Surgical simulation practices have witnessed a rapid expansion as an invaluable approach to resid... more Surgical simulation practices have witnessed a rapid expansion as an invaluable approach to resident training in recent years. One emerging way of implementing simulation is the adoption of extended reality (XR) technologies, which enable trainees to hone their skills by allowing interaction with virtual 3D objects placed in either real-world imagery or virtual environments. The goal of the present systematic review is to survey and broach the topic of XR in neurosurgery, with a focus on education. Five databases were investigated, leading to the inclusion of 31 studies after a thorough reviewing process. Focusing on user performance (UP) and user experience (UX), the body of evidence provided by these 31 studies showed that this technology has, in fact, the potential of enhancing neurosurgical education through the use of a wide array of both objective and subjective metrics. Recent research on the topic has so far produced solid results, particularly showing improvements in young ...
Questo articolo scientifico sostiene la tesi che un algoritmo di controllo, facente uso di intell... more Questo articolo scientifico sostiene la tesi che un algoritmo di controllo, facente uso di intelligenza artificiale, per poter essere efficiente necessiti di sfruttare le simmetrie integrate in ogni manipolatore robotico industrale così che quest'ultimo possa essere ulteriormente caratterizzato ed utilizzato. Il prodotto di questo miglioramento è uno spazio discreto a griglia cilindrica quadridimensionale (4D) che può direttamente sostituire complessi modelli robotici. A* è scelto per il suo ampio utilizzo tra simili algoritmi di ricerca, in modo da studiare i vantaggi e gli svantaggi del controllo di robot industriali tramite la griglia discreta cilindrica 4D. Lo studio mostra che questo approccio consente di controllare un robot senza alcuna conoscenza specifica dei modelli cinematici e dinamici del robot al momento della pianificazione e dell'esecuzione. In effetti, le posizioni dei giunti del robot per ciascuna cella della griglia vengono precalcolate e memorizzate come ...
Industrial processes are mainly based on procedural knowledge that must be continually elicited f... more Industrial processes are mainly based on procedural knowledge that must be continually elicited from experienced operators and learned by novice operators. In the context of Industry 4.0, machines already play a key role in knowledge transfer; however, new models and methods based on the artificial intelligence advances of the past few years need to be developed and applied. The future of human-machine collaboration is not limited to physical applications, but it has the potential to harness both the strength of human skills, experience and the computational power provided by the surrounding machines for truly adaptive industrial processes. The winning recipe is a balance between letting humans exploit their inherent experience and letting machines integrate the missing skills to preserve production standards. This work introduces a procedural knowledge model to be used for the design of industrial and scientific adaptive processes and it paves the way to transforming human-machine collaboration into an efficient solution to make industrial and scientific processes resilient to a constantly changing world.Industriella processer baseras huvudsakligen på den procedurella kunskapen som fortlöpande måste tas fram och anpassas av erfarna operatörer och läras in av nybörjare. Inom ramen för Industri 4.0 spelar maskiner redan en nyckelroll i kunskapsöverföring; dock behöver nya modeller och metoder utvecklas och användas, som baseras på de senaste årens framsteg inom artificiell intelligens. Framtiden för samarbete mellan människa och maskin är inte begränsad till fysiska applikationer, utan den har potential att utnyttja såväl styrkan i mänsklig kompetens och erfarenhet som den beräkningskraft som de omgivande maskinerna tillhandahåller, för att åstadkomma verkligt anpassningsbara industriella processer. Det vinnande receptet är att hitta en balans mellan att låta människor utnyttja sina egna erfarenheter och att låta maskiner tillhandahålla de saknade färdigheterna för att kunna följa produktionsstandarder. I detta arbete introduceras en procedurell kunskapsmodell som kan användas för utformning av industriella och vetenskapliga, anpassningsbara processer och banar väg för att omvandla samarbete mellan människor och maskiner till effektiva lösningar för att göra industriella och vetenskapliga processer följsamma i en ständigt föränderlig värld
This article is a citation review of the publication "A hybridization of genetic algorithms ... more This article is a citation review of the publication "A hybridization of genetic algorithms and fuzzy logic for the single-machine scheduling with flexible maintenance problem under human resource ...
