Prediction of rock mass P wave velocity using blasthole drilling information

In this paper, the development of the models for the prediction of rock mass P wave velocity is presented. For model development, the database of 53 cases including widely used and recorded drilling parameters and P wave velocity was constructed from the field studies conducted in 13 open pit lignite mines. Both conventional linear, non-linear multiple regression and Adaptive Neuro Fuzzy Inference System (ANFIS) were used for model development. Prediction performance indicators showed that ANFIS model presented the best performance and it can successfully be used for the preliminary prediction of P wave velocities of rock masses.     

Assessment of the effectiveness of steel fibre reinforcement for the punching resistance of flat slabs by experimental research and design approach

The present paper deals with the experimental assessment of the effectiveness of steel fibre reinforcement in terms of punching resistance of centrically loaded flat slabs, and to the development of an analytical model capable of predicting the punching behaviour of this type of structures. For this purpose, eight slabs of 2550 × 2550 × 150 mm³ dimensions were tested up to failure, by investigating the influence of the content of steel fibres (0, 60, 75 and 90 kg/m³) and concrete strength class (50 and 70 MPa). Two reference slabs without fibre reinforcement, one for each concrete strength class, and one slab for each fibre content and each strength class compose the experimental program. All slabs were flexurally reinforced with a grid of ribbed steel bars in a percentage to assure punching failure mode for the reference slabs. Hooked ends steel fibres provided the unique shear reinforcement. The results have revealed that steel fibres are very effective in converting brittle punching failure into ductile flexural failure, by increasing both the ultimate load and deflection, as long as adequate fibre reinforcement is assured. An analytical model was developed based on the most recent concepts proposed by the fib Mode Code 2010 for predicting the punching resistance of flat slabs and for the characterization of the behaviour of fibre reinforced concrete. The most refined version of this model was capable of predicting the punching resistance of the tested slabs with excellent accuracy and coefficient of variation of about 5%.     

Animations showing Lego manipulative tasks: Three potential moderators of effectiveness

Evidence suggests that transient visual information, such as animations, may be more challenging to learn than static visualizations. However, when a procedural-manipulative task is involved, our evolved embodied cognition seems to reverse this transitory challenge. Hence, for object manipulative tasks, instructional animations may be more suitable than statics. We investigated this argument further by comparing animations with statics using a Lego task shown to university students, by examining three potential moderators of effectiveness: (a) the environment of manipulation (virtual or physical), (b) the quality of visual information (focused or unfocused), and (c) the presence of hands (no hands or with hands). In Experiment 1 we found an advantage of animation over statics, and no differences among the environments. In Experiment 2, we again observed an animation advantage, a small advantage of focused static information compared to unfocused static information, and a positive effect of not showing the hands.     

Modelling consumer choice through the random regret minimization model: An application in the food domain

In line with findings on post-purchase food-choice regret, one can expect that pre-purchase anticipated regret with respect to forgone (non-chosen) alternatives has an impact on consumer food choices, especially when the choice is considered to be important. The traditional Random Utility Maximization (RUM) models for discrete choices may not fully capture this impact. This study investigates the usefulness and potential in the food domain of a discrete choice model that follows the regret minimization principle, the Random Regret Minimization (RRM) model, as an alternative and complement to existing RUM models. The two models are applied to consumer stated choices of cheese in a choice experiment. The study also investigates whether and to what extent a number of personality traits determine whether particular consumers rather choose according to utility-maximization, or regret-minimization principles. Results show that at the aggregate level the two models have a similar goodness of fit to the data and prediction ability. Still, each of them shows better fit for particular subgroups of consumers, based on personality traits. Hence, the present study reveals a potential for the RRM model applications in the food domain, and adds to the empirical literature supporting previous findings on the RRM model found in other contexts. Further research is needed to explore in which situations and for which consumer segments the RRM model is the most useful model.     

Model Selection for Unsupervised Learning of Visual Context

This study addresses the problem of choosing the most suitable probabilistic model selection criterion for unsupervised learning of visual context of a dynamic scene using mixture models. A rectified Bayesian Information Criterion (BICr) and a Completed Likelihood Akaike’s Information Criterion (CL-AIC) are formulated to estimate the optimal model order (complexity) for a given visual scene. Both criteria are designed to overcome poor model selection by existing popular criteria when the data sample size varies from small to large and the true mixture distribution kernel functions differ from the assumed ones. Extensive experiments on learning visual context for dynamic scene modelling are carried out to demonstrate the effectiveness of BICr and CL-AIC, compared to that of existing popular model selection criteria including BIC, AIC and Integrated Completed Likelihood (ICL). Our study suggests that for learning visual context using a mixture model, BICr is the most appropriate criterion given sparse data, while CL-AIC should be chosen given moderate or large data sample sizes.     

测试(试井)成果影响因素浅析

随着测试技术的发展、测试质量及资料解释水平的提高，测试（试井）成果的可靠程度越来越受到重视。影响解释成果的环节和因素很多，从客观和主观两方面分析其主要因素，找出症结所在，从而完善现场环节，完善资料解释过程，提高测试技术及解释水平。     

PETROLEUM MIGRATION, FAULTS AND OVERPRESSURE, PART I: CALIBRATING BASIN MODELLING USING PETROLEUM IN TRAPS — A REVIEW

This paper considers the principles of deciphering basin-scale hydrocarbon migration patterns using the geochemical information which is present in trapped petroleum. Petroleum accumulations in subsiding basins can be thought of as "data archives" within which stored information can help us to understand aspects of hydrocarbon formation and migration. This information can impart a time-resolved picture of hydrocarbon migration in a basin in response to processes associated with progressive burial, particularly in the context of the occurrence and periodic activity of faults.
This review, which includes a series of tentative models of migration-related processes in the extensional Halten Terrace area, offshore mid-Norway, illustrates how we can use information from the migrating mobile hydrocarbon phase to improve our knowledge of the static geological system. Of particular importance is the role of sub-seismic heterogeneities and faults in controlling migration processes. We focus on how the secondary migration process can be enhanced in a multi-source rock basin such as the Halten Terrace, thereby increasing prospectivity.     

横泉水库大坝土料碾压试验

在取得土料场土料物理力学性质参数的情况下，遵循碾压试验基本原理、方法及参数组合，进行了现场碾压试验，通过试验成果的分析，得出了大坝碾压试验结论，为大坝土方填筑提供了技术依据。     

A Novel Approach to Analyzing the Occupancy of the Geo/Geo/∞ Queueing System

Discrete time queueing systems have been successfully used to model packet queues in computer and digital communications systems. In this article we introduce a novel approach to analyzing the Geo^X/Geo^Y/∞ queueing system, which is suitable for modelling high speed computer and communications systems. The approach is based on characterizing the system by a functional equation which is then solved recursively to give identical results to those obtained using other approaches.