Shifting : one-inclusion mistake bounds and sample compression

We present new expected risk bounds for binary and multiclass prediction, and resolve several recent conjectures on sample compressibility due to Kuzmin and Warmuth. By exploiting the combinatorial structure of concept class F, Haussler et al. achieved a VC(F)/n bound for the natural one-inclusion prediction strategy. The key step in their proof is a d = VC(F) bound on the graph density of a subgraph of the hypercube—oneinclusion graph. The first main result of this paper is a density bound of n [n−1 <=d-1]/[n <=d] < d, which positively resolves a conjecture of Kuzmin and Warmuth relating to their unlabeled Peeling compression scheme and also leads to an improved one-inclusion mistake bound. The proof uses a new form of VC-invariant shifting and a group-theoretic symmetrization. Our second main result is an algebraic topological property of maximum classes of VC-dimension d as being d contractible simplicial complexes, extending the well-known characterization that d = 1 maximum classes are trees. We negatively resolve a minimum degree conjecture of Kuzmin and Warmuth—the second part to a conjectured proof of correctness for Peeling—that every class has one-inclusion minimum degree at most its VCdimension. Our final main result is a k-class analogue of the d/n mistake bound, replacing the VC-dimension by the Pollard pseudo-dimension and the one-inclusion strategy by its natural hypergraph generalization. This result improves on known PAC-based expected risk bounds by a factor of O(logn) and is shown to be optimal up to an O(logk) factor. The combinatorial technique of shifting takes a central role in understanding the one-inclusion (hyper)graph and is a running theme throughout.

Different kinds of openings of Luhmann's systems theory: A reply to la Cour et al

Various researchers have called for an 'opening up' of Luhmann's systems theory. We take this short paper as an occasion for a critical reflection on the necessity, existence and possibilities of such an opening. We start by pointing out the inherent openness of Luhmann's theory, and, based on this, discuss three kinds of openings: the international opening, the theoretical opening and the empirical opening. With regard to the latter, we distinguish three general options of using Luhmann's theory for empirical research. Copyright © 2007 SAGE.

Speeding by young novice drivers : what can personal characteristics and psychosocial theory add to our understanding?

Purpose: Young novice drivers continue to be overrepresented in fatalities and injuries arising from crashes even with the introduction of countermeasures such as graduated driver licensing (GDL). Enhancing countermeasures requires a better understanding of the variables influencing risky driving. One of the most common risky behaviours performed by drivers of all ages is speeding, which is particularly risky for young novice drivers who, due to their driving inexperience, have difficulty in identifying and responding appropriately to road hazards. Psychosocial theory can improve our understanding of contributors to speeding, thereby informing countermeasure development and evaluation. This paper reports an application of Akers’ social learning theory (SLT), augmented by Gerrard and Gibbons’ prototype/willingness model (PWM), in addition to personal characteristics of age, gender, car ownership, and psychological traits/states of anxiety, depression, sensation seeking propensity and reward sensitivity, to examine the influences on self-reported speeding of young novice drivers with a Provisional (intermediate) licence in Queensland, Australia. Method: Young drivers (n = 378) recruited in 2010 for longitudinal research completed two surveys containing the Behaviour of Young Novice Drivers Scale, and reported their attitudes and behaviours as pre-Licence/Learner (Survey 1) and Provisional (Survey 2) drivers and their sociodemographic characteristics. Results: An Akers’ measurement model was created. Hierarchical multiple regressions revealed that (1) personal characteristics (PC) explained 20.3%; (2) the combination of PC and SLT explained 41.1%; and (3) the combination of PC, SLT and PWM explained 53.7% of variance in self-reported speeding. Whilst there appeared to be considerable shared variance, the significant predictors in the final model included gender, car ownership, reward sensitivity, depression, personal attitudes, and Learner speeding. Conclusions: These results highlight the capacity for psychosocial theory to improve our understanding of speeding by young novice drivers, revealing relationships between previous behaviour, attitudes, psychosocial characteristics and speeding. The findings suggest multi-faceted countermeasures should target the risky behaviour of Learners, and Learner supervisors should be encouraged to monitor their Learners’ driving speed. Novice drivers should be discouraged from developing risky attitudes towards speeding.

