are investigated...
Content-based image retrieval (CBIR) systems have drawn interest from many researchers in recent years. Over the last few years, kernel-based approach has been a popular choice for the implementation of the relevance feedback based CBIR system. This is largely due to its ability to classify patterns with limited sample data. A long flat vector has been a popular choice for the input configuration...
In order to improve the process of analysis and retrieval of images, it is necessary to examine the execution of such program at the lowest level. This paper reports the results obtained from profiling the execution of an object-oriented image processing and analysis program termed ImageJ. Although profiling has been used in software engineering to identify execution bottlenecks, to our knowledge,...
In the mining industry, effective use of geographic information systems (GIS) to identify new geographic locations that are favorable for mineral exploration is very important. However, definitive prediction of such location is not an easy task. In this paper, four different neural networks, namely, the Polynomial Neural Network (PNN), General Regression Neural Network (GRNN), Probabilistic Neural...
Relevance feedback has drawn intense interest from many researchers in the field of content-based image retrieval (CBIR). In recent years, kernel-based approach has been a popular choice for the implementation of the relevance feedback based CBIR system. This is largely due to its ability to classify patterns with limited sample data. Since most of the kernel approaches reported have been treating...
A small scale distributed computing system that is able to meet the needs of parallel intelligent techniques for engineering and science applications is reported in this paper. The reported system is a cluster of general-purpose PCs interconnected in a network. Such systems are powerful yet low cost. While such systems are not new, most applications written for cluster systems are programmed in MPI-C...
Set the date range to filter the displayed results. You can set a starting date, ending date or both. You can enter the dates manually or choose them from the calendar.