The Full Cost of Cryptanalytic Attacks

An open question about the asymptotic cost of connecting many processors to a large memory using three dimensions for wiring is answered, and this result is used to find the full cost of several cryptanalytic attacks. In many cases this full cost is higher than the accepted complexity of a given algorithm based on the number of processor steps. The full costs of several cryptanalytic attacks are determined, including Shanks method for computing discrete logarithms in cyclic groups of prime order n, which requires n^1/2+o(1) processor steps, but, when all factors are taken into account, has full cost n^2/3+o(1). Other attacks analyzed are factoring with the number field sieve, generic attacks on block ciphers, attacks on double and triple encryption, and finding hash collisions. In many cases parallel collision search gives a significant asymptotic advantage over well-known generic attacks.     

From Amateur to Professional: A Neuro-cognitive Model of Categories and Expert Development

The ability to group perceptual objects into functionally relevant categories is vital to our comprehension of the world. Such categorisation aids in how we search for objects in familiar scenes and how we identify an object and its likely uses despite never having seen that specific object before. The systems that mediate this process are only now coming to be understood through considerable research efforts combining neurological, psychological and behavioural studies. What is much less well understood are the differences between the categories, how they are formed and how they are used by experts and non-experts in a complex task that can take decades to master. In a quite different direction to previous studies, this work infers the different categorical structures that might be used by amateurs and professionals in the oriental game of Go. This is achieved by using a newly developed combination of artificial neural networks (Self-organising Maps) and perceptual inference to show that categories of strategic scenes can be learned while playing games using a model of ‘conditional perceptual learning’. Applying this technique to two databases of games, one of amateurs and one of professionals, shows that a structural hierarchy of scene information develops that can be readily incorporated into traditional psychological models of decisions and readily implemented in computational systems. The results are discussed in terms of the heuristics and biases literature, emphasising where the significant similarities and differences lie between this work and previous work.     

Software and hardware architecture of advanced mobile robots for manufacturing

Modern manufacturing requires flexible and autonomous systems for materials handling and transportation. For such applications, a succession of implemented mobile robots has been developed over the past seven years. In this paper, the questions of software and hardware architecture are discussed in light of experience gained so far. Also discussed are mobile robot projects that seem realistic over the next five to ten years.     

Implementing knowledge building: Analysis of a face‐to‐face discussion by grade‐four students

Abstract:

Researchers say that teachers can implement an educational innovation without adhering to the principles underpinning its design. Such principles may not adequately take typical classroom conditions into account. The goal of this study was to explore tensions between attempts to implement the principles underpinning knowledge building and the influence of contextual factors that compete for the teacher's attention. To this end, we discuss five excerpts from a discussion of the motion of spinning tops held by a class of Grade‐4 students, coming at the end of a five‐month implementation of knowledge building. Each excerpt is followed first by the teacher's perspective and then by the researcher's perspective. Our analysis highlights two tensions that constrain agency, arising from the students’ need for social development and their need to learn scientific concepts. We offer some suggestions for addressing these tensions.     

Hybrid modeling to predict the economic feasibility of mining undiscovered porphyry copper deposits

Few studies attempt to model the economic feasibility of mining undiscovered mineral resources given the sparseness of data; and the coupled, nonlinear, spatial, and temporal relationships among variables. In this study, a type of unsupervised artificial neural network, called a self-organized map (SOM), is trained using data from 203 porphyry copper deposit sites across the world. The sparse data set includes one dependent variable indicating the economic feasibility, and seventy two independent variables from categories describing characteristics of mining method, metallurgy, dimensions, economics, and amount. Analysis of component planes reveals relations and strengths in the underlying SOM multivariate density function which are used to impute missing values. Application of the Davies–Bouldin criteria to k-means clusters of SOM neurons identified 14 regional economic resource units (conceptual models). A best subsets approach applied to median values from these models identified 20 statistically significant combinations of variables. During model fitting by the multiple linear regression technique, only four of the empirical models had variables that were all significant at the 95% confidence level. The best model explained 98% of the variability in economic feasibility and incorporated variables describing distance to natural gas, road, and water; and the total amount of resources. This model was independently validated by comparing predictions of economic feasibility at 68 mine sites not included in the training data. Eighty-four percent of the reported economic feasibility is correctly predicted with 8 false positives and 2 false negative. We demonstrate the application of this model to a permissive copper porphyry tract that crosses a portion of British Columbia and Yukon territories of Canada. The proposed hybrid approach provides an alternative modeling paradigm for translating estimates of contained metal into meaningful societal measures.     

A note on the time travel approach for handling time windows in vehicle routing problems

In this paper, we identify two cases in which the proposition for calculating time window penalties presented in Nagata, Y., Bräysy, O. and Dullaert, W. A penalty-based edge assembly memetic algorithm for the vehicle routing problem with time windows, Computers & Operations Research 2010;37(4): 724–37 yields incorrect results. We derive the corrected proposition and use numerical studies to show that a significant proportion of the evaluations performed by a Tabu Search for VRPTW falls under the two incorrect cases. Moreover, we demonstrate that the incorrect time window handling has a significant negative impact on the solution quality of the Tabu Search.     

Knowledge of the ordinal position of list items in pigeons.

Ordinal knowledge is a fundamental aspect of advanced cognition. It is self-evident that humans represent ordinal knowledge, and over the past 20 years it has become clear that nonhuman primates share this ability. In contrast, evidence that nonprimate species represent ordinal knowledge is missing from the comparative literature. To address this issue, in the present experiment we trained pigeons on three 4-item lists and then tested them with derived lists in which, relative to the training lists, the ordinal position of the items was either maintained or changed. Similar to the findings with human and nonhuman primates, our pigeons performed markedly better on the maintained lists compared to the changed lists, and displayed errors consistent with the view that they used their knowledge of ordinal position to guide responding on the derived lists. These findings demonstrate that the ability to acquire ordinal knowledge is not unique to the primate lineage. (PsycINFO Database Record (c) 2011 APA, all rights reserved)     

The cognitive differentiation-integration effort hypothesis: A synthesis between the fitness indicator and life history models of human intelligence.

This article presents a potential synthesis between the fitness indicator and life history models of human intelligence through consideration of the phenomena of ability differentiation and integration. The cognitive differentiation-integration effort hypothesis proposes that these effects result from a life history tradeoff between cognitive integration effort, a mating effort component associated with strengthening the positive manifold amongst abilities; and cognitive differentiation effort, a somatic effort component associated with the cultivation of specific abilities. This represents one of two largely independent sources of genetic variance in intelligence; the other is mediated by general fitness and mutation load and is associated with individual differences in levels of 'genetic g'. These two sources (along with a common source of environmental variance) combine to give rise to a variety of cognitive phenotypes characterized by different combinations of high or low levels of 'genetic g' and cognitive specialism or generalism. Fundamental to this model is the assumption that measures of life history speed (K) and g are essentially independent, which is demonstrated via meta-analysis of 10 studies reporting correlations between the variables (ρ = .023, ns, n = 2056). The implications of the model are discussed in an evolutionary, ecological, and developmental context. Seven key predictions are made in the discussion which if tested could provide definitive evidence for the hypothesis. (PsycINFO Database Record (c) 2011 APA, all rights reserved)