Multi-target tracking on confidence maps: An application to people tracking

We propose a generic online multi-target track-before-detect (MT-TBD) that is applicable on confidence maps used as observations. The proposed tracker is based on particle filtering and automatically initializes tracks. The main novelty is the inclusion of the target ID in the particle state, enabling the algorithm to deal with unknown and large number of targets. To overcome the problem of mixing IDs of targets close to each other, we propose a probabilistic model of target birth and death based on a Markov Random Field (MRF) applied to the particle IDs. Each particle ID is managed using the information carried by neighboring particles. The assignment of the IDs to the targets is performed using Mean-Shift clustering and supported by a Gaussian Mixture Model. We also show that the computational complexity of MT-TBD is proportional only to the number of particles. To compare our method with recent state-of-the-art works, we include a postprocessing stage suited for multi-person tracking. We validate the method on real-world and crowded scenarios, and demonstrate its robustness in scenes presenting different perspective views and targets very close to each other.     

Tensor Clustering for Rendering Many‐Light Animations

Rendering animations of scenes with deformable objects, camera motion, and complex illumination, including indirect lighting and arbitrary shading, is a long‐standing challenge. Prior work has shown that complex lighting can be accurately approximated by a large collection of point lights. In this formulation, rendering of animation sequences becomes the problem of efficiently shading many surface samples from many lights across several frames. This paper presents a tensor formulation of the animated many‐light problem, where each element of the tensor expresses the contribution of one light to one pixel in one frame. We sparsely sample rows and columns of the tensor, and introduce a clustering algorithm to select a small number of representative lights to efficiently approximate the animation. Our algorithm achieves efficiency by reusing representatives across frames, while minimizing temporal flicker. We demonstrate our algorithm in a variety of scenes that include deformable objects, complex illumination and arbitrary shading and show that a surprisingly small number of representative lights is sufficient for high quality rendering. We believe out algorithm will find practical use in applications that require fast previews of complex animation.     

Routing and resource optimization in service overlay networks

Service Overlay Networks (SONs) create a virtual topology on top of the Internet and provide end-to-end quality of service guarantees without requiring support by the underlying network.The optimization of the resources utilized by an SON is a fundamental issue for an overlay operator owing to the costs involved and the need to satisfy user requirements. Careful decisions are necessary to provide enough capacity to overlay links, to route traffic, to assign users to access nodes and to deploy overlay nodes.In this paper, we propose two mathematical programming models for the user assignment problem, the traffic routing optimization and the dimensioning of the capacity reserved on overlay links in SONs. The first model minimizes the SON installation cost while providing full access to all users. The second model maximizes the SON profit by selecting which users to serve, based on the expected gain, and taking into consideration budget constraints of the SON operator. Moreover, we extend these models to include the optimization of the number and position of overlay nodes.We provide the optimal solutions of the proposed SON design formulations on a set of realistic-size instances and discuss the effect of different parameters on the characteristics of the planned networks. Numerical results show that the proposed approach is able to solve the problem to the optimum even for large-scale networks.     

gRosSo: mining statistically robust patterns from a sequence of datasets

Knowledge and Information Systems - Pattern mining is a fundamental data mining task with applications in several domains. In this work, we consider the scenario in which we have a sequence of...     

Sorafenib delivery nanoplatform based on superparamagnetic iron oxide nanoparticles magnetically targets hepatocellular carcinoma

Currently,sorafenib is the only systemic therapy capable of increasing overall survival of hepatocellular carcinoma patients.Unfortunately,its side effects,particularly its overall toxicity,limit the therapeutic response that can be achieved.Superparamagnetic iron oxide nanoparticles (SPIONs) are very attractive for drug delivery because they can be targeted to specific sites in the body through application of a magnetic field,thus improving intratumoral accumulation and reducing adverse effects.Here,nanoformulations based on polyethylene glycol modified phospholipid micelles,loaded with both SPIONs and sorafenib,were successfully prepared and thoroughly investigated by complementary techniques.This nanovector system provided effective drug delivery,had an average hydrodynamic diameter of about 125 nm,had good stability in aqueous medium,and allowed controlled drug loading.Magnetic analysis allowed accurate determination of the amount of SPIONs embedded in each micelle.An in vitro system was designed to test whether the SPION micelles can be efficiently held using a magnetic field under typical flow conditions found in the human liver.Human hepatocellular carcinoma (HepG2) cells were selected as an in vitro system to evaluate tumor cell targeting efficacy of the superparamagnetic micelles loaded with sorafenib.These experiments demonstrated that this delivery platform is able to enhance sorafenib's antitumor effectiveness by magnetic targeting.The magnetic nanovectors described here represent promising candidates for targeting specific hepatic tumor sites,where selective release of sorafenib can improve its efficacy and safety profile.     

