A critical examination of the use of business intelligence (BI) in the optioneering of generative design models: a case study.

This research outlines the development of a generative des ign workflow for the architectural space planning of a 1,200 sq.m office located in Dublin, Ireland, and the application of statistical analysis and data visualisation for the optioneering of gen erated models. First, the paper defines a computational desig n model with the potential to generate a variety of office layouts, including circulation routes and desk locations. It then identifies three unique performance metrics that evaluate each design option. Finally, the study applies a multi objective genetic algorithm (MOGA) to explore the high dimensional design space of all potential options and describes several visualisation techniques that can assist the designer in selecting the most appropriat e option. There have been several articles published regardi ng the use of generative design systems, model evaluation processes and business intelligence (BI). However, a clearly defined methodology for relating all three remains undocumented. The aim of t his research is to critically examine the use of business in telligence in the optioneering of generative design models. It is anticipated that this research will go some way to filling the gap in the current published material regarding the impacts that th ese emerging technologies have on the building design proces s

OBLIQUE IMAGES AND DIRECT PHOTOGRAMMETRY WITH A FIXED WING PLATFORM: FIRST TEST AND RESULTS IN HIERAPOLIS OF PHRYGIA (TK)

Abstract. The complex archaeological site documentation benefits for a long time now from the aerial point of view and remote sensing methods. Moreover, the recent research on UAV photogrammetry platform equipment and flight planning actively contribute in this sense for a scaling improvement and cost-benefits balance. Frequently, the experiences on articulated topographic profiles in archaeological excavations require not only a multi-sensor approach but also and above all a multiscale one. According to this line, in a general time-cost ration framework, the geometric content of the generated DSMs should be complete of nadir and oblique point of view for the accurate 3D reconstruction of both upstanding buildings and excavations. In the same way, also the radiometric content closely depends on sensor payload quality and is strictly affected by excavation site condition, related to the site material and light. In this research, carried out in the impressive archaeological site of the ancient city of Hierapolis in Phrygia (Turkey) in the autumn 2019 campaign, the main goal was to evaluate and validate the overall performance of a novel UAV fix-wing ultralight platform with onboard GNSS receiver for RTK/PPK processing of cameras positioning and with the possibility of oblique images capturing. The expected contribute in terms of the acquisition, processing time, radiometric enhancement and geometry 3D reconstruction will be explored with preliminary test and outcomes, and with the results of the high-scale DSM and orthoimage generation of the complete Hierapolis site

OBLIQUE IMAGES and DIRECT PHOTOGRAMMETRY with A FIXED WING PLATFORM: FIRST TEST and RESULTS in HIERAPOLIS of PHRYGIA (TK)

The complex archaeological site documentation benefits for a long time now from the aerial point of view and remote sensing methods. Moreover, the recent research on UAV photogrammetry platform equipment and flight planning actively contribute in this sense for a scaling improvement and cost-benefits balance. Frequently, the experiences on articulated topographic profiles in archaeological excavations require not only a multi-sensor approach but also and above all a multiscale one. According to this line, in a general time-cost ration framework, the geometric content of the generated DSMs should be complete of nadir and oblique point of view for the accurate 3D reconstruction of both upstanding buildings and excavations. In the same way, also the radiometric content closely depends on sensor payload quality and is strictly affected by excavation site condition, related to the site material and light. In this research, carried out in the impressive archaeological site of the ancient city of Hierapolis in Phrygia (Turkey) in the autumn 2019 campaign, the main goal was to evaluate and validate the overall performance of a novel UAV fix-wing ultralight platform with onboard GNSS receiver for RTK/PPK processing of cameras positioning and with the possibility of oblique images capturing. The expected contribute in terms of the acquisition, processing time, radiometric enhancement and geometry 3D reconstruction will be explored with preliminary test and outcomes, and with the results of the high-scale DSM and orthoimage generation of the complete Hierapolis site

