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Many email users, especially business men, managers and academician receive many email messages that require sorting out within a short period of time. While most mail summarisation applications allow dialogue structure of emails, users to summarise messages into percentages or numbers of sentences. In practice this task tends to be tedious and solutions available today often require programming skills on the part of the email users. The users define rules for summarising messages. For each message, the user must first decide which message is most important. Then, the user must inform the mail summariser of that choice by selecting the appropriate icon or menu item from among what is typically a set of several dozen choices. The combined effort of choosing a message and conveying that choice to the application often discourages users from summarising their mails, resulting in unmanageable inboxes that contain hundreds or even thousands of un-precised and unnecessary messages. Intelligent email summarisation system (IESS), encourages users to have summative messages by simplifying the content of the mail. Using unsupervised machine learning techniques in combination with automated word and phrases modeller to intelligently provide a precis summary of each email messages is developed to reduce the burden of email users.

Business policy reflects way too many things not only restricting what the company should do but also predicting the future direction of the company. It is desirable that the description of business policy can be interchangeable between business descriptions and engineering specifications so that the rules can be integrated into engineering process without further misinterpreting and conflicting. This paper presents our initiatives of a work to investigate and identify suitable ontologies, as well as suitable ontology alignment framework. A set or sets of formal vocabulary will be developed across various ontologies to specify business policy in a way that different levels of business managers, business people and technical people especially engineers can exchange and share business rules without misinterpreting and inconsistency.

This paper presents the first stage of our proposed research work, i.e., integrating a business reporting language into pervasive computing processes and products. In general, our first stage is to identify and review one of the key business reporting languages, namely, Extensible Business Reporting Language (XBRL) and discuss an integrating XBRL into pervasive computing fields. XBRL is an emerging standard based on XML technology, particularly to streamline a diversification of financial information throughout the world for globalised stakeholders. This paper gives an overview and discusses potential of using XBRL for pervasive computing, as well as strengthening XBRL using smart computing technologies, bridging gaps between financial requirements and pervasive computing productions. Furthermore, current development of relevant intelligent computing technologies especially semantic web is investigated, identified and developed to assist XBRL for a more automated manner and to enhance usability of XBRL for both business users and pervasive computing researchers.

Nowadays, email has become one of the most critical personal and business applications and email users would experience serious consequences if email messages could not be available or experience high volume of messages which lead to congestions, overloads and limited storage space coupled with unstructured messages in mail boxes. A few years ago, the means of communication are via letters by post, telegraph, fax, couriers to mention a few but now the focus has changed to a faster means of obtaining quick responses and faster ways of communication-emails. We propose a new framework to help organised and prioritized email better; An intelligent email prediction system (IEPS). The goal is to organise emails better in mail boxes, prioritise emails based on the focus of the email content. The intelligent email prediction system helps to improve email users' performances, saves time, very effective and efficient tool and is cost effective for businesses and for personal use. The system is evaluated against a corpus of human-judged predictions, reaching satisfactory level of performance.

To acquire knowledge by learning automatically from the data, through a process of inference, model fitting, or learning from example is one of the rare field of email management. And when an artificial system can perform "intelligent", tasks similar to those performed by the human brain and such is implemented in email classification, such a system will be is extremely intelligent. Using neural network for email content classification with back propagation is where our technique becomes distinct and effective. This paper proposes a new email classification model using a teaching process of multi-layer neural network to implement back propagation algorithm. Our contributions are: the use of empirical analysis to select an optimum, novel collection of features of a user's email message content that enables the rapid detection of most important words, phrases in emails and a demonstration of the effectiveness of two equal sets of emails (training and testing data).

This paper presents the design and implementation of a new system to manage email messages using email evolving clustering method with unsupervised learning approach to group emails base on activities found in the email messages, namely email grouping. Users spend a lot of time reading, replying and organizing their emails. To help users organize their email messages, we propose a new framework to help organise and prioritize email better. The goal is to provide highly structured and prioritized emails, thus saving the user from browsing through each email one by one and help to save time.

