A survey of urban vehicular sensing platforms

Vehicular sensing where vehicles on the road continuously gather, process, and share location-relevant sensor data (e.g., road condition, traffic flow) is emerging as a new network paradigm for sensor information sharing in urban environments. Recently, smartphones have also received a lot of attention for their potential as portable vehicular urban sensing platforms, as they are equipped with a variety of environment and motion sensors (e.g., audio/video, accelerometer, and GPS) and multiple wireless interfaces (e.g., WiFi, Bluetooth and 2/3G). The ability to take a smartphone on board a vehicle and to complement the sensors of the latter with advanced smartphone capabilities is of immense interest to the industry. In this paper we survey recent vehicular sensor network developments and identify new trends. In particular we review the way sensor information is collected, stored and harvested using inter-vehicular communications (e.g., mobility-assist mobility-assisted dissemination and geographic storage), as well using the infrastructure (e.g., centralized and distributed storage in the wired Internet). The comparative performance of the various sensing schemes is important to us. Thus, we review key results by carefully examining and explaining the evaluation methodology, in the process gaining insight into vehicular sensor network design. Our comparative study confirms that system performance is impacted by a variety of factors such as wireless access methods, mobility, user location, and popularity of the information.     

Generic Self-calibration of Central Cameras from Two Rotational Flows

We address the self-calibration of a smooth generic central camera from only two dense rotational flows produced by rotations of the camera about two unknown linearly independent axes passing through the camera centre. We give a closed-form theoretical solution to this problem, and we prove that it can be solved exactly up to a linear orthogonal transformation ambiguity. Using the theoretical results, we propose an algorithm for the self-calibration of a generic central camera from two rotational flows.     

Time-extended multi-robot coordination for domains with intra-path constraints

Many applications require teams of robots to cooperatively execute tasks. Among these domains are those in which successful coordination must respect intra-path constraints, which are constraints that occur on the paths of agents and affect route planning. This work focuses on multi-agent coordination for disaster response with intra-path precedence constraints, a compelling application that is not well addressed by current coordination methods. In this domain a group of fire truck agents attempt to address fires spread throughout a city in the wake of a large-scale disaster. The disaster has also caused many city roads to be blocked by impassable debris, which can be cleared by bulldozer robots. A high-quality coordination solution must determine not only a task allocation but also what routes the fire trucks should take given the intra-path precedence constraints and which bulldozers should be assigned to clear debris along those routes.     

A decision support system for the diagnosis of melanoma: A comparative approach

Melanoma is the most deathful of all skin cancers and the number of cases grows every year. The extirpation in early phases implies a high degree of survival so it is fundamental to diagnose it as soon as possible. In this paper we present a clinical decision support system for melanoma diagnosis using as input an image set of the skin lesion to be diagnosed. The system analyses the image sequence to extract the affected area, determinates the characteristics which indicate the degree of damage and, according to them, it makes a decision. Several methods of classification are proposed: a multilayered perceptron, a Bayesian classifier and the algorithm of the K nearest neighbours. These methods work independently and also in combination making a collaborative decision support system. The classification rates obtained are around 87%.     

An haptic-based immersive environment for shape analysis and modelling

Currently, the design of aesthetic products is a process that requires a set of activities where digital models and physical mockups play a key role. Typically, these are modified (and built) several times before reaching the desired design, increasing the development time and, consequently, the final product cost. In this paper, we present an innovative design environment for computer-aided design (CAD) surface analysis. Our system relies on a direct visuo-haptic display system, which enables users to visualize models using a stereoscopic view, and allows the evaluation of sectional curves using touch. Profile curves are rendered using an haptic device that deforms a plastic strip, thanks to a set of actuators, to reproduce the curvature of the shape co-located with the virtual model. By touching the strip, users are able to evaluate shape characteristics, such as curvature or discontinuities (rendered using sound), and to assess the surface quality. We believe that future computer-aided systems (CAS)/CAD systems based on our approach will contribute in improving the design process at industrial level. Moreover, these will allow companies to reduce the product development time by reducing the number of physical mockups necessary for the product design evaluation and by increasing the quality of the final product, allowing a wider exploration and comparative evaluation of alternatives in the given time.     

