The importance of post-processing the results of clustering when using data mining to
support subsequent decision-making is discussed. Both the formal embedded binary logistic
regression (EBLR) and the visual profile’s assessment grid (PAG) methods are presented
as bridging tools for the real use of clustering results. EBLR is a sequence of logistic
regressions that helps to predict the class of a new object; while PAG is a graphical tool that
visualises the results of an EBLR. PAG interactively determines the most suitable class for a
new object and enables subsequent follow-ups. PAG makes the underlying mathematical
model (EBLR) more understandable, improves usability and contributes to bridging the gap
between modelling and decision-support. When applied to medical problems, these tools
can perform as diagnostic-support tools, provided that the predefined set of profiles refer
to different stages of a certain disease or different types of patients with a same medical
problem, etc. Being a graphical tool, PAG enables doctors to quickly and friendly determine
the profile of a patient in the everyday activity, without necessarily understanding the
statistical models involved in the process, which used to be a serious limitation for wider
application of these methods in clinical praxis. In this work, an application is presented
with 4 functional disability profiles.
The Foreign Exchange Market is the biggest and one of the most liquid markets in the world. This market has always been one of the most challenging markets as far as short term prediction is concerned. Due to the chaotic, noisy, and non-stationary nature of the data, the majority of the research has been focused on daily, weekly, or even monthly prediction. The literature review revealed that there is a gap for intra-day market prediction. Identifying this gap, this paper introduces a prediction and decision making model based on Artificial Neural Networks (ANN) and Genetic Algorithms. The dataset utilized for this research comprises of 70 weeks of past currency rates of the 3 most traded currency pairs: GBP\USD, EUR\GBP, and EUR\USD. The initial statistical tests confirmed with a significance of more than 95% that the daily FOREX currency rates time series are not randomly distributed. Another important result is that the proposed model achieved 72.5% prediction accuracy. Furthermore, implementing the optimal trading strategy, this model produced 23.3% Annualized Net Return.
Ricciardi, S.; Palmieri, F.; Fiore, U.; Castiglione, A.; Germán Santos-Boada Mathematical and computer modelling Vol. 58, num. 5-6, p. 1-25 DOI: 10.1016/j.mcm.2012.12.004 Data de publicació: 2013-09 Article en revista
Energy consumption is now one of the most important issues for network carriers, since the majority of the energy needed for their operation is consumed in the wireless access and optical transport networks. The continuous growth in the wireless customers and traffic volumes and the consequent energy demand on modern carriers’ broadband infrastructures require reconsidering their energy efficiency, by starting from the formulation of new, more complete and representative network models that should become the foundations for modern energy-aware control plane architectures.
Accordingly, this work presents a novel comprehensive energy model for next-generation wireless access-over-optical-transport networks characterized by hybrid power systems (i.e., multiple dynamically available power sources). The objective is to identify the energy-related information that need to be handled at the control plane layer to support energy-aware networking practices. Such information can be made available to suitable energy-aware routing and wavelength assignment algorithms that may exploit them to optimize the overall network energy-consumption and reducing the associated carbon footprint. The proposed model may be taken as a reference for the implementation of new energy-aware control plane protocols (routing and signaling) that make use of power-related considerations to achieve energy-efficiency and energy-awareness in wavelength-routed network infrastructures.
Synchronization protocols have been widely investigated in distributed systems aiming to achieve real-time and scalable properties. With the fast development of large-scale distributed systems, and due to their heterogenous nature involving wired, wireless, and mobile nodes, synchronization has again come into play. In this work, we have studied contact synchronization and handling, which is an important feature in corporate environments. Indeed, it has become very important to support collaboration of teams of mobile users by enabling anytime and anywhere access to shared contact data. We characterize the problem as a distributed systems problem, identify its desirable properties, and outline its main characteristics. A simple algorithm is proposed as an efficient solution to contact synchronization when some nodes of the system are assumed to be mobile phones under the Android operating system. The features required at both ends of the distributed system are explained in order to guarantee the correctness of the algorithm. We also analyze the implementation of the algorithm coupling the Android platform and the SugarCRM server, and provide an experimental evaluation of the performance of the proposed approach.