The Maunakea Spectroscopic Explorer Book 2018

(Abridged) This is the Maunakea Spectroscopic Explorer 2018 book. It is intended as a concise reference guide to all aspects of the scientific and technical design of MSE, for the international astronomy and engineering communities, and related agencies. The current version is a status report of MSE's science goals and their practical implementation, following the System Conceptual Design Review, held in January 2018. MSE is a planned 10-m class, wide-field, optical and near-infrared facility, designed to enable transformative science, while filling a critical missing gap in the emerging international network of large-scale astronomical facilities. MSE is completely dedicated to multi-object spectroscopy of samples of between thousands and millions of astrophysical objects. It will lead the world in this arena, due to its unique design capabilities: it will boast a large (11.25 m) aperture and wide (1.52 sq. degree) field of view; it will have the capabilities to observe at a wide range of spectral resolutions, from R2500 to R40,000, with massive multiplexing (4332 spectra per exposure, with all spectral resolutions available at all times), and an on-target observing efficiency of more than 80%. MSE will unveil the composition and dynamics of the faint Universe and is designed to excel at precision studies of faint astrophysical phenomena. It will also provide critical follow-up for multi-wavelength imaging surveys, such as those of the Large Synoptic Survey Telescope, Gaia, Euclid, the Wide Field Infrared Survey Telescope, the Square Kilometre Array, and the Next Generation Very Large Array.Comment: 5 chapters, 160 pages, 107 figure

An Algorithmic Taxonomy of Production System Machines

This paper presents a survey of computer architectures designed to execute production systems. After a brief description of production systems and production system languages, the paper summarizes match algorithms, particularly the Rete algorithm, and outlines suggested parallelizations. Most parallel production system algorithms have as their unit of sequential computation a single production's left-hand side, activations of a single Rete node, a single activation of a Rete node, or a single comparison in a Rete node. The paper discusses a number of proposed production system machine architectures in terms of the parallel and sequential computations performed in the algorithms suggested for each machine. A taxonomy of parallel production system algorithms, describing in detail the distribution and replication of data and computations, concludes the paper

Private Enterprise for Public Health: Opportunities for Business to Improve Women's and Children's Health

This guide, developed by FSG and published by the Innovation Working Group in support of the global Every Woman, Every Child effort, explores how companies can create shared value in women's and children's health. The document sets out opportunities for multiple different industries to develop new product and services, improve delivery systems and strengthen health systems that can support global efforts to save 16 million women's and children's lives between now and 2015. It particularly notes that companies need not wait for health services to "catch up" with their economic model, but rather they can work proactively to help accelerate change, by partnering with other industries, civil society and the public sector to create collective impact in a specific location. The aim of the guide is to catalyze these transformative partnerships

Application of computational intelligence to explore and analyze system architecture and design alternatives

Systems Engineering involves the development or improvement of a system or process from effective need to a final value-added solution. Rapid advances in technology have led to development of sophisticated and complex sensor-enabled, remote, and highly networked cyber-technical systems. These complex modern systems present several challenges for systems engineers including: increased complexity associated with integration and emergent behavior, multiple and competing design metrics, and an expansive design parameter solution space. This research extends the existing knowledge base on multi-objective system design through the creation of a framework to explore and analyze system design alternatives employing computational intelligence. The first research contribution is a hybrid fuzzy-EA model that facilitates the exploration and analysis of possible SoS configurations. The second contribution is a hybrid neural network-EA in which the EA explores, analyzes, and evolves the neural network architecture and weights. The third contribution is a multi-objective EA that examines potential installation (i.e. system) infrastructure repair strategies. The final contribution is the introduction of a hierarchical multi-objective evolutionary algorithm (MOEA) framework with a feedback mechanism to evolve and simultaneously evaluate competing subsystem and system level performance objectives. Systems architects and engineers can utilize the frameworks and approaches developed in this research to more efficiently explore and analyze complex system design alternatives --Abstract, page iv

Tuning compilations by multi-objective optimization: Application to Apache web server

Modern compilers present a great and ever increasing number of options which can modify the features and behavior of a compiled program. Many of these options are often wasted due to the required comprehensive knowledge about both the underlying architecture and the internal processes of the compiler. In this context, it is usual, not having a single design goal but a more complex set of objectives. In addition, the dependencies between different goals are difficult to be a priori inferred. This paper proposes a strategy for tuning the compilation of any given application. This is accomplished by using an automatic variation of the compilation options by means of multi-objective optimization and evolutionary computation commanded by the NSGA-II algorithm. This allows finding compilation options that simultaneously optimize different objectives. The advantages of our proposal are illustrated by means of a case study based on the well-known Apache web server. Our strategy has demonstrated an ability to find improvements up to 7.5% and up to 27% in context switches and L2 cache misses, respectively, and also discovers the most important bottlenecks involved in the application performance

Manipulation of Online Reviews: Analysis of Negative Reviews for Healthcare Providers

There is a growing reliance on online reviews in today’s digital world. As the influence of online reviews amplified in the competitive marketplace, so did the manipulation of reviews and evolution of fake reviews on these platforms. Like other consumer-oriented businesses, the healthcare industry has also succumbed to this phenomenon. However, health issues are much more personal, sensitive, complicated in nature requiring knowledge of medical terminologies and often coupled with myriad of interdependencies. In this study, we collated the literature on manipulation of online reviews, identified the gaps and proposed an approach, including validation of negative reviews of the 500 doctors from three different states: New York and Arizona in USA and New South Wales in Australia from the RateMDs website. The reviews of doctors was collected, which includes both numerical star ratings (1-low to 5-high) and textual feedback/comments. Compared to other existing research, this study will analyse the textual feedback which corresponds to the clinical quality of doctors (helpfulness and knowledge criteria) rather than process quality experiences. Our study will explore pathways to validate the negative reviews for platform provider and rank the doctors accordingly to minimise the risks in healthcare