Indoor robot gardening: design and implementation

This paper describes the architecture and implementation of a distributed autonomous gardening system with applications in urban/indoor precision agriculture. The garden is a mesh network of robots and plants. The gardening robots are mobile manipulators with an eye-in-hand camera. They are capable of locating plants in the garden, watering them, and locating and grasping fruit. The plants are potted cherry tomatoes enhanced with sensors and computation to monitor their well-being (e.g. soil humidity, state of fruits) and with networking to communicate servicing requests to the robots. By embedding sensing, computation, and communication into the pots, task allocation in the system is de-centrally coordinated, which makes the system scalable and robust against the failure of a centralized agent. We describe the architecture of this system and present experimental results for navigation, object recognition, and manipulation as well as challenges that lie ahead toward autonomous precision agriculture with multi-robot teams.     

Computational aspects of the expected differential probability of 4-round AES and AES-like ciphers

In this paper we study the security of the Advanced Encryption Standard (AES) and AES-like block ciphers against differential cryptanalysis. Differential cryptanalysis is one of the most powerful methods for analyzing the security of block ciphers. Even though no formal proofs for the security of AES against differential cryptanalysis have been provided to date, some attempts to compute the maximum expected differential probability (MEDP) for two and four rounds of AES have been presented recently. In this paper, we will improve upon existing approaches in order to derive better bounds on the EDP for two and four rounds of AES based on a slightly simplified S-box. More precisely, we are able to provide the complete distribution of the EDP for two rounds of this AES variant with five active S-boxes and methods to improve the estimates for the EDP in the case of six active S-boxes.     

Computing the null space of finite element problems

We present a method for computing the null space of finite element models, including models with equality constraints. The method is purely algebraic; it requires access to the element matrices, but not to the geometry or material properties of the model.Theoretical considerations show that under certain conditions, both the amount of computation and the amount of memory required by our method scale linearly with model size; memory scales linearly but computation scales quadratically with the dimension of the null space. Our experiments confirm this: the method scales extremely well on 3-dimensional model problems. In general, large industrial models do not satisfy all the conditions that the theoretical results assume; however, experimentally the method performs well and outperforms an established method on industrial models, including models with many equality constraints.The accuracy of the computed null vectors is acceptable, but the method is usually less accurate than a more naive (and computationally much more expensive) method.     

A review on cost allocation methods in collaborative transportation

Collaboration in transportation between two or more agents is becoming an important approach to find efficient solutions or plans. Efficiency can be measured in, for example, lower cost or more flexibility. An important aspect of the collaboration is to decide on how to share the benefits—for example, cost, profit, or resources. There are many sharing mechanisms or cost allocations proposed in the literature. Some are based on simple proportional rules and others are based on theoretical concepts found in game theory. We provide a survey on cost allocation methods found in the literature on collaborative transportation, including problems on planning, vehicle routing, traveling salesman, distribution, and inventory. A total of 55 scientific articles compose the main part of the survey, most of them published between 2010 and 2015. We identify more than 40 cost allocation methods used in this stream of literature. We describe the theoretical basis for the main methods as well as the cases where they are used. We also report savings from the collaborations when they are based on industrial data. Some directions for future research are discussed.     

Evaluating the impact of smart technologies on harbor’s logistics via BPMN modeling and simulation

A smart Information and Communication Technology (ICT) enables a synchronized interplay of different key factors, aligning infrastructures, consumers, and governmental policy-making needs. In the harbor’s logistics context, smart ICT has been driving a multi-year wave of growth. Although there is a standalone value in the technological innovation of a task, the impact of a new smart technology is unknown without quantitative analysis methods on the end-to-end process. In this paper, we first present a review of the smart ICT for marine container terminals, and then we propose to evaluate the impact of such smart ICT via business process model and notation (BPMN) modeling and simulation. The proposed approach is discussed in a real-world modeling and simulation analysis, made on a pilot terminal of the Port of Leghorn (Italy).