916 resultados para workflow scheduling


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Effective and efficient implementation of intelligent and/or recently emerged networked manufacturing systems require an enterprise level integration. The networked manufacturing offers several advantages in the current competitive atmosphere by way to reduce, by shortening manufacturing cycle time and maintaining the production flexibility thereby achieving several feasible process plans. The first step in this direction is to integrate manufacturing functions such as process planning and scheduling for multi-jobs in a network based manufacturing system. It is difficult to determine a proper plan that meets conflicting objectives simultaneously. This paper describes a mobile-agent based negotiation approach to integrate manufacturing functions in a distributed manner; and its fundamental framework and functions are presented. Moreover, ontology has been constructed by using the Protégé software which possesses the flexibility to convert knowledge into Extensible Markup Language (XML) schema of Web Ontology Language (OWL) documents. The generated XML schemas have been used to transfer information throughout the manufacturing network for the intelligent interoperable integration of product data models and manufacturing resources. To validate the feasibility of the proposed approach, an illustrative example along with varied production environments that includes production demand fluctuations is presented and compared the proposed approach performance and its effectiveness with evolutionary algorithm based Hybrid Dynamic-DNA (HD-DNA) algorithm. The results show that the proposed scheme is very effective and reasonably acceptable for integration of manufacturing functions.

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In aircraft components maintenance shops, components are distributed amongst repair groups and their respective technicians based on the type of repair, on the technicians skills and workload, and on the customer required dates. This distribution planning is typically done in an empirical manner based on the group leader’s past experience. Such a procedure does not provide any performance guarantees, leading frequently to undesirable delays on the delivery of the aircraft components. Among others, a fundamental challenge faced by the group leaders is to decide how to distribute the components that arrive without customer required dates. This paper addresses the problems of prioritizing the randomly arriving of aircraft components (with or without pre-assigned customer required dates) and of optimally distributing them amongst the technicians of the repair groups. We proposed a formula for prioritizing the list of repairs, pointing out the importance of selecting good estimators for the interarrival times between repair requests, the turn-around-times and the man hours for repair. In addition, a model for the assignment and scheduling problem is designed and a preliminary algorithm along with a numerical illustration is presented.

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This paper presents a stochastic mixed-integer linear programming approach for solving the self-scheduling problem of a price-taker thermal and wind power producer taking part in a pool-based electricity market. Uncertainty on electricity price and wind power is considered through a set of scenarios. Thermal units are modeled by variable costs, start-up costs and technical operating constraints, such as: ramp up/down limits and minimum up/down time limits. An efficient mixed-integer linear program is presented to develop the offering strategies of the coordinated production of thermal and wind energy generation, aiming to maximize the expected profit. A case study with data from the Iberian Electricity Market is presented and results are discussed to show the effectiveness of the proposed approach.

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The Many-Body-Perturbation Theory approach is among the most successful theoretical frameworks for the study of excited state properties. It allows to describe the excitonic interactions, which play a fundamental role in the optical response of insulators and semiconductors. The first part of the thesis focuses on the study of the quasiparticle, optical and excitonic properties of \textit{bulk} Transition Metal Oxide (TMO) perovskites using a G$_0$W$_0$+Bethe Salpeter Equation (BSE) approach. A representative set of 14 compounds has been selected, including 3d, 4d and 5d perovskites. An approximation of the BSE scheme, based on an analytic diagonal expression for the inverse dielectric function, is used to compute the exciton binding energies and is carefully bench-marked against the standard BSE results. In 2019 an important breakthrough has been achieved with the synthesis of ultrathin SrTiO3 films down to the monolayer limit. This allows us to explore how the quasiparticle and optical properties of SrTiO3 evolve from the bulk to the two-dimensional limit. The electronic structure is computed with G0W0 approach: we prove that the inclusion of the off-diagonal self-energy terms is required to avoid non-physical band dispersions. The excitonic properties are investigated beyond the optical limit at finite momenta. Lastly a study of the under pressure optical response of the topological nodal line semimetal ZrSiS is presented, in conjunction with the experimental results from the group of Prof. Dr. Kuntscher of the Augsburg University. The second part of the thesis discusses the implementation of a workflow to automate G$_0$W$_0$ and BSE calculations with the VASP software. The workflow adopts a convergence scheme based on an explicit basis-extrapolation approach [J. Klimeš \textit{et al.}, Phys. Rev.B 90, 075125 (2014)] which allows to reduce the number of intermediate calculations required to reach convergence and to explicit estimate the error associated to the basis-set truncation.

