Analysis of the economic feasibility and reduction of a building’s energy consumption and emissions when integrating hybrid solar thermal/PV/micro-CHP systems

The aim of this paper is to assess the performance of several designs of hybrid systems composed of solar thermal collectors, photovoltaic panels and natural gas internal combustion engines. The software TRNSYS 17 has been used to perform all the calculations and data processing, as well as an optimisation of the tank volumes through an add-in coupled with the GENOPT® software. The study is carried out by analysing the behaviour of the designed systems and the conventional case in five different locations of Spain with diverse climatic characteristics, evaluating the same building in all cases. Regulators, manufacturers and energy service engineers are the most interested in these results. Two major contributions in this paper are the calculations of primary energy consumption and emissions and the inclusion of a Life Cycle Cost analysis. A table which shows the order of preference regarding those criteria for each considered case study is also included. This was fulfilled in the interest of comparing between the different configurations and climatic zones so as to obtain conclusions on each of them. The study also illustrates a sensibility analysis regarding energy prices. Finally, the exhaustive literature review, the novel electricity consumption profile of the building and the illustration of the influence of the cogeneration engine working hours are also valuable outputs of this paper, developed in order to address the knowledge gap and the ongoing challenges in the field of distributed generation

Marketing management in urban passenger transportation innovations

Purpose: This main aim of the article is to explore possible approaches to innovation marketing management by the example of urban passenger transportation. Design/Methodology/Approach: In modern conditions with the digitalization of the economy enterprises that provide transportation services are aimed at managing through artificial intelligence. Modern transport depends on the preferences of the population, based on philosophy of automation, intellectualization while at the same time is focused on the quality of transportation, elimination of losses and cost reduction. The specifics of marketing activities in the urban passenger transportation market is of particular importance in this study, taking into account the formation of the marketing innovation toolkit in the urban passenger transportation market under these specifics. Findings: A model for innovational marketing management in the urban passenger transportation sector was developed and justified, which includes six key innovation management blocks based on marketing functions: research, forecasting, information, organizational, advertising and practice. Practical implications: In practice, it is about creating a concept necessary for the provision of transport services for passengers transportation, based on the use of innovational marketing. The basic directions for the introduction of innovations at the enterprises of urban passenger transport are proposed. Originality/value: In the field of urban passenger transportation in the digital economy, new opportunities are opening up for development by applying innovational marketing, the practical implementation of which ensures increased efficiency and increases the demand for public transport services.peer-reviewe

Assistive robotic device: evaluation of intelligent algorithms

Assistive robotic devices can be used to help people with upper body disabilities gaining more autonomy in their daily life. Although basic motions such as positioning and orienting an assistive robot gripper in space allow performance of many tasks, it might be time consuming and tedious to perform more complex tasks. To overcome these difficulties, improvements can be implemented at different levels, such as mechanical design, control interfaces and intelligent control algorithms. In order to guide the design of solutions, it is important to assess the impact and potential of different innovations. This paper thus presents the evaluation of three intelligent algorithms aiming to improve the performance of the JACO robotic arm (Kinova Robotics). The evaluated algorithms are 'preset position', 'fluidity filter' and 'drinking mode'. The algorithm evaluation was performed with 14 motorized wheelchair's users and showed a statistically significant improvement of the robot's performance.Comment: 4 page

Time-dependent opportunities in energy business : a comparative study of locally available renewable and conventional fuels

This work investigates and compares energy-related, private business strategies, potentially interesting for investors willing to exploit either local biomass sources or strategic conventional fuels. Two distinct fuels and related power-production technologies are compared as a case study, in terms of economic efficiency: the biomass of cotton stalks and the natural gas. The carbon capture and storage option are also investigated for power plants based on both fuel types. The model used in this study investigates important economic aspects using a "real options" method instead of traditional Discounted Cash Flow techniques, as it might handle in a more effective way the problems arising from the stochastic nature of significant cash flow contributors' evolution like electricity, fuel and CO(2) allowance prices. The capital costs have also a functional relationship with time, thus providing an additional reason for implementing, "real options" as well as the learning-curves technique. The methodology as well as the results presented in this work, may lead to interesting conclusions and affect potential private investment strategies and future decision making. This study indicates that both technologies lead to positive investment yields, with the natural gas being more profitable for the case study examined, while the carbon capture and storage does not seem to be cost efficient with the current CO(2) allowance prices. Furthermore, low interest rates might encourage potential investors to wait before actualising their business plans while higher interest rates favor immediate investment decisions. (C) 2009 Elsevier Ltd. All rights reserved

DeepASL: Enabling Ubiquitous and Non-Intrusive Word and Sentence-Level Sign Language Translation

There is an undeniable communication barrier between deaf people and people with normal hearing ability. Although innovations in sign language translation technology aim to tear down this communication barrier, the majority of existing sign language translation systems are either intrusive or constrained by resolution or ambient lighting conditions. Moreover, these existing systems can only perform single-sign ASL translation rather than sentence-level translation, making them much less useful in daily-life communication scenarios. In this work, we fill this critical gap by presenting DeepASL, a transformative deep learning-based sign language translation technology that enables ubiquitous and non-intrusive American Sign Language (ASL) translation at both word and sentence levels. DeepASL uses infrared light as its sensing mechanism to non-intrusively capture the ASL signs. It incorporates a novel hierarchical bidirectional deep recurrent neural network (HB-RNN) and a probabilistic framework based on Connectionist Temporal Classification (CTC) for word-level and sentence-level ASL translation respectively. To evaluate its performance, we have collected 7,306 samples from 11 participants, covering 56 commonly used ASL words and 100 ASL sentences. DeepASL achieves an average 94.5% word-level translation accuracy and an average 8.2% word error rate on translating unseen ASL sentences. Given its promising performance, we believe DeepASL represents a significant step towards breaking the communication barrier between deaf people and hearing majority, and thus has the significant potential to fundamentally change deaf people's lives

Predicting Tail-related Risk Measures: The Consequences of Using GARCH Filters for non-GARCH Data

We investigate the consequences for value-at-risk and expected short-fall purposes of using a GARCH filter on various mis-specified processes. We show that careful investigation of the adequacy of the GARCH filter is necessary since under mis-specifications a GARCH filter appears to do more harm than good. Using an unconditional non filtered tail estimate appears to perform satisfactorily for dependent data with a degree of dependency corresponding to actual market conditions.Extreme value theory; Value at Risk (VaR); Expected shortfall; GARCH; Markov switching; Jump diffusion; Backtesting.

Innovating Pedagogy 2017: Exploring new forms of teaching, learning and assessment, to guide educators and policy makers. Open University Innovation Report 6

This series of reports explores new forms of teaching, learning and assessment for an interactive world, to guide teachers and policy makers in productive innovation. This sixth report proposes ten innovations that are already in currency but have not yet had a profound influence on education. To produce it, a group of academics at the Institute of Educational Technology in The Open University collaborated with researchers from the Learning In a NetworKed Society (LINKS) Israeli Center of Research Excellence (I-CORE). Themes: • Big-data inquiry: thinking with data • Learners making science • Navigating post-truth societies • Immersive learning • Learning with internal values • Student-led analytics • Intergroup empathy • Humanistic knowledge-building communities • Open Textbooks • Spaced Learnin

Establishing cost-effectiveness of genetic targeting of cancer therapies

The clinical benefit of a new genomic instrument, the 70-gene signature for breast cancer patients, is being evaluated in a randomised clinical trial. The early, controlled implementation process is supported by a Constructive Technology Assessment to help decision-making in an uncertain time of development