Theoretical Computer Science
An assessment model for the periodic reviews of the market values of property assets
In this paper a mass appraisal methodology for the periodic reviews of the market values of special properties that constitute the asset balance of relevant real estate portfolios has been developed. Using the information published by Italian databases, a study sample of office properties of medium and large size, located in the city of Milan (Italy) and sold in the last decade, has been obtained.
Steady-state performance of an adaptive combined MISO filter using the multichannel affine projection algorithm
The combination of adaptive filters is an effective approach to improve filtering performance. In this paper, we investigate the performance of an adaptive combined scheme between two adaptive multiple-input single-output (MISO) filters, which can be easily extended to the case of multiple outputs. In order to generalize the analysis, we consider the multichannel affine projection algorithm (APA) to update the coefficients of the MISO filters, which increases the possibility of exploiting the capabilities of the filtering scheme.
Approximate Agreement under Mobile Byzantine Faults
In this paper, we address the Approximate Agreement problem in the Mobile Byzantine Fault model. Our contribution is three-fold. First, we refine the problem specification to adapt it to the Mobile Byzantine Fault environment. Then, we propose the first mapping from the existing variants of Mobile Byzantine models to the Mixed-mode Fault model. This mapping further help us to prove the correctness of MSR (Mean-Subsequence-Reduce) algorithms class in our context and it is of independent interest.
Optimal self-stabilizing synchronous mobile Byzantine-tolerant atomic register
This paper addresses for the first time the problem of MWMR atomic memory in a Mobile Byzantine Agents model. The register is maintained by n servers and faulty (Byzantine) agents move from one server to another and when they are affecting a server, this one behaves arbitrarily. This paper addresses the round-based synchronous communication model. We focus on four Mobile Byzantine Failure models differing in the diagnosis capabilities at server side.
Self-stabilizing repeated balls-into-bins
We study the following synchronous process that we call repeated balls-into-bins. The process is started by assigning n balls to n bins in an arbitrary fashion. In every subsequent round, one ball is extracted from each non-empty bin according to some fixed strategy (random, FIFO, etc), and re-assigned to one of the n bins uniformly at random. We define a configuration legitimate if its maximum load is (Formula presented.).
Visual Cryptography for Detecting Hidden Targets by Small-Scale Robots
The last few years have seen a growing use of robots to replace humans in dangerous activities, such as inspections, border control, and military operations. In some application areas, as the latter, there is the need to hide strategic information, such as acquired data or relevant positions. This paper presents a vision based system to find encrypted targets in unknown environments by using small-scale robots and visual cryptography. The robots acquire a scene by a standard RGB camera and use a visual cryptography based technique to encrypt the data.
Double photoionization of simple molecules of astrochemical interest
An experimental and computational investigation characterizing the processes following the double photoionization of the methyloxirane and N-methylformamide molecules has been reported. The double photoionization experiments have been performed at the Elettra Synchrotron Facility of Trieste (Italy).
Fog-computing-based heartbeat detection and arrhythmia classification using machine learning
Designing advanced health monitoring systems is still an active research topic. Wearable and remote monitoring devices enable monitoring of physiological and clinical parameters (heart rate, respiration rate, temperature, etc.) and analysis using cloud-centric machine-learning applications and decision-support systems to predict critical clinical states. This paper moves from a totally cloud-centric concept to a more distributed one, by transferring sensor data processing and analysis tasks to the edges of the network.