This article argues that despite a citation review is a rarely used research tool, this can be ve... more This article argues that despite a citation review is a rarely used research tool, this can be very useful to assess the impact of new research topics, both from the future research direction and the bibliometric perspectives. An explorative study is presented around the research area marked as Industry 4.0 with the conference paper mentioned in the title of this citation review. Even though the given reference paper is relatively recent, there are already twenty-seven citations listed among three different scholar databases. These are Google Scholar, ResearchGate and Semantic Scholar. In light of this, the article provides a bibliometric confirmation and analysis for the progression of the line of research adopted by de Giorgio et al. in the exploration of non-traditional methods using virtual reality technology and human-robot collaboration for adaptive applications in Industry 4.0. Furthermore, it represents a model for the authors’ self-development and an example of an unconvent...
Distributed and hierarchical models of control are nowadays popular in computational modeling and... more Distributed and hierarchical models of control are nowadays popular in computational modeling and robotics. In the artificial neural network literature, complex behaviors can be produced by composing elementary building blocks or motor primitives, possibly organized in a layered structure. However, it is still unknown how the brain learns and encodes multiple motor primitives, and how it rapidly reassembles, sequences and switches them by exerting cognitive control. In this paper we advance a novel proposal, a hierarchical programmable neural network architecture, based on the notion of programmability and an interpreter-programmer computational scheme. In this approach, complex (and novel) behaviors can be acquired by embedding multiple modules (motor primitives) in a single, multi-purpose neural network. This is supported by recent theories of brain functioning in which skilled behaviors can be generated by combining functional different primitives embedded in “reusable” areas of ...
This article argues that an efficient artificial intelligence control algorithm needs the built-i... more This article argues that an efficient artificial intelligence control algorithm needs the built-in symmetries of an industrial robot manipulator to be further characterized and exploited. The product of this enhancement is a four-dimensional (4D) discrete cylindrical grid space that can directly replace complex robot models. A* is chosen for its wide use among such algorithms to study the advantages and disadvantages of steering the robot manipulator within the 4D cylindrical discrete grid. The study shows that this approach makes it possible to control a robot without any specific knowledge of the robot kinematic and dynamic models at planning and execution time. In fact, the robot joint positions for each grid cell are pre-calculated and stored as knowledge, then quickly retrieved by the pathfinding algorithm when needed. The 4D cylindrical discrete space has both the advantages of the configuration space and the three-dimensional Cartesian workspace of the robot. Since path optim...
This is the version of the code released with the scientific article A. de Giorgio and L. Wang, &... more This is the version of the code released with the scientific article A. de Giorgio and L. Wang, "Artificial Intelligence Control in 4D Cylindrical Space for Industrial Robotic Applications", in IEEE Access, vol. 8, pp. 174833-174844, 2020, doi: 10.1109/ACCESS.2020.3026193.
Obiettivo della mia tesi è studiare come la presenza di circuiti neurali programmabili possa rend... more Obiettivo della mia tesi è studiare come la presenza di circuiti neurali programmabili possa rendere l'apprendimento di differenti comportamenti, da parte di una singola struttura, più efficace. A tal fine, ho messo a confronto due architetture, una programmabile e l'altra non programmabile, come parte di uno scenario robotico appositamente progettato per testare la possibilità di apprendere ed esibire comportamenti multipli. Più in particolare, ho supposto che un robot possa imparare, tramite la sua architettura di controllo, programmabile o meno, a raggiungere, su richiesta, ciascuna delle otto terminazioni differenti di un labirinto costituito da una serie di tre biforcazioni e di dimensioni variabili. Fondamentale, in tale scenario, la necessità per l'architettura di controllo di apprendere, e poi esibire, comportamenti e non semplici traiettorie. In tal modo, ho potuto raccogliere dati sufficienti per realizzare un'opportuna analisi.
