A high-level semiotic trust agent scoring model for collaborative virtual organisations

In this paper, we describe how a semiotic ladder, together with a supportive trust agent, can be used to address “soft” trust issues in the context of collaborative Virtual Organisations (VO). The intention is to offer all parties better support for trust (as reputation) management including the reduction of risk and improved reliability of VO e-services. The semiotic ladder is intended to support the VO e-service lifecycle through the articulation of e-trust at various levels of system abstraction, including trust as measurable confidence. At the social level, reputation and reliability measures of e-trust are the relevant dimensions as regards choice of VO partner and are also relevant to the negotiation of service level agreements between the VO partners. By contrast, at the lower levels of the trust ladder, e-trust measures typically address the degree to which secure sign on and message level security conforms to various tangible technological security protocols. The novel trust agent provides the e-service consumer with an objective measure of the trustworthiness of the e-service at run-time, just prior to its actual consumption. Specifically, VO e-service consumer confidence level is informed, by leveraging third party objective evidence. This evidence comprises a set of Corporate Governance (CG) scores. These scores are used as a trust proxy for the "real" owner of the VO. There are also inherent limitations associated with the use of CG scores. These are duly acknowledged

Lumps in the clump: more stirring required?

This article discusses the issue of barriers to interoperability within networked information retrieval systems, using the projects CAIRNS (the Co-operative Academic Information Retrieval Network for Scotland) and SCONE (Scottish Collections Network Extension) to illustrate this problem, and methods which can be employed to enhance interoperability

Pleading for the management controller profession in the trade area

Generalizing a reflection on strategy and controlling within the Romanian companies is rather recent. The environment changes and especially the changes in the nature and the dimensions of the markets due to the globalization and regulation put real questions for companies, generate a strategic thinking and make compulsory the appearance of an efficient management control. Generally, the scientific papers concerning the concept of management control deal with the production companies more than with the trade ones. This is why we chose to present the importance of the controller within a trade company. The management control has to assure the coherence between the adopted strategy (where the company in the trade domain wants to go) and the practical means of achieving it (what it has to do and what it is used for). The management controller is the person that contributes to obtain this coherence. There is plenty of information available, but for the decision making purposes only a restricted number of facts are correlated, namely the relevant ones. The trade management controller takes part in creating the information system useful for the decision making. Such a system has to offer reliable information in due time to the decision making persons concerning the profitability of certain markets, distribution areas, products, clients, the analysis of margins, distribution costs, advertising expenses etc. The trade management controller plays the role of a manager's copilot, he assists him in the management of the activity, alerts him when problems are encountered, helps him to make the necessary decisions to correct the trajectory. These are a few reasons that allow us to sustain the important role played by the management controller in the activity of the companies in the trade area.management controller, trade, customers, management, strategy, analysis, decision

Fog Network Task Scheduling for IoT Applications

In the Internet of Things (IoT) networks, the data traffic would be very bursty and unpredictable. It is therefore very difficult to analyze and guarantee the delay performance for delay-sensitive IoT applications in fog networks, such as emergency monitoring, intelligent manufacturing, and autonomous driving. To address this challenging problem, a Bursty Elastic Task Scheduling (BETS) algorithm is developed to best accommodate bursty task arrivals and various requirements in IoT networks, thus optimizing service experience for delay-sensitive applications with only limited communication resources in time-varying and competing environments. To better describe the stability and consistence of Quality of Service (QoS) in realistic scenarios, a new performance metric "Bursty Service Experience Index (BSEI)" is defined and quantified as delay jitter normalized by the average delay. Finally, the numeral results shows that the performance of BETS is fully evaluated, which can achieve 5-10 times lower BSEI than traditional task scheduling algorithms, e.g. Proportional Fair (PF) and the Max Carrier-to-Interference ratio (MCI), under bursty traffic conditions. These results demonstrate that BETS can effectively smooth down the bursty characteristics in IoT networks, and provide much predictable and acceptable QoS for delay-sensitive applications

What is Behind the Fall in Russian Agricultural Production?

This study analyses the causal factors of fall in Russian farm output focusing on financial determinants. Translog production function is estimated on panel of 17653 large-scale farms for 1996-1998 period using fixed-effects and accounting for inter-regional climate differences. Output elasticities are analysed for sub-samples of crop and animal producing farms. The research findings show that budget transfers to the farms are inefficient and result in taxation of farms. Farms are operating under the soft budget constraints that have to be removed to improve farm production performance.production, Russia, debts, credit, budget transfers, Production Economics,

Evolving Lucene search queries for text classification

We describe a method for generating accurate, compact, human understandable text classifiers. Text datasets are indexed using Apache Lucene and Genetic Programs are used to construct Lucene search queries. Genetic programs acquire fitness by producing queries that are effective binary classifiers for a particular category when evaluated against a set of training documents. We describe a set of functions and terminals and provide results from classification tasks