Miracle-dz/UniFAR-FTUs huggingface dataset:
Neural network modelling of naturally ventilated spaces

During operation, buildings consume a large amount of energy, in developed countries around 40% of total final energy use. A major challenge is to reduce the amount of energy used while still providing a comfortable environment for building occupants. The use of passive techniques, such as natural ventilation, is promoted in certain climates to provide low energy cooling and ventilation. However, controlling natural ventilation in an effective manner to maintain occupant comfort can be a difficult task, particularly during warm periods. One area which has been identified as having the potential for reducing energy consumption while maintaining occupant comfort is the use of more advanced control techniques and a move towards "intelligent" buildings. A technique which has been much explored in recent years for application in mechanically ventilated buildings is Model Predictive Control (MPC). The essential component of an MPC strategy is the predictive model of the building's thermal dynamics. In this paper a data driven, neural network approach to system modelling is taken to model internal temperatures. Building data from a recently built naturally ventilated school and an office building are used to train multilayer perceptron neural network models and the resulting models performance are examined. The models developed were found to have good prediction capabilities over reasonable prediction horizons; however the effect of the control input was not captured.
Turbogenerator field winding shorted turn detection by AC flux measurement

A new testing technique for detecting shorted turns in turbogenerator rotors is presented, where the field winding is supplied with power frequency voltage as for a normal impedance measurement. The circumferential flux is measured in the centerline of all slot wedges and compared between individual poles by amplitude and/or phase. When the rotor is removed, the turn short can be localized by evaluating the AC flux distribution over turns. The coils may be accessed through ventilation holes or after disassembly of retaining rings. >
Estimating Spatially and Temporally Continuous Bicycle Volumes by Using Sparse Data

Prioritization of networkwide bicycle investments is data limited in the United States. The framework proposed in this paper addresses the temporal factoring of sparse bicycle counts through Markov chain Monte Carlo sampling and introduces a novel spatial factoring method to expand estimates of bicycle usage to all network edges. Bicycle usage varies widely on the basis of weather, infrastructure, trip origin and destination, and cultural expectations, and this variability necessitates more-detailed volume models than those that suffice for automobile use. A multilevel temporal model that includes hourly, weather-related, and commute-day factors maximizes the information obtained from sparse count observations. Spatial factoring then extends these data to cover unobserved streets through Bayesian updating of prior estimates from a regional travel demand model informed by an edge correlation matrix. For a small city in the United States with some manual volunteer bicycle counts and no permanent counting infrastructure, the proposed framework was able to estimate an edge-specific bicycle usage networkwide reasonably and, unlike typical factoring methods, as distributions rather than single values. This rigorous characterization of parameter variance allows planners and software to interpret results appropriately and to avoid the common misconception that all model outputs are equally valid. The framework is globally applicable because it is based on open-source tools and data and will be used in the upcoming long-range plan for the study region. By providing comprehensive safety exposure data, the framework enables networkwide safety prioritization with empirical Bayes methods to allocate scarce funds.
Construction and Application of the Patent Knowledge System for Supporting Product Innovation

Patent which as a carrier of knowledge contains abundant information, is an important resource of supporting innovative design. Based on the analysis and organization of the patent information of mechanical and electrical fields, this article proposes a proprietary database system for product design innovation. Through a combination of TRIZ and FBS solution process, it can provide support in the product design stage. Finally, an example of folding bike design is listed to explain the application of the patent knowledge base.
New generation fluid heating appliance using high-frequency load resonant inverter

This paper presents a prototype setup of an electromagnetic induction-based fluid heating appliance using voltage-fed type series capacitor-compensated load resonant high-frequency inverter. This innovative eddy-current-based continuous moving fluid heating appliance which includes some advantages of high conversion efficiency, high safety as heat exchanger, gentle environment, high-speed heating response, high-reliability is developed as compared with the gas combustion method, the sheath wire and carbon fiber heating methods. In addition to this, specially-designed water-through metallic assemblies to be heated rapidly by electromagnetic induction eddy-current based heating are proposed in this paper. The operating characteristics in steady and dynamic states of this appliance are illustrated and evaluated on the basis of computer simulation and experimental results of 10 kW breadboard appliance developed for a hot water producer as well as superheated steamer and dryer.
Optimally Matched Space-Time Filtering Technique for BFSAR Nonstationary Clutter Suppression