In this thesis I demonstrated how a singular neural network can potentially represent the set of ... more In this thesis I demonstrated how a singular neural network can potentially represent the set of more latent neural circuits, able to execute different functions, based on an input encoding so to reprogram their functionality. Such programmable structure, in passing from one behavior to another, does not require further learning procedures, nor any structural modifications. This is ideal to execute quick and reversible transitions such as the ones showed in biological organisms’ behaviors.
Restricted Boltzmann Machines (RBMs) and autoencoders have been used - in several variants - for ... more Restricted Boltzmann Machines (RBMs) and autoencoders have been used - in several variants - for similar tasks, such as reducing dimensionality or extracting features from signals. Even though their structures are quite similar, they rely on different training theories. Lately, they have been largely used as building blocks in deep learning architectures that are called deep belief networks (instead of stacked RBMs) and stacked autoencoders.In light of this, the student has worked on this thesis with the aim to understand the extent of the similarities and the overall pros and cons of using either RBMs, autoencoders or denoising autoencoders in deep networks. Important characteristics are tested, such as the robustness to noise, the influence on training of the availability of data and the tendency to overtrain. The author has then dedicated part of the thesis to study how the three deep networks in exam form their deep internal representations and how similar these can be to each o...
Questo articolo scientifico sostiene la tesi che un algoritmo di controllo, facente uso di intell... more Questo articolo scientifico sostiene la tesi che un algoritmo di controllo, facente uso di intelligenza artificiale, per poter essere efficiente necessiti di sfruttare le simmetrie integrate in ogni manipolatore robotico industrale così che quest’ultimo possa essere ulteriormente caratterizzato ed utilizzato. Il prodotto di questo miglioramento è uno spazio discreto a griglia cilindrica quadridimensionale (4D) che può direttamente sostituire complessi modelli robotici. A* è scelto per il suo ampio utilizzo tra simili algoritmi di ricerca, in modo da studiare i vantaggi e gli svantaggi del controllo di robot industriali tramite la griglia discreta cilindrica 4D. Lo studio mostra che questo approccio consente di controllare un robot senza alcuna conoscenza specifica dei modelli cinematici e dinamici del robot al momento della pianificazione e dell’esecuzione. In effetti, le posizioni dei giunti del robot per ciascuna cella della griglia vengono precalcolate e memorizzate come conoscenza, quindi recuperate rapidamente dall’algoritmo di ricerca di percorso quando necessario. Lo spazio discreto cilindrico 4D presenta sia i vantaggi dello spazio di configurazione che dello spazio di lavoro cartesiano tridimensionale del robot. Poiché l’ottimizzazione del percorso è il nucleo di qualsiasi algortimo di ricerca, incluso A*, la griglia cilindrica 4D fornisce uno spazio di ricerca che può incorporare ulteriori conoscenze sotto forma di proprietà delle celle, inclusa la presenza di ostacoli e l’occupazione volumetrica dell’intero corpo del robot industriale, da usare in applicazioni per l’evitamento degli ostacoli. Il compromesso principale è tra una capacità limitata della conosenza precalcolata nella griglia e la velocità di ricerca del percorso migliore. Questo approccio innovativo incoraggia l’uso di algoritmi di ricerca per applicazioni robotiche industriali, apre la via allo studio di altre simmetrie fisiche presenti in altri modelli di robot e pone le basi per l’applicazione di algoritmi dinamici per l’evitamento degli ostacoli.