Digital workflows for the management of existing structures in the pre- and post-earthquake phases: BIM, CDE, drones, laser-scanning and AI

La metodologia BIM, sviluppata in America negli anni '70, ha rivoluzionato l'industria delle costruzioni introducendo i principi di innovazione e digitalizzazione per la gestione dei progetti, in un settore settore produttivo troppo legato a logiche tradizionali. I numerosi processi digitali che sono stati sviluppati da allora hanno riguardato in gran parte la progettazione di nuovi edifici, e sono principalmente legati alla disciplina del construction management. Alcune prime sperimentazioni condotte nel tempo hanno mostrato come l'estensione di questa metodologia agli edifici esistenti comporti molte difficoltà. In questo panorama, il lavoro di tesi si concentra sulla gestione delle strutture nella fase pre e post-sisma con l'obiettivo di sviluppare processi digitali basati sull'uso di tecnologie innovative applicate sia agli edifici ordinari che a quelli storici. Il primo workflow sviluppato, relativo alla fase pre-sisma, è stato denominato scan-to-FEM, ed è finalizzato a particolarizzare il classico processo scan-to-BIM nel campo dell'ingegneria strutturale, analizzando così tutti i passaggi dal rilievo dell'edificio con le tecniche digitali di fotogrammetria e laser-scanning fino all'analisi strutturale e alla valutazione della sicurezza nei confronti delle azioni sismiche. I processi di gestione delle strutture post-sisma sono invece incentrati sulla stima della sicurezza della struttura e sulla definizione delle strategie di intervento, e si basano sull'analisi delle caratteristiche intrinseche della struttura e dei danni indotti dagli eventi sismici. L'intero processo di valutazione del livello operativo di un edificio è stato quindi rivisto alla luce delle moderne tecnologie digitali. Nel dettaglio, sono state sviluppate Reti Neurali Convoluzionali (CNN) per la crack detection, e l'estrazione delle informazioni numeriche associate alle lesioni, gestite poi grazie ai modelli BIM. I quadri fessurativi sono stati digitalizzati grazie allìintroduzione un nuovo oggetto BIM "lesione" (attualmente non codificato nello standard IFC), al quale è stato aggiunto un set di parametri in parte valutati con le CNN ed in parte qualitativi. Durante lo sviluppo di questi processi, sono stati sviluppati nuovi strumenti adhoc per la gestione degli edifici esistenti. In particolare, sono state definite specifiche per lo sviluppo di schede tecniche digitali dei danni, e per la creazione del nuovo oggetto BIM "lesione". I processi di gestione degli edifici danneggiati, grazie agli sviluppi tecnologici realizzati, sono stati applicati per la digitalizzazione dell'edificio storico della chiesa di San Pietro in Vinculis danneggiato a seguito di eventi sismici, grazie ai quali sono stati sperimentati i massimi benefici in termini di riduzione di tempo e risparmio di risorse

Augmented reality for computer assisted orthopaedic surgery

In recent years, computer-assistance and robotics have established their presence in operating theatres and found success in orthopaedic procedures. Benefits of computer assisted orthopaedic surgery (CAOS) have been thoroughly explored in research, finding improvements in clinical outcomes, through increased control and precision over surgical actions. However, human-computer interaction in CAOS remains an evolving field, through emerging display technologies including augmented reality (AR) – a fused view of the real environment with virtual, computer-generated holograms. Interactions between clinicians and patient-specific data generated during CAOS are limited to basic 2D interactions on touchscreen monitors, potentially creating clutter and cognitive challenges in surgery. Work described in this thesis sought to explore the benefits of AR in CAOS through: an integration between commercially available AR and CAOS systems, creating a novel AR-centric surgical workflow to support various tasks of computer-assisted knee arthroplasty, and three pre–clinical studies exploring the impact of the new AR workflow on both existing and newly proposed quantitative and qualitative performance metrics. Early research focused on cloning the (2D) user-interface of an existing CAOS system onto a virtual AR screen and investigating any resulting impacts on usability and performance. An infrared-based registration system is also presented, describing a protocol for calibrating commercial AR headsets with optical trackers, calculating a spatial transformation between surgical and holographic coordinate frames. The main contribution of this thesis is a novel AR workflow designed to support computer-assisted patellofemoral arthroplasty. The reported workflow provided 3D in-situ holographic guidance for CAOS tasks including patient registration, pre-operative planning, and assisted-cutting. Pre-clinical experimental validation on a commercial system (NAVIO®, Smith & Nephew) for these contributions demonstrates encouraging early-stage results showing successful deployment of AR to CAOS systems, and promising indications that AR can enhance the clinician’s interactions in the future. The thesis concludes with a summary of achievements, corresponding limitations and future research opportunities.Open Acces