Clutter suppression in synthetic aperture radar (SAR) is one of the urgent and attractive problems in ground moving target indication (GMTI) application. With separate transmitter and receiver, ground clutter is nonstationary in bistatic forward-looking SAR (BFSAR), which directly leads to the inaccurate clutter covariance matrix (CCM) estimation. As a consequence, the traditional space-time adaptive processing (STAP) will suffer from a serious performance deterioration. In this article, an optimally matched space-time filtering (MSTF) technique is proposed to suppress nonstationary clutter for BFSAR systems. The main idea of the proposed method is to directly design and generate a suppression filter in space-time domain, whose space-time frequency response is matched with clutter spectrum. To construct the matched space-time filter, clutter modeling with arbitrary BFSAR configuration is first proposed to acquire space-time information of clutter spectrum. And then, the suppression filter can be designed and the design process is transferred into a constrained optimization problem (COP), according to the obtained clutter space-time information. Finally, the particle swarm optimization (PSO) algorithm is applied to solve the COP and obtain the optimal solution, i.e., the desired matched space-time filter weight, for BFSAR nonstationary clutter suppression. Since the generation of the designed filter circumvents CCM estimation, the proposed method will not be affected by the nonstationary characteristic of BFSAR clutter. In October 2020, the first airborne BFSAR-GMTI experiment in the world has been successfully conducted by us, and the experimental results are given to validate the effectiveness of the proposed method.
Extreme Air-Gap Response below Deck of Floating Structures

This paper presents the findings of a study on the air gap below deck of a typical six-column, double-pontoon semi-submersible in deep water. The writers present a method to predict the extreme air-gap by establishing the distribution of extreme air-gap response. In the case of linear incident wave, the proposed air-gap distribution suggested a better fits compared with that given by Rayleigh distribution. Moreover, the proposed approach is found to be an effective way to predict air-gap extremes within a specified duration. As a comparison, the fractile-based method cum Gumbel distribution is also applied to the same floating structure. Comparisons of the numerical results from these 2 different approaches show strong agreement in extreme air-gap response below deck.
Enhancing public transport passenger experience via mobile-mediated applications and services

Despite the rapidly urbanising population, public transport usage in metropolitan areas is not growing at a level that corresponds to the trend. Many people are reluctant to travel using public transport, as it is commonly associated with unpleasant experiences such as limited services, long wait time, and crowded spaces. This study aims to explore the use of mobile spatial interactions and services, and investigate their potential to increase the enjoyment of our everyday commuting experience. The main goal is to develop and evaluate mobile-mediated design interventions to foster interactions for and among passengers, as well as between passengers and public transport infrastructures, with the aim to positively influence the experience of commuting. Ultimately, this study hopes to generate findings and knowledge towards creating a more enjoyable public transport experience, as well as to explore innovative uses of mobile technologies and context-aware services for the urban lifestyle.
On the Effects of Institutional Arrangements for Innovation in Clusters - A comparative case study of sugar clusters in São Paulo, the North East of Brazil and Cuba.

This thesis explores the effects of institutional arrangements for innovation in clusters. Clusters have become one of the most popular concepts in innovation policy studies in recent years. They have been ascribed as places with structures that reduce transaction costs, and enable innovation processes due to the prevalence of different types of externalities. The focus of this dissertation is on dynamic externalities that support innovation. Five types of externalities that were most frequently prevalent in the literature have been explored, intense competition, knowledge spill-over, specialisation, user-producer learning and joint action. Innovation takes place through interaction and this thesis has explored how cluster externalities can influence innovation depending upon the types of institutional arrangements that govern transactions. Four arrangements have been explored, market, network, quasi hierarchy and state arrangements. A comparative case study of the sugar and ethanol clusters in Sao Paulo, the North East of Brazil and Cuba has been carried out with the purpose to identify how the conceptual pieces relate to each other and whether cluster externalities have been behind the innovation that has taken place in the clusters. The dissertation has found that externalities influence innovation in various ways, which is enabled and influenced by the institutional arrangements and these influence the externalities differently. Arrangements have stronger connection to some externalities than others, e.g. intense competition is enabled by market arrangements and network arrangements are strongly connected to joint action. At the same time some arrangements can prevent externalities or reduce their impact. Of the explored clusters, Sao Paulo is the case where most innovation is taking place. It is the most diversified cluster with regard to specialisation, actors and arrangements and the case where the cluster externalities have been the most widespread, diversified and influential. In the North East of Brazil less innovation has taken place, the cluster is thinner with regard to actors, specialisation and scientific capacity. Innovation in the North East is to a lesser extent the outcome of cluster externalities. There are fewer local networks in place than in Sao Paulo and the ones that exist are less oriented towards enabling innovation. The Cuban cluster is dense with actors, strong competencies in science and technology and knowledge of derivate production. There is equipment and machinery in place, of which some is becoming dated though. The Cuban cluster is more the outcome of national state arrangements and international linkages than cluster externalities. The development of the cluster and innovation is hampered, by the lack of markets and network arrangements. (Less)
Analytical capacitance model for high-speed interconnects with diagonal routing