Predictors of young people’s charitable intentions to donate money : an extended theory of planned behavior perspective

An extended theory of planned behavior (TPB) was used to predict young people’s intentions to donate money to charities in the future. Students (N = 210; 18-24 years) completed a questionnaire assessing their attitude, subjective norm, perceived behavioral control [PBC], moral obligation, past behavior and intentions toward donating money. Regression analyses revealed the extended TPB explained 61% of the variance in intentions to donate money. Attitude, PBC, moral norm, and past behavior predicted intentions, representing future targets for charitable giving interventions.

Problem solving in the primary school (K-2)

This article focuses on problem solving activities in a first grade classroom in a typical small community and school in Indiana. But, the teacher and the activities in this class were not at all typical of what goes on in most comparable classrooms; and, the issues that will be addressed are relevant and important for students from kindergarten through college. Can children really solve problems that involve concepts (or skills) that they have not yet been taught? Can children really create important mathematical concepts on their own – without a lot of guidance from teachers? What is the relationship between problem solving abilities and the mastery of skills that are widely regarded as being “prerequisites” to such tasks?Can primary school children (whose toolkits of skills are limited) engage productively in authentic simulations of “real life” problem solving situations? Can three-person teams of primary school children really work together collaboratively, and remain intensely engaged, on problem solving activities that require more than an hour to complete? Are the kinds of learning and problem solving experiences that are recommended (for example) in the USA’s Common Core State Curriculum Standards really representative of the kind that even young children encounter beyond school in the 21st century? … This article offers an existence proof showing why our answers to these questions are: Yes. Yes. Yes. Yes. Yes. Yes. And: No. … Even though the evidence we present is only intended to demonstrate what’s possible, not what’s likely to occur under any circumstances, there is no reason to expect that the things that our children accomplished could not be accomplished by average ability children in other schools and classrooms.

Adaptive stepsize based on control theory for stochastic differential equations

The numerical solution of stochastic differential equations (SDEs) has been focused recently on the development of numerical methods with good stability and order properties. These numerical implementations have been made with fixed stepsize, but there are many situations when a fixed stepsize is not appropriate. In the numerical solution of ordinary differential equations, much work has been carried out on developing robust implementation techniques using variable stepsize. It has been necessary, in the deterministic case, to consider the "best" choice for an initial stepsize, as well as developing effective strategies for stepsize control-the same, of course, must be carried out in the stochastic case. In this paper, proportional integral (PI) control is applied to a variable stepsize implementation of an embedded pair of stochastic Runge-Kutta methods used to obtain numerical solutions of nonstiff SDEs. For stiff SDEs, the embedded pair of the balanced Milstein and balanced implicit method is implemented in variable stepsize mode using a predictive controller for the stepsize change. The extension of these stepsize controllers from a digital filter theory point of view via PI with derivative (PID) control will also be implemented. The implementations show the improvement in efficiency that can be attained when using these control theory approaches compared with the regular stepsize change strategy.

Teaching and learning family and consumer sciences through K-W-L charts

While much of the control and many of the activities found in today’s classrooms have been placed in the hands of the learners and learning has become inquiry-based, there remains a need for teachers to use teaching tools that would facilitate this student-centered teaching process. This article identifies the K-W-L Chart as one such tool and follows a case study of four Kuwaiti ‘Family and Consumer Sciences’ teaching / learning events to evaluate their ability to enhance the learning outcomes of eight students. The research was designed from a qualitative, multi-tiered design approach and was assessed through a constant comparative method of data analysis of interview responses, classroom observations and worksheet-assessments. The results showed that the use of K-W-L Charts influenced the teachers and learners toward a more inquiry-based approach and facilitated a more student-centered and collaborative learning environment, raising the level of interest and the amount of personal input given by the students.

Testing an extended theory of planned behavior to predict young people's intentions to join a bone marrow donor registry

An extended theory of planned behavior (TPB) was used to understand the factors, particularly control perceptions and affective reactions, given conflicting findings in previous research, informing younger people's intentions to join a bone marrow registry. Participants (N  = 174) completed attitude, subjective norm, perceived behavioral control (PBC), moral norm, anticipated regret, self-identity, and intention items for registering. The extended TPB (except PBC) explained 67.2% of variance in intention. Further testing is needed as to the volitional nature of registering. Moral norm, anticipated regret, and self-identity are likely intervention targets for increasing younger people's bone marrow registry participation.

