Search results for "Artificial"
showing 10 items of 7394 documents
Tecniche di rilevamento architettonico: innovazione e integrazione
2008
In particolare si pone l’attenzione sulle problematiche della conservazione e del restauro dell’architettura dei primi decenni del ‘900 con nuove tecnologie, approfondendo alcune tipologie e problematiche di degrado più presenti sul materiale. Si propone un caso specifico di intervento su un edificio storico al fine di valutarne lo stato di salute e la durabilità del conglomerato cementizio armato tradizionale operando dei confronti con i nuovi calcestruzzi. Documentando con schede di rilievo tipologico-funzionale e tecnologico e con quadri fessurativi, si presentano i primi risultati delle indagini e delle prove distruttive e non-distruttive su alcune parti più rappresentative delle divers…
Metodologie di rilievo metrico e diagnosi materica in edifici storici. Casi studio.
2010
Ancora oggi manca una codificazione di regole da suggerire perché vengano seguite con puntualità per ripristinare e per risanare i monumenti e gli edifici di interesse storico risalenti ai primi anni del secolo scorso, realizzati in calcestruzzo o contenenti parti ornamentali ma anche funzionali in calcestruzzo. E’ prevalsa l’abitudine di trattare questi ultimi come se fossero costruiti secondo le regole dell’odierna tecnica delle costruzioni, senza considerare dunque le differenti caratteristiche che essi presentano a partire dalle metodologie utilizzate per la produzione dei materiali, fino ad arrivare alle differenze di calcolo progettuale. Se da un lato dunque sembra corretto l’utilizzo…
PIETRE ARTIFICIALI CEMENTIZIE NEGLI EDIFICI STORICI DI PALERMO. PROPOSTE DI RESTAURO CON TECNOLOGIE E CALCESTRUZZI INNOVATIVI.
2008
La ricerca approfondisce lo studio delle pietre artificiali cementizie presenti negli edifici realizzati a Palermo, tra la fine dell'ottocento ed i primi trent'anni del novecento, con l'obiettivo di proporre metodi, tecnologie di intervento e materiali innovativi per il restauro conservativo di queste.
IoT -based adversarial attack's effect on cloud data platform services in a smart building context
2020
IoT sensors and sensor networks are widely employed in businesses. The common problem is a remarkable number of IoT device transactions are unencrypted. Lack of correctly implemented and robust defense leaves the organization's IoT devices vulnerable to numerous cyber threats, such as adversarial and man-in-the-middle attacks or malware infections. A perpetrator can utilize adversarial examples when attacking machine learning (ML) models, such as convolutional neural networks (CNN) or deep neural networks (DNN) used, e.g., in DaaS cloud data platform service of smart buildings. DaaS cloud data platform's function in this study is to connect data from multiple IoT sensors, databases, private…
Active lighting applied to three-dimensional reconstruction of specular metallic surfaces by polarization imaging
2006
International audience; In the field of industrial vision, the three-dimensional inspection of highly reflective metallic objects is still a delicate task. We deal with a new automated three-dimensional inspection system based on polarization analysis. We first present an extension of the shape-from-polarization method for dielectric surfaces to metallic surfaces. Then, we describe what we believe to be a new way of solving the ambiguity concerning the normal orientation with an active lighting system. Finally, applications to shape-defect detection are discussed, and the efficiency of the system to discriminate defects on specular metallic objects made by stamping and polishing is presente…
Tekoälyn hyödyntäminen lääkehuollossa
2018
Power Line Monitoring through Data Integrity Analysis with Q-Learning Based Data Analysis Network
2022
To monitor and handle big data obtained from electrical, electronic, electro-mechanical, and other equipment linked to the power grid effectively and efficiently, it is important to monitor them continually to gather information on power line integrity. We propose that data transmission analysis and data collection from tools like digital power meters may be used to undertake predictive maintenance on power lines without the need for specialized hardware like power line modems and synthetic data streams. Neural network models such as deep learning may be used for power line integrity analysis systems effectively, safely, and reliably. We adopt Q-learning based data analysis network for anal…
Combining hyperspectral UAV and multispectral Formosat-2 imagery for precision agriculture applications
2014
Remote sensing is a key tool for precision agriculture applications as it is capable of capturing spatial and temporal variations in crop status. However, satellites often have an inadequate spatial resolution for precision agriculture applications. High-resolution Unmanned Aerial Vehicles (UAV) imagery can be obtained at flexible dates, but operational costs may limit the collection frequency. The current study utilizes data fusion to create a dataset which benefits from the temporal resolution of Formosat-2 imagery and the spatial resolution of UAV imagery with the purpose of monitoring crop growth in a potato field. The correlation of the Weighted Difference Vegetation Index (WDVI) from …
Explainable AI for Industry 4.0 : Semantic Representation of Deep Learning Models
2022
Artificial Intelligence is an important asset of Industry 4.0. Current discoveries within machine learning and particularly in deep learning enable qualitative change within the industrial processes, applications, systems and products. However, there is an important challenge related to explainability of (and, therefore, trust to) the decisions made by the deep learning models (aka black-boxes) and their poor capacity for being integrated with each other. Explainable artificial intelligence is needed instead but without loss of effectiveness of the deep learning models. In this paper we present the transformation technique between black-box models and explainable (as well as interoperable) …
Interactively Learning the Preferences of a Decision Maker in Multi-objective Optimization Utilizing Belief-rules
2020
Many real life problems can be modelled as multiobjective optimization problems. Such problems often consist of multiple conflicting objectives to be optimized simultaneously. Multiple optimal solutions exist to these problems, and a single solution cannot be said to be the best without preferences given by a domain expert. Preferences can be used to find satisfying solutions: optimal solutions, which best match the expert’s preferences. To model the preferences of the expert, and aid him/her in finding satisfying solutions, a novel method is proposed. The method utilizes machine learning combined with belief-rule based systems to adaptively train a belief rule based system to learn a domai…