Sicurezza nelle reti: utilizzo di architetture multi-core per il monitoraggio del traffico IP

The IP packet capture activity has always assumed great importance in the computer networks security. It's daily used in fact to monitor and analyze the IP traffic passing through a computer networks with the purpose to identify anomalous behaviors that could be associated with security problems. The new infrastructures for high throughput networks, also used in small or medium sized local networks, have made this activity more and more difficult showing some limits of the most recent multi-core capture systems used today. This paper has the purpose to describe the main technologies used in a generic capture system, to identify its possible limits, to diagnose its causes and to discover the possible solutions that must be adopted

Predicting student academic performance by means of associative classification

The Learning Analytics community has recently paid particular attention to early predict learners’ performance. An established approach entails training classification models from past learner-related data in order to predict the exam success rate of a student well before the end of the course. Early predictions allow teachers to put in place targeted actions, e.g., supporting at-risk students to avoid exam failures or course dropouts. Although several machine learning and data mining solutions have been proposed to learn accurate predictors from past data, the interpretability and explainability of the best performing models is often limited. Therefore, in most cases, the reasons behind classifiers’ decisions remain unclear. This paper proposes an Explainable Learning Analytics solution to analyze learner-generated data acquired by our technical university, which relies on a blended learning model. It adopts classification techniques to early predict the success rate of about 5000 students who were enrolled in the first year courses of our university. It proposes to apply associative classifiers at different time points and to explore the characteristics of the models that led to assign pass or fail success rates. Thanks to their inherent interpretability, associative models can be manually explored by domain experts with the twofold aim at validating classifier outcomes through local rule-based explanations and identifying at-risk/successful student profiles by interpreting the global rule-based model. The results of an in-depth empirical evaluation demonstrate that associative models (i) perform as good as the best performing classification models, and (ii) give relevant insights into the per-student success rate assignments

Pasture Land Management System Decision Support Software

Controlled or rotational grazing provides benefits to producers and society through profitable and sound management of grazing land and livestock. Pasture land management system (PLMS) is a decision support system developed to help university, government, and professionals provide technical pasture management assistance to beef and dairy producers. The PLMS focuses on the balance between seasonal forage supply and nutrient demand in a dairy or beef cattle operation. It allows users to explore and compare alternatives (dividing fields into multiple paddocks, changing stocking rates, and forage species) through a visual display and embedded simulation. Users enter a description of the farm by drawing a map. Maps can be drawn freehand, traced over a scanned image, or GIS data may be incorporated. Once map and field data are entered the grazing options are specified via input screens. Grazing systems can be easily compared without economic risk and with almost immediate feedback on how these alternative systems affect variables like milk production and pounds of beef sold. PLMS serves as both an educational tool and a strategic planning tool for evaluating alternative grazing operations and management related investments (website: http://clic.cses.vt.edu/PLMS/)

Experimenting MOC & MOOC in technical university

Negli ultimi dieci anni l’ICT ha prodotto una rapidissima evoluzione degli strumenti a disposizione della didattica, che hanno creato una discontinuità nel contesto sociale e nella sfera individuale. La rottura del vincolo spazio temporale e la disponibilità di nuovi canali comunicativi a disposizione di tutti hanno segnato un punto di rottura che ha cambiato decisamente i ruoli nei processi formativi: il docente non è più il titolare unico della conoscenza, ma diventa un mediatore, una guida nell’accesso alla conoscenza. Dagli anni ’90 Il Politecnico di Torino ha sperimentato diversi scenari di didattica a distanza, sviluppando ed adottando strumenti e metodologie adatte alla rapida evoluzione degli scenari educativi, passando da modelli FAD tradizionali, a modelli ibridi (blended) fino ad approcciare i nuovi paradigmi MOOC. Negli ultimi anni oltre ai tradizionali canali di fruizione, sono stati realizzati nuovi paradigmi di accesso mediante dispositivi mobili. Verranno delineati gli aspetti qualitativi e quantitativi di questa nuova modalità sia dal punto di vista tecnologico che didattico e cooperativo

VR@Polito: the virtual reality initiative of Politecnico di Torino – the experience of the Virtual tour for foreign students

Immersive content overcomes traditional multimedia one-way communication, encouraging visitor participation, combining 360° visuals with interaction and movement. Virtual Tours evoke emotions in a virtual reality, augmented with additional multimedia information: an amplified experience where the prospect student not only sees the place but he or she feels to be there and can preview what his or her life will be once there. Developed by VR@Polito, The Virtual Reality Initiative of Politecnico di Torino, PoliTour takes its origin in a Master Degree Thesis in the Departement of Control and Computer Engineering: it is the «virtual replica» of the actual tour that the incoming students actually have with Incoming Students Office when they arrive at Politecnico. Paper presents the experience of the virtual tour and discusses the growing role of VR and AR in research and education: the use of a such disrupting technology in engineering, like in all the fields of knowledge, requires that technical schools and universities provide the tools and the skills to understand and to be leader in this new technological environment

Predicting ambulatory capacity in Parkinson's disease to analyze progression, biomarkers, and trial design

Background: In Parkinson's disease (PD), gait and balance is impaired, relatively resistant to available treatment and associated with falls and disability. Predictive models of ambulatory progression could enhance understanding of gait/balance disturbances and aid in trial design. Objectives: To predict trajectories of ambulatory abilities from baseline clinical data in early PD, relate trajectories to clinical milestones, compare biomarkers, and evaluate trajectories for enrichment of clinical trials. Methods: Data from two multicenter, longitudinal, observational studies were used for model training (Tracking Parkinson's, n = 1598) and external testing (Parkinson's Progression Markers Initiative, n = 407). Models were trained and validated to predict individuals as having a “Progressive” or “Stable” trajectory based on changes of ambulatory capacity scores from the Movement Disorders Society Unified Parkinson's Disease Rating Scale parts II and III. Survival analyses compared time-to-clinical milestones and trial outcomes between predicted trajectories. Results: On external evaluation, a support vector machine model predicted Progressive trajectories using baseline clinical data with an accuracy, weighted-F1 (proportionally weighted harmonic mean of precision and sensitivity), and sensitivity/specificity of 0.735, 0.799, and 0.688/0.739, respectively. Over 4 years, the predicted Progressive trajectory was more likely to experience impaired balance, loss of independence, impaired function and cognition. Baseline dopamine transporter imaging and select biomarkers of neurodegeneration were significantly different between predicted trajectory groups. For an 18-month, randomized (1:1) clinical trial, sample size savings up to 30% were possible when enrollment was enriched for the Progressive trajectory versus no enrichment. Conclusions: It is possible to predict ambulatory abilities from clinical data that are associated with meaningful outcomes in people with early PD. © 2023 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society

Wild birds of the Italian Middle Ages: diet, environment and society

Wild birds are intrinsically associated with our perception of the Middle Ages. They often feature in heraldic designs, paintings, and books of hours; few human activities typify the medieval period better than falconry. Prominent in medieval iconography, wild birds feature less frequently in written sources (as they were rarely the subject of trade transactions or legal documents) but they can be abundant in archaeological sites. In this paper we highlight the nature of wild bird exploitation in Italian medieval societies, ranging from their role as food items to their status and symbolic importance. A survey of 13 Italian medieval sites corresponding to 19 ‘period sites’, dated from the fifth to the fifteenth centuries, reveals the occurrence of more than 100 species (certainly an under-estimate of the actual number). Anseriformes and Columbiformes played a prominent role in the mid- and late medieval Italian diet, though Passeriformes and wild Galliformes were also important. In the late Middle Ages, there is an increase in species diversity and in the role of hunting as an important marker of social status