Learning First-Order Definitions of Functions

First-order learning involves finding a clause-form definition of a relation from examples of the relation and relevant background information. In this paper, a particular first-order learning system is modified to customize it for finding definitions of functional relations. This restriction leads to faster learning times and, in some cases, to definitions that have higher predictive accuracy. Other first-order learning systems might benefit from similar specialization.Comment: See http://www.jair.org/ for any accompanying file

Unitary groups over local rings

Structural properties of unitary groups over local, not necessarily commutative, rings are developed, with applications to the computation of the orders of these groups (when finite) and to the degrees of the irreducible constituents of the Weil representation of a unitary group associated to a ramified extension of finite local rings

Improved Use of Continuous Attributes in C4.5

A reported weakness of C4.5 in domains with continuous attributes is addressed by modifying the formation and evaluation of tests on continuous attributes. An MDL-inspired penalty is applied to such tests, eliminating some of them from consideration and altering the relative desirability of all tests. Empirical trials show that the modifications lead to smaller decision trees with higher predictive accuracies. Results also confirm that a new version of C4.5 incorporating these changes is superior to recent approaches that use global discretization and that construct small trees with multi-interval splits.Comment: See http://www.jair.org/ for any accompanying file

Learning a Static Analyzer from Data

To be practically useful, modern static analyzers must precisely model the effect of both, statements in the programming language as well as frameworks used by the program under analysis. While important, manually addressing these challenges is difficult for at least two reasons: (i) the effects on the overall analysis can be non-trivial, and (ii) as the size and complexity of modern libraries increase, so is the number of cases the analysis must handle. In this paper we present a new, automated approach for creating static analyzers: instead of manually providing the various inference rules of the analyzer, the key idea is to learn these rules from a dataset of programs. Our method consists of two ingredients: (i) a synthesis algorithm capable of learning a candidate analyzer from a given dataset, and (ii) a counter-example guided learning procedure which generates new programs beyond those in the initial dataset, critical for discovering corner cases and ensuring the learned analysis generalizes to unseen programs. We implemented and instantiated our approach to the task of learning JavaScript static analysis rules for a subset of points-to analysis and for allocation sites analysis. These are challenging yet important problems that have received significant research attention. We show that our approach is effective: our system automatically discovered practical and useful inference rules for many cases that are tricky to manually identify and are missed by state-of-the-art, manually tuned analyzers

Hydrology and Water Quality in the Central Kentucky Karst: Phase II Part A: Preliminary Summary of the Hydrogeology of the Mill Hole Sub-Basin of the Turnhole Spring Groundwater Basin

Water from upland areas flows to small ephemeral and perennial springs that feed sinking streams that are tributary to low-order cave streams. These cave streams, also recharged by diffuse percolation, are part of a dendritic network in which intermediate-order streams join high-order streams that flow to major trunk streams. The trunk in the Mill Hole Sub-basin flows across the bottom of a large karst window, Mill Hole, and joins the trunk of the Patoka Creek Sub-basin. Their combined discharge bifurcates, flows around the collapsed central core of a larger karst window, Cedar Sink, and re-joins to flow as one to Turnhole Spring, along the south bank of Green River. The location of the major trunk streams can be inferred from the position and orientation of well-defined troughs in the piezometric surface. Flow velocities over the same 5-mile distance, erroneously assuming a straight path from Parker Cave to Mill Hole, range from 60 to 1100 ft per hour--depending on whether discharge is at flood or base flow conditions. Actual velocity extremes are probably lower and higher

Hydrology and Water Quality in the Central Kentucky Karst: Phase 1

Study of springs and cave streams has shown that heavy metal-rich effluent from a wastewater treatment plant can be traced to Hidden River Cave (beneath the city of Horse Cave) and thence 4 to 5 miles north to a group of 39 springs at 14 locations along a 5-mile reach of Green River. Nickel, chromium, copper and zinc in these effluent-bearing springs are in concentrations of as much as 30 times greater than other springs upstream and downstream from this reach, 20 times greater than the Green River, and 60 times greater than in shallow domestic wells between Horse Cave and the river. Mean concentration ratios, based on samples taken during moderate to flood flow, are considerably lower. Although the heavy metal content of the effluent-bearing stream in Hidden River Cave greatly exceeds various maximum concentrations set by current standards, the concentrations in the effluent-bearing springs do not exceed current maximums allowed for public water supplies. None of the domestic shallow wells between the cave and the river intercept this effluent-rich water. The distributary system that was postulated to feed the 39 springs was entered by digging in June 1975; 14.6 miles of this floodwater maze has been mapped. Water tracing over distances of as much as 15 miles has made it possible to delineate thirteen groundwater basins, eleven of them characterized by distributary flow. Study of the water quality· of five adjacent groundwater basins showed that they could be geochemically differentiated. One of these, the Three-Springs Groundwater Basin, has a distributary complex that is 2.4 miles wide and its discharge is believed to be affected by brines released by drilling. Dendritic flow paths, identified by dye-traces to and from caves (and mapping of these caves), have been recognized in the Turnhole Spring Groundwater Basin (Quinlan, 1976) and the Graham Springs Groundwater Basin. Flow converges to trunk streams as much as 40 ft wide that may rise and fall as much as 100 ft in response to heavy rains. Groundwater velocities in the upper part of the principal aquifer range from 30 ft per hour to 1300 ft per hour, depending upon the duration and intensity of rains. Recommendations are made for: 1) the use of drainage basin maps for regional planning and protection of water supplies, 2) protection of other water supplies, and 3) development of specific springs as potential public water supplies