The Smart Paradox : Stimulate the deployment of Smart grids with effective regulatory instruments

The concept of SG (Smart Grids) encompasses a set of technologies that raise the intelligence of the electrical networks, such as smart meters or instruments of communication, sensing and auto-correction of networks. Nevertheless, the cost is still an important obstacle for the transformation of the current electricity system into a smarter one. Regulation can have an important role in setting up a favorable framework that fosters investments. However, the novelty with SG is the disembodied character of the technology, which may change the incentives of the regulated network companies to invest, affecting the effectiveness of the regulatory instruments (“cost plus” or “price cap”). This paper demonstrates that the solution to this “Smart” paradox requires strong incentive regulation mechanisms able to stimulate the adoption of SG technologies. Moreover, the regulation should not jeopardize conventional investments that are unable to be substituted by SG. Thus, a combination of performance regulation and efficiency obligations may be necessary.

An exploration of students’ perceptions and attitudes towards creativity in engineering education

Thesis (Master, Mechanical and Materials Engineering) -- Queen's University, 2016-09-29 17:45:16.051

The Bereaved Post-9/11 Orphan Boy : Representing (and Relativizing) Crisis and Healing, Tradition and Invention

This article compares the sorrowing child in Jonathan Safran Foer’s Extremely Loud and Incredibly Close (2005) and Brian Selznick’s The Invention of Hugo Cabret (2007), which break traditional novelistic frames through their use of visual material. Through their employment of the orphan figure and their inventive, experimental formal aspects, both Foer’s and Selznick’s novels work as interventions in the debate about the role of fiction after 9/11. Steering clear of a never-ending state of orphanhood, or a return to the nuclear family ideal of the 1950s, they offer different solutions to the family crisis triggered by the loss of a father in a burning building, and, by extension, to the national crisis triggered by 9/11. The bond between father and son that the novels portray represents an affective masculinity that is in line with the emotional narrative work that the two orphan boys perform in the plot and for the readers, which is similar to that of orphan girls in earlier American fiction. In addition to fulfilling the time-honored function of the orphan healing the adult world in a crisis-laden present, Foer’s Oskar and Selznick’s Hugo are post-9/11 “inventions” that highlight the uses of invention in a post-9/11 world.

A fast malware feature selection approach using a hybrid of multi-linear and stepwise binary logistic regression

Malware replicates itself and produces offspring with the same characteristics but different signatures by using code obfuscation techniques. Current generation anti-virus engines employ a signature-template type detection approach where malware can easily evade existing signatures in the database. This reduces the capability of current anti-virus engines in detecting malware. In this paper, we propose a stepwise binary logistic regression-based dimensionality reduction techniques for malware detection using application program interface (API) call statistics. Finding the most significant malware feature using traditional wrapper-based approaches takes an exponential complexity of the dimension (m) of the dataset with a brute-force search strategies and order of (m-1) complexity with a backward elimination filter heuristics. The novelty of the proposed approach is that it finds the worst case computational complexity which is less than order of (m-1). The proposed approach uses multi-linear regression and the p-value of each individual API feature for selection of the most uncorrelated and significant features in order to reduce the dimensionality of the large malware data and to ensure the absence of multi-collinearity. The stepwise logistic regression approach is then employed to test the significance of the individual malware feature based on their corresponding Wald statistic and to construct the binary decision the model. When the selected most significant APIs are used in a decision rule generation systems, this approach not only reduces the tree size but also improves classification performance. Exhaustive experiments on a large malware data set show that the proposed approach clearly exceeds the existing standard decision rule, support vector machine-based template approach with complete data and provides a better statistical fitness.

Urban Agriculture Oriented towards Self-Supply, Social and Commercial Purpose: A Typology

Urban agriculture, a dynamic multifunctional phenomenon, affects the spatial diversification of urban land use, its valorization and its governance. Literature acknowledges its contribution to the development of sustainable cities. The dimension and extent of this contribution depends significantly on the particular form and function of urban agriculture. However, the complexity of interests and dimensions is insufficiently covered by theory. This paper proposes a typology for urban agriculture, supporting both theory building and practical decision processes. We reviewed and mapped the diversity of the types of agriculture found along three beneficial dimensions (self-supply, socio-cultural, commercial) for product distribution scale and actors. We distinguish between ideal types, subtypes and mixed types. Our intention is to include a dynamic perspective in the typology of urban agricultural land use because transition processes between types are observable due to the existence of complex motivations and influences. In a pilot study of 52 urban agriculture initiatives in Germany, we tested the validity of the typology and discussed it with stakeholders, proving novelty and relevance for profiling discussions.