In the age of digital manufacturing there is a need to elicit and transfer procedural knowledge b... more In the age of digital manufacturing there is a need to elicit and transfer procedural knowledge between humans and machines. Having proper knowledge is essential in decision-making. The more the knowledge, the better decisions are made. To capture experiences and turn them into knowledge is fundamental in learning processes and knowledge development. Knowledge engineering and knowledge management have been subject for research for decades and several concepts about knowledge and knowledge transfer have been introduced, but a functional approach to exploit knowledge efficiently in manufacturing is still missing. In the era of Industry 4.0, humans and machines must be able to collaborate in such way that both can exploit the best abilities of each other in a manufacturing process. This paper introduces a procedural knowledge process (PKP) approach to capturing and defining unexpected events, while a process step is able to perform its required functions and transfer that information as machine-understandable knowledge about a failure mode. Function blocks (FBs), as per the IEC-61499 standard, have been proposed as a way to achieve distributed process planning in which the manufacturing process can adapt itself to runtime conditions, e.g. machine availability, etc. However, FBs are event-driven systems and the approach is limited to work under well-known runtime conditions, e.g. machine configurations and states, or deviations which are impossible to foresee in advance, for instance the outcome of a process failure mode effects analysis (PFMEA). The PKP introduced in this paper, aims at bridging this gap by integrating at runtime an expert operator's solution based on root cause analysis (RCA) in an FB architecture, making the FB knowledge-driven systems, for further executions of the same without redesigning it. Natural language representations of procedural knowledge blocks (PKBs) allow to transfer procedural knowledge to human operators, i.e. explain the process flow of a machine decision, while machine representations of PKBs allow to embed procedural knowledge that is elicited from expert operators upon unexpected events into the FBs process. The resulting PKP enhances the FBs for smart industrial applications, such as the process planning use case described in this paper.
Surgical simulation practices have witnessed a rapid expansion as an invaluable approach to resid... more Surgical simulation practices have witnessed a rapid expansion as an invaluable approach to resident training in recent years. One emerging way of implementing simulation is the adoption of extended reality (XR) technologies, which enable trainees to hone their skills by allowing interaction with virtual 3D objects placed in either real-world imagery or virtual environments. The goal of the present systematic review is to survey and broach the topic of XR in neurosurgery, with a focus on education. Five databases were investigated, leading to the inclusion of 31 studies after a thorough reviewing process. Focusing on user performance (UP) and user experience (UX), the body of evidence provided by these 31 studies showed that this technology has, in fact, the potential of enhancing neurosurgical education through the use of a wide array of both objective and subjective metrics. Recent research on the topic has so far produced solid results, particularly showing improvements in young ...
Questo articolo scientifico sostiene la tesi che un algoritmo di controllo, facente uso di intell... more Questo articolo scientifico sostiene la tesi che un algoritmo di controllo, facente uso di intelligenza artificiale, per poter essere efficiente necessiti di sfruttare le simmetrie integrate in ogni manipolatore robotico industrale così che quest'ultimo possa essere ulteriormente caratterizzato ed utilizzato. Il prodotto di questo miglioramento è uno spazio discreto a griglia cilindrica quadridimensionale (4D) che può direttamente sostituire complessi modelli robotici. A* è scelto per il suo ampio utilizzo tra simili algoritmi di ricerca, in modo da studiare i vantaggi e gli svantaggi del controllo di robot industriali tramite la griglia discreta cilindrica 4D. Lo studio mostra che questo approccio consente di controllare un robot senza alcuna conoscenza specifica dei modelli cinematici e dinamici del robot al momento della pianificazione e dell'esecuzione. In effetti, le posizioni dei giunti del robot per ciascuna cella della griglia vengono precalcolate e memorizzate come ...
