Formal Context Generation using Dirichlet Distributions

We suggest an improved way to randomly generate formal contexts based on Dirichlet distributions. For this purpose we investigate the predominant way to generate formal contexts, a coin-tossing model, recapitulate some of its shortcomings and examine its stochastic model. Building up on this we propose our Dirichlet model and develop an algorithm employing this idea. By comparing our generation model to a coin-tossing model we show that our approach is a significant improvement with respect to the variety of contexts generated. Finally, we outline a possible application in null model generation for formal contexts.Comment: 16 pages, 7 figure

Survey of the State of the Art in Natural Language Generation: Core tasks, applications and evaluation

This paper surveys the current state of the art in Natural Language Generation (NLG), defined as the task of generating text or speech from non-linguistic input. A survey of NLG is timely in view of the changes that the field has undergone over the past decade or so, especially in relation to new (usually data-driven) methods, as well as new applications of NLG technology. This survey therefore aims to (a) give an up-to-date synthesis of research on the core tasks in NLG and the architectures adopted in which such tasks are organised; (b) highlight a number of relatively recent research topics that have arisen partly as a result of growing synergies between NLG and other areas of artificial intelligence; (c) draw attention to the challenges in NLG evaluation, relating them to similar challenges faced in other areas of Natural Language Processing, with an emphasis on different evaluation methods and the relationships between them.Comment: Published in Journal of AI Research (JAIR), volume 61, pp 75-170. 118 pages, 8 figures, 1 tabl

Siting Power Plants: Recent Experience in California and Best Practices in Other States

Compares California's power plant siting with results in other states. Includes interviews with California state agency representatives, developers and process mediators. Part of a series of research reports that examines energy issues facing California

DeepGauge: Multi-Granularity Testing Criteria for Deep Learning Systems

Deep learning (DL) defines a new data-driven programming paradigm that constructs the internal system logic of a crafted neuron network through a set of training data. We have seen wide adoption of DL in many safety-critical scenarios. However, a plethora of studies have shown that the state-of-the-art DL systems suffer from various vulnerabilities which can lead to severe consequences when applied to real-world applications. Currently, the testing adequacy of a DL system is usually measured by the accuracy of test data. Considering the limitation of accessible high quality test data, good accuracy performance on test data can hardly provide confidence to the testing adequacy and generality of DL systems. Unlike traditional software systems that have clear and controllable logic and functionality, the lack of interpretability in a DL system makes system analysis and defect detection difficult, which could potentially hinder its real-world deployment. In this paper, we propose DeepGauge, a set of multi-granularity testing criteria for DL systems, which aims at rendering a multi-faceted portrayal of the testbed. The in-depth evaluation of our proposed testing criteria is demonstrated on two well-known datasets, five DL systems, and with four state-of-the-art adversarial attack techniques against DL. The potential usefulness of DeepGauge sheds light on the construction of more generic and robust DL systems.Comment: The 33rd IEEE/ACM International Conference on Automated Software Engineering (ASE 2018

Extending a network-of-elaborations representation to polyphonic music: Schenker and species counterpoint.

A system of representing melodies as a network of elaborations has been developed, and used as the basis for software which generates melodies in response to the movements of a dancer. This paper examines the issues of extending this representation system to polyphonic music, and of deriving a structural representation of this kind from a musical score. The theories of Heinrich Schenker and of Species Counterpoint are proposed as potentially fruitful bases

Generating multimedia presentations: from plain text to screenplay

In many Natural Language Generation (NLG) applications, the output is limited to plain text – i.e., a string of words with punctuation and paragraph breaks, but no indications for layout, or pictures, or dialogue. In several projects, we have begun to explore NLG applications in which these extra media are brought into play. This paper gives an informal account of what we have learned. For coherence, we focus on the domain of patient information leaflets, and follow an example in which the same content is expressed first in plain text, then in formatted text, then in text with pictures, and finally in a dialogue script that can be performed by two animated agents. We show how the same meaning can be mapped to realisation patterns in different media, and how the expanded options for expressing meaning are related to the perceived style and tone of the presentation. Throughout, we stress that the extra media are not simple added to plain text, but integrated with it: thus the use of formatting, or pictures, or dialogue, may require radical rewording of the text itself

On the enumeration of closures and environments with an application to random generation

Environments and closures are two of the main ingredients of evaluation in lambda-calculus. A closure is a pair consisting of a lambda-term and an environment, whereas an environment is a list of lambda-terms assigned to free variables. In this paper we investigate some dynamic aspects of evaluation in lambda-calculus considering the quantitative, combinatorial properties of environments and closures. Focusing on two classes of environments and closures, namely the so-called plain and closed ones, we consider the problem of their asymptotic counting and effective random generation. We provide an asymptotic approximation of the number of both plain environments and closures of size $n$. Using the associated generating functions, we construct effective samplers for both classes of combinatorial structures. Finally, we discuss the related problem of asymptotic counting and random generation of closed environemnts and closures

Current and forthcoming issues in the South African electricity sector

One of the contentious issues in electricity reform is whether there are significant gains from restructuring systems that are moderately well run. South Africa's electricity system is a case in point. The sector's state-owned utility, Eskom, has been generating some of the lowest-priced electricity in the world, has largely achieved revenue adequacy, and has financed the bulk of the government's ambitious electrification program. Moreover, the key technical performance indicators of Eskom's generation plants have reached world-class levels. Yet the sector is confronted today with serious challenges. South Africa's electricity system is currently facing a tight demand/supply balance, and the distribution segment of the industry is in serious financial trouble. This paper provides a careful diagnostic assessment of the industry and identifies a range of policy and restructuring options to improve its performance. It suggests removing distribution from municipal control and privatizing it, calls for vertical and horizontal unbundling, and argues that the cost-benefit analysis of different structural options should focus on investment incentives and not just current operating efficiency.Energy Production and Transportation,Electric Power,Environment and Energy Efficiency,Energy and Environment,Infrastructure Economics