An information assistant system for the prevention of tunnel vision in crisis management

In the crisis management environment, tunnel vision is a set of bias in decision makers’ cognitive process which often leads to incorrect understanding of the real crisis situation, biased perception of information, and improper decisions. The tunnel vision phenomenon is a consequence of both the challenges in the task and the natural limitation in a human being’s cognitive process. An information assistant system is proposed with the purpose of preventing tunnel vision. The system serves as a platform for monitoring the on-going crisis event. All information goes through the system before arrives at the user. The system enhances the data quality, reduces the data quantity and presents the crisis information in a manner that prevents or repairs the user’s cognitive overload. While working with such a system, the users (crisis managers) are expected to be more likely to stay aware of the actual situation, stay open minded to possibilities, and make proper decisions

Thirty Years of Machine Learning: The Road to Pareto-Optimal Wireless Networks

Future wireless networks have a substantial potential in terms of supporting a broad range of complex compelling applications both in military and civilian fields, where the users are able to enjoy high-rate, low-latency, low-cost and reliable information services. Achieving this ambitious goal requires new radio techniques for adaptive learning and intelligent decision making because of the complex heterogeneous nature of the network structures and wireless services. Machine learning (ML) algorithms have great success in supporting big data analytics, efficient parameter estimation and interactive decision making. Hence, in this article, we review the thirty-year history of ML by elaborating on supervised learning, unsupervised learning, reinforcement learning and deep learning. Furthermore, we investigate their employment in the compelling applications of wireless networks, including heterogeneous networks (HetNets), cognitive radios (CR), Internet of things (IoT), machine to machine networks (M2M), and so on. This article aims for assisting the readers in clarifying the motivation and methodology of the various ML algorithms, so as to invoke them for hitherto unexplored services as well as scenarios of future wireless networks.Comment: 46 pages, 22 fig

CHORUS Deliverable 2.1: State of the Art on Multimedia Search Engines

Based on the information provided by European projects and national initiatives related to multimedia search as well as domains experts that participated in the CHORUS Think-thanks and workshops, this document reports on the state of the art related to multimedia content search from, a technical, and socio-economic perspective. The technical perspective includes an up to date view on content based indexing and retrieval technologies, multimedia search in the context of mobile devices and peer-to-peer networks, and an overview of current evaluation and benchmark inititiatives to measure the performance of multimedia search engines. From a socio-economic perspective we inventorize the impact and legal consequences of these technical advances and point out future directions of research

Solutions for IPv6-based mobility in the EU project MobyDick

Proceedings of the WTC 2002, 18th World Telecommunications Congress, Paris, France, 22 -27 September, 2002.Mobile Internet technology is moving towards a packet-based or, more precisely, IPv6-based network. Current solutions on Mobile IPv6 and other related QoS and AAA matters do not offer the security and quality users have come to take for granted. The EU IST project Moby Dick has taken on the challenge of providing a solution that integrates QoS, mobility and AAA in a heterogeneous access environment. This paper focuses on the mobility part of the project, describes and justifies the handover approach taken, shows how QoS-aware and secure handover is achieved, and introduces the project's paging concept. It shows that a transition to a fully integrated IP-RAN and IP-Backbone has become a distinct option for the future.Publicad

Efficient intrusion detection scheme based on SVM

The network intrusion detection problem is the focus of current academic research. In this paper, we propose to use Support Vector Machine (SVM) model to identify and detect the network intrusion problem, and simultaneously introduce a new optimization search method, referred to as Improved Harmony Search (IHS) algorithm, to determine the parameters of the SVM model for better classification accuracy. Taking the general mechanism network system of a growing city in China between 2006 and 2012 as the sample, this study divides the mechanism into normal network system and crisis network system according to the harm extent of network intrusion. We consider a crisis network system coupled with two to three normal network systems as paired samples. Experimental results show that SVMs based on IHS have a high prediction accuracy which can perform prediction and classification of network intrusion detection and assist in guarding against network intrusion

noteEd - A web-based lecture capture system

Electronic capture and playback of lectures has long been the aim of many academic projects. Synote is an application developed under MACFoB (Multimedia Annotation and Community Folksonomy Building) project to synchronise the playback of lecture materials. However, Synote provides no functionality to capture such multimedia. This project involves the creation of a system called noteEd, which will capture a range of multimedia from lectures and make them available to Synote. This report describes the evolution of the noteEd project throughout the design and implementation of the proposed system. The performance of the system was checked in a user acceptance test with the customer, which is discussed after screenshots of our solution. Finally, the project management is presented containing a final project evaluation