This paper presents the design and implementation of a system to group and summarize email messages. The system exploits the subject and content of email messages to classify emails based on users’ activities and auto generate summaries of each incoming messages. Our framework solves the problem of email overload, congestion, difficulties in prioritizing and successfully processing of contents of new incoming messages and difficulties in finding previously archived messages in the mail box by providing a system that groups emails based on users’ activities, and providing summaries of emails.

Email has now become the most-used communication tool in the world and has also become the primary business productivity applications for most organizations and individuals. With the ever increasing popularity of emails, email over-load and prioritization becomes a major problem for many email users. Users spend a lot of time reading, replying and organizing their emails. To help users organize and prioritize their email messages, we propose a new framework; email reply prediction with unsupervised learning. The goal is to provide concise, highly structured and prioritized emails, thus saving the user from browsing through each email one by one and help to save time. In this paper, we discuss the features used to differentiate emails, show promising initial results with unsupervised machine learning model, and outline future directions for this work.

With the ever increasing popularity of emails, email over-load and prioritization becomes a major problem for many email users. Users spend a lot of time reading, replying and organizing their emails. To help users organize their email messages, we propose a new framework to help organised and prioritized email better; email reply prediction. The goal is to provide concise, highly structured and prioritized emails, thus saving the user from browsing through each email one by one and help to save time. In this paper, we discuss the features used to differentiate emails, show promising initial results with unsupervised machine learning model, and outline future directions for this work.

This paper presents the design and implementation of a new system to predict whether email received require a reply, group emails and summarize email messages. The system uses not only subjects and headers fields but also content of email messages to classify emails based on users' activities and generate summaries of each incoming message with unsupervised learning approach. Our framework tackles the problem of email overload, congestion, difficulties in prioritizing and difficulties in finding previously archived messages in the mail box.

This discussion concerns 'metrics'. More specifically, we discuss quantitative metrics for evaluating Internet applications: what should we quantify, monitor and analyse in order to characterise, evaluate and develop Internet applications based on reusing existing Internet applications,which is widely available in the Internet. Due to the distinctive evolution nature of Internet applications, assessing quality of software will provide ease and higher accuracy for Web developers. However, there is a great gap between the rapid development of Internet applications and the slow speed of developing corresponding metric measures. To tackle this issue, we look into measuring the quality of Internet applications and enable Web developers to enhance the quality of their programs and identify reusable components from Internet-based resources.

The paper introduces AnaTempura, a tool for run-time verification of systems using Interval Temporal Logic (ITL) and its executable subset Tempura. The runtime verification technique uses assertion-points to check whether a system satisfies timing or safety properties expressed in ITL. The assertion-points are inserted in the source code of the system and these generate a trace, i.e., values of variables and timestamps of value change, during run-time. AnaTempura is being used for the analysis of mixed hardware/software systems, analysis of security policies (as part of the SANTA workbench) and for checking webservice composition.

This paper proposes a new email classification model using a teaching process of multi-layer neural network to implement back propagation technique. Email has become one of the fastest and most efficient forms of communication. However, the increase of email users with high volume of email messages could lead to un-structured mail boxes, email congestion, email overload, unprioritised email messages, and resulted in the dramatic increase of email classification management tools during the past few years. Our contributions are: the use of empirical analysis to select an optimum, novel collection of features of a users’ email contents that enable the rapid detection of most important words, phrases in emails and a demonstration of the effectiveness of two equal sets of emails training and testing data.