We propose a novel quasi-3D capacitance model based on an "effective width" (W/sub eff/) concept. The model is derived from a new analytical 2D model combined with a 3D "wall-to-wall" approach. With W/sub eff/, complicated 3D structures are readily interpreted as a combination of consecutive 2D structures, leading to efficient capacitance extraction. The analytical 2D model is generated for easy application to recent technology, featuring multilayer dielectric and non-ideal vertical profile. Finally, our model is generalized to diagonal routing and confirmed by comparison with a field solver.
Plant Identification Based on Artificial Intelligence

Species identification plays an important role in botanical research, but traditional identification tool, which mainly depends on reference books or identification keys, is often recognized as a difficult and frustrating task, especially for novices. In recent decades, many efforts have been made by taxonomists and programmers to ease the difficulty of species identification by developing a range of tools that increasingly involved the use of computers. In this paper, new advances of plant identification based on three main artificial intelligent technologies: expert system, artificial neural network, and machine vision are briefly introduced. Several trends of plant identification tools for non-expert users are also proposed in the last part.
Capacity value of offshore wind in Great Britain

The extent to which large volumes of offshore wind can contribute to a secure and reliable electricity supply is the subject of much debate. Central to providing credible answers is a detailed understanding of the wind resource and its variability in time and space. Here, a mesoscale atmospheric model was employed to create a 10 year hindcast of British onshore and offshore wind speeds and simulate the output of a British offshore wind fleet. This enabled estimation of the capacity value of British wind fleets both on- and offshore during periods of high winter demand. It provides a credible estimate of the distinct long-term contribution of production from a future British offshore wind fleet and indicates substantial improvement over onshore wind. Furthermore, a first level analysis demonstrated that the availability of offshore wind farms had a modest negative impact on the capacity value of wind but that conventional generation and demand levels played a more significant role.
Process flexibility under bill of material constraints: part II–structural properties and improving principles

For the manufacturing system that consists of multiple assembly lines, this paper investigates the method of improving its process flexibility under bill of material (BOM) constraints. Based on the flexibility measurement developed in part I, generic characteristics of the capability configuration of assembly lines that ensure it more flexible are first investigated on two hierarchical and highly interrelated levels: the assembly line level and the system level. These characteristics are termed ‘structural properties’ of process flexibility under BOM constraints, which are valuable because they provide an effective way of improving flexibility of the manufacturing system through investing in limited operational flexibility of machines in the assembly lines. According to the obtained structural properties, guidelines for improving process flexibility on the two levels are then developed. The proposed guidelines can help the manager of a manufacturing system to make effective decisions on flexibility improvement without much computation effort. Results of simulation experiments illustrate that the proposed structural properties and guidelines are effective and widely applicable to real manufacturing systems.
Prioritization of Software Requirements: a Cognitive Approach

This approach provides a novel methodology for addressing a well-known problem of Software Engineering, the prioritization of software requirements. The proposal combines the use of tools such as the Analytic Hierarchy Process (AHP), the Self-Organizing Maps (SOM) and also methods belonging to the Cognitive Psychology to build a Conceptual Framework to assess the knowledge level that stakeholders have of the domain of the software application. Hence the cognitive paradigm helps to interpret the stakeholders clusters, built up with their preferences on the prioritization of the software requirements.
Comparison of methods of locating and tracking cellular mobiles

The paper presented a comparison of some of the current techniques used for mobile location in a cellular system. It highlighted the problem of multipath fading in providing accurate estimations of time and angle of arrival and it compared the effect of location geometry on the time of arrival (TOA) and angle of arrival (AOA) in terms of their GDOP. It illustrated the impact of different AOA estimation techniques such as MUSIC and ESPRIT on the accuracy of AOA estimation. The errors of both TOA and AOA methods are obtained in multipath fading and it is concluded that, for the geometry stated, the AOA is more accurate than the TOA. (6 pages)
The more electric aircraft—assessing the benefits