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In rural and isolated areas without cellular coverage, Satellite Communication (SatCom) is the best candidate to complement terrestrial coverage. However, the main challenge for future generations of wireless networks will be to meet the growing demand for new services while dealing with the scarcity of frequency spectrum. As a result, it is critical to investigate more efficient methods of utilizing the limited bandwidth; and resource sharing is likely the only choice. The research community’s focus has recently shifted towards the interference management and exploitation paradigm to meet the increasing data traffic demands. In the Downlink (DL) and Feedspace (FS), LEO satellites with an on-board antenna array can offer service to numerous User Terminals (UTs) (VSAT or Handhelds) on-ground in FFR schemes by using cutting-edge digital beamforming techniques. Considering this setup, the adoption of an effective user scheduling approach is a critical aspect given the unusually high density of User terminals on the ground as compared to the on-board available satellite antennas. In this context, one possibility is that of exploiting clustering algorithms for scheduling in LEO MU-MIMO systems in which several users within the same group are simultaneously served by the satellite via Space Division Multiplexing (SDM), and then these different user groups are served in different time slots via Time Division Multiplexing (TDM). This thesis addresses this problem by defining a user scheduling problem as an optimization problem and discusses several algorithms to solve it. In particular, focusing on the FS and user service link (i.e., DL) of a single MB-LEO satellite operating below 6 GHz, the user scheduling problem in the Frequency Division Duplex (FDD) mode is addressed. The proposed State-of-the-Art scheduling approaches are based on graph theory. The proposed solution offers high performance in terms of per-user capacity, Sum-rate capacity, SINR, and Spectral Efficiency.

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Fruit crops are an important resource for food security, since more than being nutrient they are also a source of natural antioxidant compounds, such as polyphenols and vitamins. However, fruit crops are also among the cultivations threatened by the harmful effects of climate change This study had the objective of investigating the physiological effects of deficit irrigation on apple (2020-2021), sour cherry (2020-2021-2022) and apricot (2021-2022) trees, with a special focus on fruit nutraceutical quality. On each trial, the main physiological parameters were monitored along the growing season: i) stem and leaf water potentials; ii) leaf gas exchanges; iii) fruit and shoot growth. At harvest, fruit quality was evaluated especially in terms of fruit size, flesh firmness and soluble solids content. Moreover, it was performed: i) total phenolic content determination; ii) anthocyanidin concentration evaluation; and iii) untargeted metabolomic study. Irrigation scheduling in apricot, apple and sour cherry is surely overestimated by the decision support system available in Emilia-Romagna region. The water stress imposed on different fruit crops, each during two years of study, showed as a general conclusion that the decrease in the irrigation water did not show a straightforward decrease in plant physiological performance. This can be due to the miscalculation of the real water needs of the considered fruit crops. For this reason, there is the need to improve this important tool for an appropriate water irrigation management. Furthermore, there is also the need to study the behaviour of fruit crops under more severe deficit irrigations. In fact, it is likely that the application of lower water amounts will enhance the synthesis of specialized metabolites, with positive repercussion on human health. These hypotheses must be verified.

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LHC experiments produce an enormous amount of data, estimated of the order of a few PetaBytes per year. Data management takes place using the Worldwide LHC Computing Grid (WLCG) grid infrastructure, both for storage and processing operations. However, in recent years, many more resources are available on High Performance Computing (HPC) farms, which generally have many computing nodes with a high number of processors. Large collaborations are working to use these resources in the most efficient way, compatibly with the constraints imposed by computing models (data distributed on the Grid, authentication, software dependencies, etc.). The aim of this thesis project is to develop a software framework that allows users to process a typical data analysis workflow of the ATLAS experiment on HPC systems. The developed analysis framework shall be deployed on the computing resources of the Open Physics Hub project and on the CINECA Marconi100 cluster, in view of the switch-on of the Leonardo supercomputer, foreseen in 2023.

