Computer/computer interface

System synchronizes data transfer between two computers by generating data strobe pulses when computers are ready for data transfer. In addition, interface filters noise by sampling

SOA services in higher education

Service Oriented Architecture (SOA) is a recent architectural framework for distributed software system development in which software components are packaged as Services. It has become increasingly popular in academia and in industry, but has been principally used in the business domain. However, in higher education, SOA has rarely been applied or investigated. In this paper, we propose the idea of applying SOA technologies in the education domain, to increase both interoperability and flexibility within the e-learning environment. We expect that both students and teachers in higher educational institutions can benefit from this approach. We also describe a number of possible SOA services, along with a high level service roadmap to support a university's learning and teaching activities

Process Framework for Subscriber Management and Retention in Nigerian Telecommunication Industry

in the global telecommunication industry. Hence, a dominant approach for subscriber management and retention is churn control, since it is cheaper to retain an existing subscriber than acquiring a new one. Predictive modeling employs the use of data mining techniques to identify patterns and provide a result that a group of subscribers are likely to churn in the near future. However, the effectiveness of subscriber retention strategy in an organization can be further boosted if the reason for churn and the timing of churn can also be predicted. In this paper, we propose a data mining process framework that can be used to predict churn, determine when a subscriber is likely to churn, provides the reason why a subscriber may churn, and recommend appropriate intervention strategy for customer retention using a combination of statistical and machine learning techniques. This experiment is carried out using data from a major telecom operator in Nigeria

School algebra and the computer

How are we to use the computer in the teaching and learning of algebra? In the longterm the new technology is introducing new possibilities that may radically change the algebra curriculum. However, in the short-term we already have the National Curriculum placing its template on the development of algebra in school. The recent regrouping of topics into five attainment targets has integrated number pattern with the development of algebraic symbolism. It seems natural to build from expressing patterns in words to expressing them in a shorthand algebraic notation, but, although this proves a sound tactic for the more able, there are subtle difficulties for the majority of children. Instead I shall advocate introducing algebraic symbolism by using it as a language of communication with the computer, through programming in a suitable computer language. This has two distinct benefits – it develops a meaningful algebraic language which can be used to describe number patterns, and it gives a foundation for traditional algebra and its manipulation

Computer-based library or computer-based learning?

Traditionally, libraries have played the role of repository of published information resources and, more recently, gateway to online subscription databases. The library online catalog and digital library interface serve an intermediary function to help users locate information resources available through the library. With competition from Web search engines and Web portals of various kinds available for free, the library has to step up to play a more active role as guide and coach to help users make use of information resources for learning or to accomplish particular tasks. It is no longer sufficient for computer-based library systems to provide just search and access functions. They must provide the functionality and environment to support learning and become computer-based learning systems. This paper examines the kind of learning support that can be incorporated in library online catalogs and digital libraries, including 1) enhanced support for information browsing and synthesis through linking by shared meta-data, references and concepts; 2) visualization of related information; 3) adoption of Library 2.0 and social technologies; 4) adoption of Library 3.0 technologies including intelligent processing and text mining

Opportunities and challenges in using AI Chatbots in Higher Education

Artificial intelligence (AI) conversational chatbots have gained popularity over time, and have been widely used in the fields of e-commerce, online banking, and digital healthcare and well-being, among others. The technology has the potential to provide personalised service to a range of consumers. However, the use of chatbots within educational settings is still limited. In this paper, we present three chatbot prototypes, the Warwick Manufacturing Group, University of Warwick, are currently developing, and discuss the potential opportunities and technical challenges we face when considering AI chatbots to support our daily activities within the department. Three AI virtual agents are under development: 1) to support the delivery of a taught Master's course simulation game; 2) to support the training and use of a newly introduced educational application; 3) to improve the processing of helpdesk requests within a university department. We hope this paper is informative to those interested in using chatbots in the educational domain. We also aim to improve awareness among those within the chatbot development industry, in particular the chatbot engine providers, about the educational and operational needs within educational institutes, which may differ from those in other domains

Computer-aided diagnosis of lung nodule using gradient tree boosting and Bayesian optimization

We aimed to evaluate computer-aided diagnosis (CADx) system for lung nodule classification focusing on (i) usefulness of gradient tree boosting (XGBoost) and (ii) effectiveness of parameter optimization using Bayesian optimization (Tree Parzen Estimator, TPE) and random search. 99 lung nodules (62 lung cancers and 37 benign lung nodules) were included from public databases of CT images. A variant of local binary pattern was used for calculating feature vectors. Support vector machine (SVM) or XGBoost was trained using the feature vectors and their labels. TPE or random search was used for parameter optimization of SVM and XGBoost. Leave-one-out cross-validation was used for optimizing and evaluating the performance of our CADx system. Performance was evaluated using area under the curve (AUC) of receiver operating characteristic analysis. AUC was calculated 10 times, and its average was obtained. The best averaged AUC of SVM and XGBoost were 0.850 and 0.896, respectively; both were obtained using TPE. XGBoost was generally superior to SVM. Optimal parameters for achieving high AUC were obtained with fewer numbers of trials when using TPE, compared with random search. In conclusion, XGBoost was better than SVM for classifying lung nodules. TPE was more efficient than random search for parameter optimization.Comment: 29 pages, 4 figure

Executive computer program for linking independent computer programs: ODINEX

Program controls sequence of execution of network of program elements and maintains data base of common information which forms communication link among them. Approach is applicable to any multiple-program task