Knowledge Growth, Complexity and the Returns to R&D

This paper is concerned with the way in which R&D activity in the technological and scientific domains feeds back into the dimension, the hierarchic structure and the complexity of knowledge search spaces. The discussion sets the stage for a critical evaluation of recent contributions trying to identify foundations for the existence of laws of returns to R&D

Navigating Text-To-Image Customization:From LyCORIS Fine-Tuning to Model Evaluation

Text-to-image generative models have garnered immense attention for their ability to produce high-fidelity images from text prompts. Among these, Stable Diffusion distinguishes itself as a leading open-source model in this fast-growing field. However, the intricacies of fine-tuning these models pose multiple challenges from new methodology integration to systematic evaluation. Addressing these issues, this paper introduces LyCORIS (Lora beYond Conventional methods, Other Rank adaptation Implementations for Stable diffusion) [https://github.com/KohakuBlueleaf/LyCORIS], an open-source library that offers a wide selection of fine-tuning methodologies for Stable Diffusion. Furthermore, we present a thorough framework for the systematic assessment of varied fine-tuning techniques. This framework employs a diverse suite of metrics and delves into multiple facets of fine-tuning, including hyperparameter adjustments and the evaluation with different prompt types across various concept categories. Through this comprehensive approach, our work provides essential insights into the nuanced effects of fine-tuning parameters, bridging the gap between state-of-the-art research and practical application.Comment: 77 pages, 54 figures, 6 table

Measurement-based quantum computation with cluster states

In this thesis we describe the one-way quantum computer (QCc), a scheme of universal quantum computation that consists entirely of one-qubit measurements on a highly entangled multi-particle state, the cluster state. We prove universality of the QCc, describe the underlying computational model and demonstrate that the QCc can be operated fault-tolerantly. In Chapter 2 we show that the QCc can be regarded as a simulator of quantum logic networks. In this way, we give the universality proof and establish the link to the network model, the common model of quantum computation. We also indicate that the description of the QCc as a network simulator is not adequate in every respect. In Chapter 3 we derive the computational model underlying the one-way quantum computer, which is very different from the quantum logic network model. The QCc has no quantum input, no quantum output and no quantum register, and the unitary gates from some universal set are not the elementary building blocks of QCc-quantum algorithms. Further, all information that is processed with the QCc are the outcomes of one-qubit measurements and thus processing of information exists only at the classical level. The QCc is nevertheless quantum mechanical as it uses a highly entangled cluster state as the central physical resource. In Chapter 4 we show that there exist nonzero error thresholds for fault-tolerant quantum computation with the QCc. Further, we outline the concept of checksums in the context of the QCc which may become an element in future practicable and adequate methods for fault-tolerant QCc-computation.In dieser Dissertation beschreiben wir den Einweg-Quantenrechner (QCc), ein Schema zum universellen Quantenrechnen, das allein aus Einteilchenmessungen an einem hochgradig verschraenkten Vielteilchenzustand, dem Clusterzustand, besteht. Wir beweisen die Universalitaet des QCc, beschreiben das zugrunde liegende Rechnermodell und zeigen, dass der QCc fehlertolerantes Quantenrechnen erlaubt. In Kapitel 2 zeigen wir, dass der QCc als ein Simulator quantenlogischer Netzwerke aufgefasst werden kann. Damit beweisen wir dessen Universalitaet und stellen den Zusammenhang zum Netzwerkmodel her, welches das verbreitete Model eines Quantenrechners darstellt. Wir weisen auch darauf hin, dass die Beschreibung des QCc als Netzwerksimulator nicht in jeder Hinsicht passend ist. In Kapitel 3 leiten wir das dem Einweg-Quantenrechner zugrunde liegende Rechnermodell her. Es ist sehr verschieden vom Netzwerkmodell des Quantenrechners. Der QCc besitzt keinen Quanten-Input, keinen Quanten-Output und kein Quantenregister. Unitaere Quantengatter aus einem universellen Satz sind nicht die elementaren Bestandteile von QCc-Quantenalgorithmen. Darueber hinaus sind die Messergebnisse aus den Einteilchenmessungen die einzige Information, die vom QCc verarbeitet wird, und somit existiert Informationsverarbeitung beim QCc nur auf klassischem Niveau. Dennoch arbeitet der QCc fundamental quantenmechanisch, da er den hochverschraenkten Clusterzustand als zentrale physikalische Resource nutzt. In Kapitel 4 zeigen wir, dass positive Fehlerschranken fuer das fehlertolerante Quantenrechnen mit dem QCc existieren. Desweiteren skizzieren wir das Konzept der Pr{"u}fsummen im Zusammenhang mit dem QC, das ein Element zukuenfitiger praktikabler und zweckmaessiger Methoden fuer fehlertolerantes QCc-Quantenrechnen werden kann

