Meta-Level Inference and Program Verification

In [Bundy and Sterling 81] we described how meta-level inference was useful for controlling search and deriving control information in the domain of algebra. Similar techniques are applicable to the verification of logic programs. A developing meta-language is described, and an explicit proof plan using this language is given. A program, IMPRESS, is outlined which executes this plan

Green roofs provide habitat for urban bats

AbstractUnderstanding bat use of human-altered habitat is critical for developing effective conservation plans for this ecologically important taxon. Green roofs, building rooftops covered in growing medium and vegetation, are increasingly important conservation tools that make use of underutilized space to provide breeding and foraging grounds for urban wildlife. Green roofs are especially important in highly urbanized areas such as New York City (NYC), which has more rooftops (34%) than green space (13%). To date, no studies have examined the extent to which North American bats utilize urban green roofs. To investigate the role of green roofs in supporting urban bats, we monitored bat activity using ultrasonic recorders on four green and four conventional roofs located in highly developed areas of NYC, which were paired to control for location, height, and local variability in surrounding habitat and species diversity. We then identified bat vocalizations on these recordings to the species level. We documented the presence of five of nine possible bat species over both roof types: Lasiurus borealis, L. cinereus, L. noctivagans, P. subflavus,andE. fuscus. Of the bat calls that could be identified to the species level, 66% were from L. borealis. Overall levels of bat activity were higher over green roofs than over conventional roofs. This study provides evidence that, in addition to well documented ecosystem benefits, urban green roofs contribute to urban habitat availability for several North American bat species

An Entailment Relation for Reasoning on the Web

Reasoning on the Web is receiving an increasing attention because of emerging fields such as Web adaption and Semantic Web. Indeed, the advanced functionalities striven for in these fields call for reasoning capabilities. Reasoning on the Web, however, is usually done using existing techniques rarely fitting the Web. As a consequence, additional data processing like data conversion from Web formats (e.g. XML or HTML) into some other formats (e.g. classical logic terms and formulas) is often needed and aspects of the Web (e.g. its inherent inconsistency) are neglected. This article first gives requirements for an entailment tuned to reasoning on the Web. Then, it describes how classical logic’s entailment can be modified so as to enforce these requirements. Finally, it discusses how the proposed entailment can be used in applying logic programming to reasoning on the Web

Experimental control of a cupola furnace

In this paper the authors present some final results from a research project focused on introducing automatic control to the operation of cupola iron furnaces. The main aim of this research is to improve the operational efficiency and performance of the cupola furnace, an important foundry process used to melt iron. Previous papers have described the development of appropriate control system architectures for the cupola. In this paper experimental data is used to calibrate the model, which is taken as a first-order multivariable system with time delay. Then relative gain analysis is used to select loop pairings to be used in a multiloop controller. The resulting controller pairs melt rate with blast volume, iron temperature with oxygen addition, and carbon composition with metal-to-coke ratio. Special (nonlinear) filters are used to compute melt rate from actual scale readings of the amount of iron produced and to smooth the temperature measurement. The temperature and melt rate loops use single-loop PI control. The composition loop uses a Smith predictor to discount the deadtime associated with mass transport through the furnace. Experiments conducted at the Department of Energy Albany Research Center`s experimental research cupola validate the conceptual controller design and provide proof-of-concept of the idea of controlling a foundry cupola

Diffusive behavior for randomly kicked Newtonian particles in a spatially periodic medium

We prove a central limit theorem for the momentum distribution of a particle undergoing an unbiased spatially periodic random forcing at exponentially distributed times without friction. The start is a linear Boltzmann equation for the phase space density, where the average energy of the particle grows linearly in time. Rescaling time, the momentum converges to a Brownian motion, and the position is its time-integral showing superdiffusive scaling with time $t^{3/2}$. The analysis has two parts: (1) to show that the particle spends most of its time at high energy, where the spatial environment is practically invisible; (2) to treat the low energy incursions where the motion is dominated by the deterministic force, with potential drift but where symmetry arguments cancel the ballistic behavior.Comment: 55 pages. Some typos corrected from previous versio

Surface Instabilities and Magnetic Soft Matter

We report on the formation of surface instabilities in a layer of thermoreversible ferrogel when exposed to a vertical magnetic field. Both static and time dependent magnetic fields are employed. Under variations of temperature, the viscoelastic properties of our soft magnetic matter can be tuned. Stress relaxation experiments unveil a stretched exponential scaling of the shear modulus, with an exponent of beta=1/3. The resulting magnetic threshold for the formation of Rosensweig-cusps is measured for different temperatures, and compared with theoretical predictions by Bohlius et. al. in J. Phys.: Condens. Matter., 2006, 18, 2671-2684.Comment: accepted to Soft Matte

