Assessing the potential for knowledge-based development in transition countries

This Working Paper by Bruegel Senior Fellow Reinhilde Veugelers examines the potential for a knowledge-based growth path in transition countries of central and eastern Europe, the Caucasus and Central Asia. The paper looks closely at how total-factor productivity, a residual growth factor commonly interpreted as reflecting technological progress, drives growth rates in these economies which exhibit a much lower GDP per capita compared to the EU15 or the United States.  By analysing the prerequisites for knowledge-based growth, the author explains why transition countries are at a systemic disadvantage relative to the EU15, US and Japan and have limited potential for knowledge-based growth.

Measuring Information Security Awareness Efforts in Social Networking Sites – A Proactive Approach

For Social Network Sites to determine the effectiveness of their Information Security Awareness (ISA) techniques, many measurement and evaluation techniques are now in place to ensure controls are working as intended. While these techniques are inexpensive, they are all incident- driven as they are based on the occurrence of incident(s). Additionally, they do not present a true reflection of ISA since cyber-incidents are hardly reported. They are therefore adjudged to be post-mortem and risk permissive, the limitations that are inacceptable in industries where incident tolerance level is low. This paper aims at employing a non-incident statistic approach to measure ISA efforts. Using an object- oriented programming approach, PhP is employed as the coding language with MySQL database engine at the back-end to develop sOcialistOnline – a Social Network Sites (SNS) fully secured with multiple ISA techniques. Rather than evaluating the effectiveness of ISA efforts by success of attacks or occurrence of an event, password scanning is implemented to proactively measure the effects of ISA techniques in sOcialistOnline. Thus, measurement of ISA efforts is shifted from detective and corrective to preventive and anticipatory paradigms which are the best forms of information security approach

Knowledge-based economy

The European Union is resorting to long-term multi-annual political and economical plans. The current set of plans, “Horizons 2020”, also involves restructuring the educational system, as in the Bologna system. The idea behind it is that education should help industry to win the competitive battle with other major economical blocks. The idea is best described by the adage of the European Union of developing a so-called “knowledge-based economy”. It implies that education is a form of investment. We should educate people – the society should spend effort on educating people – in order for society to make profit on it. Contrasting this is the idea of education as a consumption good. In the latter, people study to become knowledgeable, since knowledge makes a person happy. We discuss here the dissident view why an educational system that is for investment-only will at the end not bear fruit and will destroy science, creativity and eventually any form of competitiveness in the economy. It will lead to moral as well as financial bankruptcy.info:eu-repo/semantics/publishedVersio

Knowledge-based spatiotemporal linear abstraction

We present a theoretical framework and a case study for reusing the same conceptual and computational methodology for both temporal abstraction and linear (unidimensional) space abstraction, in a domain (evaluation of traffic-control actions) significantly different from the one (clinical medicine) in which the method was originally used. The method, known as knowledge-based temporal abstraction, abstracts high-level concepts and patterns from time-stamped raw data using a formal theory of domain-specific temporal-abstraction knowledge. We applied this method, originally used to interpret time-oriented clinical data, to the domain of traffic control, in which the monitoring task requires linear pattern matching along both space and time. First, we reused the method for creation of unidimensional spatial abstractions over highways, given sensor measurements along each highway measured at the same time point. Second, we reused the method to create temporal abstractions of the traffic behavior, for the same space segments, but during consecutive time points. We defined the corresponding temporal-abstraction and spatial-abstraction domain-specific knowledge. Our results suggest that (1) the knowledge-based temporal-abstraction method is reusable over time and unidimensional space as well as over significantly different domains; (2) the method can be generalized into a knowledge-based linear-abstraction method, which solves tasks requiring abstraction of data along any linear distance measure; and (3) a spatiotemporal-abstraction method can be assembled from two copies of the generalized method and a spatial-decomposition mechanism, and is applicable to tasks requiring abstraction of time-oriented data into meaningful spatiotemporal patterns over a linear, decomposable space, such as traffic over a set of highways

Knowledge Based on Seeing

In Epistemological Disjunctivism, Duncan Prichard defends his brand of epistemological disjunctivism from three worries. In this paper I argue that his responses to two of these worries are in tension with one another

Knowledge-based simulation

An architecture for a knowledge-based simulator is described. The task of scheduling represents an area in which such a tool might be applied. More specifically, scheduling for crew and ground support activities for the shuttle and space station would benefit from the application of knowledge-based simulation. The knowledge-based simulator would allow the crew and support personnel to schedule and reschedule activities in a timely and flexible manner in order to examine and test possible plans

Knowledge-based Transfer Learning Explanation

Machine learning explanation can significantly boost machine learning's application in decision making, but the usability of current methods is limited in human-centric explanation, especially for transfer learning, an important machine learning branch that aims at utilizing knowledge from one learning domain (i.e., a pair of dataset and prediction task) to enhance prediction model training in another learning domain. In this paper, we propose an ontology-based approach for human-centric explanation of transfer learning. Three kinds of knowledge-based explanatory evidence, with different granularities, including general factors, particular narrators and core contexts are first proposed and then inferred with both local ontologies and external knowledge bases. The evaluation with US flight data and DBpedia has presented their confidence and availability in explaining the transferability of feature representation in flight departure delay forecasting.Comment: Accepted by International Conference on Principles of Knowledge Representation and Reasoning, 201