Operational Research and Machine Learning Applied to Transport Systems

The New Economy, environmental sustainability and global competitiveness drive inno- vations in supply chain management and transport systems. The New Economy increases the amount and types of products that can be delivered directly to homes, challenging the organisation of last-mile delivery companies. To keep up with the challenges, deliv- ery companies are continuously seeking new innovations to allow them to pack goods faster and more efficiently. Thus, the packing problem has become a crucial factor and solving this problem effectively is essential for the success of good deliveries and logistics. On land, rail transportation is known to be the most eco-friendly transport system in terms of emissions, energy consumption, land use, noise levels, and quantities of people and goods that can be moved. It is difficult to apply innovations to the rail industry due to a number of reasons: the risk aversion nature, the high level of regulations, the very high cost of infrastructure upgrades, and the natural monopoly of resources in many countries. In the UK, however, in 2018 the Department for Transport published the Joint Rail Data Action Plan, opening some rail industry datasets for researching purposes. In line with the above developments, this thesis focuses on the research of machine learning and operational research techniques in two main areas: improving packing operations for logistics and improving various operations for passenger rail. In total, the research in this thesis will make six contributions as detailed below. The first contribution is a new mathematical model and a new heuristic to solve the Multiple Heterogeneous Knapsack Problem, giving priority to smaller bins and consid- ering some important container loading constraints. This problem is interesting because many companies prefer to deal with smaller bins as they are less expensive. Moreover, giving priority to filling small bins (rather than large bins) is very important in some industries, e.g. fast-moving consumer goods. The second contribution is a novel strategy to hybridize operational research with ma- chine learning to estimate if a particular packing solution is feasible in a constant O(1) computational time. Given that traditional feasibility checking for packing solutions is an NP-Hard problem, it is expected that this strategy will significantly save time and computational effort. The third contribution is an extended mathematical model and an algorithm to apply the packing problem to improving the seat reservation system in passenger rail. The problem is formulated as the Group Seat Reservation Knapsack Problem with Price on Seat. It is an extension of the Offline Group Seat Reservation Knapsack Problem. This extension introduces a profit evaluation dependent on not only the space occupied, but also on the individual profit brought by each reserved seat. The fourth contribution is a data-driven method to infer the feasible train routing strate- gies from open data in the United Kingdom rail network. Briefly, most of the UK network is divided into sections called berths, and the transition point from one berth to another is called a berth step. There are sensors at berth steps that can detect the movement when a train passes by. The result of the method is a directed graph, the berth graph, where each node represents a berth and each arc represents a berth-step. The arcs rep- resent the feasible routing strategies, i.e. where a train can move from one berth. A connected path between two berths represents a connected section of the network. The fifth contribution is a novel method to estimate the amount of time that a train is going to spend on a berth. This chapter compares two different approaches, AutoRe- gressive Moving Average with Recurrent Neural Networks, and analyse the pros and cons of each choice with statistical analyses. The method is tested on a real-world case study, one berth that represent a busy junction in the Merseyside region. The sixth contribution is an adaptive method to forecast the running time of a train journey using the Gated Recurrent Units method. The method exploits the TD’s berth information and the berth graph. The case-study adopted in the experimental tests is the train network in the Merseyside region

Applications of MATLAB in Science and Engineering

The book consists of 24 chapters illustrating a wide range of areas where MATLAB tools are applied. These areas include mathematics, physics, chemistry and chemical engineering, mechanical engineering, biological (molecular biology) and medical sciences, communication and control systems, digital signal, image and video processing, system modeling and simulation. Many interesting problems have been included throughout the book, and its contents will be beneficial for students and professionals in wide areas of interest

Advances in Computer Science and Engineering

The book Advances in Computer Science and Engineering constitutes the revised selection of 23 chapters written by scientists and researchers from all over the world. The chapters cover topics in the scientific fields of Applied Computing Techniques, Innovations in Mechanical Engineering, Electrical Engineering and Applications and Advances in Applied Modeling

MIMO Systems

In recent years, it was realized that the MIMO communication systems seems to be inevitable in accelerated evolution of high data rates applications due to their potential to dramatically increase the spectral efficiency and simultaneously sending individual information to the corresponding users in wireless systems. This book, intends to provide highlights of the current research topics in the field of MIMO system, to offer a snapshot of the recent advances and major issues faced today by the researchers in the MIMO related areas. The book is written by specialists working in universities and research centers all over the world to cover the fundamental principles and main advanced topics on high data rates wireless communications systems over MIMO channels. Moreover, the book has the advantage of providing a collection of applications that are completely independent and self-contained; thus, the interested reader can choose any chapter and skip to another without losing continuity