Industrial processes are mainly based on procedural knowledge that must be continually elicited f... more Industrial processes are mainly based on procedural knowledge that must be continually elicited from experienced operators and learned by novice operators. In the context of Industry 4.0, machines already play a key role in knowledge transfer; however, new models and methods based on the artificial intelligence advances of the past few years need to be developed and applied. The future of human-machine collaboration is not limited to physical applications, but it has the potential to harness both the strength of human skills, experience and the computational power provided by the surrounding machines for truly adaptive industrial processes. The winning recipe is a balance between letting humans exploit their inherent experience and letting machines integrate the missing skills to preserve production standards. This work introduces a procedural knowledge model to be used for the design of industrial and scientific adaptive processes and it paves the way to transforming human-machine collaboration into an efficient solution to make industrial and scientific processes resilient to a constantly changing world.Industriella processer baseras huvudsakligen på den procedurella kunskapen som fortlöpande måste tas fram och anpassas av erfarna operatörer och läras in av nybörjare. Inom ramen för Industri 4.0 spelar maskiner redan en nyckelroll i kunskapsöverföring; dock behöver nya modeller och metoder utvecklas och användas, som baseras på de senaste årens framsteg inom artificiell intelligens. Framtiden för samarbete mellan människa och maskin är inte begränsad till fysiska applikationer, utan den har potential att utnyttja såväl styrkan i mänsklig kompetens och erfarenhet som den beräkningskraft som de omgivande maskinerna tillhandahåller, för att åstadkomma verkligt anpassningsbara industriella processer. Det vinnande receptet är att hitta en balans mellan att låta människor utnyttja sina egna erfarenheter och att låta maskiner tillhandahålla de saknade färdigheterna för att kunna följa produktionsstandarder. I detta arbete introduceras en procedurell kunskapsmodell som kan användas för utformning av industriella och vetenskapliga, anpassningsbara processer och banar väg för att omvandla samarbete mellan människor och maskiner till effektiva lösningar för att göra industriella och vetenskapliga processer följsamma i en ständigt föränderlig värld
This article is a citation review of the publication "A hybridization of genetic algorithms ... more This article is a citation review of the publication "A hybridization of genetic algorithms and fuzzy logic for the single-machine scheduling with flexible maintenance problem under human resource ...
This article argues that despite a citation review is a rarely used research tool, this can be ve... more This article argues that despite a citation review is a rarely used research tool, this can be very useful to assess the impact of new research topics, both from the future research direction and the bibliometric perspectives. An explorative study is presented around the research area marked as Industry 4.0 with the conference paper mentioned in the title of this citation review. Even though the given reference paper is relatively recent, there are already twenty-seven citations listed among three different scholar databases. These are Google Scholar, ResearchGate and Semantic Scholar. In light of this, the article provides a bibliometric confirmation and analysis for the progression of the line of research adopted by de Giorgio et al. in the exploration of non-traditional methods using virtual reality technology and human-robot collaboration for adaptive applications in Industry 4.0. Furthermore, it represents a model for the authors’ self-development and an example of an unconvent...
Distributed and hierarchical models of control are nowadays popular in computational modeling and... more Distributed and hierarchical models of control are nowadays popular in computational modeling and robotics. In the artificial neural network literature, complex behaviors can be produced by composing elementary building blocks or motor primitives, possibly organized in a layered structure. However, it is still unknown how the brain learns and encodes multiple motor primitives, and how it rapidly reassembles, sequences and switches them by exerting cognitive control. In this paper we advance a novel proposal, a hierarchical programmable neural network architecture, based on the notion of programmability and an interpreter-programmer computational scheme. In this approach, complex (and novel) behaviors can be acquired by embedding multiple modules (motor primitives) in a single, multi-purpose neural network. This is supported by recent theories of brain functioning in which skilled behaviors can be generated by combining functional different primitives embedded in “reusable” areas of ...
This article argues that an efficient artificial intelligence control algorithm needs the built-i... more This article argues that an efficient artificial intelligence control algorithm needs the built-in symmetries of an industrial robot manipulator to be further characterized and exploited. The product of this enhancement is a four-dimensional (4D) discrete cylindrical grid space that can directly replace complex robot models. A* is chosen for its wide use among such algorithms to study the advantages and disadvantages of steering the robot manipulator within the 4D cylindrical discrete grid. The study shows that this approach makes it possible to control a robot without any specific knowledge of the robot kinematic and dynamic models at planning and execution time. In fact, the robot joint positions for each grid cell are pre-calculated and stored as knowledge, then quickly retrieved by the pathfinding algorithm when needed. The 4D cylindrical discrete space has both the advantages of the configuration space and the three-dimensional Cartesian workspace of the robot. Since path optim...
