Designing Probabilistic Flow Counting over Sliding Windows

Probabilistic approaches allow designing very efficient data structures and algorithms aimed at computing the number of flows within a given observation window. The practical applications are many, ranging from security to network monitoring and control. We focus our investigation on approaches tailored for sliding windows, that enable continous-time measurements independently from the observation window. In particular, we show how to extend standard approaches, such as Probabilistic Counting with Stochastic Averaging (PCSA), to count over an observation window. The main idea is to modify the data structure to store a compact representation of the timestamp in the registers and to modify coherently the related algorithms. We propose a timestamp-augmented version of PCSA, denoted as TS-PCSA, and compare it with state-of-the-art solutions based on Hyper-LogLog (HLL) counters that evaluate the cardinality over a sliding window, but without storing the timestamps. We will show that TS-PCSA with a limited memory footprint is achieving a different tradeoff between memory and accuracy with respect to HLL-based solutions

A Traffic-Aware Perspective on Network Disaggregated Sketches

Sketches have emerged as a powerful tool for network traffic monitoring due to the good trade-off between accuracy and memory footprint offered by such techniques. Yet, implementing sketches on commercial switches raises numerous challenges related to availability of memory and its access frequency. Recently, disaggregated sketches, i.e., fragments of single network-wide sketches distributed across multiple switches, were introduced to cope with these limitations. However, none of the current approaches exploit any knowledge about the network traffic patterns when deploying such schemes. In this paper, we investigate the impact of traffic patterns on the performance of disaggregated sketches. Our findings show that blindly updating all fragments of a sketch might degrade the monitoring accuracy. Instead, taking into account the spatial distribution of the traffic may lead to globally better monitoring accuracy. Finally, we provide hints on the existence of an optimal solution for such a problem which opens new opportunities for the design of traffic-aware update policies for sketches

The VISTA datasets, a combination of inertial sensors and depth cameras data for activity recognition

This paper makes the VISTA database, composed of inertial and visual data, publicly available for gesture and activity recognition. The inertial data were acquired with the SensHand, which can capture the movement of wrist, thumb, index and middle fingers, while the RGB-D visual data were acquired simultaneously from two different points of view, front and side. The VISTA database was acquired in two experimental phases: in the former, the participants have been asked to perform 10 different actions; in the latter, they had to execute five scenes of daily living, which corresponded to a combination of the actions of the selected actions. In both phase, Pepper interacted with participants. The two camera point of views mimic the different point of view of pepper. Overall, the dataset includes 7682 action instances for the training phase and 3361 action instances for the testing phase. It can be seen as a framework for future studies on artificial intelligence techniques for activity recognition, including inertial-only data, visual-only data, or a sensor fusion approach

Daily gesture recognition during human-robot interaction combining vision and wearable systems

The recognition of human gestures is crucial for improving the quality of human-robot cooperation. This article presents a system composed of a Pepper robot that mounts an RGB-D camera and an inertial device called SensHand. The system acquired data from twenty people who performed five daily living activities (i.e. Having Lunch, Personal Hygiene, Working, House Cleaning, Relax). The activities were composed of at least two "basic" gestures for a total of 10 gestures. The data acquisition was performed by two cameras positioned laterally and frontally to mimic the real conditions. The acquired data were off-line classified considering different combinations of sensors to evaluate how the sensor fusion approach improves the recognition abilities. Specifically, the article presents an experimental study that evaluated four algorithms often used in computer vision, i.e. three classical machine learning and one belonging to the field of deep learning, namely Support Vector Machine, Random Forest, K-Nearest Neighbor and Long Short-Term Memory Recurrent Neural Network. The comparative analysis of the results shows a significant improvement of the accuracy when fusing camera and sensors data, i.e. 0.81 for the whole system configuration when the robot is in a frontal position with respect to the user (0.79 if we consider only the index finger sensors) and equal to 0.75 when the robot is in a lateral position. Interestingly, the system performs well in recognising the transitions between gestures when these are presented one after the other, a common event in the real-life that was often neglected in the previous studies

Valutazione di una modifica dell’attuale sistema di campionamento di polveri di legno duro

In questo lavoro è stata studiata una modifica originale del selettore IOM a tutt’oggi previsto dalle metodiche per la determinazione delle esposizioni professionali a polveri di legno duro. I risultati sin qui ottenuti sono incoraggianti, in quanto eliminano o riducono fortemente la sovrastima – segnalata a suo tempo da uno degli autori e da altri ricercatori – tipica del selettore IOM nel caso di uso di macchine da taglio legno veloci e che rappresenta una fonte di errore notevole nelle determinazioni analitiche. Il problema della determinazione della esposizione a polveri di legno duro è sicuramente di attualità, in considerazione dei seguenti aspetti: - Classificazione delle polveri di legno duro come cancerogeni, ribadita nell’allegato XLII del D. Lgs. 81/2008; - Esistenza di un valore limite ponderato sulle otto ore lavorative, ora contemplato dall’allegato XLIII dello stesso decreto, oggetto di severe e fondate critiche per il livello considerato eccessivamente elevato (5 mg/m3 riferito alla frazione inalabile), pur considerando il significato estremamente relativo di un valore limite professionale per cancerogeni; - Criticità nella determinazione della frazione inalabile aerodispersa di polveri di legno duro in funzione dei vari sistemi di campionamento segnalata in diverse ricerche

Comitato scientifico della collana di studi: Ultima Ratio – Filosofie del diritto penale

La collana, che ha visto in pochi anni la pubblicazione di testi assai cospicui di autori o attorno ad autori fondamentali (Beccaria, Welzel, Ferrajoli), si propone un approccio teorico di tipo filosofico alla questione criminale e alla pena

Air and bone conduction brain stem responses in adults and infants

Air and bone conduction brain stem responses were recorded in 20 adults and 20 infants (16-20 months postconceptional age) with normal hearing. The stimuli were administered using a shielded TDH-39 headphone and a standard B-70A vibrator. Our results show that adults and infants have similar air and bone conduction brain stem thresholds. The comparison of input latency functions obtained with air and bone conduction clicks indicates that the acoustic stimulus generated by the bone vibrator excites more apical regions than that stimulated by the air conduction transient. This is related to the spectrum of the bone conduction click which has an energy peak at 1-2 kHz. Furthermore we found that the difference in latency between adults and infants for air-conducted clicks decreases along with the stimulus intensity and the latencies tend to overlap near the threshold