Upside-down Deduction

Over the recent years, several proposals were made to enhance database systems with automated reasoning. In this article we analyze two such enhancements based on meta-interpretation. We consider on the one hand the theorem prover Satchmo, on the other hand the Alexander and Magic Set methods. Although they achieve different goals and are based on distinct reasoning paradigms, Satchmo and the Alexander or Magic Set methods can be similarly described by upside-down meta-interpreters, i.e., meta-interpreters implementing one reasoning principle in terms of the other. Upside-down meta-interpretation gives rise to simple and efficient implementations, but has not been investigated in the past. This article is devoted to studying this technique. We show that it permits one to inherit a search strategy from an inference engine, instead of implementing it, and to combine bottom-up and top-down reasoning. These properties yield an explanation for the efficiency of Satchmo and a justification for the unconventional approach to top-down reasoning of the Alexander and Magic Set methods

Program Learning Event on Violence against Children in and around Schools in East Africa

Sponsored by the Elevate Children Funders Group (ECFG), a three-day Program Learning Event (PLE) on Violence against Children in and around Schools (VACiS) held in Kampala, Uganda from 14-16 July 2015, attracted 77 practitioners, donors, advocates, researchers and government representatives in the field of violence against children from Uganda, Tanzania, Kenya, South Africa, Germany, the United Kingdom and United States of America. The theme of the event was developing a common learning agenda on preventing and responding to VACiS

A comparative study of multiple-criteria decision-making methods under stochastic inputs

This paper presents an application and extension of multiple-criteria decision-making (MCDM) methods to account for stochastic input variables. More in particular, a comparative study is carried out among well-known and widely-applied methods in MCDM, when applied to the reference problem of the selection of wind turbine support structures for a given deployment location. Along with data from industrial experts, six deterministic MCDM methods are studied, so as to determine the best alternative among the available options, assessed against selected criteria with a view toward assigning confidence levels to each option. Following an overview of the literature around MCDM problems, the best practice implementation of each method is presented aiming to assist stakeholders and decision-makers to support decisions in real-world applications, where many and often conflicting criteria are present within uncertain environments. The outcomes of this research highlight that more sophisticated methods, such as technique for the order of preference by similarity to the ideal solution (TOPSIS) and Preference Ranking Organization method for enrichment evaluation (PROMETHEE), better predict the optimum design alternative

Beyond School Closings: Effective Alternatives for Low-Performing Schools

Parents from low-income and working-class communities in New York City have been fighting for years for dramatic improvements in struggling neighborhood schools. Now the Obama administration has focused its education agenda on this challenge and is investing billions of dollars in turning around failing schools. This dramatic increase in political and financial support creates an opportunity for districts to focus on equity and finally get the work of improving lowperforming schools right. Federal funding for school turnaround has already begun to flow. In the next few months, thirty four NYC schools (thirty-three high schools and one elementary school) will start receiving up to $2 million each year for three years in School Improvement Grants (SIG) to implement one of the four federal options: Restart: Convert the school to charter, or close and reopen it as a charter schoolClosure: Close a school and enroll the students in other higher-achieving schoolsTurnaround: Phase out the existing school and replace it with new schools (NYC version of turnaround)Transformation: Replace the principal and redesign the school by increasing learning time, reforming curriculum and instruction, and increasing teaching qualityTo take strategic advantage of this opportunity to create sustainable change in our city's most struggling schools, the NYC Coalition for Educational Justice (CEJ) urges the NYC Department of Education (DOE) to create a School Transformation Zone to support these schools in implementing effective school improvement models without collateral damage to other schools. Innovation cannot be reserved only for better performing schools; the Zone will support comprehensive, innovative plans that will increase student achievement in the lowest-performing schools

How can we know if EU cohesion policy is successful? Integrating micro and macro approaches to the evaluation of Structural Funds

In this paper we describe an integrated approach for assessing the general economic effectiveness, efficiency and impact of public policy actions for large investment programs of the kind implemented over the past fifteen years in EU-aided Structural Fund programmes. Far from being rigid, our modelling philosophy includes both formal tools designed to assess all relevant effects, as well as informal (intuitive) elements to allow for flexible policy design and evaluation. When setting up an integrated micro-macro (IMM) model we are trying to over-come two major shortcomings in actual policy design and analysis: Firstly, to bridge the gap between the scientific requirements of model-based decision making and evaluation and the practical requirement for flexible and easy to use decision support tools that are well suited for day-to-day application. Secondly, to address the observed discrepancy in policy analysis between programme monitoring and evaluation realized at a highly aggregate level using quantitative macromodels (the so called “top down” approach) and the highly disaggregated approach to project evaluation, marked as micro- or “bottom up”-approaches.

Assessing carbon dioxide emission reduction potentials of improved manufacturing processes using multiregional input output frameworks

Evaluating innovative process technologies has become highly important within the last decades. As standard tools different Life Cycle Assessment methods have been established, which are continuously improved. While those are designed for evaluating single processes they run into difficulties when it comes to assessing environmental impacts of process innovations at macroeconomic level. In this paper we develop a multi-step evaluation framework building on multi regional input–output data that allows estimating macroeconomic impacts of new process technologies, considering the network characteristics of the global economy. Our procedure is as follows: i) we measure differences in material usage of process alternatives, ii) we identify where the standard processes are located within economic networks and virtually replace those by innovative process technologies, iii) we account for changes within economic systems and evaluate impacts on emissions. Within this paper we exemplarily apply the methodology to two recently developed innovative technologies: longitudinal large diameter steel pipe welding and turning of high-temperature resistant materials. While we find the macroeconomic impacts of very specific process innovations to be small, its conclusions can significantly differ from traditional process based approaches. Furthermore, information gained from the methodology provides relevant additional insights for decision makers extending the picture gained from traditional process life cycle assessment.DFG, SFB 1026, Sustainable Manufacturing - Globale Wertschöpfung nachhaltig gestalte