Supply Chain

Traditionally supply chain management has meant factories, assembly lines, warehouses, transportation vehicles, and time sheets. Modern supply chain management is a highly complex, multidimensional problem set with virtually endless number of variables for optimization. An Internet enabled supply chain may have just-in-time delivery, precise inventory visibility, and up-to-the-minute distribution-tracking capabilities. Technology advances have enabled supply chains to become strategic weapons that can help avoid disasters, lower costs, and make money. From internal enterprise processes to external business transactions with suppliers, transporters, channels and end-users marks the wide range of challenges researchers have to handle. The aim of this book is at revealing and illustrating this diversity in terms of scientific and theoretical fundamentals, prevailing concepts as well as current practical applications

Indoor wireless communications and applications

Chapter 3 addresses challenges in radio link and system design in indoor scenarios. Given the fact that most human activities take place in indoor environments, the need for supporting ubiquitous indoor data connectivity and location/tracking service becomes even more important than in the previous decades. Specific technical challenges addressed in this section are(i), modelling complex indoor radio channels for effective antenna deployment, (ii), potential of millimeter-wave (mm-wave) radios for supporting higher data rates, and (iii), feasible indoor localisation and tracking techniques, which are summarised in three dedicated sections of this chapter

Scene and crowd analysis using synthetic data generation with 3D quality improvements and deep network architectures

In this thesis, a scene analysis mainly focusing on vision-based techniques have been explored. The vision-based scene analysis techniques have a wide range of applications from surveillance, security to agriculture. A vision sensor can provide rich information about the environment such as colour, depth, shape, size and much more. This information can be further processed to have an in-depth knowledge of the scene such as type of environment, objects and distances. Hence, this thesis covers initially the background on human detection in particular pedestrian and crowd detection methods and introduces various vision-based techniques used in human detection. Followed by a detailed analysis of the use of synthetic data to improve the performance of state-of-the-art Deep Learning techniques and a multi-purpose synthetic data generation tool is proposed. The tool is a real-time graphics simulator which generates multiple types of synthetic data applicable for pedestrian detection, crowd density estimation, image segmentation, depth estimation, and 3D pose estimation. In the second part of the thesis, a novel technique has been proposed to improve the quality of the synthetic data. The inter-reflection also known as global illumination is a naturally occurring phenomena and is a major problem for 3D scene generation from an image. Thus, the proposed methods utilised a reverted ray-tracing technique to reduce the effect of inter-reflection problem and increased the quality of generated data. In addition, a method to improve the quality of the density map is discussed in the following chapter. The density map is the most commonly used technique to estimate crowds. However, the current procedure used to generate the map is not content-aware i.e., density map does not highlight the humans’ heads according to their size in the image. Thus, a novel method to generate a content-aware density map was proposed and demonstrated that the use of such maps can elevate the performance of an existing Deep Learning architecture. In the final part, a Deep Learning architecture has been proposed to estimate the crowd in the wild. The architecture tackled the challenging aspect such as perspective distortion by implementing several techniques like pyramid style inputs, scale aggregation method and self-attention mechanism to estimate a crowd density map and achieved state-of-the-art results at the time

Efficient operation of recharging infrastructure for the accommodation of electric vehicles: a demand driven approach

Large deployment and adoption of electric vehicles in the forthcoming years can have significant environmental impact, like mitigation of climate change and reduction of traffic-induced air pollutants. At the same time, it can strain power network operations, demanding effective load management strategies to deal with induced charging demand. One of the biggest challenges is the complexity that electric vehicle (EV) recharging adds to the power system and the inability of the existing grid to cope with the extra burden. Charging coordination should provide individual EV drivers with their requested energy amount and at the same time, it should optimise the allocation of charging events in order to avoid disruptions at the electricity distribution level. This problem could be solved with the introduction of an intermediate agent, known as the aggregator or the charging service provider (CSP). Considering out-of-home charging infrastructure, an additional role for the CSP would be to maximise revenue for parking operators. This thesis contributes to the wider literature of electro-mobility and its effects on power networks with the introduction of a choice-based revenue management method. This approach explicitly treats charging demand since it allows the integration of a decentralised control method with a discrete choice model that captures the preferences of EV drivers. The sensitivities to the joint charging/parking attributes that characterise the demand side have been estimated with EV-PLACE, an online administered stated preference survey. The choice-modelling framework assesses simultaneously out-of-home charging behaviour with scheduling and parking decisions. Also, survey participants are presented with objective probabilities for fluctuations in future prices so that their response to dynamic pricing is investigated. Empirical estimates provide insights into the value that individuals place to the various attributes of the services that are offered by the CSP. The optimisation of operations for recharging infrastructure is evaluated with SOCSim, a micro-simulation framework that is based on activity patterns of London residents. Sensitivity analyses are performed to examine the structural properties of the model and its benefits compared to an uncontrolled scenario are highlighted. The application proposed in this research is practice-ready and recommendations are given to CSPs for its full-scale implementation.Open Acces

The drivers of Corporate Social Responsibility in the supply chain. A case study.