Donating blood and organs : using an extended theory of planned behavior perspective to identify similarities and differences in individual motivations to donate

Due to the critical shortage and continued need of blood and organ donations (ODs), research exploring similarities and differences in the motivational determinants of these behaviors is needed. In a sample of 258 university students, we used a cross-sectional design to test the utility of an extended theory of planned behavior (TPB) including moral norm, self-identity and in-group altruism (family/close friends and ethnic group), to predict people’s blood and OD intentions. Overall, the extended TPB explained 77.0% and 74.6% of variance in blood and OD intentions, respectively. In regression analyses, common contributors to intentions across donation contexts were attitude, self-efficacy and self-identity. Normative influences varied with subjective norm as a significant predictor related to OD intentions but not blood donation intentions at the final step of regression analyses. Moral norm did not contribute significantly to blood or OD intentions. In-group altruism (family/close friends) was significantly related to OD intentions only in regressions. Future donation strategies should increase confidence to donate, foster a perception of self as the type of person who donates blood and/or organs, and address preferences to donate organs to in-group members only.

Recasting the theory of mosquito-borne pathogen transmission dynamics and control

Mosquito-borne diseases pose some of the greatest challenges in public health, especially in tropical and sub-tropical regions of theworld. Efforts to control these diseases have been underpinned by a theoretical framework developed for malaria by Ross and Macdonald, including models, metrics for measuring transmission, and theory of control that identifies key vulnerabilities in the transmission cycle. That framework, especially Macdonald’s formula for R0 and its entomological derivative, vectorial capacity, are nowused to study dynamics and design interventions for many mosquito-borne diseases. A systematic review of 388 models published between 1970 and 2010 found that the vast majority adopted the Ross–Macdonald assumption of homogeneous transmission in a well-mixed population. Studies comparing models and data question these assumptions and point to the capacity to model heterogeneous, focal transmission as the most important but relatively unexplored component in current theory. Fine-scale heterogeneity causes transmission dynamics to be nonlinear, and poses problems for modeling, epidemiology and measurement. Novel mathematical approaches show how heterogeneity arises from the biology and the landscape on which the processes of mosquito biting and pathogen transmission unfold. Emerging theory focuses attention on the ecological and social context formosquito blood feeding, themovement of both hosts and mosquitoes, and the relevant spatial scales for measuring transmission and for modeling dynamics and control.

An algebraic approach for determination of DG parameters to support voltage profiles in radial distribution networks

Rapidly increasing electricity demands and capacity shortage of transmission and distribution facilities are the main driving forces for the growth of Distributed Generation (DG) integration in power grids. One of the reasons for choosing a DG is its ability to support voltage in a distribution system. Selection of effective DG characteristics and DG parameters is a significant concern of distribution system planners to obtain maximum potential benefits from the DG unit. This paper addresses the issue of improving the network voltage profile in distribution systems by installing a DG of the most suitable size, at a suitable location. An analytical approach is developed based on algebraic equations for uniformly distributed loads to determine the optimal operation, size and location of the DG in order to achieve required levels of network voltage. The developed method is simple to use for conceptual design and analysis of distribution system expansion with a DG and suitable for a quick estimation of DG parameters (such as optimal operating angle, size and location of a DG system) in a radial network. A practical network is used to verify the proposed technique and test results are presented.

Top-k retrieval using facility location analysis

The top-k retrieval problem aims to find the optimal set of k documents from a number of relevant documents given the user’s query. The key issue is to balance the relevance and diversity of the top-k search results. In this paper, we address this problem using Facility Location Analysis taken from Operations Research, where the locations of facilities are optimally chosen according to some criteria. We show how this analysis technique is a generalization of state-of-the-art retrieval models for diversification (such as the Modern Portfolio Theory for Information Retrieval), which treat the top-k search results like “obnoxious facilities” that should be dispersed as far as possible from each other. However, Facility Location Analysis suggests that the top-k search results could be treated like “desirable facilities” to be placed as close as possible to their customers. This leads to a new top-k retrieval model where the best representatives of the relevant documents are selected. In a series of experiments conducted on two TREC diversity collections, we show that significant improvements can be made over the current state-of-the-art through this alternative treatment of the top-k retrieval problem.