This is the version of the code released with the scientific article A. de Giorgio and L. Wang, &... more This is the version of the code released with the scientific article A. de Giorgio and L. Wang, "Artificial Intelligence Control in 4D Cylindrical Space for Industrial Robotic Applications", in IEEE Access, vol. 8, pp. 174833-174844, 2020, doi: 10.1109/ACCESS.2020.3026193.
Obiettivo della mia tesi è studiare come la presenza di circuiti neurali programmabili possa rend... more Obiettivo della mia tesi è studiare come la presenza di circuiti neurali programmabili possa rendere l'apprendimento di differenti comportamenti, da parte di una singola struttura, più efficace. A tal fine, ho messo a confronto due architetture, una programmabile e l'altra non programmabile, come parte di uno scenario robotico appositamente progettato per testare la possibilità di apprendere ed esibire comportamenti multipli. Più in particolare, ho supposto che un robot possa imparare, tramite la sua architettura di controllo, programmabile o meno, a raggiungere, su richiesta, ciascuna delle otto terminazioni differenti di un labirinto costituito da una serie di tre biforcazioni e di dimensioni variabili. Fondamentale, in tale scenario, la necessità per l'architettura di controllo di apprendere, e poi esibire, comportamenti e non semplici traiettorie. In tal modo, ho potuto raccogliere dati sufficienti per realizzare un'opportuna analisi.
In this thesis I demonstrated how a singular neural network can potentially represent the set of ... more In this thesis I demonstrated how a singular neural network can potentially represent the set of more latent neural circuits, able to execute different functions, based on an input encoding so to reprogram their functionality. Such programmable structure, in passing from one behavior to another, does not require further learning procedures, nor any structural modifications. This is ideal to execute quick and reversible transitions such as the ones showed in biological organisms’ behaviors.
Restricted Boltzmann Machines (RBMs) and autoencoders have been used - in several variants - for ... more Restricted Boltzmann Machines (RBMs) and autoencoders have been used - in several variants - for similar tasks, such as reducing dimensionality or extracting features from signals. Even though their structures are quite similar, they rely on different training theories. Lately, they have been largely used as building blocks in deep learning architectures that are called deep belief networks (instead of stacked RBMs) and stacked autoencoders.In light of this, the student has worked on this thesis with the aim to understand the extent of the similarities and the overall pros and cons of using either RBMs, autoencoders or denoising autoencoders in deep networks. Important characteristics are tested, such as the robustness to noise, the influence on training of the availability of data and the tendency to overtrain. The author has then dedicated part of the thesis to study how the three deep networks in exam form their deep internal representations and how similar these can be to each o...
Questo articolo scientifico sostiene la tesi che un algoritmo di controllo, facente uso di intell... more Questo articolo scientifico sostiene la tesi che un algoritmo di controllo, facente uso di intelligenza artificiale, per poter essere efficiente necessiti di sfruttare le simmetrie integrate in ogni manipolatore robotico industrale così che quest’ultimo possa essere ulteriormente caratterizzato ed utilizzato. Il prodotto di questo miglioramento è uno spazio discreto a griglia cilindrica quadridimensionale (4D) che può direttamente sostituire complessi modelli robotici. A* è scelto per il suo ampio utilizzo tra simili algoritmi di ricerca, in modo da studiare i vantaggi e gli svantaggi del controllo di robot industriali tramite la griglia discreta cilindrica 4D. Lo studio mostra che questo approccio consente di controllare un robot senza alcuna conoscenza specifica dei modelli cinematici e dinamici del robot al momento della pianificazione e dell’esecuzione. In effetti, le posizioni dei giunti del robot per ciascuna cella della griglia vengono precalcolate e memorizzate come conoscenza, quindi recuperate rapidamente dall’algoritmo di ricerca di percorso quando necessario. Lo spazio discreto cilindrico 4D presenta sia i vantaggi dello spazio di configurazione che dello spazio di lavoro cartesiano tridimensionale del robot. Poiché l’ottimizzazione del percorso è il nucleo di qualsiasi algortimo di ricerca, incluso A*, la griglia cilindrica 4D fornisce uno spazio di ricerca che può incorporare ulteriori conoscenze sotto forma di proprietà delle celle, inclusa la presenza di ostacoli e l’occupazione volumetrica dell’intero corpo del robot industriale, da usare in applicazioni per l’evitamento degli ostacoli. Il compromesso principale è tra una capacità limitata della conosenza precalcolata nella griglia e la velocità di ricerca del percorso migliore. Questo approccio innovativo incoraggia l’uso di algoritmi di ricerca per applicazioni robotiche industriali, apre la via allo studio di altre simmetrie fisiche presenti in altri modelli di robot e pone le basi per l’applicazione di algoritmi dinamici per l’evitamento degli ostacoli.