Value Creation in Cryptocurrency Networks: Towards A Taxonomy of Digital Business Models for Bitcoin Companies

Cryptocurrency networks have given birth to a diversity of start-ups and attracted a huge influx of venture capital to invest in these start-ups for creating and capturing value within and between such networks. Synthesizing strategic management and information systems (IS) literature, this study advances a unified theoretical framework for identifying and investigating how cryptocurrency companies configure value through digital business models. This framework is then employed, via multiple case studies, to examine digital business models of companies within the bitcoin network. Findings suggest that companies within the bitcoin network exhibits six generic digital business models. These six digital business models are in turn driven by three modes of value configurations with their own distinct logic for value creation and mechanisms for value capturing. A key finding of this study is that value-chain and value-network driven business models commercialize their products and services for each value unit transfer, whereas commercialization for value-shop driven business models is realized through the subsidization of direct users by revenue generating entities. This study contributes to extant literature on value configurations and digital businesses models within the emerging and increasingly pervasive domain of cryptocurrency networks

Electrical doping of charge carrier injection and extraction layers for solution processed organic optoelectronic devices

In this work different charge transport materials are p- and n-doped by different doping reactions, processed from solution. The doping and its efficiency is characterized by different methods. Additionally crosslinkable polymers are p-doped and compared with their corresponding non-crosslinkable polymeric and low-molecular counterpart

A Comprehensive Review of Control Strategies and Optimization Methods for Individual and Community Microgrids

© 2022 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes,creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.Community Microgrid offers effective energy harvesting from distributed energy resources and efficient energy consumption by employing an energy management system (EMS). Therefore, the collaborative microgrids are essentially required to apply an EMS, underlying an operative control strategy in order to provide an efficient system. An EMS is apt to optimize the operation of microgrids from several points of view. Optimal production planning, optimal demand-side management, fuel and emission constraints, the revenue of trading spinning and non-spinning reserve capacity can effectively be managed by EMS. Consequently, the importance of optimization is explicit in microgrid applications. In this paper, the most common control strategies in the microgrid community with potential pros and cons are analyzed. Moreover, a comprehensive review of single objective and multi-objective optimization methods is performed by considering the practical and technical constraints, uncertainty, and intermittency of renewable energies sources. The Pareto-optimal solution as the most popular multi-objective optimization approach is investigated for the advanced optimization algorithms. Eventually, feature selection and neural network-based clustering algorithms in order to analyze the Pareto-optimal set are introduced.This work was supported by the Spanish Ministerio de Ciencia, Innovación y Universidades (MICINN)–Agencia Estatal de Investigación (AEI), and by the European Regional Development Funds (ERDF), a way of making Europe, under Grant PGC2018-098946-B-I00 funded by MCIN/AEI/10.13039/501100011033/.Peer ReviewedPostprint (published version

Thieno[3,2-b]thiophene based conjugated polymers for high performance organic photovoltaic and field effect transistor applications

The design, synthesis and characterisation of thirteen new semiconducting polymers for use in organic photovoltaic (OPV) and field effect transistor (OFET) devices are reported. The rational design of each polymer is discussed and their structures related to their varying chemical and physical properties, which are further used to rationalise the specific device performances. Various structural modifications are investigated with a focus on the electron-deficient bis-lactam structures diketopyrrolopyrrole (DPP) and isoindigo, that are flanked by thieno[3,2-b]thiophene donor groups. Alkyl chain optimisation of thieno[3,2-b]thiophene diketopyrrolopyrrole (DPPTT) based co-polymers was thoroughly examined and it was found that increased alkyl chain size affords improved solubility and a wider range of accessible co-monomer units. Exploiting this improved solubility, the new DPPTT-T polymer was fractionated using recycling gel permeation chromatography (GPC). This gave fractions with increased molecular weights and narrowed mass distributions resulting in OPV power conversion efficiency (PCE) ehancements of greater than 50 %. Continuing with DPPTT-T alkyl chains, a new OPV structural design consideration is introduced in which the alkyl chain branching position is systematically moved further from the polymer backbone. This resulted in higher molecular weight polymers with stronger π - π interactions and significantly enhanced device performances due to increased intermolecular interactions, with PCEs in excess of 8 %. Using the new higher performing branched alkyl chains the role of differing chalcogenophene co-monomers OPV devices was also investigated and was found that increased heteroatomic size, from thiophene to selenophene to tellurophene, resulted in narrowed optical band gaps and increased heteroatom – heteroatom interchain interactions. When these differences are taken into consideration, thiophene is shown to be the highest performing chalcogenophene comonomer of the series. Moving to isoindigo, a new thieno[3,2-b]thiophene flanked structure (iITT) was designed and synthesised for the first time. The resultant narrow band gap co-polymers were shown to be excellent candidate materials for ambipolar OFET applications. Through a comparative literature and computational study, the new iITT unit is shown to be one of the highest performing units within this family of polymer structures.Open Acces