The WebStand Project

In this paper we present the state of advancement of the French ANR WebStand project. The objective of this project is to construct a customizable XML based warehouse platform to acquire, transform, analyze, store, query and export data from the web, in particular mailing lists, with the final intension of using this data to perform sociological studies focused on social groups of World Wide Web, with a specific emphasis on the temporal aspects of this data. We are currently using this system to analyze the standardization process of the W3C, through its social network of standard setters

A framework for green manufacturing practicies in small and medium enterprises in Malaysia

Green Manufacturing Practices (GrMP) is a term used to describe manufacturing practices that do not harm the environment during any part of the manufacturing process. It emphasizes the use of processes that do not pollute the environment or harm consumers, employees, or other members of the community. Small and medium enterprises (SMEs) are moving toward sustainable alternatives through GrMP method. It stresses on critical factors such as organisational style, eco-knowledge, business environment, society influences, supply chain management and technology network. Large size industries are more compelled to do so compared to SMEs due to the fact that they are more influential with better organizational management and good financial stability compared to SMEs. However, SMEs are trying to adapt GrMP as a mandatory process, but lack of proper framework which guide them for implementation. Therefore, this study developes the framework of GrMP for local SMEs. The study involves enablers and barriers in implementing GrMP from previous literatures. This work formulate a framework based on relationship between criticals factors with enablers and barriers. 59 of respondents from local industries in Malaysia were selected as respondents based on six of critical factors divided into two parts which are enablers and barriers. The questionnaire are designed based on this. Survey were evaluated by using Statistical Package for the Social Sciences (SPSS) version 23, in terms of correlation, reliability, central tendency and variability testing. The finding on this study in the term of framework will help SMEs to implementing GrMP. Framework formulate relates the critical factors from previous literature and enablers and barriers from survey based on perception of industries expert. GrMP for SMEs are the first step of environmental awareness and ecological responsibilties

Reactive Rules for Emergency Management

The goal of the following survey on Event-Condition-Action (ECA) Rules is to come to a common understanding and intuition on this topic within EMILI. Thus it does not give an academic overview on Event-Condition-Action Rules which would be valuable for computer scientists only. Instead the survey tries to introduce Event-Condition-Action Rules and their use for emergency management based on real-life examples from the use-cases identified in Deliverable 3.1. In this way we hope to address both, computer scientists and security experts, by showing how the Event-Condition-Action Rule technology can help to solve security issues in emergency management. The survey incorporates information from other work packages, particularly from Deliverable D3.1 and its Annexes, D4.1, D2.1 and D6.2 wherever possible

Virtual Exploration of Underwater Archaeological Sites : Visualization and Interaction in Mixed Reality Environments

This paper describes the ongoing developments in Photogrammetry and Mixed Reality for the Venus European project (Virtual ExploratioN of Underwater Sites, http://www.venus-project.eu). The main goal of the project is to provide archaeologists and the general public with virtual and augmented reality tools for exploring and studying deep underwater archaeological sites out of reach of divers. These sites have to be reconstructed in terms of environment (seabed) and content (artifacts) by performing bathymetric and photogrammetric surveys on the real site and matching points between geolocalized pictures. The base idea behind using Mixed Reality techniques is to offer archaeologists and general public new insights on the reconstructed archaeological sites allowing archaeologists to study directly from within the virtual site and allowing the general public to immersively explore a realistic reconstruction of the sites. Both activities are based on the same VR engine but drastically differ in the way they present information. General public activities emphasize the visually and auditory realistic aspect of the reconstruction while archaeologists activities emphasize functional aspects focused on the cargo study rather than realism which leads to the development of two parallel VR demonstrators. This paper will focus on several key points developed for the reconstruction process as well as both VR demonstrators (archaeological and general public) issues. The ?rst developed key point concerns the densi?cation of seabed points obtained through photogrammetry in order to obtain high quality terrain reproduction. The second point concerns the development of the Virtual and Augmented Reality (VR/AR) demonstrators for archaeologists designed to exploit the results of the photogrammetric reconstruction. And the third point concerns the development of the VR demonstrator for general public aimed at creating awareness of both the artifacts that were found and of the process with which they were discovered by recreating the dive process from ship to seabed

Knowledge Organization Systems (KOS) in the Semantic Web: A Multi-Dimensional Review

Since the Simple Knowledge Organization System (SKOS) specification and its SKOS eXtension for Labels (SKOS-XL) became formal W3C recommendations in 2009 a significant number of conventional knowledge organization systems (KOS) (including thesauri, classification schemes, name authorities, and lists of codes and terms, produced before the arrival of the ontology-wave) have made their journeys to join the Semantic Web mainstream. This paper uses "LOD KOS" as an umbrella term to refer to all of the value vocabularies and lightweight ontologies within the Semantic Web framework. The paper provides an overview of what the LOD KOS movement has brought to various communities and users. These are not limited to the colonies of the value vocabulary constructors and providers, nor the catalogers and indexers who have a long history of applying the vocabularies to their products. The LOD dataset producers and LOD service providers, the information architects and interface designers, and researchers in sciences and humanities, are also direct beneficiaries of LOD KOS. The paper examines a set of the collected cases (experimental or in real applications) and aims to find the usages of LOD KOS in order to share the practices and ideas among communities and users. Through the viewpoints of a number of different user groups, the functions of LOD KOS are examined from multiple dimensions. This paper focuses on the LOD dataset producers, vocabulary producers, and researchers (as end-users of KOS).Comment: 31 pages, 12 figures, accepted paper in International Journal on Digital Librarie

Customer churn prediction in telecom using machine learning and social network analysis in big data platform

Customer churn is a major problem and one of the most important concerns for large companies. Due to the direct effect on the revenues of the companies, especially in the telecom field, companies are seeking to develop means to predict potential customer to churn. Therefore, finding factors that increase customer churn is important to take necessary actions to reduce this churn. The main contribution of our work is to develop a churn prediction model which assists telecom operators to predict customers who are most likely subject to churn. The model developed in this work uses machine learning techniques on big data platform and builds a new way of features' engineering and selection. In order to measure the performance of the model, the Area Under Curve (AUC) standard measure is adopted, and the AUC value obtained is 93.3%. Another main contribution is to use customer social network in the prediction model by extracting Social Network Analysis (SNA) features. The use of SNA enhanced the performance of the model from 84 to 93.3% against AUC standard. The model was prepared and tested through Spark environment by working on a large dataset created by transforming big raw data provided by SyriaTel telecom company. The dataset contained all customers' information over 9 months, and was used to train, test, and evaluate the system at SyriaTel. The model experimented four algorithms: Decision Tree, Random Forest, Gradient Boosted Machine Tree "GBM" and Extreme Gradient Boosting "XGBOOST". However, the best results were obtained by applying XGBOOST algorithm. This algorithm was used for classification in this churn predictive model.Comment: 24 pages, 14 figures. PDF https://rdcu.be/budK