A Hybrid Web Caching Design Model for Internet-Content Delivery

The need for online contents (or resources) to be shared and distributed in a large and sophisticated networks of users, geographical dispersed location of servers and their clients, time taken to fulfil clients requests pose major challenge. Therefore the choice of suitable architecture forInternet-based content delivery (ICD) technologies readily comes to mind. To achieve this, Akamai and Gnutella Web technologies are extensively reviewed to identify their strengths and weakness because of their popularity across the world for delivering contents. This new design for Internet-based content distribution is called AkaGnu because of the extra layer (Gnutella network)inserted into Akamai architecture, which provides greater Internet edge over each technology deployed independently. The paper presents a new ICD technology that performs better than Akamai system as a result of new features and behaviours introduced that reduce network traffic, more clients Internet connectivity, increase file sharing, improved speed of contents deliveries, andenhanced network security.Keywords/Index Terms- ICD, Akamai, Gnutella, peer-to-peer, AkaGnu, network traffic, security, architecture, technolog

Modelling Energy Content Of Municipal Solid Waste Using Artificial Neural Network

The application of artificial neural network on energy modeling needs to be researched more extensively in order to appreciate and fulfill the potential of this modeling approach. The estimation of lower heating value is required to know the actual available energy to be converted to heat or electricity. In this study, a feed forward artificial neural network, trained by error back propagation algorithm was used to predict the lower heating value of municipal solid waste. Plastic, paper, glass, textile and food were found to be essential for prediction of lower heating value of municipal solid waste. The lower heating value has strong relationship with plastic, paper, glass, textile and food. Using 60 dataset divided into 37 training dataset and 23 validating dataset, gathered from Abuja waste stream, artificial neural network was trained and validated. The efficiency and accuracy of the artificial neural network was measured based on absolute average error and determination coefficient. The artificial neural network produced results with an absolute average percentage error less than 9.13% and 9.4% for training and validating dataset, respectively, when compared to measured data. The model provided the best fit and the predicted trend followed the observed data closely; the determination coefficient for training and validating dataset were 0.992 and 0.981, respectively. These results show that artificial neural network is an effective tool in forecasting energy content

A Hybrid Web Caching Design Model for Internet-Content Delivery

The need for online contents (or resources) to be shared and distributed in a large and sophisticated networks of users, geographical dispersed location of servers and their clients, time taken to fulfil clients requests pose major challenge. Therefore the choice of suitable architecture forInternet-based content delivery (ICD) technologies readily comes to mind. To achieve this, Akamai and Gnutella Web technologies are extensively reviewed to identify their strengths and weakness because of their popularity across the world for delivering contents. This new design for Internet-based content distribution is called AkaGnu because of the extra layer (Gnutella network)inserted into Akamai architecture, which provides greater Internet edge over each technology deployed independently. The paper presents a new ICD technology that performs better than Akamai system as a result of new features and behaviours introduced that reduce network traffic, more clients Internet connectivity, increase file sharing, improved speed of contents deliveries, andenhanced network security.Keywords/Index Terms- ICD, Akamai, Gnutella, peer-to-peer, AkaGnu, network traffic, security, architecture, technolog

Software Development Outsourcing: Challenges and Opportunities in Nigeria

In recent years, several emergent regions have become software development sourcing countries. This article investigates the possibilities of sub-Saharan Africa as a sourcing destination in the software field. To find out the reasons why sub-Saharan Africa countries, in general, and Nigeria, in particular, are not considered a destination for global software development projects, the authors interviewed a set of professionals from Europe and Africa. Results indicate that there are many disadvantages and difficulties impeding Nigeria from becoming a preferred sourcing destination, mainly the absence of a strong software industry and the concerns about legislative, fiscal, and commercial premises. On the other hand, it is observed that there are also relevant added values and competitive advantages in Nigeria (English-speaking country, same time zone, and cost); therefore, it can become a potential target for software development outsourcing in the medium and long terms

Term frequency inverse document frequency (TF-IDF) technique and artificial neural network in email classification system

Electronic mail has been a competent and widely accepted communication mechanism as the Internet community increases. This has inspired attention for urgent need to manage and maintain e-mail. Email messages are expected to be sent and gathered in a warehouse for recurring use as it ranges from inert institutional information to discussions and creates complications for users in making precedence for saved and new email content. This research classified accumulated electronic messages into three class dataset of trivial, important and non-trivial. Electronic mail contents are extracted and Term Frequency Inverse Document Frequency (TF-IDF) technique was used to determine keywords in email messages to determine constructive words to be used. Nuclass 7.1 artificial neural network software was used for email classification into user defined word identity classes in an associative learning approach as the network was trained with input and matching output patterns. The performance evaluation showed that neural networks are more successfully used for automated email classification.Keywords: Electronic mail, Term Frequency Inverse Document Frequency, artificial neural network, email classification, email message

The Nwagu Aneke Project

The Nwagu Aneke script is a syllabic system of writing, among the riverian Igbo people of Umuleri in the Omambala (Anambra) basin of present day Anambra State of Nigeria. A system which occupies a well-established niche in the history of writing, syllabic writing has traditionally been categorised as an intermediate stage between phoneticized pictographic and alphabetic systems. However, as this research project intends to demonstrate, the more we can understand the provenance, nature and other aspects of the script, the more we can understand certain aspects of the evolution of writing systems on which there is doubt, debate or paucity of reliable evidence. But beyond these, the Nwagu Aneke script promises to contribute excellent data for the study of the rudiments of visual communication and for the investigation of certain aspects of the interface between literacy and orality

Development of a Plastics and Paper Waste Management System for a University Community

In Nigeria, poor waste management practices are evident in many urban centers. This study considered a University community as the model to explore the use of digital solutions in proper waste management. This study developed a web-based waste management system for the collection of plastics and paper in a University community. The framework developed utilized the use case and system block diagram. In this study, HTML, CSS, MySQL and Java programming language was used in the design of the web-based system. The result of this study was presented using screenshots. The web-based system had an interface to show profiles of the users, waste pickup information, incentive platform, and the admin dashboard to monitor and approve pickups and incentives. Past studies have indicated the success of using incentives to build sustainable behavioural change towards efficient waste disposal. Therefore, this study was able to introduce the incentive platform which converts weight of paper and plastics waste to points then to rewards for the users. The web-based waste management system for the collection of plastics and paper can be deployed for University communities to help reduce the number of paper and plastics that end up in landfills. Also, by picking the paper and plastics waste from source helps to prevent bin contamination