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2 Annals of Computer Science and Information Systems

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Pick-up & Deliver in Maintenance Management of Renewable Energy Power Plants

Vincenza Carchiolo, Francesco Di Dio, Longheu Alessandro, Malgeri Michele, Mangioni Giuseppe, Romeo Antonio, Trapani Natalia

Annals of Computer Science and Information Systems

2020

Vol. 21

579--585

Logistic optimization is a strategic element in many industrial processes, given that an optimized logistics makes the processes more efficient. A relevant case, in which the optimization of logistics can be decisive, is the maintenance in a Wind Farm where it can lead directly to a saving of energy cost. Wind farm maintenance presents, in fact, significant logistical challenges. They are usually distributed throughout the territory and also located at considerable distances from each other, they are generally found in places far from uninhabited centers and sometimes difficult to reach and finally spare parts are rarely available on the site of the plant itself. In this paper, we will study the problem concerning the optimization of maintenance logistics of wind plants based on the use of specific vehicle routing optimization algorithms. In particular a pickup-and- delivery algorithm with time-window is adopted to satisfy the maintenance requests of these plants, reducing their management costs. The solution was applied to a case study in a renewable energy power plant. Results time reduction and simplification and optimization obtained in the real case are discussed to evaluate the effectiveness and efficiency of the adopted approach.

Medical prescription classification: a NLP-based approach

Carchiolo Vincenza, Longheu Alessandro, Reitano Giuseppa, Zagarella Luca

Annals of Computer Science and Information Systems

2019

Vol. 18

605--609

The digitization of healthcare data has been consolidated in the last decade as a must to manage the vast amount of data generated by healthcare organizations. Carrying out this process effectively represents an enabling resource that will improve healthcare services provision, as well as on-the-edge related applications, ranging from clinical text mining to predictive modelling, survival analysis, patient similarity, genetic data analysis and many others. The application presented in this work concerns the digitization of medical prescriptions, both to provide authorization for healthcare services or to grant reimbursement for medical expenses. The proposed system first extract text from scanned medical prescription, then Natural Language Processing and machine learning techniques provide effective classification exploiting embedded terms and categories about patient/- doctor personal data, symptoms, pathology, diagnosis and suggested treatments. A REST ful Web Service is introduced, together with results of prescription classification over a set of 800K+ of diagnostic statements.