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Con la presente tesi di laurea si vuole analizzare la nuova procedura di ordini di “Scheduling Agreement” all’interno della realtà aziendale di ACMA S.p.A., azienda produttrice di macchine automatiche. Con il termine Scheduling Agreement si identifica una gestione di ordini con il fornitore, il quale mantiene i pezzi prodotti all’interno del proprio magazzino per massimo 18 mesi. L’accordo si basa sul principio per cui il fornitore ha una maggiore continuità di fornitura mentre ACMA S.p.A. vede un risparmio degli investimenti aziendali e nel tempo di approvvigionamento. Il principale focus dello studio verterà sulla proposta di soluzioni di stoccaggio per ricercare un punto di ottimo che permetta di ridurre al minimo il rischio di stock out e al tempo stesso minimizzi il livello delle scorte. L’analisi partirà con l’identificazione dei prodotti per cui risulta conveniente aprire uno Scheduling. Tale processo valutativo si estrinseca nell’analisi di due parametri fondamentali: frequenza e consumo. Verranno poi analizzati alcuni casi TO BE con il fine di trovare il Lead Time migliore per ridurre al minimo le giacenze ed evitare rotture di stock. Questi studi utilizzano il software di estrapolazione dati “SAP” per poi analizzarli sulla piattaforma Excel e forniscono una valutazione realistica nella gestione di tale procedura in ACMA S.p.A.. La soluzione conclusiva riesce a risolvere il problema di stock out introducendo la “scorta di sicurezza” calcolata sulla domanda futura. In particolare, utilizzando un Lead Time di approvvigionamento di 21 giorni si è riusciti a ridurre del 75% le scorte a magazzino rispetto al caso più cautelativo, mantenendo comunque basso il rischio di stock out. I risultati ottenuti forniranno un effettivo miglioramento delle prestazioni dell’azienda e il modello verrà sfruttato in futuro per l’applicazione iterativa della soluzione descritta, con risparmio di tempo e di fondi aziendali.

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Modern society is now facing significant difficulties in attempting to preserve its architectural heritage. Numerous challenges arise consequently when it comes to documentation, preservation and restoration. Fortunately, new perspectives on architectural heritage are emerging owing to the rapid development of digitalization. Therefore, this presents new challenges for architects, restorers and specialists. Additionally, this has changed the way they approach the study of existing heritage, changing from conventional 2D drawings in response to the increasing requirement for 3D representations. Recently, Building Information Modelling for historic buildings (HBIM) has escalated as an emerging trend to interconnect geometrical and informational data. Currently, the latest 3D geomatics techniques based on 3D laser scanners with enhanced photogrammetry along with the continuous improvement in the BIM industry allow for an enhanced 3D digital reconstruction of historical and existing buildings. This research study aimed to develop an integrated workflow for the 3D digital reconstruction of heritage buildings starting from a point cloud. The Pieve of San Michele in Acerboli’s Church in Santarcangelo Di Romagna (6th century) served as the test bed. The point cloud was utilized as an essential referential to model the BIM geometry using Autodesk Revit® 2022. To validate the accuracy of the model, Deviation Analysis Method was employed using CloudCompare software to determine the degree of deviation between the HBIM model and the point cloud. The acquired findings showed a very promising outcome in the average distance between the HBIM model and the point cloud. The conducted approach in this study demonstrated the viability of producing a precise BIM geometry from point clouds.

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Il settore del mobile è frammentato, caratteristica che non ha mai permesso una completa digitalizzazione dei suoi comparti: la comunicazione è risultata spesso difficoltosa, responsabile di incomprensioni e spesso mancanza di puntualità, con conseguente dispendio di risorse. Nel mio progetto di tesi analizzo principalmente la filiera degli imbottiti e quella tessile, collaterale ad essa. Il target di mio interesse sono le aziende produttrici di arredi che si servono di configuratori per la presentazione dei prodotti ai propri clienti. Ho ipotizzato un workflow suddivisibile in due fasi, una attuabile nel presente ed una seconda che implica una variazione attuabile nel futuro prossimo. Per la prima fase ho studiato un workflow agile al fine di digitalizzare le texture a partire da acquisizioni fotografiche. Analizzando il comportamento di vari tessuti ed elaborando un metodo di riproduzione digitale, ho sperimentato una metodologia per una resa superficiale degli imbottiti accurata e fotorealistica sia su piattaforme web che in realtà aumentata. Lo studio nasce dall’esigenza di apportare migliorie agli attuali configuratori e renderli effettivamente utili al fine per cui sono stati pensati: garantire una semplificazione del processo di acquisto rispondendo alle necessità degli utenti di vedere in anteprima l’aspetto finale del proprio arredo, collocato nello spazio abitativo. Il configuratore che ne deriva, restituirà una visualizzazione fedele dei tessuti anche in realtà aumentata. L’intelligenza artificiale fungerà da supporto nel processo decisionale dell’utente e la scelta dei materiali che compongono l’arredo sarà guidata in maniera tale da generare nell’utente un senso di consapevolezza circa gli impatti sull’ambiente. Per la seconda fase propongo una modalità di creazione dei tessuti completamente digitalizzata, a favore di una filiera sostenibile che riesce in questo modo ad abbattere costi e sprechi, con conseguente risparmio di risorse.