Purpose: The paper studies the way in which a SME integrates CSR into its corporate strategy, the practices it puts in place and how its CSR strategies reflect on its suppliers and customers relations. Methodology/Research limitations: A qualitative case study methodology is used. The use of a single case study limits the generalizing capacity of these findings. Findings: The entrepreneur’s ethical beliefs and value system play a fundamental role in shaping sustainable corporate strategy. Furthermore, the type of competitive strategy selected based on innovation, quality and responsibility clearly emerges both in terms of well defined management procedures and supply chain relations as a whole aimed at involving partners in the process of sustainable innovation. Originality/value: The paper presents a SME that has devised an original innovative business model. The study pivots on the issues of innovation and eco-sustainability in a context of drivers for CRS and business ethics. These values are considered fundamental at International level; the United Nations has declared 2011 the “International Year of Forestry”

Environmental and territorial modelling for planning and design

[English]: Between 5th and 8th September 2018 the tenth edition of the INPUT conference took place in Viterbo, guests of the beautiful setting of the University of Tuscia and its DAFNE Department. INPUT is managed by an informal group of Italian academic researchers working in many fields related to the exploitation of informatics in planning. This Tenth Edition pursed multiple objectives with a holistic, boundary-less character, to face the complexity of today socio-ecological systems following a systemic approach aimed to problem solving. In particular, the Conference will aim to present the state of art of modeling approaches employed in urban and territorial planning in national and international contexts. Moreover, the conference has hosted a Geodesign workshop, by Carl Steinitz (Harvard Graduate School of Design) and Hrishi Ballal (on skype), Tess Canfield, Michele Campagna. Finally, on the last day of the conference, took place the QGIS hackfest, in which over 20 free software developers from all over Italy discussed the latest news and updates from the QGIS network. The acronym INPUT was born as INformatics for Urban and Regional Planning. In the transition to graphics, unintentionally, the first term was transformed into “Innovation”, with a fine example of serendipity, in which a small mistake turns into something new and intriguing. The opportunity is taken to propose to the organizers and the scientific committee of the next appointment to formalize this change of the acronym. This 10th edition was focused on Environmental and Territorial Modeling for planning and design. It has been considered a fundamental theme, especially in relation to the issue of environmental sustainability, which requires a rigorous and in-depth analysis of processes, a theme which can be satisfied by the territorial information systems and, above all, by modeling simulation of processes. In this topic, models are useful with the managerial approach, to highlight the many aspects of complex city and landscape systems. In consequence, their use must be deeply critical, not for rigid forecasts, but as an aid to the management decisions of complex systems.[Italiano]:Dal 5 all’8 settembre 2018 l’Università della Tuscia e il Dipartimento di Scienze Agrarie e Forestali - DAFNE hanno ospitato la decima edizione del Congresso Internazionale INPUT. INPUT è un gruppo informale di ricercatori accademici italiani che operano in molti settori connessi all’uso dell’informatica nella pianificazione. Questa decima edizione del Congresso ha perseguito obiettivi multipli con un carattere olistico, senza confini, per affrontare la complessità degli attuali sistemi socio-ecologici seguendo un approccio sistemico finalizzato alla risoluzione dei problemi. In particolare, la conferenza è stata orientata a presentare lo stato dell'arte degli approcci di modellazione impiegati nella pianificazione urbana e territoriale in contesti nazionali e internazionali. Inoltre, la conferenza ha ospitato un seminario di Geodesign, di Carl Steinitz (Harvard Graduate School of Design) e Hrishi Ballal (via skype), Tess Canfield e Michele Campagna. Infine, l'ultimo giorno della conferenza, si è svolto l’hackfest di QGIS, in cui oltre 20 sviluppatori di software open source provenienti da tutta Italia hanno discusso le ultime novità e gli aggiornamenti dalla rete QGIS. L'acronimo “INPUT” è nato come “INformatics per Urban and Regional Planning”. Nella transizione alla grafica, involontariamente, il primo termine è stato trasformato in "Innovazione", con un bell'esempio di serendipità, in cui un piccolo errore si trasforma in qualcosa di nuovo e intrigante

Urban Informatics

This open access book is the first to systematically introduce the principles of urban informatics and its application to every aspect of the city that involves its functioning, control, management, and future planning. It introduces new models and tools being developed to understand and implement these technologies that enable cities to function more efficiently – to become ‘smart’ and ‘sustainable’. The smart city has quickly emerged as computers have become ever smaller to the point where they can be embedded into the very fabric of the city, as well as being central to new ways in which the population can communicate and act. When cities are wired in this way, they have the potential to become sentient and responsive, generating massive streams of ‘big’ data in real time as well as providing immense opportunities for extracting new forms of urban data through crowdsourcing. This book offers a comprehensive review of the methods that form the core of urban informatics from various kinds of urban remote sensing to new approaches to machine learning and statistical modelling. It provides a detailed technical introduction to the wide array of tools information scientists need to develop the key urban analytics that are fundamental to learning about the smart city, and it outlines ways in which these tools can be used to inform design and policy so that cities can become more efficient with a greater concern for environment and equity