Epistemic, Ontic, Axiologic, and Praxic Constructs in Knowledge Organization Research

The work of knowledge organization requires a particular set of tools. For instance we need standards of content description like Anglo-American Cataloging Rules Edition 2, Resource Description and Access (RDA), Cataloging Cultural Objects, and Describing Archives: A Content Standard. When we intellectualize the process of knowledge organization – that is when we do basic theoretical research in knowledge organization we need another set of tools. For this latter exercise we need constructs. Constructs are ideas with many conceptual elements, largely considered subjective. They allow us to be inventive as well as allow us to see a particular point of view in knowledge organization. For example, Patrick Wilson’s ideas of exploitative control and descriptive control, or S. R. Ranganathan’s fundamental categories are constructs. They allow us to identify functional requirements or operationalizations of functional requirements, or at least come close to them for our systems and schemes. They also allow us to carry out meaningful evaluation.What is even more interesting, from a research point of view, is that constructs once offered to the community can be contested and reinterpreted and this has an affect on how we view knowledge organization systems and processes. Fundamental categories are again a good example in that some members of the Classification Research Group (CRG) argued against Ranganathan’s point of view. The CRG posited more fundamental categories than Ranganathan’s five, Personality, Matter, Energy, Space, and Time (Ranganathan, 1967). The CRG needed significantly more fundamental categories for their work.1 And these are just two voices in this space we can also consider the fundamental categories of Johannes Kaiser (1911), Shera and Egan, Barbara Kyle (Vickery, 1960), and Eric de Grolier (1962). We can also reference contemporary work that continues comparison and analysis of fundamental categories (e.g., Dousa, 2011).In all these cases we are discussing a construct. The fundamental category is not discovered; it is constructed by a classificationist. This is done because it is useful in engaging in the act of classification. And while we are accustomed to using constructs or debating their merit in one knowledge organization activity or another, we have not analyzed their structure, nor have we created a typology. In an effort to probe the epistemological dimension of knowledge organization, we think it would be a fruitful exercise to do this. This is because we might benefit from clarity around not only our terminology, but the manner in which we talk about our terminology. We are all creative workers examining what is available to us, but doing so through particular lenses (constructs) identifying particular constructs. And by knowing these and being able to refer to these we would consider a core competency for knowledge organization researchers.

Authentification biométrique par dynamique de frappe pour évaluation à distance utilisant SVM à une classe

La machine à vecteurs de support à une classe est un algorithme non-supervisé qui est capable d’apprendre une fonction de décision à partir de données d’une seule classe pour la détection d’anomalie. Avec les données d’entraînement d’une seule classe, elle peut identifier si une nouvelle donnée est similaire à l’ensemble d’entraînement. Dans ce mémoire, nous nous intéressons à la reconnaissance de forme de dynamique de frappe par la machine à vecteurs de support à une classe, pour l’authentification d’étudiants dans un système d’évaluation sommative à distance à l’Université Laval. Comme chaque étudiant à l’Université Laval possède un identifiant court, unique qu’il utilise pour tout accès sécurisé aux ressources informatiques, nous avons choisi cette chaîne de caractères comme support à la saisie de dynamique de frappe d’utilisateur pour construire notre propre base de données. Après avoir entraîné un modèle pour chaque étudiant avec ses données de dynamique de frappe, on veut pouvoir l’identifier et éventuellement détecter des imposteurs. Trois méthodes pour la classification ont été testées et discutées. Ainsi, nous avons pu constater les faiblesses de chaque méthode dans ce système. L’évaluation des taux de reconnaissance a permis de mettre en évidence leur dépendance au nombre de signatures ainsi qu’au nombre de caractères utilisés pour construire les signatures. Enfin, nous avons montré qu’il existe des corrélations entre le taux de reconnaissance et la dispersion dans les distributions des caractéristiques des signatures de dynamique de frappe.