Ontologies for Intelligent e-Theraoy: Application to Obesity

[EN] In this paper we propose a new approach for mental e-health treatments named intelligent e-therapy (e-it) with capabilities for ambient intelligence and ubiquitous computing. The proposed e-it system supposes an evolution of cybertherapy and telepsychology tools used up to now. The e-it system is based in a knowledge base that includes all the knowledge related to the disorder and its treatment. We introduce the use of ontologies as the best option for the design of this knowledge base. We also present a fist e-it system for obesity treatment called etiobeZaragozá Álvarez, I.; Guixeres Provinciale, J.; Alcañiz Raya, ML. (2009). Ontologies for Intelligent e-Theraoy: Application to Obesity. Lecture Notes in Computer Science. 5518:894-901. doi:10.1007/978-3-642-02481-8_136S8949015518Baños, R.M., Botella, C., Perpiñá, C., Alcañiz, M., Lozano, J.A., Osma, J., Gallardo, M.: Virtual reality treatment of flying phobia. IEEE Transactions on Information Technology in Biomedicine 6(3), 206–212 (2002)Botella, C., Baños, R.M., Perpiña, C., et al.: Virtual reality treatment of claustrophobia: a case report. Behaviour Research & Therapy 36, 239–246 (1998)Hu, B., Dasmahapatra, S., Dupplaw, D., Lewis, P., Shadbolt, N.: Reflections on a medical ontology. International Journal of Human- Computer Studies 65(2007), 569–582 (2007)Rubin, D.L., Shah, N.H., Noy, N.F.: Biomedical ontologies: a functional perspective. Briefings in bioinformatics 9(1), 75–90 (2007)Stevens, R., Egaña Aranguren, M., Wolstencroft, K., Sattler, U., Drummond, N., Horridge, M., Rector, A.: Using OWL to model biological knowledge. International Journal of Human-Computer Studies 65(2007), 583–594 (2007)Park, S., Lee, J.K.: Rule identification using ontology while acquiring rules from Web pages. International Journal of Human-Computer Studies 65(2007), 644–658 (2007)Clark, K.L., McCabe, F.G.: Ontology schema for an agent belief store. International Journal of Human-Computer Studies 65(2007), 625–643 (2007)Gruber, T.R.: A Translation Approach to Portable Ontology Specifications. Knowledge Acquisition 5(2), 199–220 (1993)Franco, C., Bengtsson, B., Johannsson, G.: The GH/IGF-1 Axis in Obesity: Physiological and Pathological aspects. Metabolic syndrome and Related Disorders 4, 51–56 (2006

Machine-learning-based calving prediction from activity, lying, and ruminating behaviors in dairy cattle

The objective of this study was to use automated activity, lying, and rumination monitors to characterize prepartum behavior and predict calving in dairy cattle. Data were collected from 20 primiparous and 33 multiparous Holstein dairy cattle from September 2011 to May 2013 at the University of Kentucky Coldstream Dairy. The HR Tag (SCR Engineers Ltd., Netanya, Israel) automatically collected neck activity and rumination data in 2-h increments. The IceQube (IceRobotics Ltd., South Queensferry, United Kingdom) automatically collected number of steps, lying time, standing time, number of transitions from standing to lying (ly-. ing bouts), and total motion, summed in 15-min increments. IceQube data were summed in 2-h increments to match HR Tag data. All behavioral data were collected for 14 d before the predicted calving date. Retrospective data analysis was performed using mixed linear models to examine behavioral changes by day in the 14 d before calving. Bihourly behavioral differences from baseline values over the 14 d before calving were also evaluated using mixed linear models. Changes in daily rumination time, total motion, lying time, and lying bouts occurred in the 14 d before calving. In the bihourly analysis, extreme values for all behaviors occurred in the final 24 h, indicating that the monitored behaviors may be useful in calving prediction. To determine whether technologies were useful at predicting calving, random forest, linear discriminant analysis, and neural network machine -learning techniques were constructed and implemented using R version 3.1.0 (R Foundation for Statistical Computing, Vienna, Austria). These methods were used on variables from each technology and all combined variables from both technologies. A neural network analysis that combined variables from both technologies at the daily level yielded 100.0% sen-sitivity and 86.8% specificity. A neural network analysis that combined variables from both technologies in bihourly increments was used to identify 2-h periods in the 8 h before calving with 82.8% sensitivity and 80.4% specificity. Changes in behavior and machine-learning alerts indicate that commercially marketed behavioral monitors may have calving prediction potential