Computer Techniques to Analyze Shell-and-Tube Heat Exchangers

This paper outlines computer analyses to predict thermal-hydraulics, flow-induced vibration, and fretting-wear damage in shell-and-tube heat exchangers. The analytical techniques are briefly described and the results arc illustrated by example. It is concluded that computer techniques can do much to improve the reliability and performance of heat exchangers.     

Deep convolutional neural network for multi-level non-invasive tunnel lining assessment

In recent years, great attention has focused on the development of automated procedures for infrastructures control. Many efforts have aimed at greater speed and reliability compared to traditional methods of assessing structural conditions. The paper proposes a multi-level strategy, designed and implemented on the basis of periodic structural monitoring oriented to a cost- and time-efficient tunnel control plan. Such strategy leverages the high capacity of convolutional neural networks to identify and classify potential critical situations. In a supervised learning framework, Ground Penetrating Radar (GPR) profiles and the revealed structural phenomena have been used as input and output to train and test such networks. Image-based analysis and integrative investigations involving video-endoscopy, core drilling, jacking and pull-out testing have been exploited to define the structural conditions linked to GPR profiles and to create the database. The degree of detail and accuracy achieved in identifying a structural condition is high. As a result, this strategy appears of value to infrastructure managers who need to reduce the amount and invasiveness of testing, and thus also to reduce the time and costs associated with inspections made by highly specialized technicians.     

TENDERNESS, pH AND ACCEPTABILITY OF MEAT FROM PODOLIAN AND LIMOUSINE × PODOLIAN YOUNG BULLS

The relationships between meat pH, sensory tenderness and acceptability for Podolian (P) and Limousine  ×  Podolian (LP) beef were investigated. Negative linear relationships between pH measured at each of 1, 24 and 48 h post mortem and sensory tenderness were found at 2 ( P <  0.001) and 7 days of ageing ( P <  0.05). At 7 days of ageing, sensory tenderness was higher ( P <  0.001) than that at 2 days of ageing. LP beef showed higher sensory tenderness ( P <  0.001) than P. The regression between perceived tenderness and acceptability was separately calculated for LP and P beef. Both were significant ( P <  0.01 and P <  0.001, respectively). In addition, a significant difference was observed between the two regression coefficients ( P <  0.05), indicating that the two variables were more associated for P than LP beef.

PRACTICAL APPLICATIONS

Meat acceptability is obviously related to tenderness. More interestingly, other factors (e.g., familiarity, age, etc.) can affect product acceptability. In fact, the same product can be perceived by some consumers as being tough, whereas it can be considered tender by others, corresponding to low and high levels of acceptability, respectively. Therefore, along with treatments aimed to increase tenderness (e.g., ageing), information about the product, age and familiarity of consumers, etc., can increase the acceptability of meats, which are less tender because of their intrinsic properties.     

SEDAF: AN INTELLIGENT EDUCATIONAL SYSTEM FOR MATHEMATICS

The field of artificial intelligence and education, in which AI techniques and methodologies are used to build sophisticated intelligent educational systems, is developing rapidly. In this paper we present an intelligent educational system for teaching high school and college students how to analyze and draw graphs of mathematical functions. The system, named SEDAF, has been developed in a knowledge engineering environment and runs on a Lisp-machine workstation. We illustrate the various modules constituting SEDAF: the user interface; an expert module, capable of solving problems in the subject domain; a diagnosis module, which points out possible reasons for students' errors; a student modeling module, capable of building an explicit representation of the learning status of the student; and a remedial subsystem, called a therapy module, constituted by means-ends tutorial rules that execute teaching actions on the base of the status of the student model. The goal of the presentation is to stress the innovative aspects of the architecture of SEDAF, in particular the use of metalevel knowledge to embed in the system the teaching expertise that allows the system to personalize its behavior to the specific student and to pursue a didactic plan.     

PERSPECTIVES IN KNOWLEDGE REPRESENTATION

In this paper we discuss recent developments in the research on knowledge representation, focusing on hybrid formalisms, nonmonotonic reasoning, and formalisms for reasoning about knowledge and reasoning in a multiagent scenario.