In the age of digital manufacturing there is a need to elicit and transfer procedural knowledge b... more In the age of digital manufacturing there is a need to elicit and transfer procedural knowledge between humans and machines. Having proper knowledge is essential in decision-making. The more the knowledge, the better decisions are made. To capture experiences and turn them into knowledge is fundamental in learning processes and knowledge development. Knowledge engineering and knowledge management have been subject for research for decades and several concepts about knowledge and knowledge transfer have been introduced, but a functional approach to exploit knowledge efficiently in manufacturing is still missing. In the era of Industry 4.0, humans and machines must be able to collaborate in such way that both can exploit the best abilities of each other in a manufacturing process. This paper introduces a procedural knowledge process (PKP) approach to capturing and defining unexpected events, while a process step is able to perform its required functions and transfer that information as machine-understandable knowledge about a failure mode. Function blocks (FBs), as per the IEC-61499 standard, have been proposed as a way to achieve distributed process planning in which the manufacturing process can adapt itself to runtime conditions, e.g. machine availability, etc. However, FBs are event-driven systems and the approach is limited to work under well-known runtime conditions, e.g. machine configurations and states, or deviations which are impossible to foresee in advance, for instance the outcome of a process failure mode effects analysis (PFMEA). The PKP introduced in this paper, aims at bridging this gap by integrating at runtime an expert operator's solution based on root cause analysis (RCA) in an FB architecture, making the FB knowledge-driven systems, for further executions of the same without redesigning it. Natural language representations of procedural knowledge blocks (PKBs) allow to transfer procedural knowledge to human operators, i.e. explain the process flow of a machine decision, while machine representations of PKBs allow to embed procedural knowledge that is elicited from expert operators upon unexpected events into the FBs process. The resulting PKP enhances the FBs for smart industrial applications, such as the process planning use case described in this paper.
This book is the fruit of an Italian-Swedish collaborative project involving the Rotary Stockholm... more This book is the fruit of an Italian-Swedish collaborative project involving the Rotary Stockholm International (District 2350), the University of Florence and The Rotary Club Firenze Sud (District 2071).The book opens with a section on Alfred Nobel and his ties to Italy, the city of Sanremo in particular. Most of the book is dedicated to two winners of the most prestigious award, the Nobel Prize, in both cases for Physics: Guglielmo Marconi (1909) and Enrico Fermi (1938). Both were Italian and both played a key role in the development of our telecommunications era: while Marconi is credited with the invention of the radio, Fermi developed the statistics that allowed the creation of solid-state electronics, in addition to making other important contributions to the field of nuclear Physics. These two outstanding scientists are here remembered through two lectures, given at different Florentine Rotary Clubs by a fellow scientist of theirs, Nello Carrara, who was also a key figure in high frequency electronics.
Molti pensano che l'intelligenza artificiale debba essere usata per grandi applicazioni, ma in re... more Molti pensano che l'intelligenza artificiale debba essere usata per grandi applicazioni, ma in realtà anche delle applicazioni minori ma con un focus ben preciso possono servire ad ottimizzare processi industriali complessi. In particolare, questa presentazione si riferisce ai processi della produzione alimentare e riporta alcuni dei più comuni casi d'uso di intelligenza artificiale, oltre ad una breve introduzione metodologica all'applicazione di intelligenza artificiale in ambito industriale.
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