A product goes through various processes in a production flow which is also known as assembly line in manufacturing process management. Toyota created a new concept which is known as lean concept in manufacturing industry. Today it is the leading model in manufacturing plants through the globe. The linear walking worker assembly line is a flexible assembly system where each worker travels down the line carrying out each assembly task at each station; and each worker accomplishes the assembly of a unit from start to finish. This paper attempts to combine the flexibility of the walking worker and lean in order to quantify the benefits from applying the shop floor principles of lean management., {"references":["Lean Manufacturing. http://en.wikipedia.org/wiki/Lean_manufacturing\nApril, 2011, (April 28, 2011)","D. Williams. Implementation of Shop Floor Principles at Mercedez-\nBenz.Internet:\nhttp://lean.org.za/presentations/Damain_Williams_Implementation_of_S\nhop_Floor_Management_at_Mercedes_Benz.pdf.2008 (April 28, 2011)","L. Wilson. How to Implement Lean Manufacturing. M. Mc Gee, Ed.\nNew York: McGraw Hil, 2009, pp. 67-69","Mazak. Case Study. Internet http://www.mazakusa.com/pdfs/MZK-\n1164.pdf (April 28, 2011)","D. Williams. Implementation of Shop Floor Principles at Mercedez-\nBenz.Internet:\nhttp://lean.org.za/presentations/Damain_Williams_Implementation_of_S\nhop_Floor_Management_at_Mercedes_Benz.pdf .2008 (April 28, 2011)","D. Williams. Implementation of Shop Floor Principles at Mercedez-\nBenz.Internet:\nhttp://lean.org.za/presentations/Damain_Williams_Implementation_of_S\nhop_Floor_Management_at_Mercedes_Benz.pdf .2008 (April 28, 2011)","Qian Wang, Sylvain Lassalle, Antony R. Mileham, and Geraint W.\nOwen. Analysis of Production Loss on a Linear Walking Worker Line.\nInternet: http://www.waset.org/journals/waset/v65/v65-140.pdf (April \n28, 2011)","Encyclopedia of Business, 2nd Edition. Reference For Business. Internet:\nhttp://www.referenceforbusiness.com/management/Int-Loc/Layout.html\n(April 25, 2011)","R. Sirovetnukul and P. Chutima. \"The impact of walking time on ushaped\nassembly lineWorker allocationProblems.\" Internet\nhttp://www.cp.eng.chula.ac.th/~piak/project/coin/EngineeringJournal_EJ\n2010April.pdf April 2010. (April 28, 2011)"]}

Recent developments in computer and image processing technology have led to the expansion of several automatic surveillance systems. This paper describes a general, scalable, and distributed framework monitoring model for real-time video-analysis intended for research, prototyping and especially, for business economic purposes. The architecture of the system considers multiple cameras and is based on a server/client model. System modules can be connected in different ways, therefore achieving more flexibility. Three main design criteria’s have been considered 1- low computational cost 2- easy component integration, 3-sensors grouping. The experimental results show the potential use of the proposed system.

Nowadays, email has become one of the most critical personal and business applications and email users would experience serious consequences if email messages could not be available or experience high volume of messages which lead to congestions, overloads and limited storage space coupled with unstructured messages in mail boxes. A few years ago, the means of communication are via letters by post, telegraph, fax, couriers to mention a few but now the focus has changed to a faster means of obtaining quick responses and faster ways of communication-emails. We propose a new framework to help organise and prioritize email better; Machine learning email prediction system (MLEPS). The goal is to organise emails better in mail boxes, prioritise emails based on the focus of the email content. The intelligent email prediction system helps to improve email users’ performances, saves time, very effective and efficient tool and is cost effective for businesses and for personal use. The system is evaluated against a corpus of human-judged predictions, reaching satisfactory level of performance.

This paper presents a novel people counting system based on weighted fusing technique using camera and infra-red sensors. Conventional techniques are based image vision data to count people. However, these vision-based people counting methods frequently fail due to irregular illumination change and crowded environment and some geometrical limitation that may affect the accuracy level of these systems. In this paper, a dynamic data fusion technique is provided in order to provide more accuracy results.

In today’s world, much of our communication is done via e-mail. Many companies and internet users now view e-mail as one of their most critical personal and business applications and would experience serious consequences if their e-mail messages could not be available or experience high volume of messages which lead to congestions, overloads and limited storage space coupled with un-organized e-mail messages. A few years ago, the means of communication are via letter by post, telegraph, fax, couriers to mention a few but now the focus has changed to a faster means of obtaining quick responses and faster ways of communication, e-mails. We propose a new framework to help organised and prioritized e-mail better; e-mail reply prediction. The goal is to provide concise, highly structured and prioritized e-mails, thus saving the user from browsing through each email one by one and help to save time.