On the needs and requirements arising from connected and automated driving

Future 5G systems have set a goal to support mission-critical Vehicle-to-Everything (V2X) communications and they contribute to an important step towards connected and automated driving. To achieve this goal, the communication technologies should be designed based on a solid understanding of the new V2X applications and the related requirements and challenges. In this regard, we provide a description of the main V2X application categories and their representative use cases selected based on an analysis of the future needs of cooperative and automated driving. We also present a methodology on how to derive the network related requirements from the automotive specific requirements. The methodology can be used to analyze the key requirements of both existing and future V2X use cases

D4.2 Final report on trade-off investigations

Research activities in METIS WP4 include several as pects related to the network-level of future wireless communication networks. Thereby, a large variety of scenarios is considered and solutions are proposed to serve the needs envis ioned for the year 2020 and beyond. This document provides vital findings about several trade-offs that need to be leveraged when designing future network-level solutions. In more detail, it elaborates on the following trade- offs: • Complexity vs. Performance improvement • Centralized vs. Decentralized • Long time-scale vs. Short time-scale • Information Interflow vs. Throughput/Mobility enha ncement • Energy Efficiency vs. Network Coverage and Capacity Outlining the advantages and disadvantages in each trade-off, this document serves as a guideline for the application of different network-level solutions in different situations and therefore greatly assists in the design of future communication network architectures.Aydin, O.; Ren, Z.; Bostov, M.; Lakshmana, TR.; Sui, Y.; Svensson, T.; Sun, W.... (2014). D4.2 Final report on trade-off investigations. http://hdl.handle.net/10251/7676

E-retailing ethics in Egypt and its effect on customer repurchase intention

The theoretical understanding of online shopping behaviour has received much attention. Less focus has been given to the formation of the ethical issues that result from online shopper interactions with e-retailers. The vast majority of earlier research on this area is conceptual in nature and limited in scope by focusing on consumers’ privacy issues. Therefore, the purpose of this paper is to propose a theoretical model explaining what factors contribute to online retailing ethics and its effect on customer repurchase intention. The data were analysed using variance-based structural equation modelling, employing partial least squares regression. Findings indicate that the five factors of the online retailing ethics (security, privacy, non- deception, fulfilment/reliability, and corporate social responsibility) are strongly predictive of online consumers’ repurchase intention. The results offer important implications for e-retailers and are likely to stimulate further research in the area of e-ethics from the consumers’ perspective

Topology control in self-managed wireless networks

The vision for future telecommunication systems is considered as a representative example of a complex adaptive organization, where several elements, with various computational capabilities and network resources, are interconnected. The increased complexity and the continuously changing network environment make more intense the need for automation and for localized network management tasks. Self-management will allow the execution of advanced configuration actions, such as the change of the wireless network topology under various performance criteria. This paper focuses on the description of the principles and the architectural framework for the cognitive management of future communication systems, considering a complex radio access environment. This framework is used in order to present a solution on the autonomic topology control of future communication systems, where multi-hop links are established using the available relays stations, under the energy consumption constraint. © 2010 Institute for Computer Sciences, Social Informatics and Telecommunications Engineering

Non-english web search: An evaluation of indexing and searching the Greek web

The study reports on a longitudinal and comparative evaluation of Greek language searching on the web. Ten engines, five global (A9, AltaVista, Google, MSN Search, and Yahoo!) and five Greek (Anazitisi, Ano-Kato, Phantis. Trinity, and Visto), were evaluated using (a) navigational queries in 2004 and 2006; and (b) by measuring the freshness of the search engine indices in 2005 and 2006. Homepage finding queries for known Greek organizations were created and searched. Queries included the name of the organization in its Greek and non-Greek, English or transliterated equivalent forms. The organizations represented ten categories: government departments, universities, colleges, travel agencies, museums, media (TV, radio, newspapers), transportation, and banks. The freshness of the indices was evaluated by examining the status of the returned URLs (live versus dead) from the navigational queries, and by identifying if the engines have indexed 32480 active (live) Greek domain URLs. Effectiveness measures included (a) qualitative assessment of how engines handle the Greek language; (b) precision at 10 documents (P@10); (c) mean reciprocal rank (MRR); (d) Navigational Query Discounted Cumulative Gain (NQ-DCG), a new heuristic evaluation measure; (e) response time; (f) the ratio of the dead URL links returned, (g) the presence or absence of URLs and the decay observed over the period of the study. The results report on which of the global and Greek search engines perform best; and if the performance achieved is good enough from a user's perspective. © 2009 Springer Science+Business Media, LLC

Enhancing a fuzzy logic inference engine through machine learning for a self- Managed network

Existing network management systems have static and predefined rules or parameters, while human intervention is usually required for their update. However, an autonomic network management system that operates in a volatile network environment should be able to adapt continuously its decision making mechanism through learning from the system's behavior. In this paper, a novel learning scheme based on the network wide collected experience is proposed targeting the enhancement of network elements' decision making engine. The algorithm employs a fuzzy logic inference engine in order to enable self-managed network elements to identify faults or optimization opportunities. The fuzzy logic engine is periodically updated through the use of two well known data mining techniques, namely k-Means and k-Nearest Neighbor. The proposed algorithm is evaluated in the context of a load identification problem. The acquired results prove that the proposed learning mechanism improves the deduction capability, thus promoting our algorithm as an attractive approach for enhancing the autonomic capabilities of network elements. © 2011 Springer Science+Business Media, LLC