Do you really mean what you actually enforced?

In their works on the theoretical side of Polymer, Ligatti and his co-authors have identified a new class of enforcement mechanisms based on the notion of edit automata that can transform sequences and enforce more than simple safety properties. We show that there is a gap between the edit automata that one can possibly write (e.g., by Ligatti et?al in their IJIS running example) and the edit automata that are actually constructed according the theorems from Ligatti??s IJIS paper or from Talhi et?al. ??Ligatti??s automata?? are just a particular kind of edit automata. Thus, we re-open a question which seemed to have received a definitive answer: you have written your security enforcement mechanism (aka your edit automata); does it really enforce the security policy you wanted?     

Experimental evaluation of pheromone models in ACOPlan

In this paper the system ACOPlan for planning with non uniform action cost is introduced and analyzed. ACOPlan is a planner based on the ant colony optimization framework, in which a colony of planning ants searches for near optimal solution plans with respect to an overall plan cost metric. This approach is motivated by the strong similarity between the process used by artificial ants to build solutions and the methods used by state?Cbased planners to search solution plans. Planning ants perform a stochastic and heuristic based search by interacting through a pheromone model. The proposed heuristic and pheromone models are presented and compared through systematic experiments on benchmark planning domains. Experiments are also provided to compare the quality of ACOPlan solution plans with respect to state of the art satisficing planners. The analysis of the results confirm the good performance of the Action?CAction pheromone model and points out the promising performance of the novel Fuzzy?CLevel?CAction pheromone model. The analysis also suggests general principles for designing performant pheromone models for planning and further extensions of ACOPlan to other optimization models.     

Knowledge Management in Locating the Patient in an Emergency Medical Service in Italy

This study examines an Emergency Medical Service in order to analyze the composite set of activities and instruments directed at locating the patient. The good management of information about the location of the emergency is highly relevant for a reliable rescue service, but this information depends on knowledge of the territory that is socially distributed between EMS operators and callers. Accordingly, the decision-making process often has to go beyond the emergency service protocols, engaging the operator in undertaking an open negotiation in order to transform the caller’s role from layman to “co-worker”. The patient’s location turns out to be an emerging phenomenon, collaborative work based on knowledge management involving two communities—the callers and the EMS operators—that overlap partially. Drawing examples from emergency calls, the study analyzes the practice of locating a patient as a complex and multi-layered process, highlighting the role played by new and old technologies (the information system and the paper maps) in this activity. We argue that CSCW technologies enable the blended use of different kinds of instruments and support an original interconnection between the professional localization systems and the public’s way of defining a position.     

Product interface design: A participatory approach based on virtual reality

The usability of the user interface is a key aspect for the success of several industrial products. This assumption has led to the introduction of numerous design methodologies addressed to evaluate the user-friendliness of industrial products. Most of these methodologies follow the participatory design approach to involve the user in the design process. Virtual Reality is a valid tool to support Participatory Design, because it facilitates the collaboration among designers and users.The present study aims to evaluate the feasibility and the efficacy of an innovative Participatory Design approach where Virtual Reality plays a ‘double role’: a tool to evaluate the usability of the virtual product interface, and a communication channel that allows users to be directly involved in the design process as co-designers.In order to achieve these goals, we conducted three experiments: the purpose of the first experiment is to determine the influence of the virtual interface on the usability evaluation by comparing “user–real product” interaction and “user–virtual product” interaction. Subsequently, we tested the effectiveness of our approach with two experiments involving users (directly or through their participation in a focus group) in the redesign of a product user interface. The experiments were conducted with two typologies of consumer appliances: a microwave oven and a washing machine.