QoS-aware service composition is challenging due to a high number of QoS attributes, component services, and candidate services. Realistic service composition applications operate in uncertain environments where QoS values may change dynamically. Moreover, user requirements on QoS attributes should be considered, and their different nature can make it difficult to express them by adopting relative weights. Reinforcement Learning is proposed as a viable approach in order to deal with the complexity and variability of the environment. In this paper, we propose a novel approach that integrates traditional reinforcement learning with a norm-based paradigm to consider cases where component services may have a different number and types of QoS attributes. In such a way, it is possible to consider additional local requirements that may hold only for specific service components still pursuing a global optimization. Norms allow using a uniform formalism to express qualitative and quantitative as well as hard and soft user requirements. The approach has been tested on a real dataset of 2500 web services showing its performance, scalability, and adaptability properties.

Typical cruise-line itineraries are planned more than a year in advance, so it is possible to know how many passengers arrive in advance months ahead, as well as when they leave and for how long they stay. Nevertheless, cruise passengers are often responsible of what is called “tourism crowding” that has a beneficial economic outcome for a destination, but often at the cost of increment of city traffic, overloading of the public transportation means and discomfort generated for residents. So, cruise tourism requires planning and management that takes into account also port city destinations factors. In this paper, we present a Deep Reinforcement Learning based planner for the onshore touristic itineraries and the intelligent distribution of cruise passengers in a city. The aim is to maximise the number of touristic attraction locations visited during a tour by avoiding the overcrowding of the touristic attraction locations. The planner is able to compose onshore touristic itineraries meeting the constraint given within the time window available for the cruise passengers, by taking into account the number of attraction locations available in the city together with dynamic parameters as their reception capacity and the time needed to go from one attraction to another.

A new algorithm is introduced to compute the curve skeleton of 3D objects by using the notion of local convexity. The centers of maximal balls detected on the distance transform of the object are filtered to select as anchor points only those located on sharp local convexities of the object's boundary. Then, the skeleton is obtained by means of topology preserving removal operations. Pruning is finally accomplished to remove from the skeleton scarcely significant peripheral branches.

A new pruning algorithm is introduced to remove peripheral branches of scarce relevance from the curve skeleton of 3D objects, while keeping the more relevant branches untouched. The algorithm does not require fine tuning of the parameters involved in the criteria suggested to evaluate branch significance and, in the average, produces satisfactory results.

The distance labeled curve skeleton of a 3D object is used to guide the decomposition of the object into disjoint parts. To this aim, the skeleton is polygonally approximated by taking into account spatial coordinates and distance values of its voxels. The obtained skeleton segments are characterized by the absence of significant changes of curvature. Moreover, along each skeleton segment distance values are constant or show a linearly changing trend. Each segment can be interpreted as the spine of a simple part, which is characterized by the absence of significant curvature changes along its boundary, and by local thickness that is constant or evolves linearly along the part. By using exclusively the spatial coordinates and distance values of the vertices of the spines, quantitative information on shape, size, position and orientation of the corresponding simple parts can be obtained. Alternative decompositions of the object can be computed by selecting different values for the threshold used during polygonal approximation of the skeleton. Some criteria are also discussed for the selection of optimal threshold values originating approximated skeletons having a small number of segments, but still producing decompositions rather well adapting the input object boundary.

A distance-driven method to compute the surface and curve skeletons of 3D objects in voxel images is described. The method is based on the use of the <3,4,5> weighted distance transform, on the detection of anchor points, and on the application of topology preserving removal operations. The obtained surface and curve skeletons are centered within the object, have the same topology as the object, and have unit thickness. The object can be almost completely recovered from the surface skeleton since this includes almost all of the centers of maximal balls of the object. Hence, the surface skeleton is a faithful representation. In turn, though only partial recovery is possible from the curve skeleton, this still provides an appealing representation of the object.

A method to decompose a complex 3D object into simpler parts is presented, based on a suitable partition of the curvilinear skeleton of the object. The curvilinear skeleton is divided into subsets, by taking into account the regions of influence that can be associated with its branch points. The obtained subsets are then used to recover the parts into which the object can be decomposed.

A method to compute a linear medial representation of a complex surface in the 3D discrete space is presented. The method involves voxel classification, surface labeling, anchor point detection, and voxel removal.

The repeated application of topology preserving reduction operations to a gray-tone digital image produces a homotopic image including a set S which has graphlike structure and may be regarded as a stylized version of the foreground, when it is perceived as an elongated subset of the image. To improve the capability of S to represent the foreground in a perceptually appealing way, it is convenient to modify some of the arcs of S by removing part or all of them. This regularization of S is discussed in the paper with respect to different significance measures for arc points, which allow an evaluation of the saliency of each arc. We deal with two types of regularization criteria, which are respectively applied while examining the arcs from end points and from normal points. Specific criteria depend on parameters which are allowed to vary within certain ranges and should be tuned with respect to the application at hand. Both types of criteria are concerned with the closeness of an arc to the part of the background surrounding it, but the former takes also into account the region elongation, while the latter is concerned with the indentations possibly present in the profile of the arc. Experimental work has been carried out on gray-tone images including neurons, and some results are shown.

Reduction operators iteratively applied to gray-tone pictures cause dilation of the regions, the gray-value of which is locally minimal, so that a gray-tone picture with no distinction between foreground and background is transformed into a set of bottom regions separated by ridge lines. The set of ridge lines can be understood as the skeleton of what is perceived as foreground. We describe a two-subiteration parallel skeletonization algorithm employing new reduction operators which are based on the nonridge point condition and are topology preserving. The performance of the algorithm is discussed, in particular with respect to certain critical configurations, and experimental work is reported to evaluate the thinning capability of the proposed reduction operators.

Lowering operations play a key role when skeletonizing a gray-tone picture. We define ridge points in a 3/spl times/3 neighborhood, and discuss the computational advantage obtained when lowering is accomplished by parallel operations based on a non-ridge point condition rather than on a simple point condition. Two parallel algorithms are given, respectively characterized by four subiterations and two subiterations.