Enhancement of Metaheuristic Algorithm for Scheduling Workflows in Multi-fog Environments

Whether in computer science, engineering, or economics, optimization lies at the heart of any challenge involving decision-making. Choosing between several options is part of the decision- making process. Our desire to make the "better" decision drives our decision. An objective function or performance index describes the assessment of the alternative's goodness. The theory and methods of optimization are concerned with picking the best option. There are two types of optimization methods: deterministic and stochastic. The first is a traditional approach, which works well for small and linear problems. However, they struggle to address most of the real-world problems, which have a highly dimensional, nonlinear, and complex nature. As an alternative, stochastic optimization algorithms are specifically designed to tackle these types of challenges and are more common nowadays. This study proposed two stochastic, robust swarm-based metaheuristic optimization methods. They are both hybrid algorithms, which are formulated by combining Particle Swarm Optimization and Salp Swarm Optimization algorithms. Further, these algorithms are then applied to an important and thought-provoking problem. The problem is scientific workflow scheduling in multiple fog environments. Many computer environments, such as fog computing, are plagued by security attacks that must be handled. DDoS attacks are effectively harmful to fog computing environments as they occupy the fog's resources and make them busy. Thus, the fog environments would generally have fewer resources available during these types of attacks, and then the scheduling of submitted Internet of Things (IoT) workflows would be affected. Nevertheless, the current systems disregard the impact of DDoS attacks occurring in their scheduling process, causing the amount of workflows that miss deadlines as well as increasing the amount of tasks that are offloaded to the cloud. Hence, this study proposed a hybrid optimization algorithm as a solution for dealing with the workflow scheduling issue in various fog computing locations. The proposed algorithm comprises Salp Swarm Algorithm (SSA) and Particle Swarm Optimization (PSO). In dealing with the effects of DDoS attacks on fog computing locations, two Markov-chain schemes of discrete time types were used, whereby one calculates the average network bandwidth existing in each fog while the other determines the number of virtual machines existing in every fog on average. DDoS attacks are addressed at various levels. The approach predicts the DDoS attack’s influences on fog environments. Based on the simulation results, the proposed method can significantly lessen the amount of offloaded tasks that are transferred to the cloud data centers. It could also decrease the amount of workflows with missed deadlines. Moreover, the significance of green fog computing is growing in fog computing environments, in which the consumption of energy plays an essential role in determining maintenance expenses and carbon dioxide emissions. The implementation of efficient scheduling methods has the potential to mitigate the usage of energy by allocating tasks to the most appropriate resources, considering the energy efficiency of each individual resource. In order to mitigate these challenges, the proposed algorithm integrates the Dynamic Voltage and Frequency Scaling (DVFS) technique, which is commonly employed to enhance the energy efficiency of processors. The experimental findings demonstrate that the utilization of the proposed method, combined with the Dynamic Voltage and Frequency Scaling (DVFS) technique, yields improved outcomes. These benefits encompass a minimization in energy consumption. Consequently, this approach emerges as a more environmentally friendly and sustainable solution for fog computing environments