Abstract The concept of the more electric aircraft (MEA), where electrical power is used for at least some of the on-board functions at present powered by hydraulics and pneumatics, has many claimed benefits and is far from new. However, almost all larger aircraft retain hydraulics and pneumatics. Over recent years there has been a great deal of interest in the MEA concept, with developments in relevant technologies and their adoption in other areas of engineering. In support of UK efforts on this and related concepts, the College of Aeronautics has been performing studies since the mid 1980s to assess the benefits of changes. This paper describes the background to these studies and the relationships between them as well as some of their findings, concluding that it is important that such assessment work should be continued in the future.
Survey and case investigations on application of quality management tools and techniques in SMIs

Quality management (QM) cannot be assured unless some objective assessments are undertaken. A number of tools and techniques are available to conduct such analysis. Although some of them are product or service specific, however, a few basic tools and techniques are commonly used in manufacturing firms. This study focuses on the state of application of QM tools and techniques in small and medium industries (SMIs). The findings reveal that by‐and‐large, lack of methodical analysis is a major weakness of SMIs. Still some rule‐of‐thumb and subjective observations are dominating over objective evaluation in the process of quality control decisions. A few case studies which have been conducted, and one that has been briefly reported here, also support this conclusion. The methodology of the study has three folds: literature review, survey in SMIs and case studies.
Process Management in Public Transit Planning

This paper analyzes a policy-making process and discusses the role of policy process management in a public transit project. There has been no well-organized public transit planning done by local government in Japan, mainly because there is no national program for statutory local public transit planning in Japan. The Toyama light rail transit (LRT) project is one of the exceptional cases in which a local government has tackled local public transit planning. The planning process in this project is unveiled through intensive interviews with local stakeholders. The focus is on the framing recognized by the stakeholders. First, the process is classified into four phases. Next, stakeholder behaviors, the main agenda, the framework recognized by the stakeholders, and meetings in each phase are analyzed. The policy process management of the Toyama city government is examined, and the factors influencing the successful introduction of LRT are discussed from the viewpoint of policy management. In summary, three factors are involved: technology and topography, financial resources, and policy process management. Well-organized policy process management contributes to smooth consensus building; in this case, the process manager made the best use of the technological and topographical and financial factors and consequently guided the stakeholders to a consensus. Finally, the lessons learned from the Toyama LRT case are discussed. The following key factors, each of which influences the policy-making process, are described: appropriate vision setting and strong leadership, meeting management, viewpoint shift under certain constraints, the involvement of experts, and the framing arrangement vis-à-vis individual negotiation.
The Most Magical Way to Teach: Disney Music in the Classroom

The Walt Disney Company, and its subsidiaries, are responsible for some of the most popular movies in existence. One of the things that makes the classic Disney movie unique is its soundtracks. Many of the movies have key songs that can be used to teach various economics concepts in the high school and postsecondary classroom. We provide three detailed lesson plans that outline how to use Disney music to teach foundational concepts, but also include a more extensive table that includes concepts covered in a variety of Disney songs.
Universal filter using two current-feedback amplifiers

A new universal filter using two current-feedback amplifiers is presented. This filter can realise lowpass, bandpass, highpass, notch and allpass filters from the same configuration. It has the following features: orthogonal control of the natural frequency and quality factor by grounded resistors, easy conversion into a voltage-controlled filter, minimum active components, without match components except for allpass applications, low active and passive sensitivities, and cascadability. Experimental results that confirm the theoretical analyses are obtained.
Prioritization of Capacity Investment Projects with Stakeholder Divergence Criteria for Coordinated Infrastructure Development

AbstractInvestments and policies for transportation infrastructure projects are influenced and possibly undermined by diverse stakeholders with limited incentive for coordination. Effective management of such systems requires agencies to prioritize capacity projects with consideration of potential stakeholder-divergence resulting from competing stakeholder values and budgetary constraints. Strategic prioritization of investment should consider the values of several stakeholder perspectives, such as managing agencies, the public, closely associated commerce, environmental agencies, and others. This paper will demonstrate an integrated scenario analysis, multicriteria analysis, and integer-programming approach to identify investment portfolios that meet budgetary constraints while promoting investments most suitable for coordination among diverse stakeholders. The approach will be demonstrated on six high-priority federal transportation infrastructure projects in the United States. The results illustrate th.