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The study of the user scheduling problem in a Low Earth Orbit (LEO) Multi-User MIMO system is the objective of this thesis. With the application of cutting-edge digital beamforming algorithms, a LEO satellite with an antenna array and a large number of antenna elements can provide service to many user terminals (UTs) in full frequency reuse (FFR) schemes. Since the number of UTs on-ground are many more than the transmit antennas on the satellite, user scheduling is necessary. Scheduling can be accomplished by grouping users into different clusters: users within the same cluster are multiplexed and served together via Space Division Multiple Access (SDMA), i.e., digital beamforming or Multi-User MIMO techniques; the different clusters of users are then served on different time slots via Time Division Multiple Access (TDMA). The design of an optimal user grouping strategy is known to be an NP-complete problem which can be solved only through exhaustive search. In this thesis, we provide a graph-based user scheduling and feed space beamforming architecture for the downlink with the aim of reducing user inter-beam interference. The main idea is based on clustering users whose pairwise great-circle distance is as large as possible. First, we create a graph where the users represent the vertices, whereas an edge in the graph between 2 users exists if their great-circle distance is above a certain threshold. In the second step, we develop a low complex greedy user clustering technique and we iteratively search for the maximum clique in the graph, i.e., the largest fully connected subgraph in the graph. Finally, by using the 3 aforementioned power normalization techniques, a Minimum Mean Square Error (MMSE) beamforming matrix is deployed on a cluster basis. The suggested scheduling system is compared with a position-based scheduler, which generates a beam lattice on the ground and randomly selects one user per beam to form a cluster.

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As a witness on the industrialization in Bologna, since its first generation was born in the late 1760, the Battiferro lock has been coping with the innovation that the city experienced throughout the centuries, until it has lost its functionality due to the technological development for which Bologna’s canals were gradually covered starting from the 1950s under Giuseppe Dozza ’s administration, as part of the reconstruction, reclamation and urban requalification that was carried out in the aftermath the World War II and which involved the whole city. The interest of the research carried out on this case study was primarily to reintroduce the landmark that is still intact, to what is considered to be the fourth generation of the industrial revolution, namely in the construction field, which is recognized as Construction 4.0, by means of the Historic (or Heritage) Information Modeling HBIM and Virtual Reality (VR) application. A scan-to-BIM approach was followed to create 3D as-built BIM model, as a first step towards the storytelling of the abandoned industrial built asset in VR environment, or as a seed for future applications such as Digital Twins (DT), heritage digital learning, sustainable impact studies, and/or interface with other interfaces such as GIS. Based on the HBIM product, examples of the primary BIM deliverables such as 2D layouts is given, then a workflow to VR is proposed and investigated the reliability of data and the type of users that may benefit of the VR experience, then the potential future development of the model is investigated, with comparison of a relatively similar experience in the UK.

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Daytime fatigue and lack of sleep seem to increase throughout adolescent years. Several environmental, psychological, and biological factors have been associated with the development of sleep across adolescence. The aim of the present article is to summarize these factors and to give examples of various outcomes in sleep patterns among adolescents studied in different cultural settings. It is obvious from earlier work that many adolescents have displaced circadian rhythms and lack of adaptation to school hours due to an early school start or additional burdens for work. Several interventions have aimed to help the adaptation process by supporting sleep processes and changing scheduling, in this way promoting classroom alertness. In summary, adolescents worldwide shorten their sleep due to schoolwork hours and additional work, especially by disturbing their sleep due to circadian misalignment

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This paper deals with the traditional permutation flow shop scheduling problem with the objective of minimizing mean flowtime, therefore reducing in-process inventory. A new heuristic method is proposed for the scheduling problem solution. The proposed heuristic is compared with the best one considered in the literature. Experimental results show that the new heuristic provides better solutions regarding both the solution quality and computational effort.

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In this paper, we address the problem of scheduling jobs in a no-wait flowshop with the objective of minimising the total completion time. This problem is well-known for being nondeterministic polynomial-time hard, and therefore, most contributions to the topic focus on developing algorithms able to obtain good approximate solutions for the problem in a short CPU time. More specifically, there are various constructive heuristics available for the problem [such as the ones by Rajendran and Chaudhuri (Nav Res Logist 37: 695-705, 1990); Bertolissi (J Mater Process Technol 107: 459-465, 2000), Aldowaisan and Allahverdi (Omega 32: 345-352, 2004) and the Chins heuristic by Fink and Voa (Eur J Operat Res 151: 400-414, 2003)], as well as a successful local search procedure (Pilot-1-Chins). We propose a new constructive heuristic based on an analogy with the two-machine problem in order to select the candidate to be appended in the partial schedule. The myopic behaviour of the heuristic is tempered by exploring the neighbourhood of the so-obtained partial schedules. The computational results indicate that the proposed heuristic outperforms existing ones in terms of quality of the solution obtained and equals the performance of the time-consuming Pilot-1-Chins.