This paper presents a new application of logic programming to a real-life problem in hydraulic engineering. The work is developed as a collaboration of computer scientists and hydraulic engineers, and applies Constraint Logic Programming to solve a hard combinatorial problem. This application deals with one aspect of the design of a water distribution network, i.e., the valve isolation system design.We take the formulation of the problem by Giustolisi and Savić (2008) and show how, thanks to constraint propagation, we can get better solutions than the best solution known in the literature for the Apulian distribution network.We believe that the area of the so-called hydroinformatics can benefit from the techniques developed in Constraint Logic Programming and possibly from other areas of logic programming, such as Answer Set Programming.
Business organizations achieve their mission by performing a number of processes. These span from simple sequences of actions to complex structured sets of activities with complex interrelation among them. The field of Business Processes Management studies how to describe, analyze, preserve and improve processes. In particular the subfield of Process Mining aims at inferring a model of the processes from logs (i.e. the collected records of performed activities).\ud Moreover, processes can change over time to reflect mutated conditions, therefore it is often necessary to update the model. We call this activity Incremental Process Mining. To solve this problem, we modify the process mining system DPML to obtain IPM (Incremental Process Miner), which employs a subset of the SCIFF language to represent models and adopts techniques developed in Inductive Logic Programming to perform theory revision. The experimental results show that is more convenient to revise a theory rather than learning a new one from scratch
Although sometimes it is necessary, no one likes to stay in a hospital, and patients who need to stay in bed but do not require constant medical surveillance prefer their own bed at home. At the same time, a patient in a hospital has a high cost for the community, that is not acceptable if the patient needs service only a few minutes a day. For these reasons, the current trend in Europe and North-America is to send nurses to visit patients at their home: this choice reduces costs for the community and gives better quality of life to patients. The challenge is to deliver the service in a cost effective manner without a detriment of the service quality. These social and health management issues have interesting implications from the mathematical viewpoint, introducing a challenging combinatorial optimization problem. The problem consists in assigning patients' services to traveling nurses and defining the nurse itineraries so that the following optimization aspects are considered: the nurse workloads (including service as well as travel time) are balanced, patients are preferentially served by a single nurse or just a few ones, and the overall travel time is minimized. These objectives are somehow conflicting and a reasonable trade off must be found. The complexity of the problem calls for suitable optimization-based algorithmic support to decisions, in particular in the perspective of an increasing diffusion of the service.This problem is known in the literature as the Home Health Care (HHC) problem. In this paper, we address the HHC problem in the municipality of Ferrara, a mid-sized city in the North of Italy. The problem is currently solved by hand, starting from a partitioning of patients based on predefined zones. We describe a Constraint Programming model that solves the HHC problem, and show significant improvements with respect to the current manual solution. those resources can be spent for providing a better service to other patients. Moreover, patients perceive a higher quality of life when they stay at home, with their dear ones, and feel their illness more similar to a "normal" life situation. This reduces depression risk for the patient, and improves rehabilitation rate. Indeed, high quality home health care following hospital dismissal has proved essential in reducing hospital readmissions, if able to cope with preventable complications. Therefore, it is crucial to deliver the service in a cost effective manner while not deteriorating service quality. Arguments in favor of home health care and how to re-
Biomass power plants are very promising for reducing carbon oxides emissions, because they provide energy\ud with a carbon-neutral process. Biomass comes from trees and vegetables, so they provide a renewable type\ud of energy. However, biomass plants location, along with their provisioning basins, are heavily regulated by\ud economical aspects, often without careful consideration of their environmental footprint. For example, some\ud Italian biomass plants import from overseas palm-tree oil that is economically convenient. However, the\ud energy consumed for the oil transportation is definitely greater than the energy produced by the palm-tree\ud oil burning. In this way biomass power plants turn out to be environmentally inefficient, even if they produce\ud renewable energy.\ud We propose an Integer Linear Programming approach for defining the energy and cost-efficient biomass\ud plant location along with the corresponding provisioning basin. In addition, the model enables to evaluate\ud existing plants and their energy and cost efficiency. Our study is based on real data gathered in the Emilia-Romagna region of Italy.\ud Finally, this optimization tool is just a small part of a wider perspective that is aimed to define decision\ud support tools for the improvement of regional planning and its precise strategic environmental assessment
In Semantic Web technologies, searching for a service means to identify components that can potentially satisfy the user needs in terms of outputs and effects (discovery), and that, when invoked by the customer, can fruitfully interact with her (contracting). In this paper, we present an application framework that encompasses both the discovery and the contracting steps, in a unified search process. In particular, we accommodate service discovery by ontologybased reasoning, and contracting by automated reasoning about policies published in a formal language. To this purpose, we consider a formal approach grounded on Computational Logic, and Abductive Logic Programming in particular. We propose a framework, called SCIFF Reasoning Engine, able to establish, by ontological and abductive reasoning, if a semantic web service and a requester can fruitfully inter-operate, taking as input the behavioural interfaces of both the participants, and producing as output a sort of a contract.
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